(light music) >> Hi everybody. Welcome to this Cube Conversation. I'm really pleased to announce a collaboration with Rob Strechay. He's a guest cube analyst, and we'll be working together to extract the signal from the noise. Rob is a long-time product pro, working at a number of firms including AWS, HP, HPE, NetApp, Snowplow. I did a stint as an analyst at Enterprise Strategy Group. Rob, good to see you. Thanks for coming into our Marlboro Studios. >> Well, thank you for having me. It's always great to be here. >> I'm really excited about working with you. We've known each other for a long time. You've been in the Cube a bunch. You know, you're in between gigs, and I think we can have a lot of fun together. Covering events, covering trends. So. let's get into it. What's happening out there? We're sort of exited the isolation economy. Things were booming. Now, everybody's tapping the brakes. From your standpoint, what are you seeing out there? >> Yeah. I'm seeing that people are really looking how to get more out of their data. How they're bringing things together, how they're looking at the costs of Cloud, and understanding how are they building out their SaaS applications. And understanding that when they go in and actually start to use Cloud, it's not only just using the base services anymore. They're looking at, how do I use these platforms as a service? Some are easier than others, and they're trying to understand, how do I get more value out of that relationship with the Cloud? They're also consolidating the number of Clouds that they have, I would say to try to better optimize their spend, and getting better pricing for that matter. >> Are you seeing people unhook Clouds, or just reduce maybe certain Cloud activities and going maybe instead of 60/40 going 90/10? >> Correct. It's more like the 90/10 type of rule where they're starting to say, Hey I'm not going to get rid of Azure or AWS or Google. I'm going to move a portion of this over that I was using on this one service. Maybe I got a great two-year contract to start with on this platform as a service or a database as a service. I'm going to unhook from that and maybe go with an independent. Maybe with something like a Snowflake or a Databricks on top of another Cloud, so that I can consolidate down. But it also gives them more flexibility as well. >> In our last breaking analysis, Rob, we identified six factors that were reducing Cloud consumption. There were factors and customer tactics. And I want to get your take on this. So, some of the factors really, you got fewer mortgage originations. FinTech, obviously big Cloud user. Crypto, not as much activity there. Lower ad spending means less Cloud. And then one of 'em, which you kind of disagreed with was less, less analytics, you know, fewer... Less frequency of calculations. I'll come back to that. But then optimizing compute using Graviton or AMD instances moving to cheaper storage tiers. That of course makes sense. And then optimize pricing plans. Maybe going from On Demand, you know, to, you know, instead of pay by the drink, buy in volume. Okay. So, first of all, do those make sense to you with the exception? We'll come back and talk about the analytics piece. Is that what you're seeing from customers? >> Yeah, I think so. I think that was pretty much dead on with what I'm seeing from customers and the ones that I go out and talk to. A lot of times they're trying to really monetize their, you know, understand how their business utilizes these Clouds. And, where their spend is going in those Clouds. Can they use, you know, lower tiers of storage? Do they really need the best processors? Do they need to be using Intel or can they get away with AMD or Graviton 2 or 3? Or do they need to move in? And, I think when you look at all of these Clouds, they always have pricing curves that are arcs from the newest to the oldest stuff. And you can play games with that. And understanding how you can actually lower your costs by looking at maybe some of the older generation. Maybe your application was written 10 years ago. You don't necessarily have to be on the best, newest processor for that application per se. >> So last, I want to come back to this whole analytics piece. Last June, I think it was June, Dev Ittycheria, who's the-- I call him Dev. Spelled Dev, pronounced Dave. (chuckles softly) Same pronunciation, different spelling. Dev Ittycheria, CEO of Mongo, on the earnings call. He was getting, you know, hit. Things were starting to get a little less visible in terms of, you know, the outlook. And people were pushing him like... Because you're in the Cloud, is it easier to dial down? And he said, because we're the document database, we support transaction applications. We're less discretionary than say, analytics. Well on the Snowflake earnings call, that same month or the month after, they were all over Slootman and Scarpelli. Oh, the Mongo CEO said that they're less discretionary than analytics. And Snowflake was an interesting comment. They basically said, look, we're the Cloud. You can dial it up, you can dial it down, but the area under the curve over a period of time is going to be the same, because they get their customers to commit. What do you say? You disagreed with the notion that people are running their calculations less frequently. Is that because they're trying to do a better job of targeting customers in near real time? What are you seeing out there? >> Yeah, I think they're moving away from using people and more expensive marketing. Or, they're trying to figure out what's my Google ad spend, what's my Meta ad spend? And what they're trying to do is optimize that spend. So, what is the return on advertising, or the ROAS as they would say. And what they're looking to do is understand, okay, I have to collect these analytics that better understand where are these people coming from? How do they get to my site, to my store, to my whatever? And when they're using it, how do they they better move through that? What you're also seeing is that analytics is not only just for kind of the retail or financial services or things like that, but then they're also, you know, using that to make offers in those categories. When you move back to more, you know, take other companies that are building products and SaaS delivered products. They may actually go and use this analytics for making the product better. And one of the big reasons for that is maybe they're dialing back how many product managers they have. And they're looking to be more data driven about how they actually go and build the product out or enhance the product. So maybe they're, you know, an online video service and they want to understand why people are either using or not using the whiteboard inside the product. And they're collecting a lot of that product analytics in a big way so that they can go through that. And they're doing it in a constant manner. This first party type tracking within applications is growing rapidly by customers. >> So, let's talk about who wins in that. So, obviously the Cloud guys, AWS, Google and Azure. I want to come back and unpack that a little bit. Databricks and Snowflake, we reported on our last breaking analysis, it kind of on a collision course. You know, a couple years ago we were thinking, okay, AWS, Snowflake and Databricks, like perfect sandwich. And then of course they started to become more competitive. My sense is they still, you know, compliment each other in the field, right? But, you know, publicly, they've got bigger aspirations, they get big TAMs that they're going after. But it's interesting, the data shows that-- So, Snowflake was off the charts in terms of spending momentum and our EPR surveys. Our partner down in New York, they kind of came into line. They're both growing in terms of market presence. Databricks couldn't get to IPO. So, we don't have as much, you know, visibility on their financials. You know, Snowflake obviously highly transparent cause they're a public company. And then you got AWS, Google and Azure. And it seems like AWS appears to be more partner friendly. Microsoft, you know, depends on what market you're in. And Google wants to sell BigQuery. >> Yeah. >> So, what are you seeing in the public Cloud from a data platform perspective? >> Yeah. I think that was pretty astute in what you were talking about there, because I think of the three, Google is definitely I think a little bit behind in how they go to market with their partners. Azure's done a fantastic job of partnering with these companies to understand and even though they may have Synapse as their go-to and where they want people to go to do AI and ML. What they're looking at is, Hey, we're going to also be friendly with Snowflake. We're also going to be friendly with a Databricks. And I think that, Amazon has always been there because that's where the market has been for these developers. So, many, like Databricks' and the Snowflake's have gone there first because, you know, Databricks' case, they built out on top of S3 first. And going and using somebody's object layer other than AWS, was not as simple as you would think it would be. Moving between those. >> So, one of the financial meetups I said meetup, but the... It was either the CEO or the CFO. It was either Slootman or Scarpelli talking at, I don't know, Merrill Lynch or one of the other financial conferences said, I think it was probably their Q3 call. Snowflake said 80% of our business goes through Amazon. And he said to this audience, the next day we got a call from Microsoft. Hey, we got to do more. And, we know just from reading the financial statements that Snowflake is getting concessions from Amazon, they're buying in volume, they're renegotiating their contracts. Amazon gets it. You know, lower the price, people buy more. Long term, we're all going to make more money. Microsoft obviously wants to get into that game with Snowflake. They understand the momentum. They said Google, not so much. And I've had customers tell me that they wanted to use Google's AI with Snowflake, but they can't, they got to go to to BigQuery. So, honestly, I haven't like vetted that so. But, I think it's true. But nonetheless, it seems like Google's a little less friendly with the data platform providers. What do you think? >> Yeah, I would say so. I think this is a place that Google looks and wants to own. Is that now, are they doing the right things long term? I mean again, you know, you look at Google Analytics being you know, basically outlawed in five countries in the EU because of GDPR concerns, and compliance and governance of data. And I think people are looking at Google and BigQuery in general and saying, is it the best place for me to go? Is it going to be in the right places where I need it? Still, it's still one of the largest used databases out there just because it underpins a number of the Google services. So you almost get, like you were saying, forced into BigQuery sometimes, if you want to use the tech on top. >> You do strategy. >> Yeah. >> Right? You do strategy, you do messaging. Is it the right call by Google? I mean, it's not a-- I criticize Google sometimes. But, I'm not sure it's the wrong call to say, Hey, this is our ace in the hole. >> Yeah. >> We got to get people into BigQuery. Cause, first of all, BigQuery is a solid product. I mean it's Cloud native and it's, you know, by all, it gets high marks. So, why give the competition an advantage? Let's try to force people essentially into what is we think a great product and it is a great product. The flip side of that is, they're giving up some potential partner TAM and not treating the ecosystem as well as one of their major competitors. What do you do if you're in that position? >> Yeah, I think that that's a fantastic question. And the question I pose back to the companies I've worked with and worked for is, are you really looking to have vendor lock-in as your key differentiator to your service? And I think when you start to look at these companies that are moving away from BigQuery, moving to even, Databricks on top of GCS in Google, they're looking to say, okay, I can go there if I have to evacuate from GCP and go to another Cloud, I can stay on Databricks as a platform, for instance. So I think it's, people are looking at what platform as a service, database as a service they go and use. Because from a strategic perspective, they don't want that vendor locking. >> That's where Supercloud becomes interesting, right? Because, if I can run on Snowflake or Databricks, you know, across Clouds. Even Oracle, you know, they're getting into business with Microsoft. Let's talk about some of the Cloud players. So, the big three have reported. >> Right. >> We saw AWSs Cloud growth decelerated down to 20%, which is I think the lowest growth rate since they started to disclose public numbers. And they said they exited, sorry, they said January they grew at 15%. >> Yeah. >> Year on year. Now, they had some pretty tough compares. But nonetheless, 15%, wow. Azure, kind of mid thirties, and then Google, we had kind of low thirties. But, well behind in terms of size. And Google's losing probably almost $3 billion annually. But, that's not necessarily a bad thing by advocating and investing. What's happening with the Cloud? Is AWS just running into the law, large numbers? Do you think we can actually see a re-acceleration like we have in the past with AWS Cloud? Azure, we predicted is going to be 75% of AWS IAS revenues. You know, we try to estimate IAS. >> Yeah. >> Even though they don't share that with us. That's a huge milestone. You'd think-- There's some people who have, I think, Bob Evans predicted a while ago that Microsoft would surpass AWS in terms of size. You know, what do you think? >> Yeah, I think that Azure's going to keep to-- Keep growing at a pretty good clip. I think that for Azure, they still have really great account control, even though people like to hate Microsoft. The Microsoft sellers that are out there making those companies successful day after day have really done a good job of being in those accounts and helping people. I was recently over in the UK. And the UK market between AWS and Azure is pretty amazing, how much Azure there is. And it's growing within Europe in general. In the states, it's, you know, I think it's growing well. I think it's still growing, probably not as fast as it is outside the U.S. But, you go down to someplace like Australia, it's also Azure. You hear about Azure all the time. >> Why? Is that just because of the Microsoft's software state? It's just so convenient. >> I think it has to do with, you know, and you can go with the reasoning they don't break out, you know, Office 365 and all of that out of their numbers is because they have-- They're in all of these accounts because the office suite is so pervasive in there. So, they always have reasons to go back in and, oh by the way, you're on these old SQL licenses. Let us move you up here and we'll be able to-- We'll support you on the old version, you know, with security and all of these things. And be able to move you forward. So, they have a lot of, I guess you could say, levers to stay in those accounts and be interesting. At least as part of the Cloud estate. I think Amazon, you know, is hitting, you know, the large number. Laws of large numbers. But I think that they're also going through, and I think this was seen in the layoffs that they were making, that they're looking to understand and have profitability in more of those services that they have. You know, over 350 odd services that they have. And you know, as somebody who went there and helped to start yet a new one, while I was there. And finally, it went to beta back in September, you start to look at the fact that, that number of services, people, their own sellers don't even know all of their services. It's impossible to comprehend and sell that many things. So, I think what they're going through is really looking to rationalize a lot of what they're doing from a services perspective going forward. They're looking to focus on more profitable services and bringing those in. Because right now it's built like a layer cake where you have, you know, S3 EBS and EC2 on the bottom of the layer cake. And then maybe you have, you're using IAM, the authorization and authentication in there and you have all these different services. And then they call it EMR on top. And so, EMR has to pay for that entire layer cake just to go and compete against somebody like Mongo or something like that. So, you start to unwind the costs of that. Whereas Azure, went and they build basically ground up services for the most part. And Google kind of falls somewhere in between in how they build their-- They're a sort of layer cake type effect, but not as many layers I guess you could say. >> I feel like, you know, Amazon's trying to be a platform for the ecosystem. Yes, they have their own products and they're going to sell. And that's going to drive their profitability cause they don't have to split the pie. But, they're taking a piece of-- They're spinning the meter, as Ziyas Caravalo likes to say on every time Snowflake or Databricks or Mongo or Atlas is, you know, running on their system. They take a piece of the action. Now, Microsoft does that as well. But, you look at Microsoft and security, head-to-head competitors, for example, with a CrowdStrike or an Okta in identity. Whereas, it seems like at least for now, AWS is a more friendly place for the ecosystem. At the same time, you do a lot of business in Microsoft. >> Yeah. And I think that a lot of companies have always feared that Amazon would just throw, you know, bodies at it. And I think that people have come to the realization that a two pizza team, as Amazon would call it, is eight people. I think that's, you know, two slices per person. I'm a little bit fat, so I don't know if that's enough. But, you start to look at it and go, okay, if they're going to start out with eight engineers, if I'm a startup and they're part of my ecosystem, do I really fear them or should I really embrace them and try to partner closer with them? And I think the smart people and the smart companies are partnering with them because they're realizing, Amazon, unless they can see it to, you know, a hundred million, $500 million market, they're not going to throw eight to 16 people at a problem. I think when, you know, you could say, you could look at the elastic with OpenSearch and what they did there. And the licensing terms and the battle they went through. But they knew that Elastic had a huge market. Also, you had a number of ecosystem companies building on top of now OpenSearch, that are now domain on top of Amazon as well. So, I think Amazon's being pretty strategic in how they're doing it. I think some of the-- It'll be interesting. I think this year is a payout year for the cuts that they're making to some of the services internally to kind of, you know, how do we take the fat off some of those services that-- You know, you look at Alexa. I don't know how much revenue Alexa really generates for them. But it's a means to an end for a number of different other services and partners. >> What do you make of this ChatGPT? I mean, Microsoft obviously is playing that card. You want to, you want ChatGPT in the Cloud, come to Azure. Seems like AWS has to respond. And we know Google is, you know, sharpening its knives to come up with its response. >> Yeah, I mean Google just went and talked about Bard for the first time this week and they're in private preview or I guess they call it beta, but. Right at the moment to select, select AI users, which I have no idea what that means. But that's a very interesting way that they're marketing it out there. But, I think that Amazon will have to respond. I think they'll be more measured than say, what Google's doing with Bard and just throwing it out there to, hey, we're going into beta now. I think they'll look at it and see where do we go and how do we actually integrate this in? Because they do have a lot of components of AI and ML underneath the hood that other services use. And I think that, you know, they've learned from that. And I think that they've already done a good job. Especially for media and entertainment when you start to look at some of the ways that they use it for helping do graphics and helping to do drones. I think part of their buy of iRobot was the fact that iRobot was a big user of RoboMaker, which is using different models to train those robots to go around objects and things like that, so. >> Quick touch on Kubernetes, the whole DevOps World we just covered. The Cloud Native Foundation Security, CNCF. The security conference up in Seattle last week. First time they spun that out kind of like reinforced, you know, AWS spins out, reinforced from reinvent. Amsterdam's coming up soon, the CubeCon. What should we expect? What's hot in Cubeland? >> Yeah, I think, you know, Kubes, you're going to be looking at how OpenShift keeps growing and I think to that respect you get to see the momentum with people like Red Hat. You see others coming up and realizing how OpenShift has gone to market as being, like you were saying, partnering with those Clouds and really making it simple. I think the simplicity and the manageability of Kubernetes is going to be at the forefront. I think a lot of the investment is still going into, how do I bring observability and DevOps and AIOps and MLOps all together. And I think that's going to be a big place where people are going to be looking to see what comes out of CubeCon in Amsterdam. I think it's that manageability ease of use. >> Well Rob, I look forward to working with you on behalf of the whole Cube team. We're going to do more of these and go out to some shows extract the signal from the noise. Really appreciate you coming into our studio. >> Well, thank you for having me on. Really appreciate it. >> You're really welcome. All right, keep it right there, or thanks for watching. This is Dave Vellante for the Cube. And we'll see you next time. (light music)

>> From the Cube Studios in Palo Alto in Boston bringing you data-driven insights from the Cube and ETR. This is Breaking Analysis with Dave Vellante. >> The unraveling of market enthusiasm continued in Q4 of 2022 with the earnings reports from the US hyperscalers, the big three now all in. As we said earlier this year, even the cloud is an immune from the macro headwinds and the cracks in the armor that we saw from the data that we shared last summer, they're playing out into 2023. For the most part actuals are disappointing beyond expectations including our own. It turns out that our estimates for the big three hyperscaler's revenue missed by 1.2 billion or 2.7% lower than we had forecast from even our most recent November estimates. And we expect continued decelerating growth rates for the hyperscalers through the summer of 2023 and we don't think that's going to abate until comparisons get easier. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis, we share our view of what's happening in cloud markets not just for the hyperscalers but other firms that have hitched a ride on the cloud. And we'll share new ETR data that shows why these trends are playing out tactics that customers are employing to deal with their cost challenges and how long the pain is likely to last. You know, riding the cloud wave, it's a two-edged sword. Let's look at the players that have gone all in on or are exposed to both the positive and negative trends of cloud. Look the cloud has been a huge tailwind for so many companies like Snowflake and Databricks, Workday, Salesforce, Mongo's move with Atlas, Red Hats Cloud strategy with OpenShift and so forth. And you know, the flip side is because cloud is elastic what comes up can also go down very easily. Here's an XY graphic from ETR that shows spending momentum or net score on the vertical axis and market presence in the dataset on the horizontal axis provision or called overlap. This is data from the January 2023 survey and that the red dotted lines show the positions of several companies that we've highlighted going back to January 2021. So let's unpack this for a bit starting with the big three hyperscalers. The first point is AWS and Azure continue to solidify their moat relative to Google Cloud platform. And we're going to get into this in a moment, but Azure and AWS revenues are five to six times that of GCP for IaaS. And at those deltas, Google should be gaining ground much faster than the big two. The second point on Google is notice the red line on GCP relative to its starting point. While it appears to be gaining ground on the horizontal axis, its net score is now below that of AWS and Azure in the survey. So despite its significantly smaller size it's just not keeping pace with the leaders in terms of market momentum. Now looking at AWS and Microsoft, what we see is basically AWS is holding serve. As we know both Google and Microsoft benefit from including SaaS in their cloud numbers. So the fact that AWS hasn't seen a huge downward momentum relative to a January 2021 position is one positive in the data. And both companies are well above that magic 40% line on the Y-axis, anything above 40% we consider to be highly elevated. But the fact remains that they're down as are most of the names on this chart. So let's take a closer look. I want to start with Snowflake and Databricks. Snowflake, as we reported from several quarters back came down to Earth, it was up in the 80% range in the Y-axis here. And it's still highly elevated in the 60% range and it continues to move to the right, which is positive but as we'll address in a moment it's customers can dial down consumption just as in any cloud. Now, Databricks is really interesting. It's not a public company, it never made it to IPO during the sort of tech bubble. So we don't have the same level of transparency that we do with other companies that did make it through. But look at how much more prominent it is on the X-axis relative to January 2021. And it's net score is basically held up over that period of time. So that's a real positive for Databricks. Next, look at Workday and Salesforce. They've held up relatively well, both inching to the right and generally holding their net scores. Same from Mongo, which is the brown dot above its name that says Elastic, it says a little gets a little crowded which Elastic's actually the blue dot above it. But generally, SaaS is harder to dial down, Workday, Salesforce, Oracles, SaaS and others. So it's harder to dial down because commitments have been made in advance, they're kind of locked in. Now, one of the discussions from last summer was as Mongo, less discretionary than analytics i.e. Snowflake. And it's an interesting debate but maybe Snowflake customers, you know, they're also generally committed to a dollar amount. So over time the spending is going to be there. But in the short term, yeah maybe Snowflake customers can dial down. Now that highlighted dotted red line, that bolded one is Datadog and you can see it's made major strides on the X-axis but its net score has decelerated quite dramatically. Openshift's momentum in the survey has dropped although IBM just announced that OpenShift has a a billion dollar ARR and I suspect what's happening there is IBM consulting is bundling OpenShift into its modernization projects. It's got a, that sort of captive base if you will. And as such it's probably not as top of mind to the respondents but I'll bet you the developers are certainly aware of it. Now the other really notable call out here is CloudFlare, We've reported on them earlier. Cloudflare's net score has held up really well since January of 2021. It really hasn't seen the downdraft of some of these others, but it's making major major moves to the right gaining market presence. We really like how CloudFlare is performing. And the last comment is on Oracle which as you can see, despite its much, much lower net score continues to gain ground in the market and thrive from a profitability standpoint. But the data pretty clearly shows that there's a downdraft in the market. Okay, so what's happening here? Let's dig deeper into this data. Here's a graphic from the most recent ETR drill down asking customers that said they were going to cut spending what technique they're using to do so. Now, as we've previously reported, consolidating redundant vendors is by far the most cited approach but there's two key points we want to make here. One is reducing excess cloud resources. As you can see in the bars is the second most cited technique and it's up from the previous polling period. The second we're not showing, you know directly but we've got some red call outs there. Reducing cloud costs jumps to 29% and 28% respectively in financial services and tech telco. And it's much closer to second. It's basically neck and neck with consolidating redundant vendors in those two industries. So they're being really aggressive about optimizing cloud cost. Okay, so as we said, cloud is great 'cause you can dial it up but it's just as easy to dial down. We've identified six factors that customers tell us are affecting their cloud consumption and there are probably more, if you got more we'd love to hear them but these are the ones that are fairly prominent that have hit our radar. First, rising mortgage rates mean banks are processing fewer loans means less cloud. The crypto crash means less trading activity and that means less cloud resources. Third lower ad spend has led companies to reduce not only you know, their ad buying but also their frequency of running their analytics and their calculations. And they're also often using less data, maybe compressing the timeframe of the corpus down to a shorter time period. Also very prominent is down to the bottom left, using lower cost compute instances. For example, Graviton from AWS or AMD chips and tiering storage to cheaper S3 or deep archived tiers. And finally, optimizing based on better pricing plans. So customers are moving from, you know, smaller companies in particular moving maybe from on demand or other larger companies that are experimenting using on demand or they're moving to spot pricing or reserved instances or optimized savings plans. That all lowers cost and that means less cloud resource consumption and less cloud revenue. Now in the days when everything was on prem CFOs, what would they do? They would freeze CapEx and IT Pros would have to try to do more with less and often that meant a lot of manual tasks. With the cloud it's much easier to move things around. It still takes some thinking and some effort but it's dramatically simpler to do so. So you can get those savings a lot faster. Now of course the other huge factor is you can cut or you can freeze. And this graphic shows data from a recent ETR survey with 159 respondents and you can see the meaningful uptick in hiring freezes, freezing new IT deployments and layoffs. And as we've been reporting, this has been trending up since earlier last year. And note the call out, this is especially prominent in retail sectors, all three of these techniques jump up in retail and that's a bit of a concern because oftentimes consumer spending helps the economy make a softer landing out of a pullback. But this is a potential canary in the coal mine. If retail firms are pulling back it's because consumers aren't spending as much. And so we're keeping a close eye on that. So let's boil this down to the market data and what this all means. So in this graphic we show our estimates for Q4 IaaS revenues compared to the "actual" IaaS revenues. And we say quote because AWS is the only one that reports, you know clean revenue and IaaS, Azure and GCP don't report actuals. Why would they? Because it would make them look even, you know smaller relative to AWS. Rather, they bury the figures in overall cloud which includes their, you know G-Suite for Google and all the Microsoft SaaS. And then they give us little tidbits about in Microsoft's case, Azure, they give growth rates. Google gives kind of relative growth of GCP. So, and we use survey data and you know, other data to try to really pinpoint and we've been covering this for, I don't know, five or six years ever since the cloud really became a thing. But looking at the data, we had AWS growing at 25% this quarter and it came in at 20%. So a significant decline relative to our expectations. AWS announced that it exited December, actually, sorry it's January data showed about a 15% mid-teens growth rate. So that's, you know, something we're watching. Azure was two points off our forecast coming in at 38% growth. It said it exited December in the 35% growth range and it said that it's expecting five points of deceleration off of that. So think 30% for Azure. GCP came in three points off our expectation coming in 35% and Alibaba has yet to report but we've shaved a bid off that forecast based on some survey data and you know what maybe 9% is even still not enough. Now for the year, the big four hyperscalers generated almost 160 billion of revenue, but that was 7 billion lower than what what we expected coming into 2022. For 2023, we're expecting 21% growth for a total of 193.3 billion. And while it's, you know, lower, you know, significantly lower than historical expectations it's still four to five times the overall spending forecast that we just shared with you in our predictions post of between 4 and 5% for the overall market. We think AWS is going to come in in around 93 billion this year with Azure closing in at over 71 billion. This is, again, we're talking IaaS here. Now, despite Amazon focusing investors on the fact that AWS's absolute dollar growth is still larger than its competitors. By our estimates Azure will come in at more than 75% of AWS's forecasted revenue. That's a significant milestone. AWS is operating margins by the way declined significantly this past quarter, dropping from 30% of revenue to 24%, 30% the year earlier to 24%. Now that's still extremely healthy and we've seen wild fluctuations like this before so I don't get too freaked out about that. But I'll say this, Microsoft has a marginal cost advantage relative to AWS because one, it has a captive cloud on which to run its massive software estate. So it can just throw software at its own cloud and two software marginal costs. Marginal economics despite AWS's awesomeness in high degrees of automation, software is just a better business. Now the upshot for AWS is the ecosystem. AWS is essentially in our view positioning very smartly as a platform for data partners like Snowflake and Databricks, security partners like CrowdStrike and Okta and Palo Alto and many others and SaaS companies. You know, Microsoft is more competitive even though AWS does have competitive products. Now of course Amazon's competitive to retail companies so that's another factor but generally speaking for tech players, Amazon is a really thriving ecosystem that is a secret weapon in our view. AWS happy to spin the meter with its partners even though it sells competitive products, you know, more so in our view than other cloud players. Microsoft, of course is, don't forget is hyping now, we're hearing a lot OpenAI and ChatGPT we reported last week in our predictions post. How OpenAI is shot up in terms of market sentiment in ETR's emerging technology company surveys and people are moving to Azure to get OpenAI and get ChatGPT that is a an interesting lever. Amazon in our view has to have a response. They have lots of AI and they're going to have to make some moves there. Meanwhile, Google is emphasizing itself as an AI first company. In fact, Google spent at least five minutes of continuous dialogue, nonstop on its AI chops during its latest earnings call. So that's an area that we're watching very closely as the buzz around large language models continues. All right, let's wrap up with some assumptions for 2023. We think SaaS players are going to continue to be sticky. They're going to be somewhat insulated from all these downdrafts because they're so tied in and customers, you know they make the commitment up front, you've got the lock in. Now having said that, we do expect some backlash over time on the onerous and generally customer unfriendly pricing models of most large SaaS companies. But that's going to play out over a longer period of time. Now for cloud generally and the hyperscalers specifically we do expect accelerating growth rates into Q3 but the amplitude of the demand swings from this rubber band economy, we expect to continue to compress and become more predictable throughout the year. Estimates are coming down, CEOs we think are going to be more cautious when the market snaps back more cautious about hiring and spending and as such a perhaps we expect a more orderly return to growth which we think will slightly accelerate in Q4 as comps get easier. Now of course the big risk to these scenarios is of course the economy, the FED, consumer spending, inflation, supply chain, energy prices, wars, geopolitics, China relations, you know, all the usual stuff. But as always with our partners at ETR and the Cube community, we're here for you. We have the data and we'll be the first to report when we see a change at the margin. Okay, that's a wrap for today. I want to thank Alex Morrison who's on production and manages the podcast, Ken Schiffman as well out of our Boston studio getting this up on LinkedIn Live. Thank you for that. Kristen Martin also and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our Editor-in-Chief over at siliconangle.com. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com, at siliconangle.com where you can see all the data and you want to get in touch. Just all you can do is email me david.vellante@siliconangle.com or DM me @dvellante if you if you got something interesting, I'll respond. If you don't, it's either 'cause I'm swamped or it's just not tickling me. You can comment on our LinkedIn post as well. And please check out ETR.ai for the best survey data in the enterprise tech business. This is Dave Vellante for the Cube Insights powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (gentle upbeat music)

>>Hello and run. Welcome back to the Cube's live coverage here. Day three of Cube's coverage, two sets, wall to wall coverage. Third set upstairs in the Executive Briefing Center. I'm John Furry, host of the Cube with Dave Alon. Two other hosts here. Lot of action. Dave. The cheer here is the CEO of MongoDB, exclusive post on Silicon Angle for your prior to the event. Thanks for doing that. Great to see >>You. Likewise. Nice to see you >>Coming on. See you David. So it's great to catch up. Prior to the event for that exclusive story on ecosystem, your perspective that resonated with a lot of the people. The traffic on that post and comments have been off the charts. I think we're seeing a ecosystem kind of surge and not change over, but like a an and ISV and new platform. So I really appreciate your perspective as a platform ISV for aws. What's it like? What's this event like? What's your learnings? What's your takeaway from your customers here this year? What's the most important story going on? >>First of all, I think being here is important for us because we have so many customers and partners here. In fact, if you look at the customers that Amazon themselves announced about two thirds of those customers or MongoDB customers. So we have a huge overlap in customers here. So just connecting with customers and partners has been important. Obviously a lot of them are thinking about their plans going to next year. So we're kind of meeting with them to think about what their priorities are and how we can help. And also we're sharing a little bit of our product roadmap in terms of where we're going and helping them think through like how they can best use Mongadi B as they think about their data strategy, you know, going to next year. So it's been a very productive end. We have a lot of people here, a lot of sales people, a lot of product people, and there's tons of customers here. So we can get a lot accomplished in a few days. >>Dave and I always talk on the cube. Well, Dave always goes to the TAM expansion question. Expanding your total stressful market, the market is changing and you guys have a great position growing positioned. How do you look at the total addressable market for Mongo changing? Where's the growth gonna come from? How do you see your role in the market and how does that impact your current business model? >>Yeah, our whole goal is to really enable developers to think about Mongo, to be first when they're building modern applications. So what we've done is first built a fir, a first class transactional platform and now we've kind expanding the platform to do things like search and analytics, right? And so we are really offering a broad set of capabilities. Now our primary focus is the developer and helping developers build these amazing applications and giving them tools to really do so in a very quick way. So if you think about customers like Intuit, customers like Canva, customers like, you know, Verizon, at and t, you know, who are just using us to really transform their business. It's either to build new applications quickly to do things at a certain level of performance of scale they've never done before. And so really enabling them to do so much more in building these next generation applications that they can build anywhere else. >>So I was listening to McDermott, bill McDermott this morning. Yeah. And you listen to Bill, you just wanna buy from the guy, right? He's amazing. But he was basically saying, look, companies like he was talking about ServiceNow that could help organizations digitally transform, et cetera, but make money or save money or in a good position. And I said, right, Mongo's definitely one of those companies. What are those conversations like here? I know you've been meeting with customers, it's a different environment right now. There's a lot of uncertainty. I, I was talking to one of your customers said, yeah, I'm up for renewal. I love Mongo. I'm gonna see if they can stage my payments a little bit. You know, things like that. Are those conversations? Yeah, you know, similar to what >>You having, we clearly customers are getting a little bit more prudent, but we haven't seen any kind of like slow down terms of deal cycles or, or elongated sales cycles. I mean, obviously different customers in different sectors are going through different issues. What we are seeing customers think about is like how can I, you know, either drive more efficiency in my business like and big part of that is modernization of my existing legacy tech stack. How can maybe consolidate to a fewer set of vendors? I think they like our broad platform story. You know, rather than using three or four different databases, they can use MongoDB to do everything. So that that resonates with customers and the fact that they can move fast, right? Developer productivity is a proxy for innovation. And so being able to move fast to either seize new opportunities or respond to new threats is really, you know, top of mind for still C level executive. >>So can your software, you're right, consolidation is the number one way in which people are save money. Can your software be deflationary? I mean, I mean that in a good way. So >>I was just meeting with a customer who was thinking about Mongo for their transactional platform, elastic for the search platform and like a graph database for a special use case. And, and we said you can do all that on MongoDB. And he is like, oh my goodness, I can consolidate everything. Have one elegant developer interface. I can keep all the data in one place. I can easily access that data. And that makes so much more sense than having to basically use a bunch of peace parts. And so that's, that's what we're seeing more and more interest from customers about. >>So one of the things I want to get your reaction to is, I was saying on the cube, now you can disagree with me if you want, but at, in the cloud native world at Cuban and Kubernetes was going through its hype cycle. The conversation went to it's getting boring. And that's good cause they want it to be boring. They don't want people to talk about the run time. They want it to be working. Working is boring. That's invisible. It's good, it's sticky, it's done. As you guys have such a great sticky business model, you got a great install base. Mongo works, people are happy, they like the product. So it's kind of working, I won't wanna say boring cuz that's, it's irrelevant. What's the exciting things that Mongo's bringing on top of the existing base of product that is gonna really get your clients and prospects enthused about the innovation from Mongo? What's what cuz it's, it's almost like electricity in a way. You guys are very utility in, in the way you do, but it's growing. But is there an exciting element coming that you see that they should pay attention to? What's, what's your >>Vision that, right, so if you look back over the last 10, 15 years, there's been big two big platform shifts, mobile and cloud. I think the next big platform shift is from what I call dumb apps to smart apps. So building more intelligence into applications. And what that means is automating human decision making and embedding that into applications. So we believe that to be a fundamentally a developer problem to solve, yes, you need data scientist to build the machine learning algorithms to train the models. Yeah. But ultimately you can't really deploy, deployed at scale unless you give developers the tools to build those smart applications that what we focused on. And a big part of that is what we call application driven analytics where people or can, can embed that intelligence into applications so that they can instead rather having humans involved, they can make decisions faster, drive to businesses more quickly, you know, shorten it's short and time to market, et cetera. >>And so your strategy to implement those smart apps is to keep targeting the developer Yes. And build on that >>Base. Correct. Exactly. So we wanna essentially democratize the ability for any customer to use our tools to build a smart applications where they don't have the resources of a Google or you know, a large tech company. And that's essentially resonating with our customer base. >>We, we were talking about this earlier after Swami's keynote, is most companies struggle to put data at the core of their business. And I don't mean centralizing it all in a single place as data's everywhere, but, but really organizing their company and democratizing data so people can make data decisions. So I think what you're saying, essentially Atlas is the platform that you're gonna inject intelligence into and allow developers to then build applications that are, you know, intelligent, smart with ai, machine intelligence, et cetera. And that's how the ones that don't have the resources of a Google or an Amazon become correct the, that kind of AI company if >>You, and that's, that's the whole purpose of a developer data platform is to enable them to have the tools, you know, to have very sophisticated analytics, to have the ability to do very sophisticated indexes, optimized for analytics, the ability to use data lakes for very efficient storage and retrieval of data to leverage, you know, edge devices to be able to capture and synchronize data. These are all critical elements to build these next generation applications. And you have to do that, but you don't want to stitch together a thousand primitives. You want to have a platform to do that. And that's where we really focus. >>You know, Dave, Dave and I, three, two days, Dave and I, Dave Ante and I have been talking a lot about developer productivity. And one observation that's now validated is that developers are setting the pace for innovation. Correct? And if you look at the how they, the language that they speak, it's not the same language as security departments, right? They speak almost like different languages, developer and security, and then you got data language. But the developers are making choices of self-service. They can accelerate, they're driving the behavior behavior into the organizations. And this is one of the things I wrote about on Friday last week was the organizational changes are changing cuz the developers set the pace. You can't force tooling down their throat. They're gonna go with what's easy, what's workable. If you believe that to be true, then all the security's gonna be in the developer pipeline. All the innovations we've driven off that high velocity developer site, we're seeing success of security being embedded there with the developers. What are you gonna bring up to that developer layer that's going to help with security, help with maybe even new things, >>Right? So, you know, it's, it's almost a cliche to say now software is in the world, right? Because every company's value props is driven by, it's either enabled to find or created through software. What that really means is that developers are eating all the work, right? And you're seeing, you saw in DevOps, right? Where developers basically enro encroach into the ops world and made infrastructure a programmable interface. You see developers, to your point, encroaching in security, embedding more and more security features into their applications. We believe the same thing's gonna happen with data scientists and business analysts where developers are gonna embed that functionality that was done by different domains in the Alex world and embed that capability into apps themselves. So these applications are just naturally smarter. So you don't need someone to look at a dashboard and say, aha, there's some insight here now I need to go make a decision. The application will do that for you and actually make that decision for you so you can move that much more quickly to run your business either more efficiently or to drive more, you know, revenue. >>Well the interesting thing about your business is cuz you know, you got a lot of transactional activity going on and the data, the way I would say what you just described is the data stack and the application stacks are coming together, right? And you're in a really good position, I think to really affect that. You think about we've, we've operationalized so many systems, we really haven't operationalized our data systems. And, and particularly as you guys get more into analytics, it becomes an interesting, you know, roadmap for Mongo and your customers. How do you see that? >>Yeah, so I wanna be clear, we're not trying to be a data warehouse, I get it. We're not trying to be like, you know, go compete. In fact, we have nice partnership with data bricks and so forth. What we are really trying to do is enable developers to instrument and build these applications that embed analytics. Like a good analogy I'd use is like Google Maps. You think about how sophisticated Google Maps has, and I use that because everyone has used Google Maps. Yeah. Like in the old, I was old enough to print out the directions, map quest exactly, put it on my lap and drive and look down. Now have this device that tells me, you know, if there's a traffic, if there's an accident, if there's something you know, going will reroute me automatically. And what that app is doing is embedding real time data into, into its decision making and making the decision for you so that you don't have to think about which road to take. Right? You, you're gonna see that happen across almost every application over the next X number of years where these applications are gonna become so much smarter and make these decisions for you. So you can just move so much more quickly. >>Yeah. Talk about the company, what status of the company, your growth plans. Obviously you're seeing a lot of news and Salesforce co CEO just resigned, layoffs at cnn, layoffs at DoorDash. You know, tech unfortunately is not impacted, thank God. I'm not that too bad. Certainly in cloud's not impacted it is impacting some of the buying behavior. We talked about that. What's going on with the company head count? What's your goals? How's the team doing? What are your priorities? >>Right? So we we're going after a big, big opportunity. You know, we recognize, obviously the market's a little choppy right now, but our long term, we're very bullish on the opportunity. We believe that we can be the modern developer data platform to build these next generation applications in terms of costs. We're obviously being a little bit more judicious about where we're investing, but we see big, big opportunities for us. And so our overall cost base will grow next year. But obviously we also recognize that there's ways to drive more efficiency. We're at a scale now. We're a 1.2 billion business. We're gonna announce our Q3 results next week. So we'll talk a little bit more about, you know, what we're seeing in the business next week. But we, we think we're a business that's growing fast. You know, we grew, you know, over 50, 50% and so, so we're pretty fast growing business. Yeah. You see? >>Yeah, Tuesday, December 6th you guys announce Exactly. Course is a big, we always watch and love it. So, so what I'm hearing is you're not, you're not stepping on the brakes, you're still accelerating growth, but not at all costs. >>Correct. The term we're using is profitable growth. We wanna, you know, you know, drive the business in a way that we think continues to seize the opportunity. But we also, we always exercise discipline. You know, I, I'm old enough where I had to deal with 2000 and 2008, so, you know, seen the movie before, I'm not 28 and have not seen these markets. And so obviously some are, you know, emerging leaders have not seen these kinds of markets before. So we're kind of helping them think about how to continue to be disciplined. And >>I like that reference to two thousand.com bubble and the financial crisis of 2008. I mentioned this to you when we chat, I'd love to get your thoughts. Now looking back for reinvent, Amazon wasn't a force in, in 2008. They weren't really that big debt yet. Know impact agility, wasn't it? They didn't hit that, they didn't hit that cruising altitude of the value pro cloud agility, time of value moving fast. Now they are. So this is the first time that they're a part of the economic equation. You're on, you're on in the middle of it with Amazon. They could be a catalyst to recover faster if plan properly. What's your CEO take on just that general and other CEOs might be watching and saying, Hey, you know, if I play this right, I could leverage the cloud. You know, Adams is leading into the cloud during a recession. Okay, I get that. But specifically there might be a tactic. What's your view on >>That? I mean, what, what we're seeing the, the hyperscalers do is really continue to kind of compete at the raw infrastructure level on storage, on compute, on network performance, on security to provide the, the kind of the building blocks for companies like Monga Beach really build on. So we're leveraging that price performance curve that they're pushing. You know, they obviously talk about Graviton three, they're talking about their training model chip sets and their inference model chip sets and their security chip sets. Which is great for us because we can leverage those capabilities to build upon that. And I think, you know, if you had asked me, you know, in 2008, would we be talking about chip sets in 2022? I'd probably say, oh, we're way beyond that. But what it really speaks to is those things are still so profoundly important. And I think that's where you can see Amazon and Google and Microsoft compete to provide the best underlying infrastructure where companies like mongadi we can build upon and we can help customers leverage that to really build the next generation. >>I'm not saying it's 2008 all over again, but we have data from 2008 that was the first major tailwind for the cloud. Yeah. When the CFO said we're going from CapEx to opex. So we saw that. Now it's a lot different now it's a lot more mature >>I think. I think there's a fine tuning trend going on where people are right sizing, fine tuning, whatever you wanna call it. But a craft is coming. A trade craft of cloud management, cloud optimization, managing the cost structures, tuning, it's a crafting, it's more of a craft. It's kind of seems like we're >>In that era, I call it cost optimization, that people are looking to say like, I know I'm gonna invest but I wanna be rational and more thoughtful about where I invest and why and with whom I invest with. Versus just like, you know, just, you know, everyone getting a 30% increase in their opex budgets every year. I don't think that's gonna happen. And so, and that's where we feel like it's gonna be an opportunity for us. We've kind of hit scap velocity. We've got the developer mind share. We have 37,000 customers of all shapes and sizes across the world. And that customer crown's only growing. So we feel like we're a place where people are gonna say, I wanna standardize among the >>Db. Yeah. And so let's get a great quote in his keynote, he said, if you wanna save money, the place to do it is in the cloud. >>You tighten the belt, which belt you tightening? The marketplace belt, the wire belt. We had a whole session on that. Tighten your belt thing. David Chair, CEO of a billion dollar company, MongoDB, continue to grow and grow and continue to innovate. Thanks for coming on the cube and thanks for participating in our stories. >>Thanks for having me. Great to >>Be here. Thank. Okay, I, Dave ante live on the show floor. We'll be right back with our final interview of the day after this short break, day three coming to close. Stay with us. We'll be right back.

