(mid-tempo electronic music) >> Hi, I'm Peter Burris. And once again, this is another Wikibon research quick take. I'm here with David Floyer. David, Amazon did something interesting this week. What is it? What's the impact? >> Amazon, and I mean by that, Amazon, not AWS, have put into place, something following on from their data warehouse automation. They have now a store which is completely automated. You walk in, you pick something off the shelf, and you walk out. They've done all of the automation, lots and lots of cameras everywhere, lots of sophisticated work. It's taken them more than four years of hard work on AI, to get this done. The implication is if, I think this is both exciting and people who are not doing anything, they must be really fearful about this. This is an exciting time, and something that other people must get on with, which is automation of the business process that are important to them. >> Retail or not, one of the things, very quickly, that we've observed, is the process of automating employee activities is slow. The process of automating, or providing automation for customer activities is even slower. We're really talking about Amazon introducing technologies to provide the Amazon brand to the customer in an automated way. Big deal. >> Absolutely, big, big deal. >> All right, this has been a Wikibon quick take research with David Floyer. Thanks, David. (upbeat electronic music)

(upbeat music beginning) >> From the Cube Studios in Palo Alto and Boston, bringing you data-driven insights from the Cube and ETR, this is "Breaking Analysis" with Dave Vellante. >> Making predictions about the future of enterprise tech is more challenging if you strive to lay down forecasts that are measurable. In other words, if you make a prediction, you should be able to look back a year later and say, with some degree of certainty, whether the prediction came true or not, with evidence to back that up. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this breaking analysis, we aim to do just that, with predictions about the macro IT spending environment, cost optimization, security, lots to talk about there, generative AI, cloud, and of course supercloud, blockchain adoption, data platforms, including commentary on Databricks, snowflake, and other key players, automation, events, and we may even have some bonus predictions around quantum computing, and perhaps some other areas. To make all this happen, we welcome back, for the third year in a row, my colleague and friend Eric Bradley from ETR. Eric, thanks for all you do for the community, and thanks for being part of this program. Again. >> I wouldn't miss it for the world. I always enjoy this one. Dave, good to see you. >> Yeah, so let me bring up this next slide and show you, actually come back to me if you would. I got to show the audience this. These are the inbounds that we got from PR firms starting in October around predictions. They know we do prediction posts. And so they'll send literally thousands and thousands of predictions from hundreds of experts in the industry, technologists, consultants, et cetera. And if you bring up the slide I can show you sort of the pattern that developed here. 40% of these thousands of predictions were from cyber. You had AI and data. If you combine those, it's still not close to cyber. Cost optimization was a big thing. Of course, cloud, some on DevOps, and software. Digital... Digital transformation got, you know, some lip service and SaaS. And then there was other, it's kind of around 2%. So quite remarkable, when you think about the focus on cyber, Eric. >> Yeah, there's two reasons why I think it makes sense, though. One, the cybersecurity companies have a lot of cash, so therefore the PR firms might be working a little bit harder for them than some of their other clients. (laughs) And then secondly, as you know, for multiple years now, when we do our macro survey, we ask, "What's your number one spending priority?" And again, it's security. It just isn't going anywhere. It just stays at the top. So I'm actually not that surprised by that little pie chart there, but I was shocked that SaaS was only 5%. You know, going back 10 years ago, that would've been the only thing anyone was talking about. >> Yeah. So true. All right, let's get into it. First prediction, we always start with kind of tech spending. Number one is tech spending increases between four and 5%. ETR has currently got it at 4.6% coming into 2023. This has been a consistently downward trend all year. We started, you know, much, much higher as we've been reporting. Bottom line is the fed is still in control. They're going to ease up on tightening, is the expectation, they're going to shoot for a soft landing. But you know, my feeling is this slingshot economy is going to continue, and it's going to continue to confound, whether it's supply chains or spending. The, the interesting thing about the ETR data, Eric, and I want you to comment on this, the largest companies are the most aggressive to cut. They're laying off, smaller firms are spending faster. They're actually growing at a much larger, faster rate as are companies in EMEA. And that's a surprise. That's outpacing the US and APAC. Chime in on this, Eric. >> Yeah, I was surprised on all of that. First on the higher level spending, we are definitely seeing it coming down, but the interesting thing here is headlines are making it worse. The huge research shop recently said 0% growth. We're coming in at 4.6%. And just so everyone knows, this is not us guessing, we asked 1,525 IT decision-makers what their budget growth will be, and they came in at 4.6%. Now there's a huge disparity, as you mentioned. The Fortune 500, global 2000, barely at 2% growth, but small, it's at 7%. So we're at a situation right now where the smaller companies are still playing a little bit of catch up on digital transformation, and they're spending money. The largest companies that have the most to lose from a recession are being more trepidatious, obviously. So they're playing a "Wait and see." And I hope we don't talk ourselves into a recession. Certainly the headlines and some of their research shops are helping it along. But another interesting comment here is, you know, energy and utilities used to be called an orphan and widow stock group, right? They are spending more than anyone, more than financials insurance, more than retail consumer. So right now it's being driven by mid, small, and energy and utilities. They're all spending like gangbusters, like nothing's happening. And it's the rest of everyone else that's being very cautious. >> Yeah, so very unpredictable right now. All right, let's go to number two. Cost optimization remains a major theme in 2023. We've been reporting on this. You've, we've shown a chart here. What's the primary method that your organization plans to use? You asked this question of those individuals that cited that they were going to reduce their spend and- >> Mhm. >> consolidating redundant vendors, you know, still leads the way, you know, far behind, cloud optimization is second, but it, but cloud continues to outpace legacy on-prem spending, no doubt. Somebody, it was, the guy's name was Alexander Feiglstorfer from Storyblok, sent in a prediction, said "All in one becomes extinct." Now, generally I would say I disagree with that because, you know, as we know over the years, suites tend to win out over, you know, individual, you know, point products. But I think what's going to happen is all in one is going to remain the norm for these larger companies that are cutting back. They want to consolidate redundant vendors, and the smaller companies are going to stick with that best of breed and be more aggressive and try to compete more effectively. What's your take on that? >> Yeah, I'm seeing much more consolidation in vendors, but also consolidation in functionality. We're seeing people building out new functionality, whether it's, we're going to talk about this later, so I don't want to steal too much of our thunder right now, but data and security also, we're seeing a functionality creep. So I think there's further consolidation happening here. I think niche solutions are going to be less likely, and platform solutions are going to be more likely in a spending environment where you want to reduce your vendors. You want to have one bill to pay, not 10. Another thing on this slide, real quick if I can before I move on, is we had a bunch of people write in and some of the answer options that aren't on this graph but did get cited a lot, unfortunately, is the obvious reduction in staff, hiring freezes, and delaying hardware, were three of the top write-ins. And another one was offshore outsourcing. So in addition to what we're seeing here, there were a lot of write-in options, and I just thought it would be important to state that, but essentially the cost optimization is by and far the highest one, and it's growing. So it's actually increased in our citations over the last year. >> And yeah, specifically consolidating redundant vendors. And so I actually thank you for bringing that other up, 'cause I had asked you, Eric, is there any evidence that repatriation is going on and we don't see it in the numbers, we don't see it even in the other, there was, I think very little or no mention of cloud repatriation, even though it might be happening in this in a smattering. >> Not a single mention, not one single mention. I went through it for you. Yep. Not one write-in. >> All right, let's move on. Number three, security leads M&A in 2023. Now you might say, "Oh, well that's a layup," but let me set this up Eric, because I didn't really do a great job with the slide. I hid the, what you've done, because you basically took, this is from the emerging technology survey with 1,181 responses from November. And what we did is we took Palo Alto and looked at the overlap in Palo Alto Networks accounts with these vendors that were showing on this chart. And Eric, I'm going to ask you to explain why we put a circle around OneTrust, but let me just set it up, and then have you comment on the slide and take, give us more detail. We're seeing private company valuations are off, you know, 10 to 40%. We saw a sneak, do a down round, but pretty good actually only down 12%. We've seen much higher down rounds. Palo Alto Networks we think is going to get busy. Again, they're an inquisitive company, they've been sort of quiet lately, and we think CrowdStrike, Cisco, Microsoft, Zscaler, we're predicting all of those will make some acquisitions and we're thinking that the targets are somewhere in this mess of security taxonomy. Other thing we're predicting AI meets cyber big time in 2023, we're going to probably going to see some acquisitions of those companies that are leaning into AI. We've seen some of that with Palo Alto. And then, you know, your comment to me, Eric, was "The RSA conference is going to be insane, hopping mad, "crazy this April," (Eric laughing) but give us your take on this data, and why the red circle around OneTrust? Take us back to that slide if you would, Alex. >> Sure. There's a few things here. First, let me explain what we're looking at. So because we separate the public companies and the private companies into two separate surveys, this allows us the ability to cross-reference that data. So what we're doing here is in our public survey, the tesis, everyone who cited some spending with Palo Alto, meaning they're a Palo Alto customer, we then cross-reference that with the private tech companies. Who also are they spending with? So what you're seeing here is an overlap. These companies that we have circled are doing the best in Palo Alto's accounts. Now, Palo Alto went and bought Twistlock a few years ago, which this data slide predicted, to be quite honest. And so I don't know if they necessarily are going to go after Snyk. Snyk, sorry. They already have something in that space. What they do need, however, is more on the authentication space. So I'm looking at OneTrust, with a 45% overlap in their overall net sentiment. That is a company that's already existing in their accounts and could be very synergistic to them. BeyondTrust as well, authentication identity. This is something that Palo needs to do to move more down that zero trust path. Now why did I pick Palo first? Because usually they're very inquisitive. They've been a little quiet lately. Secondly, if you look at the backdrop in the markets, the IPO freeze isn't going to last forever. Sooner or later, the IPO markets are going to open up, and some of these private companies are going to tap into public equity. In the meantime, however, cash funding on the private side is drying up. If they need another round, they're not going to get it, and they're certainly not going to get it at the valuations they were getting. So we're seeing valuations maybe come down where they're a touch more attractive, and Palo knows this isn't going to last forever. Cisco knows that, CrowdStrike, Zscaler, all these companies that are trying to make a push to become that vendor that you're consolidating in, around, they have a chance now, they have a window where they need to go make some acquisitions. And that's why I believe leading up to RSA, we're going to see some movement. I think it's going to pretty, a really exciting time in security right now. >> Awesome. Thank you. Great explanation. All right, let's go on the next one. Number four is, it relates to security. Let's stay there. Zero trust moves from hype to reality in 2023. Now again, you might say, "Oh yeah, that's a layup." A lot of these inbounds that we got are very, you know, kind of self-serving, but we always try to put some meat in the bone. So first thing we do is we pull out some commentary from, Eric, your roundtable, your insights roundtable. And we have a CISO from a global hospitality firm says, "For me that's the highest priority." He's talking about zero trust because it's the best ROI, it's the most forward-looking, and it enables a lot of the business transformation activities that we want to do. CISOs tell me that they actually can drive forward transformation projects that have zero trust, and because they can accelerate them, because they don't have to go through the hurdle of, you know, getting, making sure that it's secure. Second comment, zero trust closes that last mile where once you're authenticated, they open up the resource to you in a zero trust way. That's a CISO of a, and a managing director of a cyber risk services enterprise. Your thoughts on this? >> I can be here all day, so I'm going to try to be quick on this one. This is not a fluff piece on this one. There's a couple of other reasons this is happening. One, the board finally gets it. Zero trust at first was just a marketing hype term. Now the board understands it, and that's why CISOs are able to push through it. And what they finally did was redefine what it