>> Hello, wonderful humans and welcome back to theCUBE. We are live from Las Vegas, Nevada, this week at AWS Reinvent. I am joined by analyst and 10 year reinvent veteran John Furrier. John, pleasure to join you today. >> Great to see you, great event. This is 10 years. We've got great guests coming on the Q3 days of after this wall to wall, we'll lose our voice every year, Thursday >> Host: I can feel the energy. Can you feel the volume already? >> Yes. Everyone's getting bigger, stronger, in the marketplace seeing a lot more activity new players coming into the cloud. Ones that have been around for 10 years or growing up and turning into platforms and just the growth of software in the industry is phenomenal. Our next guest is going to be great to chat about. >> I know it's funny you mentioned marketplace. We're going to be talking marketplace, in our next segment. We're bringing back a Cube alumni Chris Casey welcome back to the show. How, how you Feeling today? >> Thank you for having me. Yeah, I mean this week is the most exciting week of the year for us at AWS and you know, it's just a fantastic energy. You mentioned it before, to be here in Las Vegas at Reinvent and thank you very much for having me back. It's great to talk to John last year and lovely to meet you and talk to you this year. >> It is, it is our pleasure. It is definitely the biggest event of the year. It's wild that Amazon would do this on the biggest online shopping day of the year as well. It goes to show about the boldness and the bravery of the team, which is very impressive. So you cover a few different things at AWS So you cover a few different things at AWS you're talking about and across industries as well. Can you talk to me a little bit about why the software alliances and the data exchange are so important to the partner organization at AWS? >> Yeah, it really comes back to the importance to, to the AWS customer. As we've been working with customers over the, you know the past few years especially, and they've been embarking on their enterprise transformation and their digital transformation moving workloads to to the cloud, they've really been asking us for more and more support from the AWS ecosystem, and that includes native AWS services as well as partners to really help them start to solve some of the industry specific use cases and challenges that they're facing and really incorporate those as part of the enterprise transformation journey that they're embarking on with AWS. What, how that translates back to the AWS marketplace and the partner organization is customers have told us they're really looking for us to have the breadth and depth of the ecosystem of partners available to them that have the intellectual property that solves very niche use cases and workloads that they're looking to migrate to the cloud. A lot of the time that furnishes itself as an independent software vendor and they have software that the customer is trying to use to solve, you know an insurance workflow or an analytics workflow for your utility company as well as third party data that they need to feed into that software. And so my team's responsibility is helping work backwards from the customer need there and making sure that we have the partners available to them. Ideally in the AWS marketplace so they can go and procure those products and make them part of solutions that they're trying to build or migrate to AWS. >> A lot of success in marketplace over the past couple years especially during the pandemic people were buying and procuring through the marketplace. You guys have changed some of the operational things, data exchange enterprise sellers or your sales reps can sell in there. The partners have been glowingly saying great things about how it's just raining money for them if they do it right. And some are like, well, I don't get the marketplace. So there's a, there's kind of a new game in town and the marketplace with some of the successes. What, what is this new momentum that's happening? Is it just people are getting more comfortable they're doing it right? How does the marketplace work effectively? >> Yeah, I mean, marketplace has been around for for 10 years as well as the AWS partner organization. >> Host: It's like our coverage. >> Yes, just like. >> Host: What a nice coincidence. Decades all around happy anniversary everyone. >> Yeah, everyone's selling, celebrating the 10 year birthday, but I think to your point, John, you know, we we've continued iterate on features and functionality that have made the partner experience a much more welcoming digital experience for them to go to market with AWS. So that certainly helped and we've seen more and more customers start to adopt marketplace especially for, for some of their larger applications that they're trying to transform on the cloud. And that extends into industry verticals as well as horizontal sort of business applications whether they be ERP systems like Infor the customers are trying to procure through the marketplace. And I think even for our partners, it's customer driven. You know, we, we've, we've heard from our customers that the, the streamlining the payments and procurement process is a really key benefit for them procuring by the marketplace and also the extra governance and control and visibility they get on their third party licensing contracts is a really material benefit for them which is helping our partners lean in to marketplace as a as a digital channel for them to go to market with us. >> And also you guys have this program it's what's it called enterprise buying or something where clients can just take their spend and move it over into other products like MongoDB more Mongo gimme some more Splunk, gimme some more influence. I mean all these things are possible now, right. For some of the partners. Isn't that, that's like that's like found money for the, for the partners. >> Yeah, going back to what I said before about the AWS ecosystem, we're really looking to help customers holistically with regard to that, and certainly when customers are looking to make commitments to AWS and and move a a large swath of workloads to AWS we want to make sure they can benefit from that commitment not only from native AWS services but also third party data and software applications that they might be procuring through the marketplace. So certainly for the procurement teams not only is there technical benefits for them on the marketplace and you know foresters total economic impact study really helped quantify that for us more recently. You know, 66% of time saving for procurement professionals. >> Host: Wow. >> Which is when you calculate that in hours in person weeks or a year, that's a lot of time on undifferentiated heavy lifting that they can now be doing on value added activities. >> Host: That's a massive shift for >> Yeah, massive shift. So that in addition, you know, to, you know, some of the more contractual and commercial benefits is really helping customers look holistically at how AWS is helping them transform with third party applications and data. >> I want to stick on customers for a second 'cause in my show notes are some pretty well known customers and you mentioned in for a moment ago can you tell us a little bit about what's going on with Ferrari? >> Chris: Sure. So in four is one of our horizontal business application partners and sellers in the AWS marketplace and they sell ERP systems so helping enterprises with resource planning and Ferrari is obviously a very well known brand and you know, the oldest and most successful >> May have heard of them. >> Chris: Yes. Right. The most successful formula one racing team and Ferrari, you know a really meaningful customer for AWS from multiple angles whether they're using AWS to enhance their car design, as well as their fan engagement, as well as their actual end car consumer experience. But as it specifically relates to marketplace as part of Ferrari's technical transformation they were looking to upgrade their ERP system. And so they went through a whole swath of vendors that they wanted to assess and they actually chose Infor as their ERP system. And one of the reasons was >> Nice. >> Chris: because Infor actually have an automotive specific instance of their SaaS application. So when we're talking about really solving for some of those niche challenges for customers who operate in an industry, that was one of the key benefits. And then as an added bonus for Ferrari being able to procure that software through the AWS marketplace gave them all the procurement benefits that we just talked about. So it's super exciting that we're able to play a, you know a part in accelerating that digital transformation with Ferrari and also help Infor in terms of getting a really meaningful customer using their software services on AWS. >> Yeah. Putting a new meaning to turn key your push start. (laughing) >> You mentioned horizontal services earlier. What is it all about there? What's new there? We're hearing, I'm expecting to see that in the keynote tomorrow. Horizontal and vertical solutions and let's get the CEOs. What, what's the focus there? What's this horizontal focus for you? >> Yeah, I, I think the, the big thing is is really helping line of business users. So people in operations or marketing functions, that our customers, see the the partners and the solutions that they use on a daily basis today and how they can actually help accelerate their overall enterprise transformation. With those partners, now on AWS. Historically, you know, those line of business users might not have cared where an application historically ran whether it was on-prem or on AWS but now just the depth of those transformation journeys their enterprises are on that's really the next frontier of applications and use cases that many of our customers are saying they want to move to AWS. >> John: And what are some of those horizontal examples that you see emerging? >> So Salesforce is, is probably one, one of the best ones to call out there. And really the two meaningful things Salesforce have done there is a deep integration with our ML and AI services like SageMaker so people can actually perform some of those activities without leaving the Salesforce application. And then AWS and Salesforce have worked on a unified developer experience, which really helps remove friction in terms of data flows for anyone that's trying to build on both of those services. So the partnership with horizontal business applications like Salesforce is much deeper than just to go to market. It's also on the build side to help make it much more seamless for customers as they're trying to migrate to Salesforce on AWS as an example there. >> It's like having too many tabs open at once, everybody wants it all in one place all at one time. >> Chris: Yeah. >> And it makes sense that you're doing so much in, in the partner marketplace. Let's talk a little bit more about the data exchange. How, how is this intertwined with your vertical and horizontal efforts that the team's striving as well as with another big name example that folks know probably only because of the last few, few years, excuse me, with Moderna? Can you tell us a little more about that? >> Sure. I think when we're, when we're talking to customers about their needs when they're operating in a specific industry, but it probably goes for all customers and enterprise customers especially when they're thinking about software. Almost always that software also needs data to actually be analyzed or processed through it for really the end business outcome to be achieved. And so we're really making a conscious effort to really help our partners integrate with solutions that the AWS field teams and business development teams are talking to customers about and help tie those solutions to customer use cases, rather than it being an engagement with a specific customer on a product by product basis. And certainly software and and data going together is a really nice combination that many customers are looking for us to solve for and for looking for us to create pairings based on other customer needs or use cases that we've historically solved for in the past. >> I mean, with over a million customers, it's hard to imagine anyone could have more use cases to pull from when we're talking about these different instances >> Right. The challenge actually is identifying which are the key ones for each of the industries and which are the ones that are going to help move the needle the most for customers in there, it's, it's not an absence of selection in that case. >> Host: Right. (laughter) I can imagine. I can imagine that's actually the challenge. >> Chris: Yeah. >> Yeah. >> But it's really important. And then more specifically on the data exchange, you know I think it goes back to one of the leadership principles that we launched last year. The two new leadership principles, success and scale bring broad responsibility. You know, we take that very seriously at AWS and we think about that in our actions with our native services, but also in terms of, you know, the availability of partner solutions and then ultimately the end customer outcomes that we can help achieve. And I think Moderna's a great example of that. Moderna have been using the mRNA technology and they're using it to develop a a new vaccine for the RSV virus. And they're actually using the data exchange to procure and then analyze real world evidence data. And what that, what that helps them do is identify and and analyze in almost real time using data on Redshift who are the best vaccine candidates for the trials based on geography and demographics. So it's really helping them save costs, but not only cost really help optimize and be much more efficient in terms of how they're going about their trials from time to market.. >> Host: Time to market. >> vaccine perspective. Yeah. And more importantly, getting the analysis and the results back from those trials as fast as they possibly can. >> Yeah. >> And data exchange, great with the trend that we're going to hear and the keynote tomorrow. More data exchanging more data being more fluid addressable shows those advantages. That's a great example. Great call out there. Chris, I got to get your thoughts on the ecosystem. You know, Ruba Borno is the new head of partners, APN, Amazon Partner Network and marketplace comes together. How you guys serve your partners is also growing and evolving. What's the biggest thing going on in the ecosystem that you see from your perspective? You can put your Amazon hat on or take your your Amazon hat off a personal hat on what's going on. There's a real growth, I mean seeing people getting bigger and stronger as partners. There's more learning, there's more platforms developing. It's, it's kind of the next gen wave coming. What's going on there? What's the, what's the keynote going to be like, what's the what's this reinvent going to be for partners? Give us a share your, share your thoughts. >> Yeah, certainly. I, I think, you know, we are really trying to make sure that we're simplifying the partner experience as much as we possibly can to really help our partners become you know, more profitable or the most profitable they can be with AWS. And so, you know, certainly in Ruba's keynote on Wednesday you're going to hear a little bit about what we've done there from a programs perspective, what we're doing there from feature and capability perspectives to help, you know really push the digital custom, the digital partner experience, sorry, I should say as much as possible. And really looking holistically at that partner experience and listening to our partners as much as we possibly can to adapt partner pathways to ultimately simplify how they're going to market with AWS. Not only on the co-sell side of things and how we interact with our field teams and actually interact with the end customer, but also on how we, we build and help coil with them on AWS to make their solutions whether that be software, whether that be machine learning models, whether that be data sets most optimized to operate in the AWS ecosystem. So you're going to hear a lot of that in Ruba's keynote on Wednesday. There's certainly some really fantastic partner stories and partner launches that'll be featured. Also some customer outcomes that have been realized as a result of partners. So make sure you don't miss it >> John: More action than ever before, right now. >> It's jam-packed, certainly and throughout the week you're going to see multiple launches and releases related to what we're doing with partners on marketplace, but also more generally to help achieve those customer outcomes. >> Well said Brian. So your heart take, what is the future of partnerships the future of the cloud, if you want throw it in, what what are you going to be saying to us? Hopefully the next time you get to sit down with John and I here on theCUBE at reinvent next year. >> Chris: Yeah, I think Adam, Adam was quoted today, as you know, saying that the, the partner ecosystem is going to be around and a foundation for decades. I think is a hundred percent right for me in terms of the industry verticals, the partner ecosystem we have and the availability of these niche solutions that really are solving very specific but mission critical use cases for our customers in each of the industries is super important and it's going to be a a foundation for AWS's growth strategy across all the industry segments for many years to come. So we're super excited about the opportunity ahead of us and we're ready to get after it. >> John: If you, if you could do an Instagram reel right now, what would you say is the most important >> The Insta challenge by go >> The Insta challenge, real >> Host: Chris's Insta challenge >> Insta challenge here, what would be the the real you'd say to the audience about why this year's reinvent is so important? >> I think this year's reinvent is going to give you a clear sense of the breadth and depth of partners that are available to you across the AWS ecosystem. And there's really no industry or use case that we can't solve with partners that we have available within the partner organization. >> Anything is possible. What a note to close on. Chris Casey, thank you so much for joining us for the second time here on theCUBE. John >> He nailed Instagram challenge. >> Yeah, he did. Did he pass the John test? >> I'd say, I'd say so. >> I'd say so. And and and he certainly teased us all with the content to come this week. I want to see all the keynotes here about some of those partners. You tease them in the gaming space with us earlier. It's going to be a very exciting week. Thank you John, for your commentary. Thank you Chris, one more time. >> Thanks for having me. >> And thank you all for tuning in here at theCUBE where we are the leader in high tech coverage. My name is Savannah Peterson, joined by John Furrier with Cube Team live from Las Vegas, Nevada. AWS Reinvent will be here all week and we hope you stay tuned.

from the cube studios in Palo Alto in Boston bringing you data-driven insights from the cube and ETR this is breaking analysis with Dave vellante the ascendancy of AWS under the leadership of Andy jassy was marked by a tsunami of data and corresponding cloud services to leverage that data now those Services they mainly came in the form of Primitives I.E basic building blocks that were used by developers to create more sophisticated capabilities AWS in the 2020s being led by CEO Adam solipski will be marked by four high-level Trends in our opinion one A Rush of data that will dwarf anything we've previously seen two a doubling or even tripling down on the basic elements of cloud compute storage database security Etc three a greater emphasis on end-to-end integration of AWS services to simplify and accelerate customer adoption of cloud and four significantly deeper business integration of cloud Beyond it as an underlying element of organizational operations hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we extract and analyze nuggets from John furrier's annual sit-down with the CEO of AWS we'll share data from ETR and other sources to set the context for the market and competition in cloud and we'll give you our glimpse of what to expect at re invent in 2022. now before we get into the core of our analysis Alibaba has announced earnings they always announced after the big three you know a month later and we've updated our Q3 slash November hyperscale Computing forecast for the year as seen here and we're going to spend a lot of time on this as most of you have seen the bulk of it already but suffice to say alibaba's cloud business is hitting that same macro Trend that we're seeing across the board but a more substantial slowdown than we expected and more substantial than its peers they're facing China headwinds they've been restructuring its Cloud business and it's led to significantly slower growth uh in in the you know low double digits as opposed to where we had it at 15 this puts our year-end estimates for 2022 Revenue at 161 billion still a healthy 34 growth with AWS surpassing 80 billion in 2022 Revenue now on a related note one of the big themes in Cloud that we've been reporting on is how customers are optimizing their Cloud spend it's a technique that they use and when the economy looks a little shaky and here's a graphic that we pulled from aws's website which shows the various pricing plans at a high level as you know they're much more granular than that and more sophisticated but Simplicity we'll just keep it here basically there are four levels first one here is on demand I.E pay by the drink now we're going to jump down to what we've labeled as number two spot instances that's like the right place at the right time I can use that extra capacity in the moment the third is reserved instances or RIS where I pay up front to get a discount and the fourth is sort of optimized savings plans where customers commit to a one or three year term and for a better price now you'll notice we labeled the choices in a different order than AWS presented them on its website and that's because we believe that the order that we chose is the natural progression for customers this started on demand they maybe experiment with spot instances they move to reserve instances when the cloud bill becomes too onerous and if you're large enough you lock in for one or three years okay the interesting thing is the order in which AWS presents them we believe that on-demand accounts for the majority of AWS customer spending now if you think about it those on-demand customers they're also at risk customers yeah sure there's some switching costs like egress and learning curve but many customers they have multiple clouds and they've got experience and so they're kind of already up to a learning curve and if you're not married to AWS with a longer term commitment there's less friction to switch now AWS here presents the most attractive plan from a financial perspective second after on demand and it's also the plan that makes the greatest commitment from a lock-in standpoint now In fairness to AWS it's also true that there is a trend towards subscription-based pricing and we have some data on that this chart is from an ETR drill down survey the end is 300. pay attention to the bars on the right the left side is sort of busy but the pink is subscription and you can see the trend upward the light blue is consumption based or on demand based pricing and you can see there's a steady Trend toward subscription now we'll dig into this in a later episode of Breaking analysis but we'll share with you a little some tidbits with the data that ETR provides you can select which segment is and pass or you can go up the stack Etc but so when you choose is and paths 44 of customers either prefer or are required to use on-demand pricing whereas around 40 percent of customers say they either prefer or are required to use subscription pricing again that's for is so now the further mu you move up the stack the more prominent subscription pricing becomes often with sixty percent or more for the software-based offerings that require or prefer subscription and interestingly cyber security tracks along with software at around 60 percent that that prefer subscription it's likely because as with software you're not shutting down your cyber protection on demand all right let's get into the expectations for reinvent and we're going to start with an observation in data in this 2018 book seeing digital author David michella made the point that whereas most companies apply data on the periphery of their business kind of as an add-on function successful data companies like Google and Amazon and Facebook have placed data at the core of their operations they've operationalized data and they apply machine intelligence to that foundational element why is this the fact is it's not easy to do what the internet Giants have done very very sophisticated engineering and and and cultural discipline and this brings us to reinvent 2022 in the future of cloud machine learning and AI will increasingly be infused into applications we believe the data stack and the application stack are coming together as organizations build data apps and data products data expertise is moving from the domain of Highly specialized individuals to Everyday business people and we are just at the cusp of this trend this will in our view be a massive theme of not only re invent 22 but of cloud in the 2020s the vision of data mesh We Believe jamachtagani's principles will be realized in this decade now what we'd like to do now is share with you a glimpse of the thinking of Adam solipsky from his sit down with John Furrier each year John has a one-on-one conversation with the CEO of AWS AWS he's been doing this for years and the outcome is a better understanding of the directional thinking of the leader of the number one Cloud platform so we're now going to share some direct quotes I'm going to run through them with some commentary and then bring in some ETR data to analyze the market implications here we go this is from solipsky quote I.T in general and data are moving from departments into becoming intrinsic parts of how businesses function okay we're talking here about deeper business integration let's go on to the next one quote in time we'll stop talking about people who have the word analyst we inserted data he meant data data analyst in their title rather will have hundreds of millions of people who analyze data as part of their day-to-day job most of whom will not have the word analyst anywhere in their title we're talking about graphic designers and pizza shop owners and product managers and data scientists as well he threw that in I'm going to come back to that very interesting so he's talking about here about democratizing data operationalizing data next quote customers need to be able to take an end-to-end integrated view of their entire data Journey from ingestion to storage to harmonizing the data to being able to query it doing business Intelligence and human-based Analysis and being able to collaborate and share data and we've been putting together we being Amazon together a broad Suite of tools from database to analytics to business intelligence to help customers with that and this last statement it's true Amazon has a lot of tools and you know they're beginning to become more and more integrated but again under jassy there was not a lot of emphasis on that end-to-end integrated view we believe it's clear from these statements that solipsky's customer interactions are leading him to underscore that the time has come for this capability okay continuing quote if you have data in one place you shouldn't have to move it every time you want to analyze that data couldn't agree more it would be much better if you could leave that data in place avoid all the ETL which has become a nasty three-letter word more and more we're building capabilities where you can query that data in place end quote okay this we see a lot in the marketplace Oracle with mySQL Heatwave the entire Trend toward converge database snowflake [ __ ] extending their platforms into transaction and analytics respectively and so forth a lot of the partners are are doing things as well in that vein let's go into the next quote the other phenomenon is infusing machine learning into all those capabilities yes the comments from the michelleographic come into play here infusing Ai and machine intelligence everywhere next one quote it's not a data Cloud it's not a separate Cloud it's a series of broad but integrated capabilities to help you manage the end-to-end life cycle of your data there you go we AWS are the cloud we're going to come back to that in a moment as well next set of comments around data very interesting here quote data governance is a huge issue really what customers need is to find the right balance of their organization between access to data and control and if you provide too much access then you're nervous that your data is going to end up in places that it shouldn't shouldn't be viewed by people who shouldn't be viewing it and you feel like you lack security around that data and by the way what happens then is people overreact and they lock it down so that almost nobody can see it it's those handcuffs there's data and asset are reliability we've talked about that for years okay very well put by solipsky but this is a gap in our in our view within AWS today and we're we're hoping that they close it at reinvent it's not easy to share data in a safe way within AWS today outside of your organization so we're going to look for that at re invent 2022. now all this leads to the following statement by solipsky quote data clean room is a really interesting area and I think there's a lot of different Industries in which clean rooms are applicable I think that clean rooms are an interesting way of enabling multiple parties to share and collaborate on the data while completely respecting each party's rights and their privacy mandate okay again this is a gap currently within AWS today in our view and we know snowflake is well down this path and databricks with Delta sharing is also on this curve so AWS has to address this and demonstrate this end-to-end data integration and the ability to safely share data in our view now let's bring in some ETR spending data to put some context around these comments with reference points in the form of AWS itself and its competitors and partners here's a chart from ETR that shows Net score or spending momentum on the x-axis an overlap or pervasiveness in the survey um sorry let me go back up the net scores on the y-axis and overlap or pervasiveness in the survey is on the x-axis so spending momentum by pervasiveness okay or should have share within the data set the table that's inserted there with the Reds and the greens that informs us to how the dots are positioned so it's Net score and then the shared ends are how the plots are determined now we've filtered the data on the three big data segments analytics database and machine learning slash Ai and we've only selected one company with fewer than 100 ends in the survey and that's databricks you'll see why in a moment the red dotted line indicates highly elevated customer spend at 40 percent now as usual snowflake outperforms all players on the y-axis with a Net score of 63 percent off the charts all three big U.S cloud players are above that line with Microsoft and AWS dominating the x-axis so very impressive that they have such spending momentum and they're so large and you see a number of other emerging data players like rafana and datadog mongodbs there in the mix and then more established players data players like Splunk and Tableau now you got Cisco who's gonna you know it's a it's a it's a adjacent to their core networking business but they're definitely into you know the analytics business then the really established players in data like Informatica IBM and Oracle all with strong presence but you'll notice in the red from the momentum standpoint now what you're going to see in a moment is we put red highlights around databricks Snowflake and AWS why let's bring that back up and we'll explain so there's no way let's bring that back up Alex if you would there's no way AWS is going to hit the brakes on innovating at the base service level what we call Primitives earlier solipsky told Furrier as much in their sit down that AWS will serve the technical user and data science Community the traditional domain of data bricks and at the same time address the end-to-end integration data sharing and business line requirements that snowflake is positioned to serve now people often ask Snowflake and databricks how will you compete with the likes of AWS and we know the answer focus on data exclusively they have their multi-cloud plays perhaps the more interesting question is how will AWS compete with the likes of Specialists like Snowflake and data bricks and the answer is depicted here in this chart AWS is going to serve both the technical and developer communities and the data science audience and through end-to-end Integrations and future services that simplify the data Journey they're going to serve the business lines as well but the Nuance is in all the other dots in the hundreds or hundreds of thousands that are not shown here and that's the AWS ecosystem you can see AWS has earned the status of the number one Cloud platform that everyone wants to partner with as they say it has over a hundred thousand partners and that ecosystem combined with these capabilities that we're discussing well perhaps behind in areas like data sharing and integrated governance can wildly succeed by offering the capabilities and leveraging its ecosystem now for their part the snowflakes of the world have to stay focused on the mission build the best products possible and develop their own ecosystems to compete and attract the Mind share of both developers and business users and that's why it's so interesting to hear solipski basically say it's not a separate Cloud it's a set of integrated Services well snowflake is in our view building a super cloud on top of AWS Azure and Google when great products meet great sales and marketing good things can happen so this will be really fun to watch what AWS announces in this area at re invent all right one other topic that solipsky talked about was the correlation between serverless and container adoption and you know I don't know if this gets into there certainly their hybrid place maybe it starts to get into their multi-cloud we'll see but we have some data on this so again we're talking about the correlation between serverless and container adoption but before we get into that let's go back to 2017 and listen to what Andy jassy said on the cube about serverless play the clip very very earliest days of AWS Jeff used to say a lot if I were starting Amazon today I'd have built it on top of AWS we didn't have all the capability and all the functionality at that very moment but he knew what was coming and he saw what people were still able to accomplish even with where the services were at that point I think the same thing is true here with Lambda which is I think if Amazon were starting today it's a given they would build it on the cloud and I think we with a lot of the applications that comprise Amazon's consumer business we would build those on on our serverless capabilities now we still have plenty of capabilities and features and functionality we need to add to to Lambda and our various serverless services so that may not be true from the get-go right now but I think if you look at the hundreds of thousands of customers who are building on top of Lambda and lots of real applications you know finra has built a good chunk of their market watch application on top of Lambda and Thompson Reuters has built you know one of their key analytics apps like people are building real serious things on top of Lambda and the pace of iteration you'll see there will increase as well and I really believe that to be true over the next year or two so years ago when Jesse gave a road map that serverless was going to be a key developer platform going forward and so lipsky referenced the correlation between serverless and containers in the Furrier sit down so we wanted to test that within the ETR data set now here's a screen grab of The View across 1300 respondents from the October ETR survey and what we've done here is we've isolated on the cloud computing segment okay so you can see right there cloud computing segment now we've taken the functions from Google AWS Lambda and Microsoft Azure functions all the serverless offerings and we've got Net score on the vertical axis we've got presence in the data set oh by the way 440 by the way is highly elevated remember that and then we've got on the horizontal axis we have the presence in the data center overlap okay that's relative to each other so remember 40 all these guys are above that 40 mark okay so you see that now what we're going to do this is just for serverless and what we're going to do is we're going to turn on containers to see the correlation and see what happens so watch what happens when we click on container boom everything moves to the right you can see all three move to the right Google drops a little bit but all the others now the the filtered end drops as well so you don't have as many people that are aggressively leaning into both but all three move to the right so watch again containers off and then containers on containers off containers on so you can see a really major correlation between containers and serverless okay so to get a better understanding of what that means I call my friend and former Cube co-host Stu miniman what he said was people generally used to think of VMS containers and serverless as distinctly different architectures but the lines are beginning to blur serverless makes things simpler for developers who don't want to worry about underlying infrastructure as solipsky and the data from ETR indicate serverless and containers are coming together but as Stu and I discussed there's a spectrum where on the left you have kind of native Cloud VMS in the middle you got AWS fargate and in the rightmost anchor is Lambda AWS Lambda now traditionally in the cloud if you wanted to use containers developers would have to build a container image they have to select and deploy the ec2 images that they or instances that they wanted to use they have to allocate a certain amount of memory and then fence off the apps in a virtual machine and then run the ec2 instances against the apps and then pay for all those ec2 resources now with AWS fargate you can run containerized apps with less infrastructure management but you still have some you know things that you can you can you can do with the with the infrastructure so with fargate what you do is you'd build the container images then you'd allocate your memory and compute resources then run the app and pay for the resources only when they're used so fargate lets you control the runtime environment while at the same time simplifying the infrastructure management you gotta you don't have to worry about isolating the app and other stuff like choosing server types and patching AWS does all that for you then there's Lambda with Lambda you don't have to worry about any of the underlying server infrastructure you're just running code AS functions so the developer spends their time worrying about the applications and the functions that you're calling the point is there's a movement and we saw in the data towards simplifying the development environment and allowing the cloud vendor AWS in this case to do more of the underlying management now some folks will still want to turn knobs and dials but increasingly we're going to see more higher level service adoption now re invent is always a fire hose of content so let's do a rapid rundown of what to expect we talked about operate optimizing data and the organization we talked about Cloud optimization there'll be a lot of talk on the show floor about best practices and customer sharing data solipsky is leading AWS into the next phase of growth and that means moving beyond I.T transformation into deeper business integration and organizational transformation not just digital transformation organizational transformation so he's leading a multi-vector strategy serving the traditional peeps who want fine-grained access to core services so we'll see continued Innovation compute storage AI Etc and simplification through integration and horizontal apps further up to stack Amazon connect is an example that's often cited now as we've reported many times databricks is moving from its stronghold realm of data science into business intelligence and analytics where snowflake is coming from its data analytics stronghold and moving into the world of data science AWS is going down a path of snowflake meet data bricks with an underlying cloud is and pass layer that puts these three companies on a very interesting trajectory and you can expect AWS to go right after the data sharing opportunity and in doing so it will have to address data governance they go hand in hand okay price performance that is a topic that will never go away and it's something that we haven't mentioned today silicon it's a it's an area we've covered extensively on breaking analysis from Nitro to graviton to the AWS acquisition of Annapurna its secret weapon new special specialized capabilities like inferential and trainium we'd expect something more at re invent maybe new graviton instances David floyer our colleague said he's expecting at some point a complete system on a chip SOC from AWS and maybe an arm-based server to eventually include high-speed cxl connections to devices and memories all to address next-gen applications data intensive applications with low power requirements and lower cost overall now of course every year Swami gives his usual update on machine learning and AI building on Amazon's years of sagemaker innovation perhaps a focus on conversational AI or a better support for vision and maybe better integration across Amazon's portfolio of you know large language models uh neural networks generative AI really infusing AI everywhere of course security always high on the list that reinvent and and Amazon even has reinforce a conference dedicated to it uh to security now here we'd like to see more on supply chain security and perhaps how AWS can help there as well as tooling to make the cio's life easier but the key so far is AWS is much more partner friendly in the security space than say for instance Microsoft traditionally so firms like OCTA and crowdstrike in Palo Alto have plenty of room to play in the AWS ecosystem we'd expect of course to hear something about ESG it's an important topic and hopefully how not only AWS is helping the environment that's important but also how they help customers save money and drive inclusion and diversity again very important topics and finally come back to it reinvent is an ecosystem event it's the Super Bowl of tech events and the ecosystem will be out in full force every tech company on the planet will have a presence and the cube will be featuring many of the partners from the serial floor as well as AWS execs and of course our own independent analysis so you'll definitely want to tune into thecube.net and check out our re invent coverage we start Monday evening and then we go wall to wall through Thursday hopefully my voice will come back we have three sets at the show and our entire team will be there so please reach out or stop by and say hello all right we're going to leave it there for today many thanks to Stu miniman and David floyer for the input to today's episode of course John Furrier for extracting the signal from the noise and a sit down with Adam solipski thanks to Alex Meyerson who was on production and manages the podcast Ken schiffman as well Kristen Martin and Cheryl Knight helped get the word out on social and of course in our newsletters Rob hoef is our editor-in-chief over at siliconangle does some great editing thank thanks to all of you remember all these episodes are available as podcasts wherever you listen you can pop in the headphones go for a walk just search breaking analysis podcast I published each week on wikibon.com at siliconangle.com or you can email me at david.valante at siliconangle.com or DM me at di vallante or please comment on our LinkedIn posts and do check out etr.ai for the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thanks for watching we'll see it reinvent or we'll see you next time on breaking 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(intro upbeat music) >> Hello everyone and welcome to our continued coverage of AWS re:Invent here on theCUBE. My name is Savannah Peterson and I am very excited about the conversation coming up. Not only are we joined by two brilliant minds in the cloud, one of them happens to be a CUBE alumni. Please welcome Mike from AMD and Ali from Dropbox. Ali, welcome back to the show, how you been? >> Thanks Savannah. I'm doing great and really excited to be back on theCUBE. It was great discussion last time and really excited for both re:Invent and also to see how this video turns out. >> Hey, that makes two of us and probably three of us. How are you doing today, Mike? >> Doing great. It's really nice to be getting back to in-person events again and to be out solving problems with customers and partners like Dropbox. >> I know, isn't it? We've all missed each other. Was a lonely couple of years. Mike, I'm going to open it up with you. I'm sure a lot of people are curious. What's new at AMD? >> Well, there's a lot that's new at AMD, so I'll share a subset of what's new and what we've been working on. We've expanded our global coverage in Amazon EC2 with new regions and instance types. So users can deploy any application pretty much anywhere AWS has a presence. Our partner ecosystems for solutions and services has expanded quite a bit. We're currently focused on enabling partners and solutions that focus on cloud cost optimization, modernizing infrastructure, and pushing performance to the limit, especially for HPC. But the biggest buzz, of course, is around AMD's new fourth generation of our EPYC CPU Genoa. It's the world's fastest data center CPU with transformative energy efficiency and that's a really interesting combination, highest performance and most efficient. So on launch day, AWS announced their plans to roll out AMD EPYC Genoa processor-based EC2 instances. So we're pretty excited about that and that's what we'll be working on in the near term. >> Wow, that's a big deal and certainly not a casual announcement. Obviously, power and efficiency hot topics here at re:Invent but also looking at the greater impact on the planet is a big conversation we've been having here as well. So this is exciting and timely and congratulations to you and the team on all that seems to be going on. Ali, what's going on at Dropbox? >> Yeah, thanks Savannah. The Q3 2022 was actually a very strong quarter for Dropbox during a very difficult macroeconomic backdrop. Our focus has continued to be on innovation and this is around both new products and also driving multi-product adoption which is paying a lot of dividends for us, so essentially, bringing products like Dropbox Sign, DocSend, Capture, and other exciting products to our customers. On the infra side, it's all about how do we scale our infrastructure to meet the business needs, right? How do we keep up with the accelerated growth during the pandemic and also leveraging both AMD and AWS for investments in our public cloud? >> Let's talk about the cloud a bit. You are both cloud experts and I'm glad that you brought that up. We'll keep it there with Ali. When, why, and how should users leverage public cloud? >> Yeah, so Dropbox is hybrid cloud which means we are running applications both in private and public cloud and within a unique position to leverage the best of both worlds. And Savannah, this is a decision we continue to reevaluate on a regular basis. And there are really three key factors that come into play here. First is scale and scale, are we operating at a scale where customization is cost-efficient for us? Next is uniqueness. Is our workload unique compared to what the public cloud supports? And lastly, innovation. Do we have the expertise to innovate faster than public cloud or not? So based on these three key factors, we try and balance all of them and then come up with the best option for us at Dropbox. And kind of elaborating over here, things like international storage, we're leveraging public cloud, things like AI and ML, we're leveraging public cloud, but when we talk about Magic Pocket, which is our multi-exabyte storage system, that has the scale which is why we are doing that on our own private cloud. >> Wow, I think you just gave everybody a fantastic framework for thinking about their decision matrix there if nothing else. Mike, is there anything that you'd like to add to that? Anything that AMD considers when contemplating public cloud versus private? >> Yeah, so there's really three main drivers that I see when users consider when, why, and how should they leverage public cloud. Three main drivers: establishing a global footprint, accelerating product release cycles, and efficiently rightsizing infrastructure. So customers looking to establish a global footprint often turn to public cloud deployments to quickly reach their clients in workforces around the world, most importantly with minimal capital expense. I understand Dropbox uses public cloud to establish their global presence scaling out from their core data centers in North America. And then a lot of industries have tremendous pressure to accelerate product release cycles. With public cloud, organizations can immediately deploy new applications without a long site and hardware acquisition cycle and then the associated ongoing maintenance and operational overhead. And the third thing is customers that need to rightsize and dynamically scale their infrastructure and application deployments are drawn to public cloud, for example, customers that have cyclical compute or application load peaks can efficiently deploy in the cloud without overdeploying their on-prem infrastructure for most of the year which is off-peak during those off-peak times. That infrastructure idle time is a waste of resources and OPEX. So scalable rightsizing draws a lot of users to cloud deployment. >> Yeah, wow. I think there's a lot of factors to consider but also it seems like a pretty streamlined process for navigating that or at least you two both made it sound that way. Another hot topic in the space right now is security. Mike, let's start with you a little bit. What are the most important security issues for AMD right now that you can talk about? >> Yeah, sure. So, well, first of all, AWS provides a wide variety of really good security services to protect customers that are working in the cloud. Like from a processor technology perspective, there's three main security aspects to consider, two of which are common practice today and one of which AMD brings significant differentiation and value. The first two are protecting data at rest and data in transit. And these two are part of the prevalent security models of today where AMD provides distinct value and differentiation is in protecting data in use. So EPYC Milan and Genoa processors support a function called SEV-SNP and this enables users to reside and their applications to reside within their own cryptographic context and environment with data integrity protection to accomplish what's called comprehensive confidential computing. Ethics confidential computing solution is hardware-based. So it's easy to leverage, there's no code rewrite required unlike comparable solutions that are software-based that require recoding to a proprietary SDK and come with a significant performance trade-off. So with EPYC processors, you can protect your data at rest, in transit, and most importantly, in use. >> Everybody needs to protect their data everywhere it is. So I love that. That's fantastic to hear and I'm sure gives your customers a lot of confidence. What about over at Dropbox? What security issues are you facing, Ali? >> Yeah, so the first company value at Dropbox is actually being worthy of trust, and what this really means from a security perspective is how do we keep all of our users content safe? And this means keeping everything down to all of the infrastructure hardware secure. So partnering with AMD, which is one of our strongest partners out there, the new security features that AMD have and the hardware are critical for us and we are able to take advantage of some of these best security practices within our compute infrastructure by leveraging AMD's secure ship architecture. >> How important, you just touched on it a little bit, and I want to ask, how important are partnerships like the one you have with each other as you innovate at scale? Ali, you're nodding, I'm going to go to you first. >> Yeah, so like I mentioned, the partnership with with AMD is one of the strongest that we have and it just goes beyond like a regular partnership where it's just buy and sell. We talk about technology together, we talk about innovation together, we talk about partnership together, and for us, as I look look at our hybrid cloud strategy, we would not be able to get the benefits in terms of efficiency, scale, or liability performance without having a strong partner like AMD. >> That's awesome. Mike, anything you want to add there? >> I'd reiterate some of what Ali had to say. One of my favorite parts about my job is getting together with partners and customers to figure out how to optimize their applications and deployments around the world to get the most efficient use of the cloud infrastructure for servers that are based on AMD technology. In many cases, we can find 10% or better performance or cost optimization by working closely with partners like Dropbox. And then in addition, if we keep in lock step together to look at what's coming on the roadmap, by the time the latest and greatest technology is finally deployed, our customers and our partners are ready to take advantage of it. So that's the fun part of the job and I really appreciate the Dropbox's cooperation, optimizing their infrastructure, and using AMD products >> Well, what a synergistic relationship of mutual admiration and support. We love to hear it here in the tech world. Mike, last question for you. What's next for AMD? >> Well, heading into 2023, considering the current challenge macroeconomic environment and geopolitical instability, doing more with less will be top of mind for many CFOs and CEOs in 2023. And AMD can help accomplish that. AMD's EPYC processors, leadership performance, and lower EC2 retail costs can help users reduce costs without impacting performance, or the flip side of that, they can scale capacity without increasing costs. And because of EPYC's higher core counts, really high core density, applications can be deployed with fewer servers or smaller instances that has both economic and environmental benefits that reduce usage costs as well as environmental impacts. And that allows customers to optimize their application and infrastructure spend. And then the second thing that I've seen over the last couple of years and I see this trajectory continuing is increased geographic distribution of our colleagues and workforces is here to stay, people work from everywhere. In modern cross platform, collaboration platforms, that bring teams, tools, and content together have a really important role to play to enable that new, more flexible style of working. And those tools need to be really agile and easy to use. I think Dropbox is really well positioned to enable this new style of working. AMD's really happy to work closely with Dropbox to enable these modern work styles, both on premises, hybrid, and fully in the public cloud. >> Well, it sounds like a very exciting and optimistically, bright future for you all at AMD. We love to hear that here at theCUBE. Ali, what about you? What is 2023 going to hold for Dropbox? >> Yeah, so I think we're going to continue on this journey of transformation where our focus is on new products and also multi-product adoption. And from a cloud perspective, how do we continue to evolve our hybrid cloud so that we remain a competitive advantage for our business and also for our customers? I think right now, Savannah, we're in a very unique position to utilize some of the best AMD technology that's out there and that's both on premise and in the cloud. Some of the AMD Epic processors delivered the performance that we need for our hybrid cloud and we want to continue to leverage these also in public cloud which is the EC2 instances that are powered by AMD in the long run. So overall, Dropbox is looking forward to continue to evaluate some of the AMD's Genoa CPUs that are coming out but also want to continue to grow our EC2 footprint powered by AMD in the long run. >> Fantastic. Well, it sounds like this second showing here on theCUBE is just the tee up for your third and we'll definitely have to have Mike back on for the second time around to hear how things are going. Thank you both so much for taking the time today to join me here. Mike and Ali, it was fantastic getting to chat to you and thank you to our audience for tuning into theCUBE's special coverage of AWS re:Invent. My name's Savannah Peterson and I hope we can learn together soon. (outro upbeat music)