means. Zero trust simply means moving away from hardware security, moving towards software-defined security, with authentication as its base. The board finally gets that, and now they understand that this is necessary and it's being moved forward. The other reason it's happening now is hybrid work is here to stay. We weren't really sure at first, large companies were still trying to push people back to the office, and it's going to happen. The pendulum will swing back, but hybrid work's not going anywhere. By basically on our own data, we're seeing that 69% of companies expect remote and hybrid to be permanent, with only 30% permanent in office. Zero trust works for a hybrid environment. So all of that is the reason why this is happening right now. And going back to our previous prediction, this is why we're picking Palo, this is why we're picking Zscaler to make these acquisitions. Palo Alto needs to be better on the authentication side, and so does Zscaler. They're both fantastic on zero trust network access, but they need the authentication software defined aspect, and that's why we think this is going to happen. One last thing, in that CISO round table, I also had somebody say, "Listen, Zscaler is incredible. "They're doing incredibly well pervading the enterprise, "but their pricing's getting a little high," and they actually think Palo Alto is well-suited to start taking some of that share, if Palo can make one move. >> Yeah, Palo Alto's consolidation story is very strong. Here's my question and challenge. Do you and me, so I'm always hardcore about, okay, you've got to have evidence. I want to look back at these things a year from now and say, "Did we get it right? Yes or no?" If we got it wrong, we'll tell you we got it wrong. So how are we going to measure this? I'd say a couple things, and you can chime in. One is just the number of vendors talking about it. That's, but the marketing always leads the reality. So the second part of that is we got to get evidence from the buying community. Can you help us with that? >> (laughs) Luckily, that's what I do. I have a data company that asks thousands of IT decision-makers what they're adopting and what they're increasing spend on, as well as what they're decreasing spend on and what they're replacing. So I have snapshots in time over the last 11 years where I can go ahead and compare and contrast whether this adoption is happening or not. So come back to me in 12 months and I'll let you know. >> Now, you know, I will. Okay, let's bring up the next one. Number five, generative AI hits where the Metaverse missed. Of course everybody's talking about ChatGPT, we just wrote last week in a breaking analysis with John Furrier and Sarjeet Joha our take on that. We think 2023 does mark a pivot point as natural language processing really infiltrates enterprise tech just as Amazon turned the data center into an API. We think going forward, you're going to be interacting with technology through natural language, through English commands or other, you know, foreign language commands, and investors are lining up, all the VCs are getting excited about creating something competitive to ChatGPT, according to (indistinct) a hundred million dollars gets you a seat at the table, gets you into the game. (laughing) That's before you have to start doing promotion. But he thinks that's what it takes to actually create a clone or something equivalent. We've seen stuff from, you know, the head of Facebook's, you know, AI saying, "Oh, it's really not that sophisticated, ChatGPT, "it's kind of like IBM Watson, it's great engineering, "but you know, we've got more advanced technology." We know Google's working on some really interesting stuff. But here's the thing. ETR just launched this survey for the February survey. It's in the field now. We circle open AI in this category. They weren't even in the survey, Eric, last quarter. So 52% of the ETR survey respondents indicated a positive sentiment toward open AI. I added up all the sort of different bars, we could double click on that. And then I got this inbound from Scott Stevenson of Deep Graham. He said "AI is recession-proof." I don't know if that's the case, but it's a good quote. So bring this back up and take us through this. Explain this chart for us, if you would. >> First of all, I like Scott's quote better than the Facebook one. I think that's some sour grapes. Meta just spent an insane amount of money on the Metaverse and that's a dud. Microsoft just spent money on open AI and it is hot, undoubtedly hot. We've only been in the field with our current ETS survey for a week. So my caveat is it's preliminary data, but I don't care if it's preliminary data. (laughing) We're getting a sneak peek here at what is the number one net sentiment and mindshare leader in the entire machine-learning AI sector within a week. It's beating Data- >> 600. 600 in. >> It's beating Databricks. And we all know Databricks is a huge established enterprise company, not only in machine-learning AI, but it's in the top 10 in the entire survey. We have over 400 vendors in this survey. It's number eight overall, already. In a week. This is not hype. This is real. And I could go on the NLP stuff for a while. Not only here are we seeing it in open AI and machine-learning and AI, but we're seeing NLP in security. It's huge in email security. It's completely transforming that area. It's one of the reasons I thought Palo might take Abnormal out. They're doing such a great job with NLP in this email side, and also in the data prep tools. NLP is going to take out data prep tools. If we have time, I'll discuss that later. But yeah, this is, to me this is a no-brainer, and we're already seeing it in the data. >> Yeah, John Furrier called, you know, the ChatGPT introduction. He said it reminded him of the Netscape moment, when we all first saw Netscape Navigator and went, "Wow, it really could be transformative." All right, number six, the cloud expands to supercloud as edge computing accelerates and CloudFlare is a big winner in 2023. We've reported obviously on cloud, multi-cloud, supercloud and CloudFlare, basically saying what multi-cloud should have been. We pulled this quote from Atif Kahn, who is the founder and CTO of Alkira, thanks, one of the inbounds, thank you. "In 2023, highly distributed IT environments "will become more the norm "as organizations increasingly deploy hybrid cloud, "multi-cloud and edge settings..." Eric, from one of your round tables, "If my sources from edge computing are coming "from the cloud, that means I have my workloads "running in the cloud. "There is no one better than CloudFlare," That's a senior director of IT architecture at a huge financial firm. And then your analysis shows CloudFlare really growing in pervasion, that sort of market presence in the dataset, dramatically, to near 20%, leading, I think you had told me that they're even ahead of Google Cloud in terms of momentum right now. >> That was probably the biggest shock to me in our January 2023 tesis, which covers the public companies in the cloud computing sector. CloudFlare has now overtaken GCP in overall spending, and I was shocked by that. It's already extremely pervasive in networking, of course, for the edge networking side, and also in security. This is the number one leader in SaaSi, web access firewall, DDoS, bot protection, by your definition of supercloud, which we just did a couple of weeks ago, and I really enjoyed that by the way Dave, I