>>From the Cube Studios in Palo Alto in Boston, bringing you data driven insights from the cube and etr. This is breaking analysis with Dave Ante. >>Have you ever been driving on the highway and traffic suddenly slows way down and then after a little while it picks up again and you're cruising along and you're thinking, Okay, hey, that was weird. But it's clear sailing now. Off we go, only to find out in a bit that the traffic is building up ahead again, forcing you to pump the brakes as the traffic pattern ebbs and flows well. Welcome to the Seesaw economy. The fed induced fire that prompted an unprecedented rally in tech is being purposefully extinguished now by that same fed. And virtually every sector of the tech industry is having to reset its expectations, including the cloud segment. Hello and welcome to this week's Wikibon Cube Insights powered by etr. In this breaking analysis will review the implications of the earnings announcements from the big three cloud players, Amazon, Microsoft, and Google who announced this week. >>And we'll update you on our quarterly IAS forecast and share the latest from ETR with a focus on cloud computing. Now, before we get into the new data, we wanna review something we shared with you on October 14th, just a couple weeks back, this is sort of a, we told you it was coming slide. It's an XY graph that shows ET R'S proprietary net score methodology on the vertical axis. That's a measure of spending momentum, spending velocity, and an overlap or presence in the dataset that's on the X axis. That's really a measure of pervasiveness. In the survey, the table, you see that table insert there that shows Wiki Bond's Q2 estimates of IAS revenue for the big four hyperscalers with their year on year growth rates. Now we told you at the time, this is data from the July TW 22 ETR survey and the ETR hadn't released its October survey results at that time. >>This was just a couple weeks ago. And while we couldn't share the specific data from the October survey, we were able to get a glimpse and we depicted the slowdown that we saw in the October data with those dotted arrows kind of down into the right, we said at the time that we were seeing and across the board slowdown even for the big three cloud vendors. Now, fast forward to this past week and we saw earnings releases from Alphabet, Microsoft, and just last night Amazon. Now you may be thinking, okay, big deal. The ETR survey data didn't really tell us anything we didn't already know. But judging from the negative reaction in the stock market to these earnings announcements, the degree of softness surprised a lot of investors. Now, at the time we didn't update our forecast, it doesn't make sense for us to do that when we're that close to earning season. >>And now that all the big three ha with all the big four with the exception of Alibaba have announced we've, we've updated. And so here's that data. This chart lays out our view of the IS and PAs worldwide revenue. Basically it's cloud infrastructure with an attempt to exclude any SaaS revenue so we can make an apples to apples comparison across all the clouds. Now the reason that actual is in quotes is because Microsoft and Google don't report IAS revenue, but they do give us clues and kind of directional commentary, which we then triangulate with other data that we have from the channel and ETR surveys and just our own intelligence. Now the second column there after the vendor name shows our previous estimates for q3, and then next to that we show our actuals. Same with the growth rates. And then we round out the chart with that lighter blue color highlights, the full year estimates for revenue and growth. >>So the key takeaways are that we shaved about $4 billion in revenue and roughly 300 basis points of growth off of our full year estimates. AWS had a strong July but exited Q3 in the mid 20% growth rate year over year. So we're using that guidance, you know, for our Q4 estimates. Azure came in below our earlier estimates, but Google actually exceeded our expectations. Now the compression in the numbers is in our view of function of the macro demand climate, we've made every attempt to adjust for constant currency. So FX should not be a factor in this data, but it's sure you know that that ma the the, the currency effects are weighing on those companies income statements. And so look, this is the fundamental dynamic of a cloud model where you can dial down consumption when you need to and dial it up when you need to. >>Now you may be thinking that many big cloud customers have a committed level of spending in order to get better discounts. And that's true. But what's happening we think is they'll reallocate that spend toward, let's say for example, lower cost storage tiers or they may take advantage of better price performance processors like Graviton for example. That is a clear trend that we're seeing and smaller companies that were perhaps paying by the drink just on demand, they're moving to reserve instance models to lower their monthly bill. So instead of taking the easy way out and just spending more companies are reallocating their reserve capacity toward lower cost. So those sort of lower cost services, so they're spending time and effort optimizing to get more for, for less whereas, or get more for the same is really how we should, should, should phrase it. Whereas during the pandemic, many companies were, you know, they perhaps were not as focused on doing that because business was booming and they had a response. >>So they just, you know, spend more dial it up. So in general, as they say, customers are are doing more with, with the same. Now let's look at the growth dynamic and spend some time on that. I think this is important. This data shows worldwide quarterly revenue growth rates back to Q1 2019 for the big four. So a couple of interesting things. The data tells us during the pandemic, you saw both AWS and Azure, but the law of large numbers and actually accelerate growth. AWS especially saw progressively increasing growth rates throughout 2021 for each quarter. Now that trend, as you can see is reversed in 2022 for aws. Now we saw Azure come down a bit, but it's still in the low forties in terms of percentage growth. While Google actually saw an uptick in growth this last quarter for GCP by our estimates as GCP is becoming an increasingly large portion of Google's overall cloud business. >>Now, unfortunately Google Cloud continues to lose north of 850 million per quarter, whereas AWS and Azure are profitable cloud businesses even though Alibaba is suffering its woes from China. And we'll see how they come in when they report in mid-November. The overall hyperscale market grew at 32% in Q3 in terms of worldwide revenue. So the slowdown isn't due to the repatriation or competition from on-prem vendors in our view, it's a macro related trend. And cloud will continue to significantly outperform other sectors despite its massive size. You know, on the repatriation point, it just still doesn't show up in the data. The A 16 Z article from Sarah Wong and Martin Martin Kasa claiming that repatriation was inevitable as a means to lower cost of good sold for SaaS companies. You know, while that was thought provoking, it hasn't shown up in the numbers. And if you read the financial statements of both AWS and its partners like Snowflake and you dig into the, to the, to the quarterly reports, you'll see little notes and comments with their ongoing negotiations to lower cloud costs for customers. >>AWS and no doubt execs at Azure and GCP understand that the lifetime value of a customer is worth much more than near term gross margin. And you can expect the cloud vendors to strike a balance between profitability, near term profitability anyway and customer attention. Now, even though Google Cloud platform saw accelerated growth, we need to put that in context for you. So GCP, by our estimate, has now crossed over the $3 billion for quarter market actually did so last quarter, but its growth rate accelerated to 42% this quarter. And so that's a good sign in our view. But let's do a quick little comparison with when AWS and Azure crossed the $3 billion mark and compare their growth rates at the time. So if you go back to to Q2 2016, as we're showing in this chart, that's around the time that AWS hit 3 billion per quarter and at the same time was growing at 58%. >>Azure by our estimates crossed that mark in Q4 2018 and at that time was growing at 67%. Again, compare that to Google's 42%. So one would expect Google's growth rate would be higher than its competitors at this point in the MO in the maturity of its cloud, which it's, you know, it's really not when you compared to to Azure. I mean they're kind of con, you know, comparable now but today, but, but you'll go back, you know, to that $3 billion mark. But more so looking at history, you'd like to see its growth rate at this point of a maturity model at least over 50%, which we don't believe it is. And one other point on this topic, you know, my business friend Matt Baker from Dell often says it's not a zero sum game, meaning there's plenty of opportunity exists to build value on top of hyperscalers. >>And I would totally agree it's not a dollar for dollar swap if you can continue to innovate. But history will show that the first company in makes the most money. Number two can do really well and number three tends to break even. Now maybe cloud is different because you have Microsoft software estate and the power behind that and that's driving its IAS business and Google ads are funding technology buildouts for, for for Google and gcp. So you know, we'll see how that plays out. But right now by this one measurement, Google is four years behind Microsoft in six years behind aws. Now to the point that cloud will continue to outpace other markets, let's, let's break this down a bit in spending terms and see why this claim holds water. This is data from ET r's latest October survey that shows the granularity of its net score or spending velocity metric. >>The lime green is new adoptions, so they're adding the platform, the forest green is spending more 6% or more. The gray bars spending is flat plus or minus, you know, 5%. The pinkish colors represent spending less down 6% or worse. And the bright red shows defections or churn of the platform. You subtract the reds from the greens and you get what's called net score, which is that blue dot that you can see on each of the bars. So what you see in the table insert is that all three have net scores above 40%, which is a highly elevated measure. Microsoft's net scores above 60% AWS well into the fifties and GCP in the mid forties. So all good. Now what's happening with all three is more customers are keep keeping their spending flat. So a higher percentage of customers are saying, our spending is now flat than it was in previous quarters and that's what's accounting for the compression. >>But the churn of all three, even gcp, which we reported, you know, last quarter from last quarter survey was was five x. The other two is actually very low in the single digits. So that might have been an anomaly. So that's a very good sign in our view. You know, again, customers aren't repatriating in droves, it's just not a trend that we would bet on, maybe makes for a FUD or you know, good marketing head, but it's just not a big deal. And you can't help but be impressed with both Microsoft and AWS's performance in the survey. And as we mentioned before, these companies aren't going to give up customers to try and preserve a little bit of gross margin. They'll do what it takes to keep people on their platforms cuz they'll make up for it over time with added services and improved offerings. >>Now, once these companies acquire a customer, they'll be very aggressive about keeping them. So customers take note, you have negotiating leverage, so use it. Okay, let's look at another cut at the cloud market from the ETR data set. Here's the two dimensional view, again, it's back, it's one of our favorites. Net score or spending momentum plotted against presence. And the data set, that's the x axis net score on the, on the vertical axis, this is a view of et r's cloud computing sector sector. You can see we put that magic 40% dotted red line in the table showing and, and then that the table inserts shows how the data are plotted with net score against presence. I e n in the survey, notably only the big three are above the 40% line of the names that we're showing here. The oth there, there are others. >>I mean if you put Snowflake on there, it'd be higher than any of these names, but we'll dig into that name in a later breaking analysis episode. Now this is just another way of quantifying the dominance of AWS and Azure, not only relative to Google, but the other cloud platforms out there. So we've, we've taken the opportunity here to plot IBM and Oracle, which both own a public cloud. Their performance is largely a reflection of them migrating their install bases to their respective public clouds and or hybrid clouds. And you know, that's fine, they're in the game. That's a point that we've made, you know, a number of times they're able to make it through the cloud, not whole and they at least have one, but they simply don't have the business momentum of AWS and Azure, which is actually quite impressive because AWS and Azure are now as large or larger than IBM and Oracle. >>And to show this type of continued growth that that that Azure and AWS show at their size is quite remarkable and customers are starting to recognize the viability of on-prem hi, you know, hybrid clouds like HPE GreenLake and Dell's apex. You know, you may say, well that's not cloud, but if the customer thinks it is and it was reporting in the survey that it is, we're gonna continue to report this view. You know, I don't know what's happening with H P E, They had a big down tick this quarter and I, and I don't read too much into that because their end is still pretty small at 53. So big fluctuations are not uncommon with those types of smaller ends, but it's over 50. So, you know, we did notice a a a negative within a giant public and private sector, which is often a, a bellwether giant public private is big public companies and large private companies like, like a Mars for example. >>So it, you know, it looks like for HPE it could be an outlier. We saw within the Fortune 1000 HPE E'S cloud looked actually really good and it had good spending momentum in that sector. When you di dig into the industry data within ETR dataset, obviously we're not showing that here, but we'll continue to monitor that. Okay, so where's this Leave us. Well look, this is really a tactical story of currency and macro headwinds as you can see. You know, we've laid out some of the points on this slide. The action in the stock market today, which is Friday after some of the soft earnings reports is really robust. You know, we'll see how it ends up in the day. So maybe this is a sign that the worst is over, but we don't think so. The visibility from tech companies is murky right now as most are guiding down, which indicates that their conservative outlook last quarter was still too optimistic. >>But as it relates to cloud, that platform is not going anywhere anytime soon. Sure, there are potential disruptors on the horizon, especially at the edge, but we're still a long ways off from, from the possibility that a new economic model emerges from the edge to disrupt the cloud and the opportunities in the cloud remain strong. I mean, what other path is there? Really private cloud. It was kind of a bandaid until the on-prem guys could get their a as a service models rolled out, which is just now happening. The hybrid thing is real, but it's, you know, defensive for the incumbents until they can get their super cloud investments going. Super cloud implying, capturing value above the hyperscaler CapEx, you know, call it what you want multi what multi-cloud should have been, the metacloud, the Uber cloud, whatever you like. But there are opportunities to play offense and that's clearly happening in the cloud ecosystem with the likes of Snowflake, Mongo, Hashi Corp. >>Hammer Spaces is a startup in this area. Aviatrix, CrowdStrike, Zeke Scaler, Okta, many, many more. And even the projects we see coming out of enterprise players like Dell, like with Project Alpine and what Pure Storage is doing along with a number of other of the backup vendors. So Q4 should be really interesting, but the real story is the investments that that companies are making now to leverage the cloud for digital transformations will be paying off down the road. This is not 1999. We had, you know, May might have had some good ideas and admittedly at a lot of bad ones too, but you didn't have the infrastructure to service customers at a low enough cost like you do today. The cloud is that infrastructure and so far it's been transformative, but it's likely the best is yet to come. Okay, let's call this a rap. >>Many thanks to Alex Morrison who does production and manages the podcast. Also Can Schiffman is our newest edition to the Boston Studio. Kristin Martin and Cheryl Knight helped get the word out on social media and in our newsletters. And Rob Ho is our editor in chief over@siliconangle.com, who does some wonderful editing for us. Thank you. Remember, all these episodes are available as podcasts. Wherever you listen, just search breaking analysis podcast. I publish each week on wiki bond.com at silicon angle.com. And you can email me at David dot valante@siliconangle.com or DM me at Dante or comment on my LinkedIn posts. And please do checkout etr.ai. They got the best survey data in the enterprise tech business. This is Dave Valante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

(inspiring music) >> Announcer: theCUBE presents HPE Discover 2022. Brought to you by HPE. >> Welcome back to theCUBE's coverage of HPE Discover 2022, from the Venetian in Las Vegas, the first Discover since 2019. I really think this is my 14th Discover, when you include HP, when you include Europe. And I got to say this Discover, I think has more energy than any one that I've ever seen, about 8,000 people here. Really excited to have one of HPE's longstanding partners, Veeam CTO, Danny Allen is here, joined by David Harvey, Vice President of Strategic Alliances at Veeam. Guys, good to see you again. It was just earlier, let's see, last month, we were together out here. >> Yeah, just a few weeks ago. It's fantastic to be back and what it's telling us, technology industry is coming back. >> And the events business, of course, is coming back, which we love. I think the expectations were cautious. You saw it at VeeamON, a little more than you expected, a lot of great energy. A lot of people, 'cause it was last month, it was their first time out, >> Yes. >> in two years. Here, I think people have started to go out more, but still, an energy that's palpable. >> You can definitely feel it. Last night, I think I went to four consecutive events and everyone's out having those discussions and having conversations, it's good to be back. >> You guys hosted the Storage party last night, which is epic. I left at midnight, I took a picture, it was still packed. I said, okay, time to go, nothing good happens after midnight kids. David, talk about the alliance with HPE, how it's evolved, and where you see it going? >> I appreciate it, and certainly this, as you said, has been a big alliance for us. Over 10 years or so, fantastic integrations across the board. And you touched on 2019 Discover. We launched with GreenLake at that event, we were one of the launch partners, and we've seen fantastic growth. Overall, what we're excited about, is that continuation of the movement of the customer's buying patterns in line with HPE's portfolio and in line with Veeam. We continue to be with all their primary, secondary storage, we continue to be a spearhead position with GreenLake, which we're really excited about. And we're also really excited to hear from HPE, unfortunately under NDA, some of their future stuff they're investing in, which is a really nice invigoration for what they're doing for their portfolio. And we see that being a big deal for us over the next 24 months. >> Your relationship with HPE predates the HP, HPE split. >> Mmm. >> Yes. >> But it was weird, because they had Data Protector, and that was a quasi-competitor, or really not, but it was a competitor, a legacy competitor, of what you guys have, kind of modern data protection I think is the tagline, if I got it right. Post the split, that was an S-curve moment, wasn't it, in terms of the partnership? >> It really was. If you go back 10 years, we did our first integration sending data to StoreOnce and we had some blueprints around that. But now, if you look what we have, we have integrations on the primary side, so, 3PAR, Primera, Nimble, all their top-tier storage, we can manage the snapshots. We have integration on the target side. We integrate with Catalyst in the movement of data and the management of data. And, as David alluded to, we integrate with GreenLake. So, customers who want to take this as a consumption model, we integrate with that. And so it's been, like you said, the strongest relationship that we have on the technology alliance side. >> So, V12, you announced at VeeamON. What does that mean for HPE customers, the relationship? Maybe you guys could both talk about that. >> Technology side, to touch on a few things that we're doing with them, ransomware has been a huge issue. Security's been a big theme, obviously, at the conference, >> Dave: Yeah, you bet. and one of the things we're doing in V12 is adding immutability for both StoreOnce and StoreEver. So, we take the features that our partners have, immutability being big in the security space, and we integrate that fully into the product. So a customer checks a box and says, hey, I want to make sure that the data is secure. >> Yeah, and also, it's another signification about the relationship. Every single release we've done has had HPE at the heart of it, and the same thing is being said with V12. And it shows to our customers, the continual commitment. Relationships come and go. They're hard, and the great news is, 10 years has proven that we get through good times and tricky situations, and we both continue to invest, et cetera. And I think there's a lot of peace of mind and the revenue figures prove that, which is what we're really excited about. >> Yeah I want to come back to that, but just to follow up, Danny, on that immutability, that's a feature that you check? It's service within GreenLake, or within Veeam? How does that all work? >> We have immutability now depending on the target. We introduced the ability to send data, for example, into S3 two years ago, and make it immutable when you send it to an S3 or S3 compatible environment. We added, in Version 11, the ability to take a Linux repository and make it, and harden it, essentially make it immutable. But what we're doing now is taking our partner systems like StoreOnce, like StoreEver, and when we send data there, we take advantage of an API flag or whatever it happens to be, that it makes the data, when it's written to that system, can't be deleted, can't be encrypted. Now, what does that mean for a customer? Well, we do all the hard work in the back end, it's just a check box. They say, I want to make it immutable, and we manage how long it's immutable. Because if you made everything immutable forever, that's hugely expensive, right? So, it's all about, how long is that immutable before you age it out and make sure the new data coming in is immutable. >> Dave: It's like an insurance policy, you have that overlap. >> Yes. >> Right, okay. And then David, you mentioned the revenue, Lou bears that out. I got the IDC guys comin' on later on today. I'll ask 'em about that, if that's their swim lane. But you guys are basically a statistical tie, with Dell for number one? Am I getting that right? And you're growing at a faster rate, I believe, it's hard to tell 'cause I don't think Dell reports on the pace of its growth within data protection. You guys obviously do, but is that right? It's a statistical tie, is it? >> Yeah, hundred percent. >> Yeah, statistical tie for first place, which we're super excited about. When I joined Veeam, I think we were in fifth place, but we've been in the leader's quadrant of the Gartner Magic- >> Cause and effect there or? (panelists laughing) >> No, I don't think so. >> Dave: Ha, I think maybe. >> We've been on a great trajectory. But statistical tie for first place, greatest growth sequentially, and year-over-year, of all of the data protection vendors. And that's a testament not just to the technology that we're doing, but partnerships with HPE, because you never do this, the value of a technology is not that technology alone, it's the value of that technology within the ecosystem. And so that's why we're here at HPE Discover. It's our joint technology solutions that we're delivering. >> What are your thoughts or what are you seeing in the field on As-a-service? Because of course, the messaging is all about As-a-service, you'd think, oh, a hundred percent of everything is going to be As-a-service. A lot of customers, they don't mind CapEx, they got good, balance sheet, and they're like, hey, we'll take care of this, and, we're going to build our own little internal cloud. But, what are you seeing in the market in terms of As-a-service, versus, just traditional licensing models? >> Certainly, there's a mix between the two. What I'd say, is that sources that are already As-a-service, think Microsoft 365, think AWS, Azure, GCP, the cloud providers. There's a natural tendency for the customer to want the data protection As-a-service, as well for those. But if you talk about what's on premises, customers who have big data centers deployed, they're not yet, the pendulum has not shifted for that to be data protection As-a-service. But we were early to this game ourselves. We have 10,000, what we call, Veeam Cloud Service Providers, that are offering data protection As-a-service, whether it be on premises, so they're remotely managing it, or cloud hosted, doing data protection for that. >> So, you don't care. You're providing the technology, and then your customers are actually choosing the delivery model. Is that correct? >> A hundred percent, and if you think about what GreenLake is doing for example, that started off as being a financial model, but now they're getting into that services delivery. And what we want to do is enable them to deliver it, As-a-service, not just the financial model, but the outcome for the customer. And so our technology, it's not just do backup, it's do backup for a multi-tenant, multi-customer environment that does all of the multi-tenancy and billing and charge back as part of that service. >> Okay, so you guys don't report on this, but I'm going to ask the question anyway. You're number one now, let's call you, let's declare number one, 'cause we're well past that last reporting and you're growin' faster. So go another quarter, you're now number one, so you're the largest. Do you spend more on R&D in data protection than any other company? >> Yes, I'm quite certain that we do. Now, we have an unfair advantage because we have 450,000 customers. I don't think there's any other data protection company out there, the size and scope and scale, that we have. But we've been expanding, our largest R&D operation center's in Prague, it's in Czech Republic, but we've been expanding that. Last year it grew 40% year on year in R&D, so big investment in that space. You can see this just through our product space. Five years ago, we did data protection of VMware only, and now we do all the virtual environments, all the physical environments, all the major cloud environments, Kubernetes, Microsoft 365, we're launching Salesforce. We announced that at VeeamON last month and it will be coming out in Q3. All of that is coming from our R&D investments. >> A lot of people expect that when a company like Insight, a PE company, purchases a company like Veeam, that one of the things they'll dial down is R&D. That did not happen in this case. >> No, they very much treat us as a growth company. We had 22% year-over-year growth in 2020, and 25% year-over-year last year. The growth has been tremendous, they continue to give us the freedom. Now, I expect they'll want returns like that continuously, but we have been delivering, they have been investing. >> One of my favorite conversations of the year was our supercloud conversation, which was awesome, thank you for doing that with me. But that's clearly an area of focus, what we call supercloud, and you don't use that term, I know, you do sometimes, but it's not your marketing, I get that. But that is an R&D intensive effort, is it not? To create that common experience. And you see HPE, attempting to do that as well, across all these different estates. >> A hundred percent. We focus on three things, I always say, our differentiators, simplicity, flexibility, and reliability. Making it simple for the customers is not an easy thing to do. Making that checkbox for immutability? We have to do a lot behind the scenes to make it simple. Same thing on flexibility. We don't care if they're using 3PAR, Primera, Nimble, whatever you want to choose as the primary storage, we will take that out of your hands and make it really easy. You mentioned supercloud. We don't care what the cloud infrastructure, it can be on GreenLake, it can be on AWS, can be on Azure, it can be on GCP, it can be on IBM cloud. It is a lot of effort on our part to abstract the cloud infrastructure, but we do that on behalf of our customers to take away that complexity, it's part of our platform. >> Quick follow-up, and then I want to ask a question of David. I like talking to you guys because you don't care where it is, right? You're truly agnostic to it all. I'm trying to figure out this repatriation thing, cause I hear a lot of hey, Dave, you should look into repatriation that's happened all over the place, and I see pockets of it. What are you seeing in terms of repatriation? Have customers over-rotated to the cloud and now they're pullin' back a little bit? Or is it, as I'm claiming, in pockets? What's your visibility on that? >> Three things I see happening. There's the customers who lifted up their data center, moved it into the cloud and they get the first bill. >> (chuckling) Okay. >> And they will repatriate, there's no question. If I talk to those customers who simply lifted up and moved it over because the CIO told them to, they're moving it back on premises. But a second thing that we see is people moving it over, with tweaks. So they'll take their SQL server database and they'll move it into RDS, they'll change some things. And then you have people who are building cloud-native, they're never coming back on premises, they are building it for the cloud environment. So, we see all three of those. We only really see repatriation on that first scenario, when they get that first bill. >> And when you look at the numbers, I think it gets lost, 'cause you see the cloud is growing so fast. So David, what are the conversations like? You had several events last night, The Veeam party, slash Storage party, from HPE. What are you hearing from your alliance partners and the customers at the event. >> I think Danny touched on that point, it's about philosophy of evolution. And I think at the end of the day, whether we're seeing it with our GSI alliances we've got out there, or with the big enterprise conversations we're having with HPE, it's about understanding which workloads they want to move. In our mind, the customers are getting much smarter in making that decision, rather than experimenting. They're really taking a really solid look. And the work we're doing with the GSIs on workplace modernization, data center transformation, they're really having that investment work up front on the workloads, to be able to say, this works for me, for my personality and my company. And so, to the point about movement, it's more about decisive decision at the start, and not feeling like the remit is, I have to do one thing or another, it's about looking at that workflow position. And that's what we've seen with the revenue part as well. We've seen our movement to GreenLake tremendously grow in the last 18 months to two years. And from our GSI work as well, we're seeing the types of conversations really focus on that workload, compared to, hey, I just need a backup solution, and that's really exciting. >> Are you having specific conversations about security, or is it a data protection conversation still, (David chuckles) that's an adjacency to security? >> That's a great question. And I think it's a complex one, because if you come to a company like Veeam, we are there, and you touched on it before, we provide a solution when something has happened with security. We're not doing intrusion detection, we're not doing that barrier position at the end of it, but it's part of an end-to-end assumption. And I don't think that at this particular point, I started in security with RSA and Check Point, it was about layers of protection. Now it's layers of protection, and the inevitability that at some point something will happen, so about the recovery. So the exciting conversations we're having, especially with the big enterprises, is not about the fear factor, it's about, at some point something's going to occur. Speed of recovery is the conversation. And so for us, and your question is, are they talking to us about security, or more, the continuity position? And that's where the synergy's getting a lot simpler, rather than a hard demark between security and backup. >> Yeah, when you look at the stock market, everything's been hit, but security, with the exception of Okta, 'cause it got that weird benign hack, but security, generally, is an area that CIOs have said, hey, we can't really dial that back. We can maybe, some other discretionary stuff, we'll steal and prioritize. But security seems to be, and I think data protection is now part of that discussion. You're not a security company. We've seen some of your competitors actually pivot to become security companies. You're not doing that, but it's very clearly an adjacency, don't you think? >> It's an adjacency, and it's a new conversation that we're having with the Chief Information Security Officer. I had a meeting an hour ago with a customer who was hit by ransomware, and they got the call at 2:00 AM in the morning, after the ransomware they recovered their entire portfolio within 36 hours, from backups. Didn't even contact Veeam, I found out during this meeting. But that is clearly something that the Chief Information Security Officer wants to know about. It's part of his purview, is the recovery of that data. >> And they didn't pay the ransom? >> And they did not pay the ransom, not a penny. >> Ahh, we love those stories. Guys, thanks so much for coming on theCUBE. Congratulations on all the success. Love when you guys come on, and it was such a fun event at VeeamON. Great event here, and your presence is, was seen. The Veeam green is everywhere, so appreciate your time. >> Thank you. >> Thanks, Dave. >> Okay, and thank you for watching. This is Dave Vellante for John Furrier and Lisa Martin. We'll be back right after this short break. You're watching theCUBE's coverage of HPE Discover 2022, from Las Vegas. (inspiring music)

(upbeat music) >> Once a staid and boring business dominated by IBM, Oracle, and at the time newcomer Microsoft, along with a handful of wannabes, the database business has exploded in the past decade and has become a staple of financial excellence, customer experience, analytic advantage, competitive strategy, growth initiatives, visualizations, not to mention compliance, security, privacy and dozens of other important use cases and initiatives. And on the vendor's side of the house, we've seen the rapid ascendancy of cloud databases. Most notably from Snowflake, whose massive raises leading up to its IPO in late 2020 sparked a spate of interest and VC investment in the separation of compute and storage and all that elastic resource stuff in the cloud. The company joined AWS, Azure and Google to popularize cloud databases, which have become a linchpin of competitive strategies for technology suppliers. And if I get you to put your data in my database and in my cloud, and I keep innovating, I'm going to build a moat and achieve a hugely attractive lifetime customer value in a really amazing marginal economics dynamic that is going to fund my future. And I'll be able to sell other adjacent services, not just compute and storage, but machine learning and inference and training and all kinds of stuff, dozens of lucrative cloud offerings. Meanwhile, the database leader, Oracle has invested massive amounts of money to maintain its lead. It's building on its position as the king of mission critical workloads and making typical Oracle like claims against the competition. Most were recently just yesterday with another announcement around MySQL HeatWave. An extension of MySQL that is compatible with on-premises MySQLs and is setting new standards in price performance. We're seeing a dramatic divergence in strategies across the database spectrum. On the far left, we see Amazon with more than a dozen database offerings each with its own API and primitives. AWS is taking a right tool for the right job approach, often building on open source platforms and creating services that it offers to customers to solve very specific problems for developers. And on the other side of the line, we see Oracle, which is taking the Swiss Army Knife approach, converging database functionality, enabling analytic and transactional workloads to run in the same data store, eliminating the need to ETL, at the same time adding capabilities into its platform like automation and machine learning. Welcome to this database Power Panel. My name is Dave Vellante, and I'm so excited to bring together some of the most respected industry analyst in the community. Today we're going to assess what's happening in the market. We're going to dig into the competitive landscape and explore the future of database and database platforms and decode what it means to customers. Let me take a moment to welcome our guest analyst today. Matt Kimball is a vice president and principal analysts at Moor Insights and Strategy, Matt. He knows products, he knows industry, he's got real world IT expertise, and he's got all the angles 25 plus years of experience in all kinds of great background. Matt, welcome. Thanks very much for coming on theCUBE. Holgar Mueller, friend of theCUBE, vice president and principal analyst at Constellation Research in depth knowledge on applications, application development, knows developers. He's worked at SAP and Oracle. And then Bob Evans is Chief Content Officer and co-founder of the Acceleration Economy, founder and principle of Cloud Wars. Covers all kinds of industry topics and great insights. He's got awesome videos, these three minute hits. If you haven't seen 'em, checking them out, knows cloud companies, his Cloud Wars minutes are fantastic. And then of course, Marc Staimer is the founder of Dragon Slayer Research. A frequent contributor and guest analyst at Wikibon. He's got a wide ranging knowledge across IT products, knows technology really well, can go deep. And then of course, Ron Westfall, Senior Analyst and Director Research Director at Futurum Research, great all around product trends knowledge. Can take, you know, technical dives and really understands competitive angles, knows Redshift, Snowflake, and many others. Gents, thanks so much for taking the time to join us in theCube today. It's great to have you on, good to see you. >> Good to be here, thanks for having us. >> Thanks, Dave. >> All right, let's start with an around the horn and briefly, if each of you would describe, you know, anything I missed in your areas of expertise and then you answer the following question, how would you describe the state of the database, state of platform market today? Matt Kimball, please start. >> Oh, I hate going first, but that it's okay. How would I describe the world today? I would just in one sentence, I would say, I'm glad I'm not in IT anymore, right? So, you know, it is a complex and dangerous world out there. And I don't envy IT folks I'd have to support, you know, these modernization and transformation efforts that are going on within the enterprise. It used to be, you mentioned it, Dave, you would argue about IBM versus Oracle versus this newcomer in the database space called Microsoft. And don't forget Sybase back in the day, but you know, now it's not just, which SQL vendor am I going to go with? It's all of these different, divergent data types that have to be taken, they have to be merged together, synthesized. And somehow I have to do that cleanly and use this to drive strategic decisions for my business. That is not easy. So, you know, you have to look at it from the perspective of the business user. It's great for them because as a DevOps person, or as an analyst, I have so much flexibility and I have this thing called the cloud now where I can go get services immediately. As an IT person or a DBA, I am calling up prevention hotlines 24 hours a day, because I don't know how I'm going to be able to support the business. And as an Oracle or as an Oracle or a Microsoft or some of the cloud providers and cloud databases out there, I'm licking my chops because, you know, my market is expanding and expanding every day. >> Great, thank you for that, Matt. Holgar, how do you see the world these days? You always have a good perspective on things, share with us. >> Well, I think it's the best time to be in IT, I'm not sure what Matt is talking about. (laughing) It's easier than ever, right? The direction is going to cloud. Kubernetes has won, Google has the best AI for now, right? So things are easier than ever before. You made commitments for five plus years on hardware, networking and so on premise, and I got gray hair about worrying it was the wrong decision. No, just kidding. But you kind of both sides, just to be controversial, make it interesting, right. So yeah, no, I think the interesting thing specifically with databases, right? We have this big suite versus best of breed, right? Obviously innovation, like you mentioned with Snowflake and others happening in the cloud, the cloud vendors server, where to save of their databases. And then we have one of the few survivors of the old guard as Evans likes to call them is Oracle who's doing well, both their traditional database. And now, which is really interesting, remarkable from that because Oracle it was always the power of one, have one database, add more to it, make it what I call the universal database. And now this new HeatWave offering is coming and MySQL open source side. So they're getting the second (indistinct) right? So it's interesting that older players, traditional players who still are in the market are diversifying their offerings. Something we don't see so much from the traditional tools from Oracle on the Microsoft side or the IBM side these days. >> Great, thank you Holgar. Bob Evans, you've covered this business for a while. You've worked at, you know, a number of different outlets and companies and you cover the competition, how do you see things? >> Dave, you know, the other angle to look at this from is from the customer side, right? You got now CEOs who are any sort of business across all sorts of industries, and they understand that their future success is going to be dependent on their ability to become a digital company, to understand data, to use it the right way. So as you outline Dave, I think in your intro there, it is a fantastic time to be in the database business. And I think we've got a lot of new buyers and influencers coming in. They don't know all this history about IBM and Microsoft and Oracle and you know, whoever else. So I think they're going to take a long, hard look, Dave, at some of these results and who is able to help these companies not serve up the best technology, but who's going to be able to help their business move into the digital future. So it's a fascinating time now from every perspective. >> Great points, Bob. I mean, digital transformation has gone from buzzword to imperative. Mr. Staimer, how do you see things? >> I see things a little bit differently than my peers here in that I see the database market being segmented. There's all the different kinds of databases that people are looking at for different kinds of data, and then there is databases in the cloud. And so database as cloud service, I view very differently than databases because the traditional way of implementing a database is changing and it's changing rapidly. So one of the premises that you stated earlier on was that you viewed Oracle as a database company. I don't view Oracle as a database company anymore. I view Oracle as a cloud company that happens to have a significant expertise and specialty in databases, and they still sell database software in the traditional way, but ultimately they're a cloud company. So database cloud services from my point of view is a very distinct market from databases. >> Okay, well, you gave us some good meat on the bone to talk about that. Last but not least-- >> Dave did Marc, just say Oracle's a cloud company? >> Yeah. (laughing) Take away the database, it would be interesting to have that discussion, but let's let Ron jump in here. Ron, give us your take. >> That's a great segue. I think it's truly the era of the cloud database, that's something that's rising. And the key trends that come with it include for example, elastic scaling. That is the ability to scale on demand, to right size workloads according to customer requirements. And also I think it's going to increase the prioritization for high availability. That is the player who can provide the highest availability is going to have, I think, a great deal of success in this emerging market. And also I anticipate that there will be more consolidation across platforms in order to enable cost savings for customers, and that's something that's always going to be important. And I think we'll see more of that over the horizon. And then finally security, security will be more important than ever. We've seen a spike (indistinct), we certainly have seen geopolitical originated cybersecurity concerns. And as a result, I see database security becoming all the more important. >> Great, thank you. Okay, let me share some data with you guys. I'm going to throw this at you and see what you think. We have this awesome data partner called Enterprise Technology Research, ETR. They do these quarterly surveys and each period with dozens of industry segments, they track clients spending, customer spending. And this is the database, data warehouse sector okay so it's taxonomy, so it's not perfect, but it's a big kind of chunk. They essentially ask customers within a category and buy a specific vendor, you're spending more or less on the platform? And then they subtract the lesses from the mores and they derive a metric called net score. It's like NPS, it's a measure of spending velocity. It's more complicated and granular than that, but that's the basis and that's the vertical axis. The horizontal axis is what they call market share, it's not like IDC market share, it's just pervasiveness in the data set. And so there are a couple of things that stand out here and that we can use as reference point. The first is the momentum of Snowflake. They've been off the charts for many, many, for over two years now, anything above that dotted red line, that 40%, is considered by ETR to be highly elevated and Snowflake's even way above that. And I think it's probably not sustainable. We're going to see in the next April survey, next month from those guys, when it comes out. And then you see AWS and Microsoft, they're really pervasive on the horizontal axis and highly elevated, Google falls behind them. And then you got a number of well funded players. You got Cockroach Labs, Mongo, Redis, MariaDB, which of course is a fork on MySQL started almost as protest at Oracle when they acquired Sun and they got MySQL and you can see the number of others. Now Oracle who's the leading database player, despite what Marc Staimer says, we know, (laughs) and they're a cloud player (laughing) who happens to be a leading database player. They dominate in the mission critical space, we know that they're the king of that sector, but you can see here that they're kind of legacy, right? They've been around a long time, they get a big install base. So they don't have the spending momentum on the vertical axis. Now remember this is, just really this doesn't capture spending levels, so that understates Oracle but nonetheless. So it's not a complete picture like SAP for instance is not in here, no Hana. I think people are actually buying it, but it doesn't show up here, (laughs) but it does give an indication of momentum and presence. So Bob Evans, I'm going to start with you. You've commented on many of these companies, you know, what does this data tell you? >> Yeah, you know, Dave, I think all these compilations of things like that are interesting, and that folks at ETR do some good work, but I think as you said, it's a snapshot sort of a two-dimensional thing of a rapidly changing, three dimensional world. You know, the incidents at which some of these companies are mentioned versus the volume that happens. I think it's, you know, with Oracle and I'm not going to declare my religious affiliation, either as cloud company or database company, you know, they're all of those things and more, and I think some of our old language of how we classify companies is just not relevant anymore. But I want to ask too something in here, the autonomous database from Oracle, nobody else has done that. So either Oracle is crazy, they've tried out a technology that nobody other than them is interested in, or they're onto something that nobody else can match. So to me, Dave, within Oracle, trying to identify how they're doing there, I would watch autonomous database growth too, because right, it's either going to be a big plan and it breaks through, or it's going to be caught behind. And the Snowflake phenomenon as you mentioned, that is a rare, rare bird who comes up and can grow 100% at a billion dollar revenue level like that. So now they've had a chance to come in, scare the crap out of everybody, rock the market with something totally new, the data cloud. Will the bigger companies be able to catch up and offer a compelling alternative, or is Snowflake going to continue to be this outlier. It's a fascinating time. >> Really, interesting points there. Holgar, I want to ask you, I mean, I've talked to certainly I'm sure you guys have too, the founders of Snowflake that came out of Oracle and they actually, they don't apologize. They say, "Hey, we not going to do all that complicated stuff that Oracle does, we were trying to keep it real simple." But at the same time, you know, they don't do sophisticated workload management. They don't do complex joints. They're kind of relying on the ecosystems. So when you look at the data like this and the various momentums, and we talked about the diverging strategies, what does this say to you? >> Well, it is a great point. And I think Snowflake is an example how the cloud can turbo charge a well understood concept in this case, the data warehouse, right? You move that and you find steroids and you see like for some players who've been big in data warehouse, like Sentara Data, as an example, here in San Diego, what could have been for them right in that part. The interesting thing, the problem though is the cloud hides a lot of complexity too, which you can scale really well as you attract lots of customers to go there. And you don't have to build things like what Bob said, right? One of the fascinating things, right, nobody's answering Oracle on the autonomous database. I don't think is that they cannot, they just have different priorities or the database is not such a priority. I would dare to say that it's for IBM and Microsoft right now at the moment. And the cloud vendors, you just hide that right through scripts and through scale because you support thousands of customers and you can deal with a little more complexity, right? It's not against them. Whereas if you have to run it yourself, very different story, right? You want to have the autonomous parts, you want to have the powerful tools to do things. >> Thank you. And so Matt, I want to go to you, you've set up front, you know, it's just complicated if you're in IT, it's a complicated situation and you've been on the customer side. And if you're a buyer, it's obviously, it's like Holgar said, "Cloud's supposed to make this stuff easier, but the simpler it gets the more complicated gets." So where do you place your bets? Or I guess more importantly, how do you decide where to place your bets? >> Yeah, it's a good question. And to what Bob and Holgar said, you know, the around autonomous database, I think, you know, part of, as I, you know, play kind of armchair psychologist, if you will, corporate psychologists, I look at what Oracle is doing and, you know, databases where they've made their mark and it's kind of, that's their strong position, right? So it makes sense if you're making an entry into this cloud and you really want to kind of build momentum, you go with what you're good at, right? So that's kind of the strength of Oracle. Let's put a lot of focus on that. They do a lot more than database, don't get me wrong, but you know, I'm going to short my strength and then kind of pivot from there. With regards to, you know, what IT looks at and what I would look at you know as an IT director or somebody who is, you know, trying to consume services from these different cloud providers. First and foremost, I go with what I know, right? Let's not forget IT is a conservative group. And when we look at, you know, all the different permutations of database types out there, SQL, NoSQL, all the different types of NoSQL, those are largely being deployed by business users that are looking for agility or businesses that are looking for agility. You know, the reason why MongoDB is so popular is because of DevOps, right? It's a great platform to develop on and that's where it kind of gained its traction. But as an IT person, I want to go with what I know, where my muscle memory is, and that's my first position. And so as I evaluate different cloud service providers and cloud databases, I look for, you know, what I know and what I've invested in and where my muscle memory is. Is there enough there and do I have enough belief that that company or that service is going to be able to take me to, you know, where I see my organization in five years from a data management perspective, from a business perspective, are they going to be there? And if they are, then I'm a little bit more willing to make that investment, but it is, you know, if I'm kind of going in this blind or if I'm cloud native, you know, that's where the Snowflakes of the world become very attractive to me. >> Thank you. So Marc, I asked Andy Jackson in theCube one time, you have all these, you know, data stores and different APIs and primitives and you know, very granular, what's the strategy there? And he said, "Hey, that allows us as the market changes, it allows us to be more flexible. If we start building abstractions layers, it's harder for us." I think also it was not a good time to market advantage, but let me ask you, I described earlier on that spectrum from AWS to Oracle. We just saw yesterday, Oracle announced, I think the third major enhancement in like 15 months to MySQL HeatWave, what do you make of that announcement? How do you think it impacts the competitive landscape, particularly as it relates to, you know, converging transaction and analytics, eliminating ELT, I know you have some thoughts on this. >> So let me back up for a second and defend my cloud statement about Oracle for a moment. (laughing) AWS did a great job in developing the cloud market in general and everything in the cloud market. I mean, I give them lots of kudos on that. And a lot of what they did is they took open source software and they rent it to people who use their cloud. So I give 'em lots of credit, they dominate the market. Oracle was late to the cloud market. In fact, they actually poo-pooed it initially, if you look at some of Larry Ellison's statements, they said, "Oh, it's never going to take off." And then they did 180 turn, and they said, "Oh, we're going to embrace the cloud." And they really have, but when you're late to a market, you've got to be compelling. And this ties into the announcement yesterday, but let's deal with this compelling. To be compelling from a user point of view, you got to be twice as fast, offer twice as much functionality, at half the cost. That's generally what compelling is that you're going to capture market share from the leaders who established the market. It's very difficult to capture market share in a new market for yourself. And you're right. I mean, Bob was correct on this and Holgar and Matt in which you look at Oracle, and they did a great job of leveraging their database to move into this market, give 'em lots of kudos for that too. But yesterday they announced, as you said, the third innovation release and the pace is just amazing of what they're doing on these releases on HeatWave that ties together initially MySQL with an integrated builtin analytics engine, so a data warehouse built in. And then they added automation with autopilot, and now they've added machine learning to it, and it's all in the same service. It's not something you can buy and put on your premise unless you buy their cloud customers stuff. But generally it's a cloud offering, so it's compellingly better as far as the integration. You don't buy multiple services, you buy one and it's lower cost than any of the other services, but more importantly, it's faster, which again, give 'em credit for, they have more integration of a product. They can tie things together in a way that nobody else does. There's no additional services, ETL services like Glue and AWS. So from that perspective, they're getting better performance, fewer services, lower cost. Hmm, they're aiming at the compelling side again. So from a customer point of view it's compelling. Matt, you wanted to say something there. >> Yeah, I want to kind of, on what you just said there Marc, and this is something I've found really interesting, you know. The traditional way that you look at software and, you know, purchasing software and IT is, you look at either best of breed solutions and you have to work on the backend to integrate them all and make them all work well. And generally, you know, the big hit against the, you know, we have one integrated offering is that, you lose capability or you lose depth of features, right. And to what you were saying, you know, that's the thing I found interesting about what Oracle is doing is they're building in depth as they kind of, you know, build that service. It's not like you're losing a lot of capabilities, because you're going to one integrated service versus having to use A versus B versus C, and I love that idea. >> You're right. Yeah, not only you're not losing, but you're gaining functionality that you can't get by integrating a lot of these. I mean, I can take Snowflake and integrate it in with machine learning, but I also have to integrate in with a transactional database. So I've got to have connectors between all of this, which means I'm adding time. And what it comes down to at the end of the day is expertise, effort, time, and cost. And so what I see the difference from the Oracle announcements is they're aiming at reducing all of that by increasing performance as well. Correct me if I'm wrong on that but that's what I saw at the announcement yesterday. >> You know, Marc, one thing though Marc, it's funny you say that because I started out saying, you know, I'm glad I'm not 19 anymore. And the reason is because of exactly what you said, it's almost like there's a pseudo level of witchcraft that's required to support the modern data environment right in the enterprise. And I need simpler faster, better. That's what I need, you know, I am no longer wearing pocket protectors. I have turned from, you know, break, fix kind of person, to you know, business consultant. And I need that point and click simplicity, but I can't sacrifice, you know, a depth of features of functionality on the backend as I play that consultancy role. >> So, Ron, I want to bring in Ron, you know, it's funny. So Matt, you mentioned Mongo, I often and say, if Oracle mentions you, you're on the map. We saw them yesterday Ron, (laughing) they hammered RedShifts auto ML, they took swipes at Snowflake, a little bit of BigQuery. What were your thoughts on that? Do you agree with what these guys are saying in terms of HeatWaves capabilities? >> Yes, Dave, I think that's an excellent question. And fundamentally I do agree. And the question is why, and I think it's important to know that all of the Oracle data is backed by the fact that they're using benchmarks. For example, all of the ML and all of the TPC benchmarks, including all the scripts, all the configs and all the detail are posted on GitHub. So anybody can look at these results and they're fully transparent and replicate themselves. If you don't agree with this data, then by all means challenge it. And we have not really seen that in all of the new updates in HeatWave over the last 15 months. And as a result, when it comes to these, you know, fundamentals in looking at the competitive landscape, which I think gives validity to outcomes such as Oracle being able to deliver 4.8 times better price performance than Redshift. As well as for example, 14.4 better price performance than Snowflake, and also 12.9 better price performance than BigQuery. And so that is, you know, looking at the quantitative side of things. But again, I think, you know, to Marc's point and to Matt's point, there are also qualitative aspects that clearly differentiate the Oracle proposition, from my perspective. For example now the MySQL HeatWave ML capabilities are native, they're built in, and they also support things such as completion criteria. And as a result, that enables them to show that hey, when you're using Redshift ML for example, you're having to also use their SageMaker tool and it's running on a meter. And so, you know, nobody really wants to be running on a meter when, you know, executing these incredibly complex tasks. And likewise, when it comes to Snowflake, they have to use a third party capability. They don't have the built in, it's not native. So the user, to the point that he's having to spend more time and it increases complexity to use auto ML capabilities across the Snowflake platform. And also, I think it also applies to other important features such as data sampling, for example, with the HeatWave ML, it's intelligent sampling that's being implemented. Whereas in contrast, we're seeing Redshift using random sampling. And again, Snowflake, you're having to use a third party library in order to achieve the same capabilities. So I think the differentiation is crystal clear. I think it definitely is refreshing. It's showing that this is where true value can be assigned. And if you don't agree with it, by all means challenge the data. >> Yeah, I want to come to the benchmarks in a minute. By the way, you know, the gentleman who's the Oracle's architect, he did a great job on the call yesterday explaining what you have to do. I thought that was quite impressive. But Bob, I know you follow the financials pretty closely and on the earnings call earlier this month, Ellison said that, "We're going to see HeatWave on AWS." And the skeptic in me said, oh, they must not be getting people to come to OCI. And then they, you remember this chart they showed yesterday that showed the growth of HeatWave on OCI. But of course there was no data on there, it was just sort of, you know, lines up and to the right. So what do you guys think of that? (Marc laughs) Does it signal Bob, desperation by Oracle that they can't get traction on OCI, or is it just really a smart tame expansion move? What do you think? >> Yeah, Dave, that's a great question. You know, along the way there, and you know, just inside of that was something that said Ellison said on earnings call that spoke to a different sort of philosophy or mindset, almost Marc, where he said, "We're going to make this multicloud," right? With a lot of their other cloud stuff, if you wanted to use any of Oracle's cloud software, you had to use Oracle's infrastructure, OCI, there was no other way out of it. But this one, but I thought it was a classic Ellison line. He said, "Well, we're making this available on AWS. We're making this available, you know, on Snowflake because we're going after those users. And once they see what can be done here." So he's looking at it, I guess you could say, it's a concession to customers because they want multi-cloud. The other way to look at it, it's a hunting expedition and it's one of those uniquely I think Oracle ways. He said up front, right, he doesn't say, "Well, there's a big market, there's a lot for everybody, we just want on our slice." Said, "No, we are going after Amazon, we're going after Redshift, we're going after Aurora. We're going after these users of Snowflake and so on." And I think it's really fairly refreshing these days to hear somebody say that, because now if I'm a buyer, I can look at that and say, you know, to Marc's point, "Do they measure up, do they crack that threshold ceiling? Or is this just going to be more pain than a few dollars savings is worth?" But you look at those numbers that Ron pointed out and that we all saw in that chart. I've never seen Dave, anything like that. In a substantive market, a new player coming in here, and being able to establish differences that are four, seven, eight, 10, 12 times better than competition. And as new buyers look at that, they're going to say, "What the hell are we doing paying, you know, five times more to get a poor result? What's going on here?" So I think this is going to rattle people and force a harder, closer look at what these alternatives are. >> I wonder if the guy, thank you. Let's just skip ahead of the benchmarks guys, bring up the next slide, let's skip ahead a little bit here, which talks to the benchmarks and the benchmarking if we can. You know, David Floyer, the sort of semiretired, you know, Wikibon analyst said, "Dave, this is going to force Amazon and others, Snowflake," he said, "To rethink actually how they architect databases." And this is kind of a compilation of some of the data that they shared. They went after Redshift mostly, (laughs) but also, you know, as I say, Snowflake, BigQuery. And, like I said, you can always tell which companies are doing well, 'cause Oracle will come after you, but they're on the radar here. (laughing) Holgar should we take this stuff seriously? I mean, or is it, you know, a grain salt? What are your thoughts here? >> I think you have to take it seriously. I mean, that's a great question, great point on that. Because like Ron said, "If there's a flaw in a benchmark, we know this database traditionally, right?" If anybody came up that, everybody will be, "Oh, you put the wrong benchmark, it wasn't audited right, let us do it again," and so on. We don't see this happening, right? So kudos to Oracle to be aggressive, differentiated, and seem to having impeccable benchmarks. But what we really see, I think in my view is that the classic and we can talk about this in 100 years, right? Is the suite versus best of breed, right? And the key question of the suite, because the suite's always slower, right? No matter at which level of the stack, you have the suite, then the best of breed that will come up with something new, use a cloud, put the data warehouse on steroids and so on. The important thing is that you have to assess as a buyer what is the speed of my suite vendor. And that's what you guys mentioned before as well, right? Marc said that and so on, "Like, this is a third release in one year of the HeatWave team, right?" So everybody in the database open source Marc, and there's so many MySQL spinoffs to certain point is put on shine on the speed of (indistinct) team, putting out fundamental changes. And the beauty of that is right, is so inherent to the Oracle value proposition. Larry's vision of building the IBM of the 21st century, right from the Silicon, from the chip all the way across the seven stacks to the click of the user. And that what makes the database what Rob was saying, "Tied to the OCI infrastructure," because designed for that, it runs uniquely better for that, that's why we see the cross connect to Microsoft. HeatWave so it's different, right? Because HeatWave runs on cheap hardware, right? Which is the breadth and butter 886 scale of any cloud provider, right? So Oracle probably needs it to scale OCI in a different category, not the expensive side, but also allow us to do what we said before, the multicloud capability, which ultimately CIOs really want, because data gravity is real, you want to operate where that is. If you have a fast, innovative offering, which gives you more functionality and the R and D speed is really impressive for the space, puts away bad results, then it's a good bet to look at. >> Yeah, so you're saying, that we versus best of breed. I just want to sort of play back then Marc a comment. That suite versus best of breed, there's always been that trade off. If I understand you Holgar you're saying that somehow Oracle has magically cut through that trade off and they're giving you the best of both. >> It's the developing velocity, right? The provision of important features, which matter to buyers of the suite vendor, eclipses the best of breed vendor, then the best of breed vendor is in the hell of a potential job. >> Yeah, go ahead Marc. >> Yeah and I want to add on what Holgar just said there. I mean the worst job in the data center is data movement, moving the data sucks. I don't care who you are, nobody likes it. You never get any kudos for doing it well, and you always get the ah craps, when things go wrong. So it's in- >> In the data center Marc all the time across data centers, across cloud. That's where the bleeding comes. >> It's right, you get beat up all the time. So nobody likes to move data, ever. So what you're looking at with what they announce with HeatWave and what I love about HeatWave is it doesn't matter when you started with it, you get all the additional features they announce it's part of the service, all the time. But they don't have to move any of the data. You want to analyze the data that's in your transactional, MySQL database, it's there. You want to do machine learning models, it's there, there's no data movement. The data movement is the key thing, and they just eliminate that, in so many ways. And the other thing I wanted to talk about is on the benchmarks. As great as those benchmarks are, they're really conservative 'cause they're underestimating the cost of that data movement. The ETLs, the other services, everything's left out. It's just comparing HeatWave, MySQL cloud service with HeatWave versus Redshift, not Redshift and Aurora and Glue, Redshift and Redshift ML and SageMaker, it's just Redshift. >> Yeah, so what you're saying is what Oracle's doing is saying, "Okay, we're going to run MySQL HeatWave benchmarks on analytics against Redshift, and then we're going to run 'em in transaction against Aurora." >> Right. >> But if you really had to look at what you would have to do with the ETL, you'd have to buy two different data stores and all the infrastructure around that, and that goes away so. >> Due to the nature of the competition, they're running narrow best of breed benchmarks. There is no suite level benchmark (Dave laughs) because they created something new. >> Well that's you're the earlier point they're beating best of breed with a suite. So that's, I guess to Floyer's earlier point, "That's going to shake things up." But I want to come back to Bob Evans, 'cause I want to tap your Cloud Wars mojo before we wrap. And line up the horses, you got AWS, you got Microsoft, Google and Oracle. Now they all own their own cloud. Snowflake, Mongo, Couchbase, Redis, Cockroach by the way they're all doing very well. They run in the cloud as do many others. I think you guys all saw the Andreessen, you know, commentary from Sarah Wang and company, to talk about the cost of goods sold impact of cloud. So owning your own cloud has to be an advantage because other guys like Snowflake have to pay cloud vendors and negotiate down versus having the whole enchilada, Safra Catz's dream. Bob, how do you think this is going to impact the market long term? >> Well, Dave, that's a great question about, you know, how this is all going to play out. If I could mention three things, one, Frank Slootman has done a fantastic job with Snowflake. Really good company before he got there, but since he's been there, the growth mindset, the discipline, the rigor and the phenomenon of what Snowflake has done has forced all these bigger companies to really accelerate what they're doing. And again, it's an example of how this intense competition makes all the different cloud vendors better and it provides enormous value to customers. Second thing I wanted to mention here was look at the Adam Selipsky effect at AWS, took over in the middle of May, and in Q2, Q3, Q4, AWS's growth rate accelerated. And in each of those three quotas, they grew faster than Microsoft's cloud, which has not happened in two or three years, so they're closing the gap on Microsoft. The third thing, Dave, in this, you know, incredibly intense competitive nature here, look at Larry Ellison, right? He's got his, you know, the product that for the last two or three years, he said, "It's going to help determine the future of the company, autonomous database." You would think he's the last person in the world who's going to bring in, you know, in some ways another database to think about there, but he has put, you know, his whole effort and energy behind this. The investments Oracle's made, he's riding this horse really hard. So it's not just a technology achievement, but it's also an investment priority for Oracle going forward. And I think it's going to form a lot of how they position themselves to this new breed of buyer with a new type of need and expectations from IT. So I just think the next two or three years are going to be fantastic for people who are lucky enough to get to do the sorts of things that we do. >> You know, it's a great point you made about AWS. Back in 2018 Q3, they were doing about 7.4 billion a quarter and they were growing in the mid forties. They dropped down to like 29% Q4, 2020, I'm looking at the data now. They popped back up last quarter, last reported quarter to 40%, that is 17.8 billion, so they more doubled and they accelerated their growth rate. (laughs) So maybe that pretends, people are concerned about Snowflake right now decelerating growth. You know, maybe that's going to be different. By the way, I think Snowflake has a different strategy, the whole data cloud thing, data sharing. They're not trying to necessarily take Oracle head on, which is going to make this next 10 years, really interesting. All right, we got to go, last question. 30 seconds or less, what can we expect from the future of data platforms? Matt, please start. >> I have to go first again? You're killing me, Dave. (laughing) In the next few years, I think you're going to see the major players continue to meet customers where they are, right. Every organization, every environment is, you know, kind of, we use these words bespoke in Snowflake, pardon the pun, but Snowflakes, right. But you know, they're all opinionated and unique and what's great as an IT person is, you know, there is a service for me regardless of where I am on my journey, in my data management journey. I think you're going to continue to see with regards specifically to Oracle, I think you're going to see the company continue along this path of being all things to all people, if you will, or all organizations without sacrificing, you know, kind of richness of features and sacrificing who they are, right. Look, they are the data kings, right? I mean, they've been a database leader for an awful long time. I don't see that going away any time soon and I love the innovative spirit they've brought in with HeatWave. >> All right, great thank you. Okay, 30 seconds, Holgar go. >> Yeah, I mean, the interesting thing that we see is really that trend to autonomous as Oracle calls or self-driving software, right? So the database will have to do more things than just store the data and support the DVA. It will have to show it can wide insights, the whole upside, it will be able to show to one machine learning. We haven't really talked about that. How in just exciting what kind of use case we can get of machine learning running real time on data as it changes, right? So, which is part of the E5 announcement, right? So we'll see more of that self-driving nature in the database space. And because you said we can promote it, right. Check out my report about HeatWave latest release where I post in oracle.com. >> Great, thank you for that. And Bob Evans, please. You're great at quick hits, hit us. >> Dave, thanks. I really enjoyed getting to hear everybody's opinion here today and I think what's going to happen too. I think there's a new generation of buyers, a new set of CXO influencers in here. And I think what Oracle's done with this, MySQL HeatWave, those benchmarks that Ron talked about so eloquently here that is going to become something that forces other companies, not just try to get incrementally better. I think we're going to see a massive new wave of innovation to try to play catch up. So I really take my hat off to Oracle's achievement from going to, push everybody to be better. >> Excellent. Marc Staimer, what do you say? >> Sure, I'm going to leverage off of something Matt said earlier, "Those companies that are going to develop faster, cheaper, simpler products that are going to solve customer problems, IT problems are the ones that are going to succeed, or the ones who are going to grow. The one who are just focused on the technology are going to fall by the wayside." So those who can solve more problems, do it more elegantly and do it for less money are going to do great. So Oracle's going down that path today, Snowflake's going down that path. They're trying to do more integration with third party, but as a result, aiming at that simpler, faster, cheaper mentality is where you're going to continue to see this market go. >> Amen brother Marc. >> Thank you, Ron Westfall, we'll give you the last word, bring us home. >> Well, thank you. And I'm loving it. I see a wave of innovation across the entire cloud database ecosystem and Oracle is fueling it. We are seeing it, with the native integration of auto ML capabilities, elastic scaling, lower entry price points, et cetera. And this is just going to be great news for buyers, but also developers and increased use of open APIs. And so I think that is really the key takeaways. Just we're going to see a lot of great innovation on the horizon here. >> Guys, fantastic insights, one of the best power panel as I've ever done. Love to have you back. Thanks so much for coming on today. >> Great job, Dave, thank you. >> All right, and thank you for watching. This is Dave Vellante for theCube and we'll see you next time. (soft music)