think CloudFlare is the one that fits your definition best, because it's bringing all of these aspects together, and most importantly, it's cloud agnostic. It does not need to rely on Azure or AWS to do this. It has its own cloud. So I just think it's, when we look at your definition of supercloud, CloudFlare is the poster child. >> You know, what's interesting about that too, is a lot of people are poo-pooing CloudFlare, "Ah, it's, you know, really kind of not that sophisticated." "You don't have as many tools," but to your point, you're can have those tools in the cloud, Cloudflare's doing serverless on steroids, trying to keep things really simple, doing a phenomenal job at, you know, various locations around the world. And they're definitely one to watch. Somebody put them on my radar (laughing) a while ago and said, "Dave, you got to do a breaking analysis on CloudFlare." And so I want to thank that person. I can't really name them, 'cause they work inside of a giant hyperscaler. But- (Eric laughing) (Dave chuckling) >> Real quickly, if I can from a competitive perspective too, who else is there? They've already taken share from Akamai, and Fastly is their really only other direct comp, and they're not there. And these guys are in poll position and they're the only game in town right now. I just, I don't see it slowing down. >> I thought one of your comments from your roundtable I was reading, one of the folks said, you know, CloudFlare, if my workloads are in the cloud, they are, you know, dominant, they said not as strong with on-prem. And so Akamai is doing better there. I'm like, "Okay, where would you want to be?" (laughing) >> Yeah, which one of those two would you rather be? >> Right? Anyway, all right, let's move on. Number seven, blockchain continues to look for a home in the enterprise, but devs will slowly begin to adopt in 2023. You know, blockchains have got a lot of buzz, obviously crypto is, you know, the killer app for blockchain. Senior IT architect in financial services from your, one of your insight roundtables said quote, "For enterprises to adopt a new technology, "there have to be proven turnkey solutions. "My experience in talking with my peers are, "blockchain is still an open-source component "where you have to build around it." Now I want to thank Ravi Mayuram, who's the CTO of Couchbase sent in, you know, one of the predictions, he said, "DevOps will adopt blockchain, specifically Ethereum." And he referenced actually in his email to me, Solidity, which is the programming language for Ethereum, "will be in every DevOps pro's playbook, "mirroring the boom in machine-learning. "Newer programming languages like Solidity "will enter the toolkits of devs." His point there, you know, Solidity for those of you don't know, you know, Bitcoin is not programmable. Solidity, you know, came out and that was their whole shtick, and they've been improving that, and so forth. But it, Eric, it's true, it really hasn't found its home despite, you know, the potential for smart contracts. IBM's pushing it, VMware has had announcements, and others, really hasn't found its way in the enterprise yet. >> Yeah, and I got to be honest, I don't think it's going to, either. So when we did our top trends series, this was basically chosen as an anti-prediction, I would guess, that it just continues to not gain hold. And the reason why was that first comment, right? It's very much a niche solution that requires a ton of custom work around it. You can't just plug and play it. And at the end of the day, let's be very real what this technology is, it's a database ledger, and we already have database ledgers in the enterprise. So why is this a priority to move to a different database ledger? It's going to be very niche cases. I like the CTO comment from Couchbase about it being adopted by DevOps. I agree with that, but it has to be a DevOps in a very specific use case, and a very sophisticated use case in financial services, most likely. And that's not across the entire enterprise. So I just think it's still going to struggle to get its foothold for a little bit longer, if ever. >> Great, thanks. Okay, let's move on. Number eight, AWS Databricks, Google Snowflake lead the data charge with Microsoft. Keeping it simple. So let's unpack this a little bit. This is the shared accounts peer position for, I pulled data platforms in for analytics, machine-learning and AI and database. So I could grab all these accounts or these vendors and see how they compare in those three sectors. Analytics, machine-learning and database. Snowflake and Databricks, you know, they're on a crash course, as you and I have talked about. They're battling to be the single source of truth in analytics. They're, there's going to be a big focus. They're already started. It's going to be accelerated in 2023 on open formats. Iceberg, Python, you know, they're all the rage. We heard about Iceberg at Snowflake Summit, last summer or last June. Not a lot of people had heard of it, but of course the Databricks crowd, who knows it well. A lot of other open source tooling. There's a company called DBT Labs, which you're going to talk about in a minute. George Gilbert put them on our radar. We just had Tristan Handy, the CEO of DBT labs, on at supercloud last week. They are a new disruptor in data that's, they're essentially making, they're API-ifying, if you will, KPIs inside the data warehouse and dramatically simplifying that whole data pipeline. So really, you know, the ETL guys should be shaking in their boots with them. Coming back to the slide. Google really remains focused on BigQuery adoption. Customers have complained to me that they would like to use Snowflake with Google's AI tools, but they're being forced to go to BigQuery. I got to ask Google about that. AWS continues to stitch together its bespoke data stores, that's gone down that "Right tool for the right job" path. David Foyer two years ago said, "AWS absolutely is going to have to solve that problem." We saw them start to do it in, at Reinvent, bringing together NoETL between Aurora and Redshift, and really trying to simplify those worlds. There's going to be more of that. And then Microsoft, they're just making it cheap and easy to use their stuff, you know, despite some of the complaints that we hear in the community, you know, about things like Cosmos, but Eric, your take? >> Yeah, my concern here is that Snowflake and Databricks are fighting each other, and it's allowing AWS and Microsoft to kind of catch up against them, and I don't know if that's the right move for either of those two companies individually, Azure and AWS are building out functionality. Are they as good? No they're not. The other thing to remember too is that AWS and Azure get paid anyway, because both Databricks and Snowflake run on top of 'em. So (laughing) they're basically collecting their toll, while these two fight it out with each other, and they build out functionality. I think they need to stop focusing on each other, a little bit, and think about the overall strategy. Now for Databricks, we know they came out first as a machine-learning AI tool. They were known better for that spot, and now they're really trying to play catch-up on that data storage compute spot, and inversely for Snowflake, they were killing it with the compute separation from storage, and now they're trying to get into the MLAI spot. I actually wouldn't be surprised to see them make some sort of acquisition. Frank