(upbeat music) >> When Oracle acquired Sun in 2009, it paid $5.6 billion net of Sun's cash and debt. Now I argued at the time that Oracle got one of the best deals in the history of enterprise tech, and I got a lot of grief for saying that because Sun had a declining business, it was losing money, and its revenue was under serious pressure as it tried to hang on for dear life. But Safra Catz understood that Oracle could pay Sun's lower profit and lagging businesses, like its low index 86 product lines, and even if Sun's revenue was cut in half, because Oracle has such a high revenue multiple as a software company, it could almost instantly generate $25 to $30 billion in shareholder value on paper. In addition, it was a catalyst for Oracle to initiate its highly differentiated engineering systems business, and was actually the precursor to Oracle's Cloud. Oracle saw that it could capture high margin dollars that used to go to partners like HP, it's original exit data partner, and get paid for the full stack across infrastructure, middleware, database, and application software, when eventually got really serious about cloud. Now there was also a major technology angle to this story. Remember Sun's tagline, "the network is the computer"? Well, they should have just called it cloud. Through the Sun acquisition. Oracle also got a couple of key technologies, Java, the number one programming language in the world, and MySQL, a key ingredient of the LAMP stack, that's Linux, Apache, MySQL and PHP, Perl or Python, on which the internet is basically built, and is used by many cloud services like Facebook, Twitter, WordPress, Flicker, Amazon, Aurora, and many other examples, including, by the way, Maria DB, which is a fork of MySQL created by MySQL's creator, basically in protest to Oracle's acquisition; the drama is Oscar worthy. It gets even better. In 2020, Oracle began introducing a new version of MySQL called MySQL HeatWave, and since late 2020 it's been in sort of a super cycle rolling, out three new releases in less than a year and a half in an attempt to expand its Tam and compete in new markets. Now we covered the release of MySQL Autopilot, which uses machine learning to automate management functions. And we also covered the bench marketing that Oracle produced against Snowflake, AWS, Azure, and Google. And Oracle's at it again with HeatWave, adding machine learning into its database capabilities, along with previously available integrations of OLAP and OLTP. This, of course, is in line with Oracle's converged database philosophy, which, as we've reported, is different from other cloud database providers, most notably Amazon, which takes the right tool for the right job approach and chooses database specialization over a one size fits all strategy. Now we've asked Oracle to come on theCUBE and explain these moves, and I'm pleased to welcome back Nipun Agarwal, who's the senior vice president for MySQL Database and HeatWave at Oracle. And today, in this video exclusive, we'll discuss machine learning, other new capabilities around elasticity and compression, and then any benchmark data that Nipun wants to share. Nipun's been a leading advocate of the HeatWave program. He's led engineering in that team for over 10 years, and he has over 185 patents in database technologies. Welcome back to the show Nipun. Great to see you again. Thanks for coming on. >> Thank you, Dave. Very happy to be back. >> Yeah, now for those who may not have kept up with the news, maybe to kick things off you could give us an overview of what MySQL HeatWave actually is so that we're all on the same page. >> Sure, Dave, MySQL HeatWave is a fully managed MySQL database service from Oracle, and it has a builtin query accelerator called HeatWave, and that's the part which is unique. So with MySQL HeatWave, customers of MySQL get a single database which they can use for transactional processing, for analytics, and for mixed workloads because traditionally MySQL has been designed and optimized for transaction processing. So in the past, when customers had to run analytics with the MySQL based service, they would need to move the data out of MySQL into some other database for running analytics. So they would end up with two different databases and it would take some time to move the data out of MySQL into this other system. With MySQL HeatWave, we have solved this problem and customers now have a single MySQL database for all their applications, and they can get the good performance of analytics without any changes to their MySQL application. >> Now it's no secret that a lot of times, you know, queries are not, you know, most efficiently written, and critics of MySQL HeatWave will claim that this product is very memory and cluster intensive, it has a heavy footprint that adds to cost. How do you answer that, Nipun? >> Right, so for offering any database service in the cloud there are two dimensions, performance and cost, and we have been very cognizant of both of them. So it is indeed the case that HeatWave is a, in-memory query accelerator, which is why we get very good performance, but it is also the case that we have optimized HeatWave for commodity cloud services. So for instance, we use the least expensive compute. We use the least expensive storage. So what I would suggest is for the customers who kind of would like to know what is the price performance advantage of HeatWave compared to any database we have benchmark against, Redshift, Snowflake, Google BigQuery, Azure Synapse, HeatWave is significantly faster and significantly lower price on a multitude of workloads. So not only is it in-memory database and optimized for that, but we have also optimized it for commodity cloud services, which makes it much lower price than the competition. >> Well, at the end of the day, it's customers that sort of decide what the truth is. So to date, what's been the customer reaction? Are they moving from other clouds from on-prem environments? Both why, you know, what are you seeing? >> Right, so we are definitely a whole bunch of migrations of customers who are running MySQL on-premise to the cloud, to MySQL HeatWave. That's definitely happening. What is also very interesting is we are seeing that a very large percentage of customers, more than half the customers who are coming to MySQL HeatWave, are migrating from other clouds. We have a lot of migrations coming from AWS Aurora, migrations from RedShift, migrations from RDS MySQL, TerriData, SAP HANA, right. So we are seeing migrations from a whole bunch of other databases and other cloud services to MySQL HeatWave. And the main reason we are told why customers are migrating from other databases to MySQL HeatWave are lower cost, better performance, and no change to their application because many of these services, like AWS Aurora are ETL compatible with MySQL. So when customers try MySQL HeatWave, not only do they get better performance at a lower cost, but they find that they can migrate their application without any changes, and that's a big incentive for them. >> Great, thank you, Nipun. So can you give us some names? Are there some real world examples of these customers that have migrated to MySQL HeatWave that you can share? >> Oh, absolutely, I'll give you a few names. Stutor.com, this is an educational SaaS provider raised out of Brazil. They were using Google BigQuery, and when they migrated to MySQL HeatWave, they found a 300X, right, 300 times improvement in performance, and it lowered their cost by 85 (audio cut out). Another example is Neovera. They offer cybersecurity solutions and they were running their application on an on-premise version of MySQL when they migrated to MySQL HeatWave, their application improved in performance by 300 times and their cost reduced by 80%, right. So by going from on-premise to MySQL HeatWave, they reduced the cost by 80%, improved performance by 300 times. We are Glass, another customer based out of Brazil. They were running on AWS EC2, and when they migrated, within hours they found that there was a significant improvement, like, you know, over 5X improvement in database performance, and they were able to accommodate a very large virtual event, which had more than a million visitors. Another example, Genius Senority. They are a game designer in Japan, and when they moved to MySQL HeatWave, they found a 90 times percent improvement in performance. And there many, many more like a lot of migrations, again, from like, you know, Aurora, RedShift and many other databases as well. And consistently what we hear is (audio cut out) getting much better performance at a much lower cost without any change to their application. >> Great, thank you. You know, when I ask that question, a lot of times I get, "Well, I can't name the customer name," but I got to give Oracle credit, a lot of times you guys have at your fingertips. So you're not the only one, but it's somewhat rare in this industry. So, okay, so you got some good feedback from those customers that did migrate to MySQL HeatWave. What else did they tell you that they wanted? Did they, you know, kind of share a wishlist and some of the white space that you guys should be working on? What'd they tell you? >> Right, so as customers are moving more data into MySQL HeatWave, as they're consolidating more data into MySQL HeatWave, customers want to run other kinds of processing with this data. A very popular one is (audio cut out) So we have had multiple customers who told us that they wanted to run machine learning with data which is stored in MySQL HeatWave, and for that they have to extract the data out of MySQL (audio cut out). So that was the first feedback we got. Second thing is MySQL HeatWave is a highly scalable system. What that means is that as you add more nodes to a HeatWave cluster, the performance of the system improves almost linearly. But currently customers need to perform some manual steps to add most to a cluster or to reduce the cluster size. So that was other feedback we got that people wanted this thing to be automated. Third thing is that we have shown in the previous results, that HeatWave is significantly faster and significantly lower price compared to competitive services. So we got feedback from customers that can we trade off some performance to get even lower cost, and that's what we have looked at. And then finally, like we have some results on various data sizes with TPC-H. Customers wanted to see if we can offer some more data points as to how does HeatWave perform on other kinds of workloads. And that's what we've been working on for the several months. >> Okay, Nipun, we're going to get into some of that, but, so how did you go about addressing these requirements? >> Right, so the first thing is we are announcing support for in-database machine learning, meaning that customers who have their data inside MySQL HeatWave can now run training, inference, and prediction all inside the database without the data or the model ever having to leave the database. So that's how we address the first one. Second thing is we are offering support for real time elasticity, meaning that customers can scale up or scale down to any number of nodes. This requires no manual intervention on part of the user, and for the entire duration of the resize operation, the system is fully available. The third, in terms of the costs, we have double the amount of data that can be processed per node. So if you look at a HeatWave cluster, the size of the cluster determines the cost. So by doubling the amount of data that can be processed per node, we have effectively reduced the cluster size which is required for planning a given workload to have, which means it reduces the cost to the customer by half. And finally, we have also run the TPC-DS workload on HeatWave and compared it with other vendors. So now customers can have another data point in terms of the performance and the cost comparison of HeatWave with other services. >> All right, and I promise, I'm going to ask you about the benchmarks, but I want to come back and drill into these a bit. How is HeatWave ML different from competitive offerings? Take for instance, Redshift ML, for example. >> Sure, okay, so this is a good comparison. Let's start with, let's say RedShift ML, like there are some systems like, you know, Snowflake, which don't even offer any, like, processing of machine learning inside the database, and they expect customers to write a whole bunch of code, in say Python or Java, to do machine learning. RedShift ML does have integration with SQL. That's a good start. However, when customers of Redshift need to run machine learning, and they invoke Redshift ML, it makes a call to another service, SageMaker, right, where so the data needs to be exported to a different service. The model is generated, and the model is also outside RedShift. With HeatWave ML, the data resides always inside the MySQL database service. We are able to generate models. We are able to train the models, run inference, run explanations, all inside the MySQL HeatWave service. So the data, or the model, never have to leave the database, which means that both the data and the models can now be secured by the same access control mechanisms as the rest of the data. So that's the first part, that there is no need for any ETL. The second aspect is the automation. Training is a very important part of machine learning, right, and it impacts the quality of the predictions and such. So traditionally, customers would employ data scientists to influence the training process so that it's done right. And even in the case of Redshift ML, the users are expected to provide a lot of parameters to the training process. So the second thing which we have worked on with HeatWave ML is that it is fully automated. There is absolutely no user intervention required for training. Third is in terms of performance. So one of the things we are very, very sensitive to is performance because performance determines the eventual cost to the customer. So again, in some benchmarks, which we have published, and these are all available on GitHub, we are showing how HeatWave ML is 25 times faster than Redshift ML, and here's the kicker, at 1% of the cost. So four benefits, the data all remain secure inside the database service, it's fully automated, much faster, much lower cost than the competition. >> All right, thank you Nipun. Now, so there's a lot of talk these days about explainability and AI. You know, the system can very accurately tell you that it's a cat, you know, or for you Silicon Valley fans, it's a hot dog or not a hot dog, but they can't tell you how the system got there. So what is explainability, and why should people care about it? >> Right, so when we were talking to customers about what they would like from a machine learning based solution, one of the feedbacks we got is that enterprise is a little slow or averse to uptaking machine learning, because it seems to be, you know, like magic, right? And enterprises have the obligation to be able to explain, or to provide a answer to their customers as to why did the database make a certain choice. With a rule based solution it's simple, it's a rule based thing, and you know what the logic was. So the reason explanations are important is because customers want to know why did the system make a certain prediction? One of the important characteristics of HeatWave ML is that any model which is generated by HeatWave ML can be explained, and we can do both global explanations or model explanations as well as we can also do local explanations. So when the system makes a specific prediction using HeatWave ML, the user can find out why did the system make such a prediction? So for instance, if someone is being denied a loan, the user can figure out what were the attribute, what were the features which led to that decision? So this ensures, like, you know, fairness, and many of the times there is also like a need for regulatory compliance where users have a right to know. So we feel that explanations are very important for enterprise workload, and that's why every model which is generated by HeatWave ML can be explained. >> Now I got to give Snowflakes some props, you know, this whole idea of separating compute from storage, but also bringing the database to the cloud and driving elasticity. So that's been a key enabler and has solved a lot of problems, in particular the snake swallowing the basketball problem, as I often say. But what about elasticity and elasticity in real time? How is your version, and there's a lot of companies chasing this, how is your approach to an elastic cloud database service different from what others are promoting these days? >> Right, so a couple of characteristics. One is that we have now fully automated the process of elasticity, meaning that if a user wants to scale up or scale down, the only thing they need to specify is the eventual size of the cluster and the system completely takes care of it transparently. But then there are a few characteristics which are very unique. So for instance, we can scale up or scale down to any number of nodes. Whereas in the case of Snowflake, the number of nodes someone can scale up or scale down to are the powers of two. So if a user needs 70 CPUs, well, their choice is either 64 or 128. So by providing this flexibly with MySQL HeatWave, customers get a custom fit. So they can get a cluster which is optimized for their specific portal. So that's the first thing, flexibility of scaling up or down to any number of nodes. The second thing is that after the operation is completed, the system is fully balanced, meaning the data across the various nodes is fully balanced. That is not the case with many solutions. So for instance, in the case of Redshift, after the resize operation is done, the user is expected to manually balance the data, which can be very cumbersome. And the third aspect is that while the resize operation is going on, the HeatWave cluster is completely available for queries, for DMLS, for loading more data. That is, again, not the case with Redshift. Redshift, suppose the operation takes 10 to 15 minutes, during that window of time, the system is not available for writes, and for a big part of that chunk of time, the system is not even available for queries, which is very limiting. So the advantages we have are fully flexible, the system is in a balanced state, and the system is completely available for the entire duration operation. >> Yeah, I guess you got that hypergranularity, which, you know, sometimes they say, "Well, t-shirt sizes are good enough," but then I think of myself, some t-shirts fit me better than others, so. Okay, I saw on the announcement that you have this lower price point for customers. How did you actually achieve this? Could you give us some details around that please? >> Sure, so there are two things for announcing this service, which lower the cost for the customers. The first thing is that we have doubled the amount of data that can be processed by a HeatWave node. So if we have doubled the amount of data, which can be a process by a node, the cluster size which is required by customers reduces to half, and that's why the cost drops to half. The way we have managed to do this is by two things. One is support for Bloom filters, which reduces the amount of intermediate memory. And second is we compress the base data. So these are the two techniques we have used to process more data per node. The second way by which we are lowering the cost for the customers is by supporting pause and resume of HeatWave. And many times you find customers of like HeatWave and other services that they want to run some other queries or some other workloads for some duration of time, but then they don't need the cluster for a few hours. Now with the support for pause and resume, customers can pause the cluster and the HeatWave cluster instantaneously stops. And when they resume, not only do we fetch the data, in a very, like, you know, a quick pace from the object store, but we also preserve all the statistics, which are used by Autopilot. So both the data and the metadata are fetched, extremely fast from the object store. So with these two capabilities we feel that it'll drive down the cost to our customers even more. >> Got it, thank you. Okay, I promised I was going to get to the benchmarks. Let's have it. How do you compare with others but specifically cloud databases? I mean, and how do we know these benchmarks are real? My friends at EMC, they were back in the day, they were brilliant at doing benchmarks. They would produce these beautiful PowerPoints charts, but it was kind of opaque, but what do you say to that? >> Right, so there are multiple things I would say. The first thing is that this time we have published two benchmarks, one is for machine learning and other is for SQL analytics. All the benchmarks, including the scripts which we have used are available on GitHub. So we have full transparency, and we invite and encourage customers or other service providers to download the scripts, to download the benchmarks and see if they get any different results, right. So what we are seeing, we have published it for other people to try and validate. That's the first part. Now for machine learning, there hasn't been a precedence for enterprise benchmarks so we talk about aiding open data sets and we have published benchmarks for those, right? So both for classification, as well as for aggression, we have run the training times, and that's where we find that HeatWave MLS is 25 times faster than RedShift ML at one percent of the cost. So fully transparent, available. For SQL analytics, in the past we have shown comparisons with TPC-H. So we would show TPC-H across various databases, across various data sizes. This time we decided to use TPC-DS. the advantage of TPC-DS over TPC-H is that it has more number of queries, the queries are more complex, the schema is more complex, and there is a lot more data skew. So it represents a different class of workloads, and which is very interesting. So these are queries derived from the TPC-DS benchmark. So the numbers we have are published this time are for 10 terabyte TPC-DS, and we are comparing with all the four majors services, Redshift, Snowflake, Google BigQuery, Azure Synapse. And in all the cases, HeatWave is significantly faster and significantly lower priced. Now one of the things I want to point out is that when we are doing the cost comparison with other vendors, we are being overly fair. For instance, the cost of HeatWave includes the cost of both the MySQL node as well as the HeatWave node, and with this setup, customers can run transaction processing analytics as well as machine learning. So the price captures all of it. Whereas with the other vendors, the comparison is only for the analytic queries, right? So if customers wanted to run RDP, you would need to add the cost of that database. Or if customers wanted to run machine learning, you would need to add the cost of that service. Furthermore, with the case of HeatWave, we are quoting pay as you go price, whereas for other vendors like, you know, RedShift, and like, you know, where applicable, we are quoting one year, fully paid upfront cost rate. So it's like, you know, very fair comparison. So in terms of the numbers though, price performance for TPC-DS, we are about 4.8 times better price performance compared to RedShift We are 14.4 times better price performance compared to Snowflake, 13 times better than Google BigQuery, and 15 times better than Synapse. So across the board, we are significantly faster and significantly lower price. And as I said, all of these scripts are available in GitHub for people to drive for themselves. >> Okay, all right, I get it. So I think what you're saying is, you could have said this is what it's going to cost for you to do both analytics and transaction processing on a competitive platform versus what it takes to do that on Oracle MySQL HeatWave, but you're not doing that. You're saying, let's take them head on in their sweet spot of analytics, or OLTP separately and you're saying you still beat them. Okay, so you got this one database service in your cloud that supports transactions and analytics and machine learning. How much do you estimate your saving companies with this integrated approach versus the alternative of kind of what I called upfront, the right tool for the right job, and admittedly having to ETL tools. How can you quantify that? >> Right, so, okay. The numbers I call it, right, at the end of the day in a cloud service price performance is the metric which gives a sense as to how much the customers are going to save. So for instance, for like a TPC-DS workload, if we are 14 times better price performance than Snowflake, it means that our cost is going to be 1/14th for what customers would pay for Snowflake. Now, in addition, in other costs, in terms of migrating the data, having to manage two different databases, having to pay for other service for like, you know, machine learning, that's all extra and that depends upon what tools customers are using or what other services they're using for transaction processing or for machine learning. But these numbers themselves, right, like they're very, very compelling. If we are 1/5th the cost of Redshift, right, or 1/14th of Snowflake, these numbers, like, themselves are very, very compelling. And that's the reason we are seeing so many of these migrations from these databases to MySQL HeatWave. >> Okay, great, thank you. Our last question, in the Q3 earnings call for fiscal 22, Larry Ellison said that "MySQL HeatWave is coming soon on AWS," and that caught a lot of people's attention. That's not like Oracle. I mean, people might say maybe that's an indication that you're not having success moving customers to OCI. So you got to go to other clouds, which by the way I applaud, but any comments on that? >> Yep, this is very much like Oracle. So if you look at one of the big reasons for success of the Oracle database and why Oracle database is the most popular database is because Oracle database runs on all the platforms, and that has been the case from day one. So very akin to that, the idea is that there's a lot of value in MySQL HeatWave, and we want to make sure that we can offer same value to the customers of MySQL running on any cloud, whether it's OCI, whether it's the AWS, or any other cloud. So this shows how confident we are in our offering, and we believe that in other clouds as well, customers will find significant advantage by having a single database, which is much faster and much lower price then what alternatives they currently have. So this shows how confident we are about our products and services. >> Well, that's great, I mean, obviously for you, you're in MySQL group. You love that, right? The more places you can run, the better it is for you, of course, and your customers. Okay, Nipun, we got to leave it there. As always it's great to have you on theCUBE, really appreciate your time. Thanks for coming on and sharing the new innovations. Congratulations on all the progress you're making here. You're doing a great job. >> Thank you, Dave, and thank you for the opportunity. >> All right, and thank you for watching this CUBE conversation with Dave Vellante for theCUBE, your leader in enterprise tech coverage. We'll see you next time. (upbeat music)

>>Hey everyone. Welcome back to the cube. Live in Las Vegas, Lisa Martin, with Dave Nicholson, we are covering AWS reinvent 2021. This was probably one of the most important and largest hybrid tech events this year with AWS and its enormous ecosystem of partners. We're going to be talking with a hundred guests in the next couple of days. We started a couple of days ago and about really the innovation that's going to be going on in the cloud and tech in the next decade. We're pleased to welcome Rick Tam Daniel's as our next guest VP of strategic ecosystems at Informatica. Rick. Welcome to >>The program. Thank you for having me. It's a, it's a pleasure to be back. >>Isn't it nice to be back in person? Oh, it's amazing. All these conversations you just can't replicate by video conferencing. Absolutely >>Great to reconnect with folks haven't seen in a few years as well. >>Absolutely. That's been the sentiment. I think one of the, one of the sentiments that we've heard the last three days, so one of the things thematically that we've also been hearing about in, in between all of the plethora of AWS announcements, typical reinvent is that every company has to become a data company, public sector, private sector, small business, large business. Talk to us about how Informatica and AWS are helping companies become data companies so that they don't get left behind. >>But one of the biggest things that we're hearing at reinvent is that customers are really concerned with data, fragmentation, data silos, access to trusted data, and how do they, how do they get that information to really affect data led transformation? In fact, we did a survey earlier in the year of chief, the chief data officers were found that up to 80, almost 80% of organizations had 50% or more of their data in hybrid or multi-cloud environments. And also a 79% are looking to leverage more than 100 data sources. And 30% are looking to leverage more than 1000 data sources. So Informatica we, with our intelligent data management cloud, we're really focused on enabling customers to bring together the data assets, no matter where they live, what format they're in, on-premise cloud, multi-cloud bringing that all together. >>Well, we sold this massive scatter 22 months ago now, right? Of everyone just, and the edge exploded and data exploded and volumes and data sources exploded hard for organizations to get their head around that, to go or that the data is going to be living in all these different places. You talked about a lot of customers and every industry being hybrid multi-cloud because based on strategy, based on acquisition, but to get their arms around that data and to be able to actually extract value from it fast is going to be the difference between those businesses that succeed and those that don't >>Absolutely. And our partnership with AWS, that's a long standing partnership and we're very much focused on addressing the challenges you're talking about. Uh, and in fact, earlier this year we announced our cloud first, our cloud native, uh, data governance and data catalog on AWS, which is really focused on creating that central point of trusted data access and visibility for the organization. And just today, we had an announcement about how we're bringing data democratization and really accelerating data democratization for AWS lake formation. >>What is, when you, when you, we talk about data democratization often, what does that mean to you? What does that mean to Informatica? How do you deliver that to customers so that they can really be able to extract as much value as they can? >>Yeah. So a great question. And really that whole data management journey is a big piece of this. So it starts with data discovery. How do I even begin to find my data assets? How do I get them from where they are to where they need to go in the cloud? How do I make sure they're clean, they're ready to use. I trust them. I understand where they came from. And so the solution that we announced today is really focused on how do we provide a business users with a self-service way of getting access to data lake data, sitting in Amazon S3 with lake formation governance, but doing it in a way that doesn't create an undue burden on those business users, around data compliance and data policies. And so what we've done is we brought our business user-friendly self-service experience an axon data marketplace together with AWS lake formation. >>So Informatica has had a long history in the data world. Um, I think of terms like MDM and ETL. Yes. Where does, where does Informatica is history dovetail with the present day in terms of cloud the con does the concept of extract translate load? I think that's what ETL stood for too many TLAs running as far as trying to transform, uh, w where does that play in today's world? Are you focused separately on cloud from on-premise data center or do you, or do you link the two? Yeah, >>So we focus on, uh, addressing data management, uh, when, no matter where the data lives. So on-premise cloud multi-cloud, uh, on our intelligent data management cloud platform is a, is the industry's first end-to-end cloud native as a service data management platform that delivers all those capabilities. I mentioned before, uh, to customers. So we can manage all those workloads that are distributed from a single cloud-based as a service data management platform. So >>The platform is, is as a service in the cloud, but you could be managing data assets that are in traditional on premises, data centers, the like, absolutely. >>Okay. >>So congratulations on the IPO. Of course we can't, we can't not talk to Informatica without that. I imagined the momentum is probably pretty great right about now when we think of AWS, I, when I think of AWS, I always think of momentum. We, I mean the, the volume of announcements, but also when I think about AWS, I think about their absolute focus on the customer, that working backwards approach from a partnership perspective. Is there alignment there? I imagine, like I said, with the IPO, a lot of momentum right now, probably a lot of excitement are, is infant medical also was focused and customer obsessed as AWS's. >>Yeah. So, um, first of all, thank you so much. Congratulations. Uh, so we had a very successful IPO last month. And in fact, just yesterday, our CEO I'm at Wailea presented our Q3 results, uh, which showcase the continued growth of our subscription revenue or cloud revenue. And in fact, our cloud revenue grew 44% year over year, which is really reflective of our big shift to being a cloud first company and also the success of our intelligent data management cloud platform. Right. And, and that platform, again, as I mentioned, it's spanning all those aspects of data management and we're delivering that for more than 5,000 customers globally. Uh, and just from an adoption perspective, we processed about 23 trillion transactions a month for customers in our cloud platform. And that's doubling every six to 12 months. So it's incredible amount of adoption. Some of the biggest enterprises in the world like Unilever, Sanofi folks like that are using the cloud is their preferred data management platform of choice in the cloud. >>Well, you know, of course, congratulations is in order for the IPO, but also really on what you just mentioned, the trajectory of where Informatica is going, because Informatica wasn't born yesterday. Right. And, uh, we shouldn't overlook the fact that there are challenges associated with moving from the world as it exists on premises for still 80% of it spend at least navigating that transition, going from private to public, getting the right kind of investment where people realize that cloud is a significant barrier to entry, uh, for, for a lot of companies. I think it's, it's, you know, you have a lot of folks cheering for you as you navigate this transition. >>Well, one thing I do I say is, yes, we have it in the business of data for a long time, but we also then the business of cloud quite a long time. So this is true. This is the 10th reinvent. This is also the ten-year anniversary of the Informatica AWS partnership, right? So we've been working in the cloud with AWS for, for that long innovating all of these different, different core services. So, um, and from that perspective, you know, I think we're doing a tremendous amount of innovation together, you know, solutions like when we talked about for lake formation, but we also announced today a couple of key programs that we partnered with AWS around, around modernization and migration, right? So that's a big area of focus as well is how do we help customers modernize and take advantage of all the great services that AWS offers? So that's how we announced our membership and what's called the workload migration program and also the data lead migrations program, which is part of the public sector focus at AWS as well. >>The station perspective that was talked a lot about by Adam yesterday. And we've talked about it a lot today, every organization needs to monitorize, even some of those younger ones that you think, oh, aren't, they already, you know, fairly modern, but where, where are your customer conversations happening from a modernization perspective is that elevated up the, the C stat that we've got to modernize our or our organization get better handle of our data, be able to use it more protected, secure it so that we can be competitive and deliver outstanding customer experiences. >>What happens is the pain points that the legacy infrastructure has from the business perspective really do elevate the conversation to the C-suite. They're looking at saying, Hey, especially with the pandemic, right? We have to transform our business. We have to have data. We have to have trust in data. How do we do that? And we're not going to get there >>On rigid on-premise infrastructure. We need to be in a cloud native footprint. And so we've been focused on helping customers get to those cloud native end points, but also to a truly cloud native data management, we talked about earlier can manage all those different workloads, right? From a single that SAS serverless type experience. Right? What have been some of the interesting conversations that you've had here? Again, we are in person yep. Fresh off the IPO, lots of announcements coming out. You guys made announcements today. What's been the sentiment from the, those customers and partners that you've talked about. >>Well, I'll give you guys actually a little sneak preview of another announcement we have coming tomorrow, uh, with our friends at Databricks. So we, uh, we are announcing a data, data democratization solution with Databricks accelerating some of the same, you know, addressing some of the same challenges we were talking about here, but in the data breaks in the Lakehouse environment. Um, so, so, but around that, and I had a great conversation with some partners here, some of the global system integrators, and they're just so happy to see that, right, because a lot of the infrastructure that's around data lakes are lake formation. It's pretty technical it's for a technical audience. And, and Informatica has really been focused on how do we expand the base of users that are able to tap into data and that's through no code experiences, right? It's through visual experiences. And we bring that tightly coupled together with the performance and the power and scale of platforms like Databricks and the AWS Redshift and S3, it's really transformative for customers. >>What are some of the things that here we are wrapping up the 10th, re-invent almost as tomorrow, but also wrapping up the end of 2021. What are some of the things that th th that there's obviously a lot of momentum with Informatica right now that from a partnership perspective, anything that you, you just gave us some breaking news. Thank you. We always love that. What are some of the things that you're looking forward to in 2022 that you think are really going to help Informatica customers just be incredibly competitive and utilizing data in the cloud on prem to their maximum? >>Well, I think as we go into the next year data complexity data fragmentation, it's gonna continue to grow. It's, it's, it's exploding out there. Uh, and one of the key components of our platform or the IDMC platform is we call it Clare, which is the industry first kind of metadata driven AI engine. And what we've done is we've taken the intelligence of machine learning and AI, and brought that to the business of data management. And we truly believe that the way customers are going to tame that data, they're going to address those problems and continue to scale and keep up is leveraging the power of AI in a cloud native cloud, first data management platform. >>Excellent. Rick, thank you so much for joining us today. Again, congratulations on last month, Informatica IPO, great solid, strong, deep partnership with AWS. We thank you for your insights and best of luck next year. >>Awesome. Thank you so much. Pleasure being here. Our >>Pleasure to have you for my co-host David Nicholson, I'm Martin. You're watching the cube, the global leader in live tech coverage.

>>Welcome back to the cubes, continuous coverage of AWS reinvent 2021 live in Las Vegas. I'm Lisa Martin pleased to be here in person. We are actually with AWS and its massive ecosystem of partners running. One of the industry's largest and most important hybrid tech events of the year. We've got two life sets over a hundred guests to remote studios. I'm pleased to welcome two guests from Laos here with me. Next, Derek is here, the VP and director of digital modernization and David chow, the director of cloud capabilities, Derek and David. Welcome to the program. Thanks for having us great to be here in person. Isn't it? >>Absolutely. Last year we missed out. So if we've got to get it all in this week. >>Exactly and well, this is day one and the amount of people that are in here, there's a lot of noise in the background. I'm sure the audience can hear it is, is really nice. AWS has done such a great job of getting us all in here. Nice and safely. So let's go ahead and start. Light is coming off a very strong Q3. When we look at the things that have happened, nearly all defense and classified customers are engaged in digital modernization efforts. We've seen so much acceleration of that in the last 20 months, but let's talk about some of the current challenges Derek that customers are facing across operations sustainment with respect to the need to modernize. >>Sure, sure thing. Um, so over the past two years, we spent a better part of all that time, trying to really figure out what are our customers' hardest problems. And, you know, that's across the health vertical, the DOD vertical, uh, the Intel vertical, uh, you name it. We spent a lot of time trying to figure it out. And we kept coming up on three reoccurring themes, one, which is the explosion of data. There's so much data being generated across our customer's environments. Um, there's not enough human brain power to deal with it. All right. So we need to be able to apply technology in a way that reduces the cognitive burden on operators who must do operations and sustainment to get to a business outcome. Uh, the second one and most importantly for us is advanced cyber threats. We've all heard about the colonial pipeline hack. >>We've heard about solar winds. The scary part about that is what about the hacks that we don't know about? Right. And that's something that here at lighthouse, we're really focused on applying technology, cyber AIML in a way that we can detect when someone's in our environments or in our customer environments. And then we can opt out, obviously, um, do some remediation and get them out of our environment. So mission operations are not compromised. And then lastly, customer environments are heterogeneous. You have cloud, you have on-premise infrastructure. Uh, you have edge devices, IOT devices. It's very difficult to be able to do management and orchestration over all these different devices, all the different platforms that are out there. So working in concert with AWS, we build a solution to be able to do just that, which we'll talk about a little later, David, anything else that you want to, >>We talked about the explosion of data, the cybersecurity landscape changing dramatically, and the customers needing to be able to modernize and leverage the power of technology. Yeah, >>So our customers, uh, we have basically three areas that we see our customers having challenges in. And one of them, once they get to the cloud, they don't have the transparency on cost and usage, right. Uh, when you get the engineers are excited, the mission is exploded with extra activities. Um, but our customers don't have a sense on where the cost is going and how that relates to their mission, right? So we help them figure out, okay, your, your cost is going up, which is fine because it's applying to your mission and it's helping you actually be more successful than before. Right? And the other area is, uh, they need, uh, a multi-platform strategy that doesn't impact their existing conditions, right? They don't have the practicality or the funding that's required to just rip and replace everything. And you can't do that. You have to maintain your mission. >>If you have to maintain about a lot of critical capability that they already have, but at the same time, figure out how am I going to add the extensions and the new capabilities, right? And we have certain ways that we can do that to allow them to start getting into the cloud, leveraging a lot of additional capability that they never had before, but maintaining the investment that they've done in the past years to maintain their mission success. Right. Uh, and then the third is skill up-skilling. So we found that a lot of people have a hard time. Once we move them into AWS, specifically their operational duties and things change. And there's a big gap there in terms of training, uh, getting familiar with how that impacts their process and methodology, and that that's where we helped them a lot, uh, modify that revolution and how they do that stuff. >>That's excellent. That upskilling is critical, as things are changing so dramatically, we have, you talked about data and the cybersecurity changes Derek. And you know, every company, every branch of the federal is probably a data company or data organization, or if it's not, it has to become one. But the cyber threats are crazy. The things that have been going on in the last 20 months, the acceleration of ransomware, ransomware as a service, you talked about colonial, like we only hear about the big ones, but how many it's no longer a will we get hit by ransomware? Or will we be hacked? It's when, talk to me about some of those, about those challenges and also the need to be able to deliver real-time data as real-time missions are going on in that real-time is now no longer a nice to have. >>Right? So, um, it's a great question. And one of the things that I'll say is there's some studies out there that said 75% of the computing, uh, that will be happening over the next 10 years will be at the edge, right? So we're not going to be able to go at the edge, collect all this data, ship it back to a centralized way to process it. We're not going to be able to do that. What we have to do is take capability that may have been clouded, able push that capability to the edge. Where did that be? AI ML. It could be your mission applications, and we need to be able to exploit data in near real time, um, to which allows us to make mission critical decisions at the point of need. There's not going to be enough time to collect a big swath of data, move it back across a bandwidth that is temporarily constrained. In many cases, we just can't do it that way. So I think moving as much capability to the edge as possible in order for us to be able to make an impact in near real time, that's what we need to do across all of our verticals, not just DOD, but on the healthcare side to the Intel side, you name it. We gotta be able to move capability as far forward as >>Possible. And where Derek with you for a minute, where are those verticals with respect to embracing that, adopting that being ready to be able to take on those technologies? Because culturally, I can imagine, you know, legacy his story, history organizations to change his heart >>Change is hard. Um, and one of the strategies that we've tried to implement within that context is that the legacy systems, the culture that is already out there, we're not just going to be able to turn all of that off, right. We're going to have to make sure that the new capabilities and the legacy systems co-exist. So that's one of the reasons that we have an approach where we use microservices, very much API driven, such that, uh, you know, a mission critical system that may have been online for the last 20 years. We're not just going to turn it off, but what we can do is start to build sidecar capabilities, microservices, to extend that capability of that system without rebuilding it, we can't build our way out of all the technical debt. What we can do is figure out how do we need to extend this capability to get to a mission need and build a microservices. That's very thin. That's very lightweight. And that's how you start to connect the dots between your mission applications, the data, the data centricity that we talked about and other capabilities that need access to data, to be able to effectuate a decision. >>You make it sound so easy. Derek, >>It's certainly not easy, but in working with AWS, we really have taken this forward and we're really deploying, uh, similar capabilities today. Um, so it's really the way that we have to modernize. We have to be able to do it step by step strangle out the old as we bring in the new right. >>So David, let's talk about the AWS partnership, what you guys are doing as the critical importance of being able to help the verticals modernize at speed at scale in real time. Talk to me about what Leidos and AWS are doing together. >>So we work with Adobe very closely, um, for every engagement we have with our customers, we have AWS as our side, we do the reviews of, of their architecture and their approach. We take, we take into account the data strategy of the organization as long along with their cloud, uh, because we found that you have to combine their cloud and their data strategy because of the volumes of data that Derrick talked about, right. That they needed to integrate. And so we come up with a custom strategy and a roadmap for them to adopt that without like Derek said, um, deprecating any old capabilities that currently have any extending it out into, into the cloud so that those areas are what we strive to get them through. And we talk about a lot about the digital enterprise and how that is for us from light of this point of view, we see that as building an API ecosystem for our customer, right? Because the API is really the key. And if you look at companies like Twilio that have an API first approach, that's, what's allowed them to integrate very old technology like telephones into the new cloud, right? So that approach is really the unique approach that was taken with our customers for to see the success that we've seen. >>Well, can you tell me, David's sticking with you for a minute about upscaling. I know that AWS has a big focus on that. It's got a restart program for helping folks that were unemployed during the pandemic or underemployed, but the upskilling, as we talked about during this interview is incredibly important. As things change are changing so quickly, is there any sort of upskilling kind of partnerships that you're doing with AWS that you, >>Uh, so as a partner, we ourselves get a lot of free upskilling and training, uh, as AWS from your partner. Um, but also with our customers, we're able to customize and build specific training plans and curriculums that is targeted specifically for the operators, right? They don't come from a technology background like we do, but they come from a mission background so we can modify and understand what they need to learn and what they don't really need to worry about so much and just target exactly what they need to do. So they can just do their day-to-day jobs and their duties for the mission. >>That's what it's all about. Derek, can you share an example that you think really speaks volumes to light us and AWS together to help customers modernize? >>One thing I like about AWS is that the partnership is what we describe as a deep technical partnership. It's not just transactional. It's not like, Hey, buy this X services and we'll, we'll do this. I have a great example of this year. We kicked off a pilot with an army customer and we actually leveraged AWS pro. So we were literally building a proof of concept together. So in 90 days, what we, what we did was get the customer to understand we're moving more to native AWS services, EMR, uh, to be more specific that you can save money on tons of licensing costs that you otherwise would have had to pay for it. After the pilot was over, we recognized that we will save the government $1.2 million and they have now said, yes, let's go AWS native, which is, uh, which is, uh, a methodology that we still want to stamp out and use continually because the more and more that you adopt that native services, you're going to be able to move faster. Because as soon as you deploy a system, it's already legacy. When you start to do the native services, as things more services come online, we're sort of their glue where to make sure those things that are coming, the services that are AWS are deploying out, we'd bring, we, we then bring that innovation into our customer environment. So saving a customer, the government $1.2 million at a big deal for us. >>It's huge. And I'm sure you there's, that's one of many examples of significant outcomes that you're helping the verticals achieve. Absolutely. >>Yeah. One of our >>Core focuses. That's excellent. And also to do it so quickly and 90 days to be able to show the army a significant savings is a, is a huge, uh, kudos to, to Linus and to AWS. David, talk to me a little bit about the, from a partnership perspective, how do you guys go into a joint organizations together? I imagine one of the most important things is that transparency from the verticals perspective, whether it's DOD or health or Intel, talk to me about that, that kind of unified partnership. And what is the customer and customer experience? I imagine one team. >>Yes. So we go into, we engage with our AWS counterparts at the very beginning of an engagement. So they have their dedicated teams. We have our dedicated teams and we are fully transparent with each other, what the customers are facing. And we both focus on the customer pain points, right? What was really going to drive the customer. Um, and that's how we sort of approach the customer. So the customer sees us as a single team. Uh, we do things like we'll build out what we call the well-architected framework or wafer for short, right. And that allows us to make sure that we're leveraging all the best practices from AWS, from their clients on the commercial side. And we can leverage that into the government, right. They can get a lot of learnings and lessons learned that they don't have to repeat because some of the commercial cupboard companies who are ahead of us have I've done the hard learning, right. And we can incorporate that into their mission and into their operations. >>That's critical because there isn't the time. Right? I think that's one of the things that Penn has taught us is that there isn't there, like we talked about real-time data, there is, it's no longer a nice to have, right. But even from a training and from a deployment perspective that needs to be done incredibly efficiently with, we're talking about probably large groups of people. I imagine with Leidos folks, AWS folks, and the verticals. So that coordination between, I imagine what are probably two fairly culturally aligned organizations is critical. No. >>Yeah. One of the things that we put in places, this idea of bachelors environment, so that means you could be a Leidos person. You could be an AWS person, there's no badge. We're just sitting there, we're here to do good work, to bring value to a customer. And that's something that's really fantastic about our relationship that we do have. So every week we are literally building things together and that's, that's what the government, that's what the public sector folks expect. No, one's not gonna own it all. You have to be able to work together to be able to bring value to our customers across all the verticals that >>I like. That badge list environment, that's critical for organizations to work together. Harmoniously given there's as the data explosion just continues as does the edge explosion and the IOT device explosion more and more complexity comes into the environment. So that Badger less environment I met David from your perspective is really critical to the success of every mission that you're working on. >>Yeah. I mean, I think the badge approaches is critical without it, the existing teams have a hard time building that trust and being, and feeling like we're part of that team, right? Trust is really important in, in mission success. And so when we enter a new arena, we try to get, build that trust as quickly as we can show them that, you know, we're there to help them with their mission. And we're not really there for anything else. So they feel comfortable to share, you know, the really deep pain points that they're not really sharing all the time. And that's what allows Leidos specifically to, to really be successful with them because they share all their skeletons and we don't judge them. Right. We've say, okay, here's your problems. Here's some solutions. And here are the pros and cons and we figure out a solution together, right. It's a really built together sort of mindset that makes us successful. Okay. >>Togetherness as key, last question, guys, what are some of the things that attendees can learn and feel and see, and smell from Leidos this week at reinvent? >>We want to take that one. >>Um, yeah. So with Leidos, um, we're around, we have, uh, various custom, uh, processes with AWS, uh, because of our peer partnership. We have the MSSP that we just got as a launch partner. So there's a lot of interaction that we have with AWS. Um, anytime that AWS sees that there is opportunity for us to talk to a customer and talk to potential vendor, they'll pull us in. So if you guys come by the booth and you need to talk to an SSI, they'll, they'll pull us in and we'll have those conversations. >>Excellent guys, thank you so much for joining me, talking about Leidos, AWS, what you guys are doing together and how you're helping transform government. You make it sound easy. Like I said, Derek, I know that it's not, but it's great to hear the transparency with which guys are all working. Thank you so much for your time. Thank you. Thank you. My pleasure for my guests. I'm Lisa Martin. You're watching the cube, the leader in global live tech coverage.

>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE in ETR. This is "Breaking Analysis" with Dave Vellante. >> Despite all the talk about repatriation, hybrid and multi-Cloud opportunities, and Cloud is an increasingly expensive option for customers, the data continues to show the importance of public Cloud to the digital economy. Moreover, the two leaders, AWS and Azure, are showing signs of accelerated momentum that point to those two giants pulling away from the pack in the years ahead, with each firm's showing broad based momentum across their respective product lines. It's unclear if anything, other than government intervention or self-inflicted wounds will slow these two companies down this decade. Despite their commanding lead, a winning strategy for companies that don't run their own Cloud continues to be innovating on top of their massive CapEx investments. The most notable example here being Snowflake. Hello, everyone. Welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we provide our quarterly market share update for the big four hyperscale Cloud providers. And we'll share some new ETR data from their most recent survey. And we'll drill into some of the reasons for the momentum of these two companies and drill further into the database and data warehouse sector to see what, if anything, has changed in that space. First, let's look at some of the noteworthy comments from AWS and Microsoft in their recent earnings updates. We heard from Amazon, the following, "AWS has seen a reacceleration of revenue growth as customers have expanded their commitment to the Cloud and selected AWS as their Cloud partner." Notably, AWS revenues increased 39% in Q3 2021. That's a thousand basis point increase in growth relative to Q3 2020. That's an astounding milestone for a company that we expect to surpass $60 billion in revenue this year. Further, AWS touted the adoption of its custom silicon, and specifically its Graviton2 processors. AWS is fond of emphasizing Graviton's 40% price performance improvements relative to x86 processors, something we've reported on quite extensively. AWS is investing in custom silicon, encouraging ISVs to port their code to the platform so that customers will experience little or no code changes when they migrate. Again, we believe this is a secret weapon for AWS as its cost structure will continue to improve at a rate faster than competitors that don't have the resources or the skills or the stomach to develop such capabilities. Microsoft, for its part, also saw astoundingly good growth of 48% this past quarter for Azure. This is a company that we forecast will approach $40 billion in IaaS and PaaS public Cloud revenue this year. Microsoft's CEO, Satya Nadella, on its earnings call, emphasized the changing nature of Cloud expanding in a distributed fashion to the edge. He referenced Azure as the world's computer. Building on his statements last year that Microsoft is building out a powerful, ubiquitous, intelligent, sensing and predictive Cloud. Yes, folks, it does feel like we're entering the so-called Metaverse, doesn't it? Okay, to underscore the momentum of these two companies, let's take a look at the ETR breakdown of Net score, which measures spending momentum. This chart will be familiar to our listeners. It shows the breakdown of net score for AWS, with the lime green showing new adoptions. That's 11%. The forest green is spending more than 6% relative to the first half of this year. That's a very robust 53%. The gray is flat spending. That's 30% on a very, very large base. And the pink is spending declines of minus 6% or worse. That's 4%. And the bright red is defections i.e those leaving AWS. That's 1%. That's virtually non-existent. You subtract the reds from the greens and you get a net score of 59. Remember, anything over 40, we can still consider to be elevated. Let's look at that same data for Microsoft again. You have some new ads that lime green, that's 7%. The forest green is at 46% of customers spending more, which is an incredible figure for a company with revenues that will in the near term surpass $200 billion. And the red is in the low single digits. Buffered by its enormous PC software profits over the years, Microsoft is powered through its Window's Dogma and transitioned into a Cloud powerhouse. Let's now share some of our latest numbers for the big four hyperscale players, AWS, Azure, Alibaba and Google. Here, we show data for these companies from 2018 and our estimates for 2021. This data includes our final figures for AWS, Azure and GCP for Q3 with Alibaba yet to report. Remember, only AWS and Alibaba report IaaS revenue cleanly with Microsoft and Google, they give us a little breadcrumb nuggets that allow us to triangulate with our survey data and other intelligence. But it's our attempt to do an apples to apples comparison for those four companies using AWS and it's reporting as a baseline. In Q3, AWS reported more than $16 billion in revenue. We estimate Azure at 10 billion, Alibaba, we expect to come in at just under 3 billion, and GCP at 2.5 billion for the quarter. With three quarters of data in, with the exception of Alibaba, we're forecasting AWS to capture 51% of the big four revenue, the hyperscale revenue. And really we believe these are the only four hyperscalers. AWS will surpass 60 billion with Azure just under 40 billion, Alibaba approaching 11 billion, and Google coming in just under 10 billion for the year is our expectation. We forecast these four will account for $120 billion this year. That's a 41% increase over 2020 and the same collective growth rate as 2020 relative to 2019. We expect Azure to be 63% of the size of AWS revenue. So it is gaining share. Both of those companies, however, saw accelerated growth this past quarter with Alibaba and GCP's growth rates decelerating relative to last year. Now, let's take a closer look at those growth rates. This chart shows the quarterly growth rates for each of the four going back to the beginning of 2019. Both GCP and Alibaba are showing dramatic declines in growth rates, whereas, this past quarter Azure saw accelerated growth and AWS has now seen an increased rate of growth for the past two quarters. In fact, AWS' growth is about where it was in 2019 when it was around half of its current revenue size. And in 2019 growth was decelerating through the quarters as you can see where today that trend has reversed. It's quite amazing. All right, let's take a look at the broader Cloud landscape and bring back some ETR data. This chart that we're showing here, it shows net score or spending momentum on the vertical axis and market share or presence in the dataset on the horizontal axis. Note that red dotted line, anything above that we can still consider elevated and impressive. As when we've previously shared this data, AWS and Microsoft Azure are up and to the right. Now remember, this chart is not just counting IaaS and PaaS as we showed you earlier, it's however the customers views whatever they think Cloud is. And so they're likely including Microsoft SaaS in this picture. Which is why Microsoft shows larger than AWS despite what we showed you earlier. Nonetheless, these two are well ahead of the pack and the growth rates indicate that they're pulling away. But we've added some of the other players, most notably VMware Cloud on AWS. It's showing momentum as is VMware Cloud, which is VMware Cloud foundation and other on-prem Cloud offerings, even though it's below the red line for the on-prem piece, it's very respectable. The VMware Cloud on AWS has been consistently up above that red line. Has popped beneath it in some quarters, but it's very, very strong. As is, you know, Red Hat OpenShift, it's a little bit below the line, but it is respectable. We've superimposed this by the way. Red Hat OpenShift in the ETR platform is under the container orchestration taxonomy, but we'd like to put it in next to the Cloud players for context. That's how Red Hat sort of thinks about this as well. They think about OpenShift as Cloud. And then you can see the other players. Alibaba has got a small sample in the ETR dataset. Just does not enough presence in China. But Dell and HPE have started to show up in the Cloud taxonomy. So buyers are associating their private Clouds with Cloud. So Dell's Apex, HPE's GreenLake. So that's a positive. And you can see Oracle, which of course is OCI, Oracle Cloud infrastructure. And then IBM with its public Cloud. So, it's a positive that these on-prem players are showing up in this data, but the reality is the hyperscalers are growing collectively at 40% annually and the on-prem players are growing in the low single digits. So, and if you carve out the IaaS business of AWS and Azure, they're larger than most of the on-premises infrastructure players. And all the on-prem players are moving toward an as a service model, as I just alluded to. So, undoubtedly, hybrid multicloud edge are going to present opportunities for the likes of Dell, HPE, Cisco, VMware, IBM, Red Hat, et cetera. But they also present opportunities for the public Cloud players who have vibrant ecosystems and marketplaces much more diverse and deep than the traditional vendors. You know, we have a clearer picture of Microsoft's sort of hybrid and edge strategy because the company has such an enormous legacy business, it really had to think about that much more deeply. It wasn't a blank sheet of paper like AWS. It's going to be interesting at reinvent this year if new CEO, Adam Selipsky, will talk about this. And it will be good to hear how he's thinking about the next decade, how AWS thinks about hybrid and edge, I guarantee that with their developer affinity and custom Silicon capabilities, they're thinking about it differently than traditional enterprise players. And as we've stressed in this segment, they have across the board momentum. Now to quantify that, let's take a look at AWS as portfolio in the spending momentum within its product segments. This chart shows AWS's net scores or spending momentum in the areas where AWS participates in the ETR taxonomy. Again, note that red line. Anything above 40% is considered an elevated watermark. We're showing data from last October, this past July and the latest October 21 survey. That yellow line or a bar. What's notable is the yellow versus the gray bars up across the board for the most part, other than chime... And by the way, other than chime, everything is above the 40% mark as well. Now, we've highlighted database because we feel it's one of the most strategic sectors in a real battleground. So we want to drill into that a bit. Here's our familiar X Y graph showing Net score on the Y axis, remember, that's, again, spending momentum and market share or pervasiveness in the survey on the horizontal axis. This data, by the way, includes on-prem and Cloud database data warehouse. So keep that in mind. Let's start with one of our favorite topics; Snowflake. We've reported again and again and again, that we've never seen anything like this. The company's net score has moderated ever so slightly this quarter, but it's still just below 80%. Very highly elevated. Well, above that 40% mark. It's Snowflake's presence continues to grow as a gain share in the market. Snowflake is growing revenue in the triple digits. It's an insane pace, hence its current $115 billion market cap as of this episode. Now that said, all three US-based Cloud players there are above the 40% line with AWS and Microsoft having significant presence on the horizontal axis. You see Cockroach Labs, Redis, Couchbase, they're all elevated or highly elevated. Couchbase just went public this summer. So that may help with its presence. MongoDB, they're killing it. They have a $37 billion market cap as of this episode. The stock has been on a tear. You see MariaDB was also in the mix. And then of course you have Oracle, the database leader. Look, they continue to invest in making the Oracle database and other software like MySQL, the best solution for mission critical workloads, and they're investing in their Cloud. But you can see overall, they just don't have the momentum from a spending standpoint that the others do because the declines in their legacy business. And they've been around a long time. Those declines are not fully offset by the growth in Cloud database and Cloud migration. But look, Oracle is a financial powerhouse with a $250 billion plus market cap. And the stock has done very well this past year. Up over 60%. Cloudera is going private. So it can hide the pain of the transitions that it's undergoing between the legacy install bases of Cloudera and Hortonworks. It's just a tough situation. When the companies came together, Cloudera essentially had a dead end. Each of those respective platforms and migrate their customers to a more modern stack as part of its Cloud strategy. Ironic that it's name is Cloudera. You know, that's always a difficult thing to do. So as a private company, Cloudera can maybe get off that 90 day shot clock and buy some time to invest without getting hammered by the street. And you know, Teradata consistently has not shown up well in the ETR dataset. It's transitioned to Cloud and cross-Cloud still hasn't shown momentum in the surveys. So, look right now, it's looking like the rich get richer. So just to quantify that a little bit, let's line up some of the database players and look a little bit more closely at net score. This chart shows the spending momentum or lack thereof with the net score or spending velocity granularity that we described before. Remember, green is spending more, red is spending less, bright red is leaving the platform, bright green is adding the platform. You take red, subtract red from the green, and that gives you a net score. Snowflake, as we said, tops the list. You can see the granularity there. You can compare the performance. In a little different view to understand how these scores are derived, look, the ideal profile is a solid lime green, a big forest green, a not too large gray and ideally little or no bright red AKA defections. And you can see the green funnel in the gray increasing prominence as the vendor momentum declines. Interestingly, with the exception of Cloudera and Teradata, defections are all in the single digits or nonexistent. In the case of Snowflake, Redis, red is no red at all, but small sample, Couchbase has no defections and very little defection for the giant Microsoft. Incredibly impressive. This speaks to how hard it is to migrate off of a database no matter how disgruntled you are. The more common scenario is to isolate the database and build new functionality on modern platforms. Okay, so what to watch out for. Well, reinvent this coming up next month. Oh this month. It's the first time someone other than Andy Jassy will be keynoting as CEO. 15 years of Cloud, this is the 10th re-invent, which is always a market for the direction of the industry. I've said many times that the last decade was largely about IT transformation powered by the Cloud. I believe we're entering a new era of business transformation where the Cloud is going to play a significant role. But the Cloud is evolving from a set of remote services out there in the Cloud to an omnipresent platform on top of which many customers and technology companies can innovate. And virtually every industry will be impacted by Cloud. However it evolves in the coming decade. The question will be, how fast can you go? And how will players like AWS and Microsoft and many others that are building on top of these platforms make it easier for you to go fast? That's what I'll be watching for at re-invent and beyond. Okay, that's a wrap for today. Remember, these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis podcasts. Check out ETR's website at etr.plus. We also publish a full report every week on wikibon.com and siliconangle.com. You can get in touch with me, david.vellante@siliconangle.com. You can DM me @dvellante or comment on our LinkedIn posts. This is Dave Vellante for theCUBE insights powered by ETR. Have a great week, everybody. Stay safe, be well. And we'll see you next time. We'll see you at re-invent. (soft upbeat music)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante five publicly traded u.s based companies have market valuations over or just near a trillion dollars as of october 29th apple and microsoft topped the list each with 2.5 trillion followed by alphabet at 2 trillion amazon at 1.7 and facebook now meta at just under a trillion off from a tie of 1.1 trillion prior to its recent troubles these companies have reached extraordinary levels of success and power what if anything could disrupt their market dominance in his book seeing digital author david micheller made three key points that i want to call out first in the technology industry disruptions of the norm the waves of mainframes minis pcs mobile and the internet all saw new companies emerge and power structures that dwarfed previous eras of innovation is that dynamic changing second every industry has a disruption scenario not just the technology industry and third silicon valley broadly defined to include seattle or at least amazon has a dual disruption agenda the first being horizontally disrupting the technology industry and the second as digital disruptors in virtually any industry how relevant is that to the future power structure of the digital industry generally in amazon specifically hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we welcome in author speaker researcher and thought leader david michela to assess what could possibly disrupt today's trillionaire companies and we're going to start with amazon dave good to see you welcome thanks dave good to see you yeah so dave approached us about a month or so ago he was working on these disruption scenarios and we agreed to make this a community research project where we're going to tap the knowledge of the cube crowd and its adjacent communities and to that end we're initiating a community survey that asks folks to rate the likelihood of seven plus one disruption scenarios so we have a slide here that sort of shows what that survey structure is going to look like and so as i say there's seven plus another one which is kind of an open open-ended and we're going to start with amazon as the disruptee so dave you've been writing about the technology industry for decades and digital disruption and china and automation and hundreds of other topics what prompted you to start this project yeah it's a great question you know as you said that the whole history of our business has been you know every decade or so you have a new set of leaders ibm digital microsoft the internet companies etc but when i started looking at it you know that seems in some ways to have actually stopped that you know microsoft is now 40 years old amazon is what 1995 is getting towards 30. you know google's been a dominant company for 20 years and you know apple of course and facebook more recently so so whatever reason this sort of longevity of these firms has been longer than we've seen in the past so i sort of say well is there anything that's going to change that so part of it and we'll get into it is what could happen to disrupt those big five but then the sort of second question was well maybe the uh disruptive energies of the of the tech business have moved elsewhere they've moved to crypto currencies or they've moved to tesla and so you start to sort of broaden your sense of disruption and when you talked about that dual disruption agenda that whole ability of tech to disrupt other sectors banking health care insurance automobiles whatever is sort of a second wave of disruption so uh we started coming out all right what sort of scenarios are we really looking at over say for the 2020s what might shake up the big five as we know them and how might disruption spread to sort of more industry specific parts of the world and that was really the the genesis of the project and really just my own thinking of all right what scenarios can i come up with and then reaching out to companies like yourselves to figure out okay how can we get more input on that how can we crowdsource it how can we get a sense of of what the community thinks of all this it's great love it and as you know we're very open to do that so we're going to crowdsource this we're going to open it up to virtually anyone and use multiple channels so let's go through some of the scenarios all of them actually and explain the reasoning behind their inclusion the first one the govern government mandated separation divestment and or limits on amazon's cloud computing retail media credit card and or in-house product groups it probably no coincidence that this was the first one you chose today but why start here well i think the government interest in doing something to get back at big tech is is pretty clear and probably one of the few things that has bipartisan support in washington these days and also government interventions have always been an enormous part of the tech industry's history the the antitrust efforts against ibm and att in particular and more recently microsoft a smaller one but it's it's always been there there's a vibe to do it now and when you look at all the big ones but particularly amazon you can see that potential divestments and breakups are sitting there right in front of you the separation of retail and aws uh perhaps breaking out credit card or music or media businesses these sorts of things are all on the surface at least relatively clean things to do and i think when you look at the formation of an alphabet or a meta those companies themselves are starting to see their own businesses as consisting of multiple firms yeah so i just want to kind of drill into the cloud piece just to emphasize the importance of aws in the context of amazon amazon announced earnings thursday night after the close aws is now a 64 billion revenue run rate company and they're growing at 39 percent year over year that's actually an accelerated growth rate from q3 2020 when the company was grew at 29 it's astounding think about a company this size moreover aws accounted for more than actually but 100 of amazon's operating profit last quarter so the aws cloud is obviously crucial as a funding vehicle and ecosystem accelerant for amazon and i just wanted to share some data points dave before we move on to these other scenarios yeah and just on that uh i think that is the fundamental point it's very easy to see aws on its own as a powerhouse but i think you know if you figure how much freedom aws money has given the retail business or the credit card business or the music businesses to launch themselves and to essentially make no money for very long periods of time uh you see that you know if you're a walmart trying to compete with amazon as a retailer well that money from aws is is an awful big problem and and so when they look at separation that's the sort of stuff people talk about right so i just want to i want to put that into context just in in terms of the the cloud business so this chart is one from our etr surveys that isolates the four hyperscale cloud providers and adds in oracle and ibm we both own public clouds but don't you know don't have nearly the the scale we don't have apple or facebook they have clouds as well and we can talk about that in a moment but the chart shows net score or spending momentum on the vertical axis and market share or pervasiveness in the survey on the horizontal axis it's it's really mentioned share not dollar market share but it's an indicator and the red line is an indicator of elevated spending momentum and you can see azure and aws they're up and to the right i mean amazon is 64 billion you know uh azure will claim larger because they're including their application business but just their their their i asked business obviously smaller than amazon's but you can see in the survey the respondents define cloud they include that sas business so they they both impressively have this high spending momentum on the vertical axis well above that 40 line despite their size google obviously well behind those to the left and then alibaba which has a small sample in the etr survey it's you know it's not as prominent in china but even though it's ias cloud businesses larger than google's by probably a couple billion dollars now the point is these four hyperscalers and there really are only four in my view anyway they have a presence that allows them to build new businesses and disrupt ecosystems and enact that dual disruption agenda should they choose to do so at least in the case of amazon oracle and ibm are not in a position to do that it's not part of their agenda they don't they don't have that scale but dave can you talk about your dual disruption scenario very clearly amazon fits in there and i would think alibaba as well but what about microsoft facebook apple google yeah i mean you know people often say what's the biggest difference between microsoft and amazon from from a cloud point of view and the answer is pretty clear that microsoft goes out of its way to assure its customers that it really doesn't have any interest in competing directly about them so you don't see microsoft going into the retail business or the banking business or the healthcare business all that seriously in contrast that's really what amazon is all about is taking its capabilities to essentially any industry it likes and therefore as one is as great as the service aws provides it's often being provided to people who amazon is actually competing with at least some degree or another and you know that's a huge part of microsoft's sales pitch and it's certainly a potential vulnerability down the road uh it's very hard in the end to be an essential supplier and a direct competitor at the same time but so far they've managed to do that yeah so we put together just another sort of aside here this little thought experiment to see what aws would look like as a separate entity and so it's a chart that looks at a number of tech companies and lays out their revenue run rate the growth rates gross margin probably should have done operating margin might have been more relevant but market cap and revenue multiple again given the size of aws at 64 billion run rate and accelerating growth trajectory it's just it's remarkable and so we we figured this out based on industry norms and today's valuations it's not inconceivable that aws could be you know in the trillionaire club or close to it so based on that discussion we had earlier amazon amazon's dual disruption agenda being funded by empowered by aws as we just discussed dave yeah and just keep in mind nothing that you or i are saying are predictions or saying that anything is going to happen they are possible scenarios of what might happen that seem to make some plausible sense so that when amazon is making the sort of profits that it's making aws naturally that's going to attract other companies because there's margin to to be had there and similarly you know look at uh you look at microsoft for all those years the profits it made in windows or in office software allowed it to do all kinds of other things and essentially that's what amazon is doing today but if a google or a microsoft could cut into those profits through some sort of aggressive pricing and perhaps we'll talk about that you know that would have a lot of impact on amazon as a whole all right so let's quickly go through the other description scenarios and maybe make some comments the next one sort of major companies increasingly choose to do their own cloud computing and or sell their products directly for competitive cost security or other reasons so dave i saw this and look at a company like walmart and others no way they're going to run their business on aws walmart as we know is building out its own cloud and maybe it doesn't have the size of a hyperscaler but it's very large it's got the technical chops it can most likely do it a lot cheaper than renting cloud space what was your thinking in this scenario yeah the broader thing here is essentially one of that computing paradigms have been proven to go in cycles you know a long time ago people shared computers and called timeshare and then people ran their own and now they're sharing again through the cloud and who knows it's possible that the cycle could shift again through some innovation and you know a lot of companies today look at the bills they're getting for cloud or for various sas services and some of them are pretty high and a lot of them will look at and say hey maybe we actually can do some of this stuff cheaper so the scenario is that essentially the the cycle shifts once again uh and it makes more sense to do stuff in-house again that's not a prediction but uh certainly something that's happened before and couldn't plausibly happen again yeah there's a lot of discussion about that in the industry of martine casado and sarah wong wrote that piece about the you know the trillion dollar basically sucking sound basically saying the the scenario was the the the premise rather was the that that sas companies their cost of goods sold are increasingly going to be you know chewed up by cloud costs and then of course mark andreessen says every company is going to be a sas company so as the sassification of business occurs that's something to consider okay next scenario is environmental policies raise costs change packaging delivery recycling rules and or consumer preferences can you comment dave on your thinking on this scenario yeah first i'll just back up a bit we're used to thinking of technology is the great disrupter and clearly that's still important but there are now other forces out there china which will talk about uh the environment uh various cultural forces and and here with the environment you see all kinds of things that could change that you know if you look at amazon and its model of very high levels of packaging lots of delivery vehicles and all the things it is doing are those necessarily the best environmentally and will there potentially be various taxes carbon metrics or things that might work against that model and tend to favor more traditional stores where people go to pick them up that seems to be a plausible scenario and i think everybody here knows that desire to do something in the in the climate environmental spaces is pretty strong and you know if you look at you know just throws aside the recycling industry itself has arguably been quite a failure in that much of what is so-called recycled is basically put in tankers and shipped to the third world which no longer wants it uh and so the backlog of packaging and concerns about packaging and uh what to do with all that you know those those issues are rising and and will be real and i i don't know whether amazon has a good answer to that they're you know they obviously are very aware of it they're working very hard to do everything they can in that space but their fundamental model of essentially packaging every good in its own little box or envelope or whatever is arguably not the greenest way of doing business got it thank you so okay so the next one is price in slash trade wars with the u.s and or china cloud and e-commerce giant so protectionism favors national players so we talking here about for example google bombing prices or alibaba or trade policy making it difficult for amazon to do business in certain parts of the world can you add some color on this one yeah all those things and i would just start with with china itself you know you could argue that covet has been the biggest disruptor of the last couple years but if you look out the next five or eight you had to look at all these things you'd probably say china the size of the chinese market the power of its vendors players like alibaba clearly can rival amazon in many different ways uh you know it's no secret that it'd be hard for amazon to they're not going to be a big success in china uh but you can see it in harder ways that you imagine across asia or other markets where alibaba is strong and you're in today's sort of environment where there's scarce goods and maybe certain products well maybe they go chinese may probably go to alibaba first and you want to buy that product well amazon doesn't have it but alibaba has it you know those sort of scenarios if you get into a sharp trade war with china or even if the current tensions continue it's quite easy to see how that could uh play some havoc with amazon's supply chains in many ways the whole amazon retail model is based on a steady flow of goods manufactured in china and that clearly is not as stable as it was right got it the next one actually caught my attention and this is a big part of the reason why we want to survey the community to see how plausible folks think this is in its its technology related scenario so that would potentially disrupt aws and by fault by default hit amazon so that's major computing innovations such as quantum edge machine machine would obsolete today's cloud architectures okay so so here what you're thinking just as aws changed the game in i.t some future innovations or new business models that we haven't conceived yet could disrupt the prevailing cloud computing model right yeah absolutely i mean you know again we'll go back to where we started that new technologies have always been the main disruptors and here we're looking at some potentially very powerful uh new technologies you know your guess is good in mind about what's gonna happen with quantum is clearly a very different way of computing quite possibly led by other vendors possibly even led by china which would be a huge issue you look at the cloud well cloud's not very good at sort of edge stuff or machine to a machine stuff or sort of near field things out cars in the highway talking to each other uh you know again amazon's totally aware of these things and they are working on it but they have a huge investment in other ways of doing things and historically that inertia that need to protect existing bases of activity and practices has made it difficult for a lot of companies to adjust to new things and so that could happen again uh and there's certainly a puzzle but yeah in all these cases so far amazon has been aware of it is trying to do it but you can still see the scenario playing out and in a truly disruptive technology it's not always possible for the incumbent to effectively cope with it okay the next scenario speaks to i think some of the work that you've done in automation and related areas software replaces centralized warehouses as delivery services are directly connected to suppliers and factories so dave this is like cut out the middle man right software and automation changes the nature of the route absolutely i mean you know in a world of ubiquitous delivery services and product standardization metrics and products being built and shipped from all over the world the concept of running them all through a centralized warehouse is at least at a minimum uh seems like something that might be uh obsoleted and replaced and you know imagine if google built a significant taxonomy of of core products that could be traced directly to where they are either manufactured supplied or brought into the country from whatever company that tries to sell them and the delivery service connected directly to that uh and so that model has always been out there i think at various times people have looked at it it hasn't happened so far and i think amazon itself is is is looking at this particularly as it gets more into food that the idea of shipping all fresh food any sort of centralized warehouse is a pretty bad idea uh and so you know that model of software essentially replacing giant automated warehouses uh is out there and and seems to me uh likely and i just say that you know alibaba for the record doesn't really use that warehouse model it uses a network of suppliers and does it that way and and there do seem to be uh some efficiencies that would likely come with that the next one is was really interesting from a historian's perspective and it's the penultimate uh scenario and that's the proverbial self-inflicted wound and you and i certainly remember ibm's you know fateful decision to outsource the microprocessor and operating system to intel and and and and and microsoft sorry ibm's decision to do that lotus you might recall it refused to allow 123 to run on windows back in the day novell buying word perfect jim barksdale a lot of young people the audience won't of course remember this but jim barksdale poo-pooing microsoft's decision to bundle internet explorer into the operating system all those were kind of self-inflicted or blind spots so this one is complacency arrogance blindness abuse of power loss of trust so much more than the examples i gave consumer and or employee backlash you're seeing some of that at facebook now and i guess this is taking their eye off the customer ball losing the day zero in amazon's case forgetting that customer obsession formula they're working backwards culture and i think this is a big reason why andy jassy was put in charge so this wouldn't happen but we've seen time and time again as the examples i just gave blind spots have absolutely killed companies haven't they dave absolutely he listed many of the most famous but perhaps my favorite of all was kennels and the founder of digital equipment corporation one of the great tech visionaries of his time who stated over and over again why would anybody want a home computer or eunuch's snake oil was his other beautiful all of those things and and so there's the blindness uh there's the area ibm who just came to the view that they and att both came to the view that they were invincible and nothing could ever crack their control of their customer base so we've seen all that i think uh more recently i think some of these things can actually go from the bottom up and you know what's happening to facebook today well they're being hurt by former employees speaking out uh you know this never really happened too much to in the ibm and t days but people calling into question amazon's work labor practices and such things is certainly a possible scenario and the whole sort of you know in the end you know people talk about a cultural backlash against technology i'm not sure i believe it'll happen but it certainly is possible that people will start to rebel against these firms you see it more likely with facebook is fairly well along there uh amazon's still popular but you know in the end and as you i think you said the the core thing that companies routinely fail on is they lose their customer focus and they get caught up in other things their financial numbers their their power inside their position of their company but they they lose track of staying close to the customer has need and terrific job of staying close to the customers over the years uh so if anyone you know was maybe less vulnerable that they they would be well along that that line but it can happen to anyone and new management is often you know one of the real tests and there's many examples of that through history when a new executive comes in will they have that same focus that same thing particularly you know as the first generation's employees get wealthy and retired in a new set of people come in you know you look at microsoft the new people who came in well they're not going to be multi-millionaires they may have missed the great runs they're there to work and and the culture of companies changes when you get to that state the m is not that there yet but you can envision that comings soon enough so you know cultural issues have always been a factor and it's hard to imagine there won't be some sort of factor going forward well and you know you talk about that the the succession of founders and ceos i mean that's what to me makes microsoft so astounding because during the bomber years it was unclear that they were ever going to become relevant again and so nadella has done a masterful job but of course they had the margins from the pc software business that allowed them to buy that time but look at intel and the troubles it's going through uh and so many other examples of companies that just sort of said all right well we're going to pack it in and either sell the company or which is again what i think makes think companies like oracle and dell which you know founder-led ceos not ceo in the case of oracle but still running the business uh so quite uh significant yeah yeah and you know we've talked a lot about things that might hurt answers but you gotta recognize how in many ways how amazing they are and most tech companies a lot of them anyways have essentially been one trick ponies i mean google still makes overwhelming amount of its money selling ads and the things it's tried to do in cars and healthcare and various things you know they've often struggled you know apple still makes the core of its money around it's it's cell phone platform amazon's one of the few that continually generates entirely new huge businesses and and you have to give them an enormous amount of credit for that you know microsoft uh was a they failed repeatedly over and over again with internet stuff and phone stuff and all these things and it really wasn't until you know satya came in and really focused on their customers and their need for enterprise services that he that he really got the company on the right track so you know amazon has always been good listeners customers and if they continue to do so it bodes well but history says other stuff comes along okay and the last scenario is open-ended dave included uh you know what did we miss is there another scenario that we haven't put forth that you could feel it could be disruptive to amazon right i mean you've got to have the at least what'd we miss yeah i mean you know these are things that me and you and i just sort of made up the top of our head these are things we see that that might happen but you know in your huge audience of people in this community every day i'm sure there are other people out there who have thoughts of what might shake things up or even doing things that might shake things up already uh and you know one of the things you do for you guys is get this sort of material out there and and see what ideas surface so hopefully people will uh participate in this and we'll see what comes out of it all right so what happens from here is we're going to publish the the link to the survey in this video description and in our posts we ask you to take the survey please tell your friends we're going to publish the results as always we do in an open and free david michelle thanks so much for putting your brain power on this and collaborating with us i'm really excited to see the results and and and run through the other giants with you as well once we see what this survey says yeah thanks david great and yeah if we can make this one work be fun to do it for for google and microsoft and facebook and apple and see where it all goes thanks a lot all right okay that's it for today remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcast i publish each week on wikibon.com and siliconangle.com etr.plus is where all the cool survey data lives they just dropped their october survey with some great findings so do check that out you can reach me on twitter at d velante he's at d michelle or comment on my linkedin post or email me at david.vellante at siliconangle.com this is dave vellante for dave michelle thanks for watching thecube insights powered by etr be well and we'll see you next time