Slootman has been a little bit quiet, in my opinion there. The other thing to mention is your comment about DBT Labs. If we look at our emerging technology survey, last survey when this came out, DBT labs, number one leader in that data integration space, I'm going to just pull it up real quickly. It looks like they had a 33% overall net sentiment to lead data analytics integration. So they are clearly growing, it's fourth straight survey consecutively that they've grown. The other name we're seeing there a little bit is Cribl, but DBT labs is by far the number one player in this space. >> All right. Okay, cool. Moving on, let's go to number nine. With Automation mixer resurgence in 2023, we're showing again data. The x axis is overlap or presence in the dataset, and the vertical axis is shared net score. Net score is a measure of spending momentum. As always, you've seen UI path and Microsoft Power Automate up until the right, that red line, that 40% line is generally considered elevated. UI path is really separating, creating some distance from Automation Anywhere, they, you know, previous quarters they were much closer. Microsoft Power Automate came on the scene in a big way, they loom large with this "Good enough" approach. I will say this, I, somebody sent me a results of a (indistinct) survey, which showed UiPath actually had more mentions than Power Automate, which was surprising, but I think that's not been the case in the ETR data set. We're definitely seeing a shift from back office to front soft office kind of workloads. Having said that, software testing is emerging as a mainstream use case, we're seeing ML and AI become embedded in end-to-end automations, and low-code is serving the line of business. And so this, we think, is going to increasingly have appeal to organizations in the coming year, who want to automate as much as possible and not necessarily, we've seen a lot of layoffs in tech, and people... You're going to have to fill the gaps with automation. That's a trend that's going to continue. >> Yep, agreed. At first that comment about Microsoft Power Automate having less citations than UiPath, that's shocking to me. I'm looking at my chart right here where Microsoft Power Automate was cited by over 60% of our entire survey takers, and UiPath at around 38%. Now don't get me wrong, 38% pervasion's fantastic, but you know you're not going to beat an entrenched Microsoft. So I don't really know where that comment came from. So UiPath, looking at it alone, it's doing incredibly well. It had a huge rebound in its net score this last survey. It had dropped going through the back half of 2022, but we saw a big spike in the last one. So it's got a net score of over 55%. A lot of people citing adoption and increasing. So that's really what you want to see for a name like this. The problem is that just Microsoft is doing its playbook. At the end of the day, I'm going to do a POC, why am I going to pay more for UiPath, or even take on another separate bill, when we know everyone's consolidating vendors, if my license already includes Microsoft Power Automate? It might not be perfect, it might not be as good, but what I'm hearing all the time is it's good enough, and I really don't want another invoice. >> Right. So how does UiPath, you know, and Automation Anywhere, how do they compete with that? Well, the way they compete with it is they got to have a better product. They got a product that's 10 times better. You know, they- >> Right. >> they're not going to compete based on where the lowest cost, Microsoft's got that locked up, or where the easiest to, you know, Microsoft basically give it away for free, and that's their playbook. So that's, you know, up to UiPath. UiPath brought on Rob Ensslin, I've interviewed him. Very, very capable individual, is now Co-CEO. So he's kind of bringing that adult supervision in, and really tightening up the go to market. So, you know, we know this company has been a rocket ship, and so getting some control on that and really getting focused like a laser, you know, could be good things ahead there for that company. Okay. >> One of the problems, if I could real quick Dave, is what the use cases are. When we first came out with RPA, everyone was super excited about like, "No, UiPath is going to be great for super powerful "projects, use cases." That's not what RPA is being used for. As you mentioned, it's being used for mundane tasks, so it's not automating complex things, which I think UiPath was built for. So if you were going to get UiPath, and choose that over Microsoft, it's going to be 'cause you're doing it for more powerful use case, where it is better. But the problem is that's not where the enterprise is using it. The enterprise are using this for base rote tasks, and simply, Microsoft Power Automate can do that. >> Yeah, it's interesting. I've had people on theCube that are both Microsoft Power Automate customers and UiPath customers, and I've asked them, "Well you know, "how do you differentiate between the two?" And they've said to me, "Look, our users and personal productivity users, "they like Power Automate, "they can use it themselves, and you know, "it doesn't take a lot of, you know, support on our end." The flip side is you could do that with UiPath, but like you said, there's more of a focus now on end-to-end enterprise automation and building out those capabilities. So it's increasingly a value play, and that's going to be obviously the challenge going forward. Okay, my last one, and then I think you've got some bonus ones. Number 10, hybrid events are the new category. Look it, if I can get a thousand inbounds that are largely self-serving, I can do my own here, 'cause we're in the events business. (Eric chuckling) Here's the prediction though, and this is a trend we're seeing, the number of physical events is going to dramatically increase. That might surprise people, but most of the big giant events are going to get smaller. The exception is AWS with Reinvent, I think Snowflake's going to continue to grow. So there are examples of physical events that are growing, but generally, most of the big ones are getting smaller, and there's going to be many more smaller intimate regional events and road shows. These micro-events, they're going to be stitched together. Digital is becoming a first class citizen, so people really got to get their digital acts together, and brands are prioritizing earned media, and they're beginning to build their own news networks, going direct to their customers. And so that's a trend we see, and I, you know, we're right in the middle of it, Eric, so you know we're going to, you mentioned RSA, I think that's perhaps going to be one of those crazy ones that continues to grow. It's shrunk, and then it, you know, 'cause last year- >> Yeah, it did shrink. >> right, it was the last one before the pandemic, and then they sort of made another run at it last year. It was smaller but it was very vibrant, and I think this year's going to be huge. Global World Congress is another one, we're going to be there end of Feb. That's obviously a big big show, but in general, the brands and the technology vendors, even Oracle is going to scale down. I don't know about Salesforce. We'll see. You had a couple of bonus predictions. Quantum and maybe some others? Bring us home. >> Yeah, sure. I got a few more. I think we touched upon one, but I definitely think the data prep tools are facing extinction, unfortunately, you