>>Welcome back to the cubes, continuous coverage of HP es latest Green Lake announcement firehose of innovation. We're seeing a >>cadence >>that HP is delivering in cloud services. Daniel Newman is here, he's the principal analyst at the tour, um, extraordinary research company. Daniel great to see you how you doing man. >>Dave Great to, great to be in person again six ft and safe. But it's good to be back. >>Yeah, it really is uh, been a blur. Right? So we're gonna talk about the pivot to cloud based services. We're seeing that everybody is sort of leaning in HP es all in. I want to talk about value and what this all means to investors. We talk about data, but let me start with the whole as a service move. As I said, everybody's doing it. You see it virtually every companies. Hp was certainly the first to say we're all in, It communicated very well to Wall Street. Everybody's in a debate. No, we were first. No, we were first, but you gotta evaluate based upon the actions that they're taking. How do you look at the trends in this space and how do you look at H. P. S performance? >>Yeah, I admired and Antonio's early pivot, you know, when he got on stage and he said, We're gonna move everything to as a service. I believe that was about two years ago now and the ambition was to have it by 2022. It immediately stood out to me because the momentum, the momentum was behind public cloud, you would have believed three years ago that every workload was going to be in the public cloud and unfortunately guys like us knew that wasn't true. But what we did know was the customers, the enterprise, we're all becoming very comfortable and preference was starting to be shown with that consumption of it meaning subscription based, moving from Capex to apex. That to me was a signal that the timing was right now. Once they got the timing right, it was really about how does this all happened right? It's not necessarily just, we're gonna flip a switch and we're going to start to offer everything as a subscription as a service. There's a lot of standing up those services, putting all that compute all that network, all that storage into a data center, making sure that you have a way to accurately price it and make it quickly consumable, which is something by the way I've admired over the past couple of years, watching the evolution of the software that HP has been rolling. Whether that's Green Lake Central as moral, is that, you know, whether that's kubernetes in the orchestration of hybrid cloud using containers or that's just the ability to spin up a single compute workload in a timely fashion. That's the attraction to public cloud. So, you know, take H P E and its strategy aside and what we have now is you have all of the traditional big iron I T O E M all moving in this direction concurrently. They all understand from both evaluation standpoint meeting Wall Street and also meeting the customer where they are, they have to step up. They had to, uh, whether that was what I was doing with apex Cisco with plus iBMS acquisition of red hat. All these companies were going from, you know, public to private, private to public and then of course you gotta go horizontal from edge to cloud as well. It's a lot to undertake Dave but it's an exciting time and knowing that hybrid is the answer the data is proving that it puts a lot of these companies in a good position to compete. >>Now you mentioned that is the customer preference for good reason. Right? That gives them more flexibility but there's also Wall Street's preference, right? You see that, you know, huge valuations companies like snowflake data, dog elastic. It's that annual recurring revenue that is appealing. They want that they want growth. We saw Q3 hp that did a beaten raise I think 1100 customers for green lake, they announced the orders were up well over 40%. I think revenue was up 30 30 plus percent. So those are the kind of metrics that Wall Street wants to see interestingly though Daniel of course the shift to an A. R. R. Model hurts the income statement but it makes it more predictable and that's what investors today want, what your thoughts. >>Absolutely. I had a chance to speak multiple times over the past few years with the leadership at HP. And it was the exact thing. David that I that I raised, I said you realize that it might be a sidestep or even a half a step backwards before you start to gain momentum. And the real problem with Wall Street is there's no patients. So you mentioned a couple of names like data dog and snowflake. These companies have exponential valuations to earnings because they don't earn anything yet. But most of the market is forward looking and the market tries to anticipate where growth is going to come and saAS companies tend to drive fast growth and fast multiples. This is also left for somewhat slow growth evaluation for companies like HP. Despite the fact that it's doing a lot of the right things you mentioned of course mid double digit growth in green lake, large customer growth numbers. You know, I believe you're serving a billion dollars in revenue or in subscription dollars. Um, fact check that on their >>way to a billion on their way to be honest. I think >>it's booked maybe over >>700 million in revenue that way. >>And so as all those, the confluence of all those events, the market has to be able to basically cherry pick though a part of the business. And I think that's been a little bit of a problem. Not just for HP, but just for all these companies that are, that are struggling with smaller multiples of their P. E ratios. This is true for Cisco? This is true for IBM this is true for for HP and I'll kind of close my thought here. But as the company continues to talk about green Lake and it continues to lean into this, this is the part that has to rise to the front front of the Wall Street investor of the business media to say that existing part of the business is stable, It's solid. They have great customers. However, concurrently the part of the business that is the future, the subscription part that attaches to the public cloud that is enabling companies to grow. That is where they're at. And that is why we see more value. There's a lot of value to unlock and it's because, you know, these small multiples and the business is heading in what I believe is the right >>direction. And HPV last quarter cited, they hit almost 35% gross margin, which is, which is a high mark, high water mark for them if you extract VM ware out of Dell there in the mid twenties. So these are two different businesses and I think that's a big reason why Dell's moving into the space. I almost think like the board conversation at HP was, hey, let's, let's not keep thinking about building boxes. Let's build services and let's add value to those services that are software based and then we can kind of control our own destiny as opposed to kind of intel getting all the margins and or M. D. Or whatever it is. So so that so how do you see as a service driving value for H. P. E. It's customers and ultimately what do they have to do to convince Wall street >>recurring revenue companies drive higher multiples? It's not even a debate and companies that have a large percentage of their business as recurring tend to drive much higher evaluation and tend to also be more beloved by shareholders. The performance of HP has been good, it's been solid, it's been in the right place especially given the circumstances of the pandemic and the impact of on prem it we all saw the explosion of SAS the explosion of cloud, you know, SAS and chips are hot, they're always hot. But everything that was sort of sandwiched in the middle became a little bit more murky throughout the pandemic times. And the ability for HP. And these companies that are in this space are operating to be able to bridge this gap. The companies have 25 or so percent of workload during the public cloud. That means the rest need services from companies like HP. So the tam is growing because the overall size of the workload, the volumes of data are all growing exponentially and that's an opportunity but the market wants to see fast growth. Dave I mean they're not going to accept the single digit overall growth if you want to get the kind of multiples of a, you know, even a Microsoft at a 40 or a sales force at 100. But HPV with its software is starting to play in those spaces where investors in the market maybe can start to recognize that it is undervalued. >>So we live in a data centric world, Antonio talks about this all the time and we're seeing HP makes some moves in terms of data data management, you see what they're doing with his moral and that's a big part of the software place. So to the extent that you can lean into that wave have a higher contribution from software, higher margin business obviously and a more predictable revenue stream. That seems to be the right direction in my view. Um it's gonna take some time to play out. They're not gonna overnight, you know, they don't have a green sheet of paper, they clean sheet of paper, they have a business that they have to manage and they have to service their customers. But to the extent that the majority of their business over time can become as a service, shouldn't that confer higher margins and and greater value to investors? Yeah, it's sticky >>for enterprise users when you move to that subscription model, it's not as easy as just lifting and shifting you build your entire business process around these investments in these technologies. Software. It's sticky, it's organizationally complex because where HP sits in the stack, where their analytic solutions and software help you more successfully deploy S. A. P type workloads. The entire company runs on that. So the involvement and the importance of the role that HP is playing is huge. The challenge for customers isn't as big customers get this, the enterprise users, the C I O. S. They get the importance Wall Street though it's a little harder for them sometimes to digest. Whereas they might be looking at something like a snowflake that you mentioned. That's fairly straightforward. Almost all of its revenue is pure subscription and it's looked at as 20 years in a perpetuity where people are still trying to wonder is HP gonna be sticky? Are these customers not only going to keep with HP but are they going to increase? Right. Is that net revenue expansion going to take place across the portfolio? And HP rolls out more services right. Started with storage and then it moves to compute and then it adds edge layer services. Are people going to buy the whole stack? Because that of course, also as we've seen with some of the bigger players can be an extremely attractive value proposition. >>Well, I also think as they move into cloud, HP has always been about optionality. So I feel as though with their day to play, for example, they can get deeper into data management but they can also partner with others, you're leaning into open source so that means you can expand your portfolio that's kind of what the cloud game is is you know, here's the cloud, we got all these different options, choose what you want, we'll manage it for you, charge you for that but we'll take away that headache. That's a good business, >>choose your own cloud adventure last week oracle reported. Um and I'm only pointing this out because you know, you look at the company and everybody was what's with their i as number? Why is it not big or smaller? Why don't we know right. But over the last couple of years we've realized that it's no longer little seeing big see little C which I would call infrastructure as a service no longer exists. Cloud is one big number. So H P E being in the cloud through its hybrid services, its software, its platform support is just as much about being in the cloud is a company that offers I. S. Or company that offers SAs however convincing the market that this is the case is the trick. We're starting to see companies because you you hear when IBM reports how their numbers are, you know, they're they're tying in all kinds of global business services and they're tying in you know, red hat numbers and they're telling in their public cloud numbers but what I'm saying is up to this point, a lot of these hybrid services are kind of not necessarily being bucket ID like this big sea of cloud but it really is the entire stack of of infrastructure platform software and then of course all those attached services for companies to deploy this that equal a cloud number. And so the subscription number grows. Green Lakes customer account grows. And I think convincing the street and everybody in between that this is a cloud number and not a on prem or a attached to the cloud number is going to really help boomer boom, the overall value that people see and what HP is doing. >>And I think not only H P E but I think others are I think finally they're starting to realize that wow, you know, we all know everything is not going to public cloud. We understand it's a hybrid world Public cloud spend a company's the hyper scale is collectively spent $100 billion dollars last year on Capex. That's like a gift to a company like HP that can connect the dots and create that abstraction layer that hides the underlying complexity. We'll take care of that for you will make everything cloud native. We can bring cloud native on prem and go out to the edge, which is like the Wild West that is a that's a trillion dollar opportunity that there's no limit to market potential for companies out there and HP specifically. >>Well the edges a massive opportunity and that's what I said, you know, a lot of us are and we do this ourselves as both analysts and sometimes media personalities is we like to debate how big the opportunity of cloud is. And of course there are some firms that try to market size this, but I actually think it's extraordinarily difficult to market sizes, especially because of the edge. You talk about data and analytics. I recently attended the a event. It's a car event in Munich and you just look at the amount of data that vehicles are going to be creating in the in the coming years. They're basically massive rolling data centers full of chips, compute networking storage. This is all going to take significant infrastructure investments at scale and it's creating this humongous opportunity at the edge and you look at five Gs impact and as we roll out five G it's scale. Every one of these things brings more data connects, more devices and all that intelligence needs infrastructure, It needs software, it needs services. So the overall tam Dave is going to continue to grow and I think if anything it tends to be underestimated because it's really hard to define just how big the data equation is actually going to be in the market. >>Digital changes the equation. It's not, it's no longer servers, storage, networking database, its cloud services that are enabling digital transformations. I'll give you one more >>thing that just crossed my mind. But I think is important is if you even look at the the S. G. And sustainability efforts that most companies are going to be taking the amount of investment in trying to capture, comprehend manage just the data and analytics to understand your footprint and understand how you are going to achieve carbon neutrality and how you're going to do this up and down. And I mean that's just one thing and of course that's a, I wouldn't call it table stakes at this point, the market expects every company to be making this kind of investment well, when you run a multi national global enterprise that has edge, that has data centers that has manufacturing facilities, there is just unbelievable requirements on technology. And again, we've got to connect that public cloud somehow. So we can't ignore the fact that those public cloud players are all addressing this, they're all bringing solutions out. But companies like HP, this is where their sweet spot is, and this is where I believe they're going to have to compete very aggressively and efficiently to show we are a great partner to the public cloud, but our legacy and our capabilities mean we understand this part of the business, we believe we're the right fit and trust me, the Azure and AWS are, they're not going to make this easy, they're going to be competitive but they're also going to going to be very cooperative >>well, and they're coming into the home court of the on prem vendors. So that's gonna be interesting to see how that plays out as an observer, as an analyst, what do you want to see from HP, Green Lake cloud services? What are the, what are the areas that you're gonna be watching that could serve as indicators of success and momentum? >>Well, we didn't even talk because we did talk about some of that, but we didn't even talk about aI and amount for instance, all this data itself has to be managed and processed. So the fact that you're getting to that data management at scale, the fact that you're building out orchestration for containers. Well this is because of that data delusion conundrum, whatever word we want to use for it. But the best companies in the world are going to find a way to extract more value from that data and that's going to be through the application of aI of ml of neural networks, deep learning and other important capabilities. Having a foot into that Dave is something I want to see HP and it already does, but I want to see the participation there. This is an area that I think public cloud is doing really well there. They really made big investments both with homegrown chips with partnering with the likes of videos and intel to, to offer a lot of enhancement acceleration, um Ml and AI services. I think this is gonna be an area that on prem and through hybrid offerings. We're gonna want to see the company compete. Uh and then of course, I think back to the one thing Dave, I'll just kind of wrap on this, is that that customer growth, I mean you talked about how to get evaluation, how to get the street up, people get excited about overall growth. They need to get that narrative carved out about green, like about the subscription growth, the service growth point next and all that stuff, but all that has to start to equate to overall growth. Um you know, I think it needs to be made at least single high digits, single overall percentage growth, especially because the whole portfolio supposed to be there. You know, companies get those big multiples are growing >>fast growth on, on that large of a base would get people's attention. You mentioned custom chips, H P >>E, you >>know, H P S H P S heritage and HP. They have chops in custom silicon. So be interesting to see if, if you know the future, you talk about ai inference at the edge, huge disruptive potential opportunities and I'm really curious as to see how that plays out because that is another trillion dollar market opportunity. Daniel, thanks so much for coming to the cubes. Great to have you looking forward to working with you in the future. >>Yeah, it's great to be here. And sorry, we didn't get to those chips earlier. We could have gone down a whole, another whole, another >>half hour. Great, great to talk to you. All right, thank you for watching everybody. This is the cubes, continuous coverage of HBs, Big Green Lake announcement. Keep it right there for more, great content. Mhm.

(upbeat music) >> Welcome to the Q3 "AWS Startup Showcase", I'm Lisa Martin. We're going to be talking about new breakthroughs in DevOps, Data Analytics and Cloud Management Tools, with WhiteSource Software, at least for the DevOps track. I'm excited to welcome Susan StClair, Director of Product at WhiteSource software to the program. Susan, it's great to see you! >> Oh, very excited to be here, Lisa, thank you. >> We've got a lot of stuff to talk about today, but ultimately, the theme that Susan's going to talk to us about us is, winning developer's trust is key to scaling-up open source security for the enterprise. We're going to unpack that. You talk about, that winning that trust is key, shifting left won't work without developers buy-in. Susan, help us understand this. >> Yeah, sure, so- on some of the topics we have later but you look at the rate of applications of being the pool of how fast that is, and you look at development teams of hundreds and you have the OpSec teams of five or ten, and they just can't do it all, so, really, you need to leverage everybody who's part of the application to really be able to make sure that you're developing and deploying and releasing a secure application. So, that's the Shifting Left. Unfortunately, I think what's happened is, because application security is overwhelmed and because they're like, "Oh, we have all of these developer teams over here, and it's their code, and they should fix it." And they just kind of dumped application security on them and the poor development teams are like, "but that's not what I do, I don't have any expertise in there." So if you really, truly, want a Shift Left to work, you do need to build that buy-in, you do need to build the trust with your extended team, for lack of a better word. And, really start to look at things that are important to them. So automated tools, making sure that they work with their tools sets and their processes. Looking at automation, not just in terms of scanning but also remediation. You just really need to start to work with them and think about application releases in a different mindset. >> And your recommendation here is also to build that trust gradually, and to let developers control the pace- >> Absolutely >> And the level of automation. Talk to me about why it's important to give the developers that control? >> Yeah, sure. Again, I think nobody likes to be told what to do, I certainly don't, don't tell me how to do my job. So, I think, that because historically application security and development have really been at odds. It has been somewhat of a confrontational relationship, so, I think as you're starting to build that trust, you do need to go slow. Where does it make sense to add in auto-remediation solution like WhiteSource, right? Where does it make sense? We don't want to do it everywhere, we don't want to overwhelm development teams with this. So, really start to look, let them control the pace, build that trust, build that. This is a good thing for everybody. And, again, I think with tools like WhiteSource, the solution software, you can pick and choose, it's not an all or nothing. We're going full automation, full remediation, one-stop-shopping, I mean you can kind of control the pace as you start to build that trust between the various teams. >> Is that differentiator for WhiteSource the ability for this auto-remediation tool to let them control that? >> Yeah, it definitely is, and I know it just rolls off the tongue, doesn't it? Just rolls off the tongue. >> It really does. (both laughing) >> Say it ten times fast >> I'm afraid to. >> Exactly, exactly. So, no, it actually, absolutely is a differentiator for us. And again when we look at, looking at our customer base and enterprise and we look at, even maybe smaller teams that trust is really made us successful and the key to that trust is really that controlling the pace with auto-remediation. And, some of the other automation pieces to the solution. >> And speaking of customers, you guys have 23% of the Fortune 100 as customers, give me an example of one of your favorite customers that you think really shows the value that WhiteSource is giving to those developers by giving them that control. >> Yeah, sure. So I feel like we're like the big company or bigger company that nobody has heard of outside of this space. But, not naming names, but large financial customers and really shifting application security, open-source application security, to the hands of the development teams. So they've actually, again, small application team, they've really pushed it out to the development teams as part of a repo-integration for scanning, for ticket creation, for auto-remediation, and that's really, let them scale beyond, just one or two teams to thousands of repos, for example. I mean, that is, in my opinion, a huge use case or huge validation of that this works. This isn't just somebody talking about how cool their software is and it's not based in reality. >> A stat that I read about WhiteSource offer that I wanted to get your feedback on, is that, "WhiteSource goes beyond traditional detection, providing dependency and trace analysis and that this helps organizations eliminate upto 85% of security alerts." That's a big number. Talk to me about how you guys do that and the advantages that delivers. >> Yeah, sure, so I think like the one of the challenges with, historically, with open-source solutions, is that they scan and they get this result, and you could have hundreds and thousands of insecure libraries and you're like, "Holy moly, where do I even start?" It's just completely overwhelming. And then you dig into little deeper and again starting to build that trust with development teams, and the development teams comes back to you and says, "Well, hey, guess what? Yeah I know that library is insecure, but I'm not using that part of that library." So, it's really kind of a false-positive. So, what this dependency tracing does and how it helps with prioritization, is it says, "Okay, we see this particular library, this vulnerable open-source library, and it is in your execution path, we can see that you're using it." So then, you're able to say, "Okay, I should definitely fix this, because we're using it, or maybe not." Maybe, again, it's part my backlog yes, we should always keep up-to-date, and be completely secure. But having that ability to prioritize where to start and having the alerts based on that really reduces the noise. And again, it builds the trust between the teams. >> So, we talked from the beginning about shifting left isn't going to work without developers buy-in, the idea of using auto-remediation tools to let developers control that pace, the OpSec folks, the Dev folks, we also have for, I believe, it's the fifth consecutive year now, a huge gap in cybersecurity skills. I think I've seen some reports estimating that there needs to be another three million professionals in the next five years to help fill that gap and at the same time we're seeing the security landscape changing dramatically. Talk to me about how the cybersecurity skills gap is affecting developers, OpSec folks, and what your seeing as a tool that can help remediate some of that. >> Sure, yeah, no, that's, I mean that is the challenge. And I would even say that there seems to those skills gap on the development side too. But, I think that in terms of some of the challenges with that, so you have to look at ways, how can we be smarter about things. So, we don't have people, large teams where they know everything about application security and open-source security that we can really rely on to drive remediation, but, also to use these tools that all of us bought that do different things, that aren't correlated but to kind of provide that glue. So, where WhiteSource, I think is trying to address this is, again, if I don't have the people, and I don't have the skillsets, first of all automation, right? So, the more that we can automate, the better. But, not just again, automating on the scanning side, I think that's certainly a part of it, but again, looking at how we can help development teams that are maybe not security experts, and keeping them up-to-date and giving them, again, automatic remediation so that they can fix things without having a really depth that you would expect in a cybersecurity professional. >> I'm sure they appreciate that, not having to have that depth, because there really isn't, in terms of developers, there isn't the time. Speed is always of the essence there. One of the things too that I know, is there's lot of tools being used, you mentioned that. How can WhiteSource Software help the developers to better utilize some of the tools that they have or not just be buying tools to check boxes? >> Yeah, sure. So, yeah it's sad fact, I think, within our industry, probably more than just our hours, but really a lot of decisions, purchasing decision are based on the, "Well, I need to scan because somebody told me to and I that I had to, and I'm going to check the box. I'm not really interested in fixing anything, I just need to check that box." And, I think, historically, when it comes to tool selection, again, because application security is really focused on that check-the-box because they need to do that for a compliance or governance reason, they really haven't taken into heart the teams that would actually be using them and having to make the magic happen. So, they would prioritize things that, again, maybe OpDev wouldn't, so, again does it work with my tools? As a developer, I live in my IDE, I live in my code-repo, I live in my ticketing system, security doesn't typically care anything about that. So, I think with WhiteSource, again, providing the tools that the OpSec team needs. So again, the compliance reports and the policies and all this stuff we love. Also providing, again, the way to easily fit into developer workflows, that's how we're helping to move beyond, okay, we're checking the box but we do want to actually fix something and we want to move the target along. So we're really, I think, helping address that need as well. >> I know you guys did a DevSec Ops Insights Report recently, unpack that a little bit with some of the key findings that have come out of that. >> Yeah, no, that's great, so it's very interesting. First of all I think we in the industry we talk a lot about DevSecOps and that security is part of the DevOps process and everything is good. But when you actually talk to people, I think, two things, one, it's very much a work in progress, absolutely, and a lot of that is part of the tooling. I think, too, like what we've found as a part of this survey, is that the developers, are often, they feel forced to, okay, I'm shifting left, you're telling me I own security, but you're also telling me that I need to get this application out the door. I need this to compete. So, they're really being forced into hard choices of which one to prioritize, and that really comes down to a culture thing. What is more important to you. Being secure or being competitive? And how do you weigh that? So, I thought that was actually very interesting, I think that we tend to give OpDev teams a bad rap but they're really doing the best they can and they need clear guidance and there needs to be a security culture for them to operate in. >> Right, that's a really big one that you just hit on, that cultural impact. It's hard to change. In the last 18 months, we've all been through so much change, personally and professionally. We've seen this massive acceleration in digital transformation, so probably more pressure on developers who need to be able to be productive from work, from anywhere environments, that that cultural change, is really critical. I'm curious if you have some feedback from customers that have done it successfully or are in the process of doing it successfully that you can share? >> Yeah, change is hard, no matter where it's at. Absolutely. So, I think, like where we've seen the most successful of our customers, around this specifically, it truly is both a top-down and bottom-up approach. From a top-down, you can't just give lip-service that application security is important. You can't just say, "Oh, again from a compliance check-the-box, point-of-view, we scan, and we're looking, and, oh look, we have these statistics. You have to really have to live it. And what I mean by that is, when you're developing new applications it's just as important as the feature list. Security bugs are just as important as any other type of bugs. So again, it goes into the workflow of the application development teams and you don't make them make these hard trade-offs all the time between security and release. And then, from the bottom-up, again, you need to be where your teams are at. You can't ask them to go into another tool, or another thing, or another this and that. They have things to do. You have to be where they are. And you, have to give targeted, actionable, not things they have to go research, a guidance, and automate as much as you can. Again, both on the scanning as well as on the remediation side. >> Meet them where they are and facilitate that automation. Susan, thank you so much for joining me today, talking about- >> My pleasure. >> How WhiteSource Software is helping that, and also for the challenge of saying auto-remediation 10 times in a row, fast. (Susan laughing) I might practice that later. But it's been great talking to you. >> That will be my home work. Likewise. >> Exactly! Thank you so much for joining me. >> My pleasure. >> This has been our coverage of the "AWS Startup Showcase", New Breakthroughs in DevOps, Data Analytics and Cloud Management tools. For Susan StClair, I'm Lisa Martin. Thanks for watching. (gentle music)

(upbeat music) >> Welcome to the Q3 AWS Startup Showcase. I'm Lisa Martin. I'm pleased to welcome Knox Anderson, the VP of Product Management, from Sysdig, to the program. Knox, welcome. >> Thanks for having me, Lisa. >> Excited to uncover Sysdig. Talk to me about what you guys do. >> So Sysdig, we are a secure DevOps platform, and we're going to really allow customers to secure the entire lifecycle of an application from source to production. So give you the ability to scan IAC for security best practices, misconfiguration, help you facilitate things like image scanning as part of the build process, and then monitor runtime behavior for compliance or threats, and then finish up with incident response, so that you can respond to and recover from incidents quickly. >> What are some of the main challenges that you're solving and have those changed in the last 18 months? >> I'd say the main challenge people face today is a skills gap with Kubernetes. Everyone wants to use Kubernetes, but the amount of people that can operate those platforms is really difficult. And then getting visibility into the apps, that's running in those environments is also a huge challenge. So with Sysdig, we provide just an easy way to get your Kubernetes clusters instrumented, and then provide strong coverage for threat detection, compliance, and then observability for those environments. >> One of the things that we've seen in the last 18 months is a big change in the front landscape. So, I'm very curious to understand how you're helping customers navigate some of the major dynamics that are going on. >> Yeah, I'd say, the adoption of cloud and the adoption of Kubernetes have, have changed drastically. I'd say every single week, there's a different environment that has a cryptomining container. That's spun up in there. Obviously, if the price of a Bitcoin and things like that go up, there's more and more people that want to steal your resources for mining. So, we're seeing attacks of people pulling public images for Docker hub onto their clusters, and there's a couple of different ways that we'll help customers see that. We have default Falco rules, better vetted by the open source community to detect cryptomining. And then we also see a leading indicator of this as some of the metrics we, we collect for resource abuse and those types of things where you'll see the CPU spike, and then can easily identify some workload that could have been compromised and is now using your resources to mine Bitcoin or some other alt-coin. >> Give me a picture of a Sysdig customer. Help me understand the challenges they had, why they chose you and some of the results that they're achieving. >> Yeah, I used to say that we were very focused on financial services, but now everyone is doing Kubernetes. Really where we get introduced to an organization is they have their two or three clusters that are now in production and I'm going through a compliance audit, or it's now a big enough part of my estate that I need to get security for this Kubernetes and cloud environment. And, so we come in to really provide kind of the end-to-end tools that you would need for that compliance audit or to meet your internal security guidelines. So they'll usually have us integrated within their Dev pipelines so that developers are getting actionable data about what they need to do to make sure their workloads are as secure as possible before they get deployed to production. So that's part of that shift, left mindset. And then the second main point is around runtime detection. And that's where we started off by building our open source tool Falco, which is now a CNCF project. And that gives people visibility into the common things like, who's accessing my environment? Are there any suspicious connections? Are my workloads doing what they expected? And, those types of things. >> Since the threat landscape has changed so much in the last year and a half, as I mentioned. Are the conversations you're having with customers changing? Is this something at the C-suite or the board level from a security and a visibility standpoint? >> I think containers and Kubernetes and cloud adoption under the big umbrella of digital transformation is definitely at board level objective. And then, that starts to trickle down to, okay, we're taking this app from my on-prem data center, it's now in the cloud and it has to meet the twenty security mandates have been meeting for the last fifteen years. What am I going to do? And so definitely there's practitioners that are coming in and picking tools for different environments. But, I would definitely say that cloud adoption and Kubernetes adoption are something that everyone is trying to accelerate as quickly as possible. >> We've seen a lot of acceleration of cloud adoption in the last eighteen months here, right? Now, something that I want to get into with you is the recent executive order, the White House getting involved. How is this changing the cybersecurity discussion across industries? >> I really like how they kind of brought better awareness to some of the cybersecurity best practices. It's aligned with a lot of the NIST guidance that's come out before, but now cloud providers are picking, private sector, public sector are all looking at this as kind of a new set of standards that we need to pay attention to. So, the fact that they call out things like unauthorized access, you can look at that with Kubernetes audit logs, cloud trail, a bunch of different things. And then, the other term that I think you're going to hear a lot of, at least within the federal community and the tech community, over the next year, is this thing called an 'S bomb', which is for, which is a software bill of materials. And, it's basically saying, "as I'm delivering software to some end user, how can I keep track of everything that's in it?" A lot of this probably came out of solar winds where now you need to have a better view of what are all the different components, how are those being tracked over time? What's the life cycle of that? And, so the fact that things like S bombs are being explicitly called out is definitely going to raise a lot of the best practices as organizations move. And then the last point, money always talks. So, when you see AWS, Azure, Google all saying, we're putting 10, 10 billion plus dollars behind this for training and tooling and building more secure software, that's going to raise the cybersecurity industry as a whole. And so it's definitely driving a lot of investment and growth in the market. >> It's validation. Absolutely. Talk to me about some of the, maybe some of the leading edges that you're seeing in private sector versus public sector of folks and organizations who are going alright, we've got to change. We've got to adopt some of these mandates because the landscape is changing dramatically. >> I think Kubernetes at auction goes hand in hand with that, where it's a declarative system. So, the way you define your infrastructure and source code repost is the same way that runs in production. So, things like auditing are much easier, being able to control what's in your environment. And then containers, it's much easier to package it once and then deploy it wherever you want. So container adoption really makes it easier to be more secure. It's a little tricky where normally like you move to something that's bleeding edge, and a lot of things become much harder. And there's operational parts that are hard about Kubernetes. But, from a pure security perspective, the apps are meant to do one thing. It should be easy to profile them. And so definitely I think the adoption of more modern technology and things like cloud services and Kubernetes is a way to be more secure as you move into these environments. >> Right? Imagine a way to be more secure and faster as well. I want to dig in now to the Sysdig AWS partnership. Talk to me about that. What do you guys do together? >> AWS is a great partner. We, as a company, wouldn't be able to deliver our software without AWS. So we run our SAS services on Amazon. We're in multiple regions around the globe. So we can deliver that to people in Europe and meet all the GDPR requirements and those kinds of things. So from a, a vendor partnership perspective, it's great there. And then on a co-development side, we've had a lot of success and a fun time working with the Fargate team, Fargate is a service on Amazon, that makes it easier for you to run your containers without worrying about the underlying compute. And so they faced the challenge about a year and a half ago where customers didn't want to deploy on Fargate because they couldn't do deeper detection and incident response. So we worked together to figure out different hooks that Amazon could provide to open source tools like Falco or commercial products like Sysdig. So then customers could meet those incident response needs, and those detection needs for Fargate. And really, we're seeing more and more Fargated option as kind of more and more companies are moving to the cloud. And, you don't want to worry about managing infrastructure, a service like Fargate is a great place to get started there. >> Talk to me a little bit about your joint. Go to mark. Is there a joint go-to-market? I should say. >> Yeah, we sell through the AWS marketplace. So customers can procure Sysdig software directly though AWS. It'll end up on your AWS bill. You can kind of take some of your committed spend and draw it down there. So that's a great way. And then we also work closely with different solutions architects teams, or people who are more boots on the ground with different AWS customers trying to solve those problems like PCI-compliance and Fargate, or just building a detection and response strategy for EKS and those types of things. >> Let's kind of shift gears now and talk about the role of open source, in security. What is Sysdig's perspective? >> Yeah, so the platform, open source is a platform, is something that driving more and more adoption these days. So, if you look at like the fundamental platform like Kubernetes, it has a lot of security capabilities baked in there's admission controllers, there's network policies. And so you used to buy a firewall or something like that. But with Kubernetes, you can enforce services, service communication, you put a service mesh on top of that, and you can almost pretend it's a WAF sometimes. So open source is building a lot of fundamental platform level security, and by default. And then the second thing is, we're also seeing a rise of just open source tools that traditionally had always come from commercial products. So, there's things like OPA, which handle authorization, which is becoming a standard. And then there's also projects like Falco, that provide an easy way for people to do IDS use cases and auditing use cases in these environments. >> Last question for you. Talk to me about some of the things that you're most excited about. That's coming down here. We are at, this is the, our Q3 AWS Startup Showcase, but what are some of the things that you're most excited about in terms of being able to help customers resolve some of those challenges even faster? >> I think there's more and more Kubernetes standardization that's going on. So a couple of weeks ago, Amazon released EKS Anywhere, which allows companies who still have an on-prem footprint to run Kubernetes locally the same way that they would run it in the cloud. That's only going to increase cloud adoption, because once you get used to just doing something that matches the cloud, the next question you're going to answer is, okay, how fast can I move that to the cloud? So that's something I'm definitely really excited about. And then, also, the different, or AWS is putting a lot of investment behind tools like security hub. And we're doing a lot of native integrations where we can publish different findings and events into security hubs, so that different practitioners who are used to working in the AWS console can remediate those quickly without ever kind of leading that native AWS ecosystem. And that's a trend I expect to see more and more of over time, as well. >> So a lot of co-innovation coming up with AWS. Where can folks go to learn more information? Is there a specific call to action that you'd like to point them to? >> The Sysdig blog is one of the best sources that I can recommend. We have a great mixture of technical practitioner content, some just one-oh-one level, it's, I'm starting with container security. What do I need to know? So I'd say we do a good job of touching the different areas and then really the best way to learn about anything is to get hands-on. We have a SAS trial. Most of the security vendors have something behind a paywall. You can come in, get started with us for free and start uncovering what's actually running in your infrastructure. >> Knox, let's talk about the secure DevOps movement. As we see that DevOps is becoming more and more common, how is it changing the role of security? >> Yeah, so a lot of traditional security requirements are now getting baked into what a DevOps team does day-to-day. So the DevOps team is doing things like implementing IAC. So your infrastructure is code, and no changes are manually made to environments anymore. It's all done by a Terraform file, a cloud formation, some code that's representing what your infrastructure looks at. And so now security teams, or sorry, these DevOps teams have to bake security into that process. So they're scanning their IAC, making sure there's not elevated privileges. It's not doing something, it shouldn't. DevOps teams, also, traditionally, now are managing your CI/CD Pipeline. And so that's where they're integrating scanning tools in as well, to go in and give actionable feedback to the developers around things like if there's a critical vulnerability with a fix, I'm not going to push that to my registry. So it can be deployed to production. That's something a developer needs to go in and change. So really a lot of these kind of actions and the day-to-day work is driven by corporate security requirements, but then DevOps has the freedom to go in and implement it however they want. And this is where Sysdig adds a lot of value because we provide both monitoring and security capabilities through a single platform. So that DevOps teams can go into one product, see what they need for capacity planning, chargebacks, health monitoring, and then in the same interface, go in and see, okay, is that Kubernetes cluster meeting my SOC 2 controls? How many images have my developers submitted to be scanned over the past day? And all those kinds of things without needing to learn to how to use four or five different tools? >> It sounds to me like a cultural shift almost in terms of the DevOps, the developers working with security. How does Sysdig help with that? If that's a cultural shift? >> Yeah, it's definitely a cultural shift. I see some people in the community getting angry when they see oh we're hiring for a Head of DevOps. They're like DevOps is a movement, not a person. So would totally agree with that there, I think the way we help is if you're troubleshooting an issue, if you're trying to uncover what's in your environment and you are comparing results across five different products, it always turns into kind of a point the finger, a blame game. There's a bunch of confusion. And so what we think, how we help that cultural shift, is by bringing different teams and different use cases together and doing that through a common lens of data, user workflows, integrations, and those types of things. >> Excellent. Knox, thank you for joining me on the program today, sharing with us, Sysdig, what you do, your partnership with AWS and how customers can get started. We appreciate your information. - Thank you. For Knox Anderson. I'm Lisa Martin. You're watching the cube.