know, the Talons Informatica is some of those names. The problem there is that the BI tools are kind of including data prep into it already. You know, an example of that is Tableau Prep Builder, and then in addition, Advanced NLP is being worked in as well. ThoughtSpot, Intelius, both often say that as their selling point, Tableau has Ask Data, Click has Insight Bot, so you don't have to really be intelligent on data prep anymore. A regular business user can just self-query, using either the search bar, or even just speaking into what it needs, and these tools are kind of doing the data prep for it. I don't think that's a, you know, an out in left field type of prediction, but it's the time is nigh. The other one I would also state is that I think knowledge graphs are going to break through this year. Neo4j in our survey is growing in pervasion in Mindshare. So more and more people are citing it, AWS Neptune's getting its act together, and we're seeing that spending intentions are growing there. Tiger Graph is also growing in our survey sample. I just think that the time is now for knowledge graphs to break through, and if I had to do one more, I'd say real-time streaming analytics moves from the very, very rich big enterprises to downstream, to more people are actually going to be moving towards real-time streaming, again, because the data prep tools and the data pipelines have gotten easier to use, and I think the ROI on real-time streaming is obviously there. So those are three that didn't make the cut, but I thought deserved an honorable mention. >> Yeah, I'm glad you did. Several weeks ago, we did an analyst prediction roundtable, if you will, a cube session power panel with a number of data analysts and that, you know, streaming, real-time streaming was top of mind. So glad you brought that up. Eric, as always, thank you very much. I appreciate the time you put in beforehand. I know it's been crazy, because you guys are wrapping up, you know, the last quarter survey in- >> Been a nuts three weeks for us. (laughing) >> job. I love the fact that you're doing, you know, the ETS survey now, I think it's quarterly now, right? Is that right? >> Yep. >> Yep. So that's phenomenal. >> Four times a year. I'll be happy to jump on with you when we get that done. I know you were really impressed with that last time. >> It's unbelievable. This is so much data at ETR. Okay. Hey, that's a wrap. Thanks again. >> Take care Dave. Good seeing you. >> All right, many thanks to our team here, Alex Myerson as production, he manages the podcast force. Ken Schiffman as well is a critical component of our East Coast studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hoof is our editor-in-chief. He's at siliconangle.com. He's just a great editing for us. Thank you all. Remember all these episodes that are available as podcasts, wherever you listen, podcast is doing great. Just search "Breaking analysis podcast." Really appreciate you guys listening. I publish each week on wikibon.com and siliconangle.com, or you can email me directly if you want to get in touch, david.vellante@siliconangle.com. That's how I got all these. I really appreciate it. I went through every single one with a yellow highlighter. It took some time, (laughing) but I appreciate it. You could DM me at dvellante, or comment on our LinkedIn post and please check out etr.ai. Its data is amazing. Best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights, powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis." (upbeat music beginning) (upbeat music ending)

(soft techno upbeat music) >> Hi there. Welcome back to Las Vegas. This is Dave Villante with Paul Gillon. Reinvent day one and a half. We started last night, Monday, theCUBE after dark. Now we're going wall to wall. Today. Today was of course the big keynote, Adam Selipsky, kind of the baton now handing, you know, last year when he did his keynote, he was very new. He was sort of still getting his feet wet and finding his guru swing. Settling in a little bit more this year, learning a lot more, getting deeper into the tech, but of course, sharing the love with other leaders like Peter DeSantis. Tomorrow's going to be Swamy in the keynote. Adrian Cockcroft is here. Former AWS, former network Netflix CTO, currently an analyst. You got your own firm now. You're out there. Great to see you again. Thanks for coming on theCUBE. >> Yeah, thanks. >> We heard you on at Super Cloud, you gave some really good insights there back in August. So now as an outsider, you come in obviously, you got to be impressed with the size and the ecosystem and the energy. Of course. What were your thoughts on, you know what you've seen so far, today's keynotes, last night Peter DeSantis, what stood out to you? >> Yeah, I think it's great to be back at Reinvent again. We're kind of pretty much back to where we were before the pandemic sort of shut it down. This is a little, it's almost as big as the, the largest one that we had before. And everyone's turned up. It just feels like we're back. So that's really good to see. And it's a slightly different style. I think there were was more sort of video production things happening. I think in this keynote, more storytelling. I'm not sure it really all stitched together very well. Right. Some of the stories like, how does that follow that? So there were a few things there and some of there were spelling mistakes on the slides, you know that ELT instead of ETL and they spelled ZFS wrong and something. So it just seemed like there was, I'm not quite sure just maybe a few things were sort of rushed at the last minute. >> Not really AWS like, was it? It's kind of remind the Patriots Paul, you know Bill Belichick's teams are fumbling all over the place. >> That's right. That's right. >> Part of it may be, I mean the sort of the market. They have a leader in marketing right now but they're going to have a CMO. So that's sort of maybe as lack of a single threaded leader for this thing. Everything's being shared around a bit more. So maybe, I mean, it's all fixable and it's mine. This is minor stuff. I'm just sort of looking at it and going there's a few things that looked like they were not quite as good as they could have been in the way it was put together. Right? >> But I mean, you're taking a, you know a year of not doing Reinvent. Yeah. Being isolated. You know, we've certainly seen it with theCUBE. It's like, okay, it's not like riding a bike. You know, things that, you know you got to kind of relearn the muscle memories. It's more like golf than is bicycle riding. >> Well I've done AWS keynotes myself. And they are pretty much scrambled. It looks nice, but there's a lot of scrambling leading up to when it actually goes. Right? And sometimes you can, you sometimes see a little kind of the edges of that, and sometimes it's much more polished. But you know, overall it's pretty good. I think Peter DeSantis keynote yesterday was a lot of really good meat there. There was some nice presentations, and some great announcements there. And today I was, I thought I was a little disappointed with some of the, I thought they could have been more. I think the way Andy Jesse did it, he crammed more announcements into his keynote, and Adam seems to be taking sort of a bit more of a measured approach. There were a few things he picked up on and then I'm expecting more to be spread throughout the rest of the day. >> This was more poetic. Right? He took the universe as the analogy for data, the ocean for security. Right? The Antarctic was sort of. >> Yeah. It looked pretty, >> yeah. >> But I'm not sure that was like, we're not here really to watch nature videos >> As analysts and journalists, You're like, come on. >> Yeah, >> Give it the meat >> That was kind the thing, yeah, >> It has always been the AWS has always been Reinvent has always been a shock at our approach. 