(upbeat music) >> Welcome to theCUBE and our Q3 AWS Startup Showcase. I'm Lisa Martin. I've got two guests here with me, Erez Berkner is back, the Co-Founder and CEO of Lumigo. Hey, Erez, good to see you. >> Hey, Lisa, great to be here again. >> And Kevin O'Neill, the CTO at Flex is here as well. Kevin, welcome. >> Hi, Lisa, nice to meet you. >> Likewise, we're going to give the audience an overview of Lumigo and Flex. Let's go ahead, Erez, and start with you. Talk to us about Lumigo, and I think you have a slide to pull up to walk us through? >> Yeah, I have a couple, so, great to be here again. And just as an overview, Lumigo is a serverless monitoring and debugging platform. Basically allowing the user, the developer to get an end-to-end view of every transaction in his cloud. It's basically distributed tracing that allows you from one hand to monitor, to see a visual representation of your transaction, but also allows you to drill down and debug the failure to get to the root cause. So essentially, once you have the visualization and if we'll move to the next slide, you can actually click and drill down and see all the relevant debug information like environment variables, duct rays, inputs, outputs, and so on and so forth. And by that, understanding the root cause. And sometimes those root causes of the problems are not just errors, they are latencies, they are hiccups. And for that, we can see on the next slide, where Lumigo allows you to see where do you spend your time? Where are the hiccups in your system? What's running in Paula to what in the same transaction, where you can optimize. And that's the essence of what Lumigo provides in a distributed environment and focusing on serverless. >> Got it, focusing on serverless, we'll dig into that in a second. Kevin, give us an overview of Flex. You're a customer of Lumigo? >> We are indeed. So Flex is a build smoothing platform. We help people pay their rent and other bills, in these times of uncertainty and cashflow, the first of the month for your rent, it's a big bill. Being able to split that up into multiple payments is a lot easier. And when we entered the market, you were looking at a place where people were using things like payday loans, which are just ridiculous, really hurting, hurt people in the longterm. So we want to come in with something that is a little more equitable, little fairer and help people who can well afford their rent. They just can't afford it on the first, right? And so we started with rent, and now we cover all the bills like utilities and things like that. >> What a great use case, and I can't even imagine, Kevin, in the last year and a half, how helpful that's been as the world has been so dynamic. So talk to me a little bit about what you were doing before Lumigo and we'll get into then why you went the serverless route. >> Right, so I came to Flex to help them out with some problems that we're having as our servers were scaling up. Obviously, when the business hit, it was really, it went from zero to 100 miles an hour so quickly. And so I came in to help sort out some of the growing issues. And so when I started looking at that, we were three developers and didn't want to spend time on ops, didn't want to spend time on all of the things that you have to do just to be in business, right? And it's really expensive in the technical space. If you get into something about Kubernetes or things like that, you spend a lot of time building that infrastructure, making sure, and that's really minimal value to your business. It's there for reliability, but it doesn't really focus in on the thing that is important to you. So we wanted to build something that minimized that, we talk about DevOps, we want it ops zero, right? So that's like DevOps is a really nice practice, but having people in that role, it seems like you're still doing ops, right? You still got people who are doing those things, and we want it to kind of eliminate that. So I had some experience with serverless before joining Flex. I thought we'll run up a few things and spike up a few things. When you come out of environments like Kubernetes or your more traditional AC to type infrastructure, you'd lose some things. And one of the big things you'd lose is platforms of visibility. So things like OpenTrace and Datadog, and things like that, that do these jobs of telling you what's going on in your infrastructure, you've got fairly complex infrastructure going on, lots of things happening. And so, we initially started with what was available on the platforms, right? So we started with your CloudWatch logs and New Relics, right? Which got us somewhere. But as soon as we started to get into more complex scenarios where we're talking across multiple hops, so through SQS and then through EventBridge and Dynamo, it was very difficult to be able to retrace a piece of information. And that's when we started looking around for solutions, we looked at big traditional pliers, the Datadogs, the New Relics and people like that. And then the serverless specific players, and we ended up landing on Lumigo, and I couldn't have been happier with the results, from day one, I was getting results. >> That's great, I want to talk about that too, especially as you say, we wanted to be able to focus on our core competencies and not spend time in resources that we didn't have in areas where we could actually outsource. So I want to go back to Erez, talk to me about some of the challenges that Kevin articulated, are those common across the board, across industries that Lumigo sees? >> Yeah, I think the main thing when we met Kevin main were about visibility and about ability to zoom out, see the bigger picture and when something actually fails or about to fail in production, being able to drill down to understand what happened, what is the root cause, and go ahead and fix it instead of going through different CloudWatch logs, and log groups and connecting the dots manually. And that's one of the most common challenges when enterprise, where software engineers are heading toward serverless, toward managed services. So, definitely we'll hear that it was many of our customers. >> So Kevin, talk about the infrastructure that you've set up with serverless and go through some of the main benefits that Flex is getting. >> Right, so look, the day one thing of course, is the number of people we need doing operations as we've grown is next to nothing, right? We are able to create in that, we all want this independence of execution, right? So as you scale, I think there's two ways really to scale a system, right? You can build a monolith and shot it, that works really, really well, right? You can just build something that just holds a ton of data and everything seems connected when you release it all in one place, or you build something that's a little more distributed and relies on asynchronous interactions effectively, like in everywhere but the edges, both of those things scale. The middle ground doesn't scale, right? That middle ground of synchronous systems talking to synchronous systems, at some point, your lightency is your sum of all the things you're talking to, right? So doing anything in a quick way is not possible. So when we started to look at things like, I'm sorry, so the other challenge is things like logging and understanding what's happening in your system. Logging is one of those things that you always don't have the thing logged that you're interested in, right? You put in whatever logging you like, but the thing you need will always be missing, which is why we've always taken a tracing approach, right? Why you want to use something like Lumigo or an OpenTrace, you don't sit there and say, "Hey, log this specifically," you log the information that's moving through the system. At that point, you can then look at what's happening specifically. So again, the biggest challenge for us is that we run 1500 landlords, right? We run 600 queues. There's a lot of information. We use an EventBridge, we use Dynamo, we use RDS, we've got information spread out. We moved stuff, but to third party vendors, we're talking out to say, two guys like Stripe and Co, and we're making calls out of those. And we want to understand when we've made those calls, what's the latency on those calls. And for a given interaction, it might touch 20 or 30 of those components. And so for us, the ability to say, "Hey, I want to know why this file to write down here." We need to actually look through everywhere, explain, and understand how it's complex, right? Where this piece of data that was wrong come from? And so, yeah, which is difficult in a distributed environment where your infrastructure is so much a part of somebody else's systems, you don't have direct access to assistance. You'd only got the side effects of the system. >> Right, so talk to me in that distributed environment, Kevin, how does Lumigo help to improve that? Especially as we're talking about payments and billing and sensitive financial information. >> Right, so in a couple of ways, the nice part about Lumigo is I really don't have to do much in order for it to just do its thing, right? This comes back to that philosophy of zero ops, right? Zero effort. I don't want to be concentrating on how I build my tracing infrastructure, right? I just want it to work. I want it to work out of the box when something happens, I want it to have happened. So Lumigo, when I looked at it, when I was looking at the platforms, the integration's so straightforward, the cost integration being straightforward is kind of useless, if it doesn't actually give you the information you want. And we had a challenge initially, which was, we use a lot of EventBridge, and of course, nothing tries to EventBridge until we got, I mentioned this to Erez and Co, and said, "Hey guys, we really need to try to EventBridge, and a little while later, we were tracing through EventBridge, which was fantastic. And because I would say 70% of our transactions evolve something that goes through EventBridge, the other thing there. We're also from an architectural standpoint, we're also what's known as an event source system. So we derive the state of the information from the things that have occurred rather than a current snapshot of what something looks like, right? So rather than you being Lisa with a particular phone number and particular email address stored in a database as a record, you are, Lisa changed the phone number, Lisa changed her email address. And then we take that sequence of things and create a current view of Lisa. So that also helps us with ordering, right? And at those lower levels, we can do a lot of our security. We can do a lot of our encryption, we can say that this particular piece of information, for example, a social security number is encrypted and never is available as plain text. And you need the keys to be able to unlock that particular piece of information. So we can do a lot of that, a lower level infrastructure, but that does generate a lot of movement of information. >> Right. >> And if you can't trace that movement of information, you're in a hurting place. >> So Erez, we just got a great testimonial from Kevin on how Lumigo's really fundamental to their environment and what they're able to deliver to customers, and also Kevin talked about, it sounds like some of the collaboration that went on to help get that EventBridge. Talk to me, Erez, about the collaborative partnership that you have with Flex. >> Yeah, so I think that it's more of a, I would say a philosophy of customers, the users come first. So this is what we're really trying to about. We always try to make sure there's an open communication with all of our customers and for us customer is a key and user's a key, not even a customer. And this is why we try to accommodate the different requests, specifically on this event, this was actually a while after AWS released the service and due to the partnership that we have with AWS, we were able to get this supported relatively fast and first to market supporting EventBridge, and connecting the dots around it. So that's one of the things that we really, really focused on. >> Kevin, back to you, how do you quantify the ROI of what Lumigo is delivering to Flex? >> That's a really good question. And Erez, and I've talked about this a few times, because the simple fact is if I add up the numbers, it costs me more to trace than it does to execute. But if I look at the slightly bigger picture, I also don't have op stuff, right? And I also have an ability to look at things very quickly. The service cost is nothing compared to what I would need if I was running my own tracing through OpenTrace with my own database, monitor the staff to support those things. But the management of those things, the configuration of those things, the multiple touchpoints I'd need for those things, they're not the simple thing. So, if you look at a raw cost, you go, oh man, that part is actually more than my execution costs at least certainly in the early days, but when I look at the entire cost of what it takes to watch manage and trace a system, it's a really easy song, right? And a lot of these things don't pay off until something goes wrong. Now we're heavy users of EventBridge. EventBridge has had two incidents in USA in the last six months, right? And we were able to say through our traffic, that was going through EventBridge, that the slowdown was occurring in EventBridge. In fact, we were saying that before was alerted in the IDR VUS dashboards, to say, "Hey, EventBridge is having problems," like we watch all their alerts, but we were saying an hour before leading into Titus saying, "Hey, there's something going wrong here." Right? Because we were seeing delays in the system. So things like that give you an opportunity to adjust, right? You can't do it. You're not going to be able to get everything off of EventBridge for that period. But at least I can talk to the business and say, "Hey, we're having an impact here, and this is what's going on. We don't think it's our systems, we think it's actually something external. We can see the tries, we see it going in, we see it coming out, it's a 20 minute delay." >> There's a huge amount of value in that, sorry, Kevin, in that visibility alone, as you said, and even maybe even some cost avoidance is there, if you're seeing something going wrong, you maybe can pivot and adjust as needed. But without that visibility, you don't have that. There's a lot of potential loss. >> Yeah, and it's one of those things that doesn't pay for itself until it pays for itself, right? It's like insurance, you don't need insurance until you need insurance. These sort of things, people look at these things and go, "Ah, what am I getting it from day to day?" And day to day, I'll use Lumigo, right? When I'm developing now, Lumigo is part of my development process, in that, I use it to make sure the information is flowing in the way I expect it to, right? Which wasn't what I expected to be able to do with it, right? It wasn't even a plan or anything I intended to use it for, but day to day now, when I buy something off, one of the checks I go through when I'm debugging or when I'm looking at a problem, especially distributed problem is what went through Lumigo. What happened here, here and here, and why did that happen in response to this? So, these things are, again, it's that insurance thing, you don't need it until you need it, and when you need it, you're so glad you've got it. >> Right, exactly. >> Actually it's already said, I have a question because, yeah, I think that it's clear on that part. And how did this, if it change the developer work in Flex, do you feel different on that part? >> I think it's down to individual developers, how they use the different tools, just like individual developers use different tools. I tend to, and a couple of people that I work closely with tend to use these tools in this way, probably where the more advanced users of serverless in general inside the organization. So we were more aware of these weird little things that occur and justly double-checks you want to do. But I feel like when I don't have something like Lumigo in place, it's very hard for me to understand, did everything happen? I can write my acceptance tests, but I want to make sure that, testing is a really fun art, right? And it's picking my cabinets nice and easy, and you can run all these formulas to do things, it's just not right, and there's just too many, especially in distributed space, too many cases where things look odd, things look strange, you've got weird edge cases. We get new timeouts in Dynamo. We hit the 100,000 limit in fresh hall on Dynamo, right? In production, that was really interesting because it meant we needed to do some additional things. >> Lisa: Kevin, oh, go ahead. >> Go ahead, no, go ahead, Lisa. >> I was just going to ask you, I'd love to get your perspective. It sounds like, you look at other technologies, there's been some clear benefits and differentiators that you saw, which is why you chose Lumigo, but it also sounds like there were some things that surprised you. So in your opinion, what are some of the key differentiators of Lumigo versus its competitors? >> So I guess I've been a partner with Lumigo for like eight months now, right? Which is a long time in the history of Flex, right? 'Cause we're just out of two and a half years old. So, when I did the initial evaluation, I was looking for the things. I'm lazy, so I wanted something that I could just drop in and it would just work, right? And get the information I wanted to ask. I wanted something that was giving me information consistently. So I try to figure these things out and hit them with some load. I wanted it to have coverage of the assistance that we use. We use Dynamo a lot. We use Lambros a lot, and I want it not just cursory coverage, how it's just another one of the 20,000 things that they do, I wanted something that was dedicated to it. That gave me information that was useful for me. And really the specialist serverless providers were the obvious choice there. When you looked at the more general providers, the Datadogs and New Relics, I think if you're in an environment that has a lot of other different types of systems running on, then maybe the specificity that you'd lose is worthwhile, right? There's trade off you can make, but we're in a highly serverless environment, so one of the specificity. When I looked at the vendors, Lumigo was the one that worked best straight out of the box for me, it gave me the information I wanted. It gave me the experience I wanted, and to be frank, they've reached out really quickly and had a chat about what were my specific problems, what I was thinking. And all of those things add up, a proactive vendor, just doing the things you wanted to do, and what became and has become a lasting partnership, and I don't say partnership lightly 'cause we've worked with a number of other vendors, right? For different things. But Lumigo, I have turned to these guys, 'cause these guys know serverless, right? So I've turned to these guys when I've gone, "Look, I am not sure what the best approach here is." You have trusted me about it, this is vendor, right? >> Right, but it sounds like it's very synergistic, collaborative trusted relationship. And to your point, not using the term partner lightly, I think arises, probably couldn't have been a better testimonial for Lumigo, its capabilities, and what you guys are able to do. So I'll give you, Erez the last word, just give the audience a little bit of an overview of the AWS partnership. >> Sure, so AWS has been a very strategic partner for Lumigo, and that means that, I would say the most critical part is a product, is a technology. And we are design partners with the serverless team. And that means that we work with AWS to make sure that before new services are released, they get our feedback on whether we can integrate easily or not, and making sure that on the launch date, we are able to be a launch partner for a lot of their services. And this strong partnership with R&D team is what's allowing Lumigo to support new services out of the box like Kevin mentioned. >> Excellent, gentlemen, thank you so much for joining me today, talking about, not just about Lumigo, but getting this great perspective of it through the CTO lens with Kevin, we appreciate your insights, your time, and what a great testimonial. >> Thank you very much, thank you, Kevin. >> Thanks, Lisa, thanks Erez. >> You're most welcome. For Erez Berkner and Kevin O'Neill, I'm Lisa Martin, you're watching the AWS Startup Showcase for Q3. (gentle music)

>>Hi everyone. And welcome to data citizens. Thank you for making the time to join me and the over 5,000 data citizens like you that are looking to become United by data. My name is Jim Cushman. I serve as the chief product officer at Collibra. I have the benefit of sharing with you, the product, vision, and strategy of Culebra. There's several sections to this presentation, and I can't wait to share them with you. The first is a story of how we're taking a business user and making it possible for him or her data, use data and gain. And if it and insight from that data, without relying on anyone in the organization to write code or do the work for them next I'll share with you how Collibra will make it possible to manage metadata at scales, into the billions of assets. And again, load this into our software without writing any code third, I will demonstrate to you the integration we have already achieved with our newest product release it's data quality that's powered by machine learning. >>Right? Finally, you're going to hear about how Colibra has become the most universally available solution in the market. Now, we all know that data is a critical asset that can make or break an organization. Yet organizations struggle to capture the power of their data and many remain afraid of how their data could be misused and or abused. We also observe that the understanding of and access to data remains in the hands of just a small few, three out of every four companies continue to struggle to use data, to drive meaningful insights, all forward looking companies, looking for an advantage, a differentiator that will set them apart from their peers and competitors. What if you could improve your organization's productivity by just 5%, even a modest 5% productivity improvement compounded over a five-year period will make your organization 28% more productive. This will leave you with an overwhelming advantage over your competition and uniting your data. >>Litter employees with data is the key to your success. And dare I say, sorry to unlock this potential for increased productivity, huge competitive advantage organizations need to enable self-service access to data for everyday to literate knowledge worker. Our ultimate goal at Cleaver has always been to enable this self-service for our customers to empower every knowledge worker to access the data they need when they need it. But with the peace of mind that your data is governed insecure. Just to imagine if you had a single integrated solution that could deliver a seamless governed, no code user experience of delivering the right data to the right person at the right time, just as simply as ordering a pair of shoes online would be quite a magic trick and one that would place you and your organization on the fast track for success. Let me introduce you to our character here. >>Cliff cliff is that business analyst. He doesn't write code. He doesn't know Julian or R or sequel, but is data literate. When cliff has presented with data of high quality and can actually help find that data of high-quality cliff knows what to do with it. Well, we're going to expose cliff to our software and see how he can find the best data to solve his problem of the day, which is customer churn. Cliff is going to go out and find this information is going to bring it back to him. And he's going to analyze it in his favorite BI reporting tool. Tableau, of course, that could be Looker, could be power BI or any other of your favorites, but let's go ahead and get started and see how cliff can do this without any help from anyone in the organization. So cliff is going to log into Cleaver and being a business user. >>The first thing he's going to do is look for a business term. He looks for customer churn rate. Now, when he brings back a churn rate, it shows him the definition of churn rate and various other things that have been attributed to it such as data domains like product and customer in order. Now, cliff says, okay, customer is really important. So let me click on that and see what makes up customer definition. Cliff will scroll through a customer and find out the various data concepts attributes that make up the definition of customer and cliff knows that customer identifier is a really important aspect to this. It helps link all the data together. And so cliff is going to want to make sure that whatever source he brings actually has customer identifier in it. And that it's of high quality cliff is also interested in things such as email address and credit activity and credit card. >>But he's now going to say, okay, what data sets actually have customer as a data domain in, and by the way, why I'm doing it, what else has product and order information? That's again, relevant to the concept of customer churn. Now, as he goes on, he can actually filter down because there's a lot of different results that could potentially come back. And again, customer identifier was very important to cliff. So cliff, further filters on customer identifier any further does it on customer churn rate as well. This results in two different datasets that are available to cliff for selection, which one to use? Well, he's first presented with some data quality information you can see for customer analytics. It has a data quality score of 76. You can see for sales data enrichment dataset. It has a data quality score of 68. Something that he can see right at the front of the box of things that he's looking for, but let's dig in deeper because the contents really matter. >>So we see again the score of 76, but we actually have the chance to find out that this is something that's actually certified. And this is something that has a check mark. And so he knows someone he trusts is actually certified. This is a dataset. You'll see that there's 91 columns that make up this data set. And rather than sifting through all of that information, cliff is going to go ahead and say, well, okay, customer identifier is very important to me. Let me search through and see if I can find what it's data quality scores very quickly. He finds that using a fuzzy search and brings back and sees, wow, that's a really high data quality score of 98. Well, what's the alternative? Well, the data set is only has 68, but how about, uh, the customer identifier and quickly, he discovers that the data quality for that is only 70. >>So all things being equal, customer analytics is the better data set for what cliff needs to achieve. But now he wants to look and say, other people have used this, what have they had to say about it? And you can see there are various reviews for different reviews from peers of his, in the organization that have given it five stars. So this is encourages cliffs, a confidence that this is great data set to use. Now cliff wants to look a little bit more detailed before he finally commits to using this dataset. Cliff has the opportunity to look at it in the broader set. What are the things can I learn about customer analytics, such as what else is it related to? Who else uses it? Where did it come from? Where does it go and what actually happens to it? And so within our graph of information, we're able to show you a diagram. >>You can see the customer analytics actually comes from the CRM cloud system. And from there you can inherit some wonderful information. We know exactly what CRM cloud is about as an overall system. It's related to other logical models. And here you're actually seeing that it's related to a policy policy about PII or personally identifiable information. This gets cliff almost the immediate knowledge that there's going to be some customer information in this PII information that he's not going to be able to see given his user role in the organization. But cliff says, Hey, that's okay. I actually don't need to see somebody's name and social security number to do my work. I can actually work with other information in the data file. That'll actually help me understand why our customers churning in, what can I actually do about it. If we dig in deeper, we can see what is personally identifiable information that actually could cause issues. >>And as we scroll down and take a little bit of a focus on what we call or what you'll see here is customer phone, because we'll show that to you a little bit later, but these show the various information that once cliff actually has it fulfilled and delivered to him, he will see that it's actually massed and or redacted from his use. Now cliff might drive in deeper and see more information. And he says, you know what? Another piece that's important to me in my analysis is something called is churned. This is basically suggesting that has a customer actually churned. It's an important flag, of course, because that's the analysis that he's performing cliff sees that the score is a mere 65. That's not exactly a great data quality score, but cliff has, is kind of in a hurry. His bosses is, has come back and said, we need to have this information so we can take action. >>So he's not going to wait around to see if they can go through some long day to quality project before he pursues, but he is going to come up and use it. The speed of thinking. He's going to create a suggestion, an issue. He's going to submit this as a work queue item that actually informs others that are responsible for the quality of data. That there's an opportunity for improvement to this dataset that is highly reviewed, but it may be, it has room for improvement as cliff is actually typing in his explanation that he'll pass along. We can also see that the data quality is made up of multiple components, such as integrity, duplication, accuracy, consistency, and conformity. Um, we see that we can submit this, uh, issue and pass it through. And this will go to somebody else who can actually work on this. >>And we'll show that to you a little bit later, but back to cliff, cliff says, okay, I'd like to, I'd like to work with this dataset. So he adds it to his data basket. And just like if he's shopping online, cliff wants that kind of ability to just say, I want to just click once and be done with it. Now it is data and there's some sensitivity about it. And again, there's an owner of this data who you need to get permission from. So cliff is going to provide information to the owner to say, here's why I need this data. And how long do I need this data for starting on a certain date and ending on a certain date and ultimately, what purpose am I going to have with this data? Now, there are other things that cliff can choose to run. This one is how do you want this day to deliver to you? >>Now, you'll see down below, there are three options. One is borrow the other's lease and others by what does that mean? Well, borrow is this idea of, I don't want to have the data that's currently in this CRM, uh, cloud database moved somewhere. I don't want it to be persistent anywhere else. I just want to borrow it very short term to use in my Tablo report and then poof be gone. Cause I don't want to create any problems in my organization. Now you also see lease. Lease is a situation where you actually do need to take possession of the data, but only for a time box period of time, you don't need it for an indefinite amount of time. And ultimately buy is your ability to take possession of the data and have it in perpetuity. So we're going to go forward with our bar use case and cliff is going to submit this and all the fun starts there. >>So cliff has actually submitted the order and the owner, Joanna is actually going to receive the request for the order. Joanna, uh, opens up her task, UCS there's work to perform. It says, oh, okay, here's this there's work for me to perform. Now, Joanna has the ability to automate this using incorporated workflow that we have in Colibra. But for this situation, she's going to manually review that. Cliff wants to borrow a specific data set for a certain period of time. And he actually wants to be using in a Tablo context. So she reviews. It makes an approval and submits it this in turn, flips it back to cliff who says, okay, what obligations did I just take on in order to work for this data? And he reviews each of these data sharing agreements that you, as an organization would set up and say, what am I, uh, what are my restrictions for using this data site? >>As cliff accepts his notices, he now has triggered the process of what we would call fulfillment or a service broker. And in this situation we're doing a virtualization, uh, access, uh, for the borrow use case. Cliff suggests Tablo is his preferred BI and reporting tool. And you can see the various options that are available from power BI Looker size on ThoughtSpot. There are others that can be added over time. And from there, cliff now will be alerted the minute this data is available to them. So now we're running out and doing a distributed query to get the information and you see it returns back for raw view. Now what's really interesting is you'll see, the customer phone has a bunch of X's in it. If you remember that's PII. So it's actually being massed. So cliff can't actually see the raw data. Now cliff also wants to look at it in a Tablo report and can see the visualization layer, but you also see an incorporation of something we call Collibra on the go. >>Not only do we bring the data to the report, but then we tell you the reader, how to interpret the report. It could be that there's someone else who wants to use the very same report that cliff helped create, but they don't understand exactly all the things that cliff went through. So now they have the ability to get a full interpretation of what was this data that was used, where did it come from? And how do I actually interpret some of the fields that I see on this report? Really a clever combination of bringing the data to you and showing you how to use it. Cliff can also see this as a registered asset within a Colibra. So the next shopper comes through might actually, instead of shopping for the dataset might actually shop for the report itself. And the report is connected with the data set he used. >>So now they have a full bill of materials to run a customer Shern report and schedule it anytime they want. So now we've turned cliff actually into a creator of data assets, and this is where intelligent, it gets more intelligence and that's really what we call data intelligence. So let's go back through that magic trick that we just did with cliff. So cliff went into the software, not knowing if the source of data that he was looking for for customer product sales was even available to him. He went in very quickly and searched and found his dataset, use facts and facets to filter down to exactly what was available. Compare to contrast the options that were there actually made an observation that there actually wasn't enough data quality around a certain thing was important to him, created an idea, or basically a suggestion for somebody to follow up on was able to put that into his shopping basket checkout and have it delivered to his front door. >>I mean, that's a bit of a magic trick, right? So, uh, cliff was successful in finding data that he wanted and having it, deliver it to him. And then in his preferred model, he was able to look at it into Tableau. All right. So let's talk about how we're going to make this vision a reality. So our first section here is about performance and scale, but it's also about codeless database registration. How did we get all that stuff into the data catalog and available for, uh, cliff to find? So allow us to introduce you to what we call the asset life cycle and some of the largest organizations in the world. They might have upwards of a billion data assets. These are columns and tables, reports, API, APIs, algorithms, et cetera. These are very high volume and quite technical and far more information than a business user like cliff might want to be engaged with those very same really large organizations may have upwards of say, 20 to 25 million that are critical data sources and data assets, things that they do need to highly curate and make available. >>But through that as a bit of a distillation, a lifecycle of different things you might want to do along that. And so we're going to share with you how you can actually automatically register these sources, deal with these very large volumes at speed and at scale, and actually make it available with just a level of information you need to govern and protect, but also make it available for opportunistic use cases, such as the one we presented with cliff. So as you recall, when cliff was actually trying to look for his dataset, he identified that the is churned, uh, data at your was of low quality. So he passed this over to Eliza, who's a data steward and she actually receives this work queue in a collaborative fashion. And she has to review, what is the request? If you recall, this was the request to improve the data quality for his churn. >>Now she needs to familiarize herself with what cliff was observing when he was doing his shopping experience. So she digs in and wants to look at the quality that he was observing and sure enough, as she goes down and it looks at his churn, she sees that it was a low 65% and now understands exactly what cliff was referring to. She says, aha, okay. I need to get help. I need to decide whether I have a data quality project to fix the data, or should I see if there's another data set in the organization that has better, uh, data for this. And so she creates a queue that can go over to one of her colleagues who really focuses on data quality. She submits this request and it goes over to, uh, her colleague, John who's really familiar with data quality. So John actually receives the request from Eliza and you'll see a task showing up in his queue. >>He opens up the request and finds out that Eliza's asking if there's another source out there that actually has good is churned, uh, data available. Now he actually knows quite a bit about the quality of information sturdiness. So he goes into the data quality console and does a quick look for a dataset that he's familiar with called customer product sales. He quickly scrolls down and finds out the one that's actually been published. That's the one he was looking for and he opens it up to find out more information. What data sets are, what columns are actually in there. And he goes down to find his churned is in fact, one of the attributes in there. It actually does have active rules that are associated with it to manage the quality. And so he says, well, let's look in more detail and find out what is the quality of this dataset? >>Oh, it's 86. This is a dramatic improvement over what we've seen before. So we can see again, it's trended quite nicely over time each day, it hasn't actually degraded in performance. So we actually responds back to realize and say, this data set, uh, is actually the data set that you want to bring in. It really will improve. And you'll see that he refers to the refined database within the CRM cloud solution. Once he actually submits this, it goes back to Eliza and she's able to continue her work. Now when Eliza actually brings this back open, she's able to very quickly go into the database registration process for her. She very quickly goes into the CRM cloud, selects the community, to which she wants to register this, uh, data set into the schemas community. And the CRM cloud is the system that she wants to load it in. >>And the refined is the database that John told her that she should bring in. After a quick description, she's able to click register. And this triggers that automatic codeless process of going out to the dataset and bringing back its metadata. Now metadata is great, but it's not the end all be all. There's a lot of other values that she really cares about as she's actually registering this dataset and synchronizing the metadata she's also then asked, would you like to bring in quality information? And so she'll go out and say, yes, of course, I want to enable the quality information from CRM refined. I also want to bring back lineage information to associate with this metadata. And I also want to select profiling and classification information. Now when she actually selects it, she can also say, how often do you want to synchronize this? This is a daily, weekly, monthly kind of update. >>That's part of the change data capture process. Again, all automated without the require of actually writing code. So she's actually run this process. Now, after this loads in, she can then open up this new registered, uh, dataset and actually look and see if it actually has achieved the problem that cliff set her out on, which was improved data quality. So looking into the data quality for the is churn capability shows her that she has fantastic quality. It's at a hundred, it's exactly what she was looking for. So she can with confidence actually, uh, suggest that it's done, but she did notice something and something that she wants to tell John, which is there's a couple of data quality checks that seem to be missing from this dataset. So again, in a collaborative fashion, she can pass that information, uh, for validity and completeness to say, you know what, check for NOLs and MPS and send that back. >>So she submits this onto John to work on. And John now has a work queue in his task force, but remember she's been working in this task forklift and because she actually has actually added a much better source for his churn information, she's going to update that test that was sent to her to notify cliff that the work has actually been done and that she actually has a really good data set in there. In fact, if you recall, it was 100% in terms of its data quality. So this will really make life a lot easier for cliff. Once he receives that data and processes, the churn report analysis next time. So let's talk about these audacious performance goals that we have in mind. Now today, we actually have really strong performance and amazing usability. Our customers continue to tell us how great our usability is, but they keep asking for more well, we've decided to present to you. >>Something you can start to bank on. This is the performance you can expect from us on the highly curated assets that are available for the business users, as well as the technical and lineage assets that are more available for the developer uses and for things that are more warehoused based, you'll see in Q1, uh, our Q2 of this year, we're making available 5 million curated assets. Now you might be out there saying, Hey, I'm already using the software and I've got over 20 million already. That's fair. We do. We have customers that are actually well over 20 million in terms of assets they're managing, but we wanted to present this to you with zero conditions, no limitations we wouldn't talk about, well, it depends, et cetera. This is without any conditions. That's what we can offer you without fail. And yes, it can go higher and higher. We're also talking about the speed with which you can ingest the data right now, we're ingesting somewhere around 50,000 to a hundred thousand records per and of course, yes, you've probably seen it go quite a bit faster, but we are assuring you that that's the case, but what's really impressive is right now, we can also, uh, help you manage 250 million technical assets and we can load it at a speed of 25 million for our, and you can see how over the next 18 months about every two quarters, we show you dramatic improvements, more than doubling of these. >>For most of them leading up to the end of 2022, we're actually handling over a billion technical lineage assets and we're loading at a hundred million per hour. That sets the mark for the industry. Earlier this year, we announced a recent acquisition Al DQ. LDQ brought to us machine learning based data quality. We're now able to introduce to you Collibra data quality, the first integrated approach to Al DQ and Culebra. We've got a demo to follow. I'm really excited to share it with you. Let's get started. So Eliza submitted a task for John to work on, remember to add checks for no and for empty. So John picks up this task very quickly and looks and sees what's what's the request. And from there says, ah, yes, we do have a quality check issue when we look at these churns. So he jumps over to the data quality console and says, I need to create a new data quality test. >>So cliff is able to go in, uh, to the solution and, uh, set up quick rules, automated rules. Uh, he could inherit rules from other things, but it starts with first identifying what is the data source that he needs to connect to, to perform this. And so he chooses the CRM refined data set that was most recently, uh, registered by Lysa. You'll see the same score of 86 was the quality score for the dataset. And you'll also see, there are four rules that are associated underneath this. Now there are various checks that, uh, that John can establish on this, but remember, this is a fairly easy request that he receives from Eliza. So he's going to go in and choose the actual field, uh, is churned. Uh, and from there identify quick rules of, uh, an empty check and that quickly sets up the rules for him. >>And also the null check equally fast. This one's established and analyzes all the data in there. And this sets up the baseline of data quality, uh, for this. Now this data, once it's captured then is periodically brought back to the catalog. So it's available to not only Eliza, but also to cliff next time he, uh, where to shop in the environment. As we look through the rules that were created through that very simple user experience, you can see the one for is empty and is no that we're set up. Now, these are various, uh, styles that can be set up either manually, or you can set them up through machine learning again, or you can inherit them. But the key is to track these, uh, rule creation in the metrics that are generated from these rules so that it can be brought back to the catalog and then used in meaningful context, by someone who's shopping and the confidence that this has neither empty nor no fields, at least most of them don't well now give a confidence as you go forward. >>And as you can see, those checks have now been entered in and you can see that it's a hundred percent quality score for the Knoll check. So with confidence now, John can actually respond back to Eliza and say, I've actually inserted them they're up and running. And, uh, you're in good status. So that was pretty amazing integration, right? And four months after our acquisition, we've already brought that level of integration between, uh, Colibra, uh, data intelligence, cloud, and data quality. Now it doesn't stop there. We have really impressive and high site set early next year. We're getting introduced a fully immersive experience where customers can work within Culebra and actually bring the data quality information all the way in as well as start to manipulate the rules and generate the machine learning rules. On top of it, all of that will be a deeply immersive experience. >>We also have something really clever coming, which we call continuous data profiling, where we bring the power of data quality all the way into the database. So it's continuously running and always making that data available for you. Now, I'd also like to share with you one of the reasons why we are the most universally available software solutions in data intelligence. We've already announced that we're available on AWS and Google cloud prior, but today we can announce to you in Q3, we're going to be, um, available on Microsoft Azure as well. Now it's not just these three cloud providers that were available on we've also become available on each of their marketplaces. So if you are buying our software, you can actually go out and achieve that same purchase from their marketplace and achieve your financial objectives as well. We're very excited about this. These are very important partners for, uh, for our, for us. >>Now, I'd also like to introduce you our system integrators, without them. There's no way we could actually achieve our objectives of growing so rapidly and dealing with the demand that you customers have had Accenture, Deloitte emphasis, and even others have been instrumental in making sure that we can serve your needs when you need them. Uh, and so it's been a big part of our growth and will be a continued part of our growth as well. And finally, I'd like to actually introduce you to our product showcases where we can go into absolute detail on many of the topics I talked about today, such as data governance with Arco or data privacy with Sergio or data quality with Brian and finally catalog with Peter. Again, I'd like to thank you all for joining us. Uh, and we really look forward to hearing your feedback. Thank you..