100, 150 announcements. And they're really, that kind of pressure seems to be off them now. Their position at the top of the market seems to be unshakeable. There's no clear competition that's creeping up behind them. So how does that affect the messaging you think that AWS brings to market when it doesn't really have to prove that it's a leader anymore? It can go after maybe more of the niche markets or fix the stuff that's a little broken more fine tuning than grandiose statements. >> I think so AWS for a long time was so far out that they basically said, "We don't think about the competition, we are listen to the customers." And that was always the statement that works as long as you're always in the lead, right? Because you are introducing the new idea to the customer. Nobody else got there first. So that was the case. But in a few areas they aren't leading. Right? You could argue in machine learning, not necessarily leading in sustainability. They're not leading and they don't want to talk about some of these areas and-- >> Database. I mean arguably, >> They're pretty strong there, but the areas when you are behind, it's like they kind of know how to play offense. But when you're playing defense, it's a different set of game. You're playing a different game and it's hard to be good at both. I think and I'm not sure that they're really used to following somebody into a market and making a success of that. So there's something, it's a little harder. Do you see what I mean? >> I get opinion on this. So when I say database, David Foyer was two years ago, predicted AWS is going to have to converge somehow. They have no choice. And they sort of touched on that today, right? Eliminating ETL, that's one thing. But Aurora to Redshift. >> Yeah. >> You know, end to end. I'm not sure it's totally, they're fully end to end >> That's a really good, that is an excellent piece of work, because there's a lot of work that it eliminates. There's are clear pain points, but then you've got sort of the competing thing, is like the MongoDB and it's like, it's just a way with one database keeps it simple. >> Snowflake, >> Or you've got on Snowflake maybe you've got all these 20 different things you're trying to integrate at AWS, but it's kind of like you have a bag of Lego bricks. It's my favorite analogy, right? You want a toy for Christmas, you want a toy formula one racing car since that seems to be the theme, right? >> Okay. Do you want the fully built model that you can play with right now? Or do you want the Lego version that you have to spend three days building. Right? And AWS is the Lego technique thing. You have to spend some time building it, but once you've built it, you can evolve it, and you'll still be playing those are still good bricks years later. Whereas that prebuilt to probably broken gathering dust, right? So there's something about having an vulnerable architecture which is harder to get into, but more durable in the long term. And so AWS tends to play the long game in many ways. And that's one of the elements that they do that and that's good, but it makes it hard to consume for enterprise buyers that are used to getting it with a bow on top. And here's the solution. You know? >> And Paul, that was always Andy Chassy's answer to when we would ask him, you know, all these primitives you're going to make it simpler. You see the primitives give us the advantage to turn on a dime in the marketplace. And that's true. >> Yeah. So you're saying, you know, you take all these things together and you wrap it up, and you put a snowflake on top, and now you've got a simple thing or a Mongo or Mongo atlas or whatever. So you've got these layered platforms now which are making it simpler to consume, but now you're kind of, you know, you're all stuck in that ecosystem, you know, so it's like what layer of abstractions do you want to tie yourself to, right? >> The data bricks coming at it from more of an open source approach. But it's similar. >> We're seeing Amazon direct more into vertical markets. They spotlighted what Goldman Sachs is doing on their platform. They've got a variety of platforms that are supposedly targeted custom built for vertical markets. How do successful do you see that play being? Is this something that the customers you think are looking for, a fully integrated Amazon solution? >> I think so. There's usually if you look at, you know the MongoDB or data stacks, or the other sort of or elastic, you know, they've got the specific solution with the people that really are developing the core technology, there's open source equivalent version. The AWS is running, and it's usually maybe they've got a price advantage or it's, you know there's some data integration in there or it's somehow easier to integrate but it's not stopping those companies from growing. And what it's doing is it's endorsing that platform. So if you look at the collection of databases that have been around over the last few years, now you've got basically Elastic Mongo and Cassandra, you know the data stacks as being endorsed by the cloud vendors. These are winners. They're going to be around for a very long time. You can build yourself on that architecture. But what happened to Couch base and you know, a few of the other ones, you know, they don't really fit. Like how you going to bait? If you are now becoming an also ran, because you didn't get cloned by the cloud vendor. So the customers are going is that a safe place to be, right? >> But isn't it, don't they want to encourage those partners though in the name of building the marketplace ecosystem? >> Yeah. >> This is huge. >> But certainly the platform, yeah, the platform encourages people to do more. And there's always room around the edge. But the mainstream customers like that really like spending the good money, are looking for something that's got a long term life to it. Right? They're looking for a long commitment to that technology and that it's going to be invested in and grow. And the fact that the cloud providers are adopting and particularly AWS is adopting some of these technologies means that is a very long term commitment. You can base, you know, you can bet your future architecture on that for a decade probably. >> So they have to pick winners. >> Yeah. So it's sort of picking winners. And then if you're the open source company that's now got AWS turning up, you have to then leverage it and use that as a way to grow the market. And I think Mongo have done an excellent job of that. I mean, they're top level sponsors of Reinvent, and they're out there messaging that and doing a good job of showing people how to layer on top of AWS and make it a win-win both sides. >> So ever since we've been in the business, you hear the narrative hardware's going to die. It's just, you know, it's commodity and there's some truth to that. But hardware's actually driving good gross margins for the Cisco's of the world. Storage companies have always made good margins. Servers maybe not so much, 'cause Intel sucked all the margin out of it. But let's face it, AWS makes most of its money. We know on compute, it's got 25 plus percent operating margins depending on the seasonality there. What do you think happens long term to the infrastructure layer discussion? Okay, commodity cloud, you know, we talk about super cloud. Do you think that AWS, and the other cloud vendors that infrastructure, IS gets commoditized and they have to go up market or you see that continuing I mean history would say that still good margins in hardware. What are your thoughts on that? >> It's not commoditizing, it's becoming more specific. We've got all these accelerators and custom chips now, and this is something, this almost goes back. I mean, I was with some micro systems 20,30 years ago and we developed our own chips and HP developed their own chips and SGI mips, right? We were like, the architectures were all squabbling of who had the best processor chips and it took years to get chips that worked. Now if you make a chip and it doesn't work immediately, you screwed up somewhere right? It's become the technology of building these immensely complicated powerful chips that has become commoditized. So the cost of building a custom chip, is now getting to the point where Apple and Amazon, your Apple laptop has got full custom chips your phone, your iPhone, whatever and you're getting Google making custom chips and we've got Nvidia now getting into CPUs as well as GPUs. So we're seeing that the ability to build a custom chip, is becoming something that everyone is leveraging. And the cost of doing that is coming down to startups are doing it. So we're going to see many, many more, much more innovation I think, and this is like Intel and AMD are, you know they've got the compatibility legacy, but of the most powerful, most interesting new things I think are going to be custom. And we're seeing that with Graviton three particular in the three E that was announced last night with like 30, 40% whatever it was, more performance for HPC workloads. And that's, you know, the HPC market is going to have to deal with cloud. I mean they are starting to, and I was at Supercomputing a few weeks ago and they are tiptoeing around the edge of cloud, but those supercomputers are water cold. They are monsters. I mean you go around supercomputing, there are plumbing vendors on the booth. >> Of course. Yeah. >> Right? And they're highly concentrated systems, and that's really the only difference, is like, is it water cooler or echo? The rest of the technology stack is pretty much off the shelf stuff with a few tweets software. >> You point about, you know, the chips and what AWS is doing. The Annapurna acquisition. >> Yeah. >> They're on a dramatically different curve now. I think it comes down to, again, David Floyd's premise, really comes down to volume. The arm wafer volumes are 10 x those of X 86, volume always wins. And the economics of semis. >> That kind of got us there. But now there's also a risk five coming along if you, in terms of licensing is becoming one of the bottlenecks. Like if the cost of building a chip is really low, then it comes down to licensing costs and do you want to pay the arm license And the risk five is an open source chip set which some people are starting to use for things. So your dis controller may have a risk five in it, for example, nowadays, those kinds of things. So I think that's kind of the the dynamic that's playing out. There's a lot of innovation in hardware to come in the next few years. There's a thing called CXL compute express link which is going to be really interesting. I think that's probably two years out, before we start seeing it for real. But it lets you put glue together entire rack in a very flexible way. So just, and that's the entire industry coming together around a single standard, the whole industry except for Amazon, in fact just about. >> Well, but maybe I think eventually they'll get there. Don't use system on a chip CXL. >> I have no idea whether I have no knowledge about whether going to do anything CXL. >> Presuming I'm not trying to tap anything confidential. It just makes sense that they would do a system on chip. It makes sense that they would do something like CXL. Why not adopt the standard, if it's going to be as the cost. >> Yeah. And so that was one of the things out of zip computing. The other thing is the low latency networking with the elastic fabric adapter EFA and the extensions to that that were announced last night. They doubled the throughput. So you get twice the capacity on the nitro chip. And then the other thing was this, this is a bit technical, but this scalable datagram protocol that they've got which basically says, if I want to send a message, a packet from one machine to another machine, instead of sending it over one wire, I consider it over 16 wires in parallel. And I will just flood the network with all the packets and they can arrive in any order. This is why it isn't done normally. TCP is in order, the packets come in order they're supposed to, but this is fully flooding them around with its own fast retry and then they get reassembled at the other end. So they're not just using this now for HPC workloads. They've turned it on for TCP for just without any change to your application. If you are trying to move a large piece of data between two machines, and you're just pushing it down a network, a single connection, it takes it from five gigabits per second to 25 gigabits per second. A five x speed up, with a protocol tweak that's run by the Nitro, this is super interesting. >> Probably want to get all that AIML that stuff is going on. >> Well, the AIML stuff is leveraging it underneath, but this is for everybody. Like you're just copying data around, right? And you're limited, "Hey this is going to get there five times faster, pushing a big enough chunk of data around." So this is turning on gradually as the nitro five comes out, and you have to enable it at the instance level. But it's a super interesting announcement from last night. >> So the bottom line bumper sticker on commoditization is what? >> I don't think so. I mean what's the APIs? Your arm compatible, your Intel X 86 compatible or your maybe risk five one day compatible in the cloud. And those are the APIs, right? That's the commodity level. And the software is now, the software ecosystem is super portable across those as we're seeing with Apple moving from Intel to it's really not an issue, right? The software and the tooling is all there to do that. But underneath that, we're going to see an arms race between the top providers as they all try and develop faster chips for doing more specific things. We've got cranium for training, that instance has they announced it last year with 800 gigabits going out of a single instance, 800 gigabits or no, but this year they doubled it. Yeah. So 1.6 terabytes out of a single machine, right? That's insane, right? But what you're doing is you're putting together hundreds or thousands of those to solve the big machine learning training problems. These super, these enormous clusters that they're being formed for doing these massive problems. And there is a market now, for these incredibly large supercomputer clusters built for doing AI. That's all bandwidth limited. >> And you think about the timeframe from design to tape out. >> Yeah. >> Is just getting compressed It's relative. >> It is. >> Six is going the other way >> The tooling is all there. Yeah. >> Fantastic. Adrian, always a pleasure to have you on. Thanks so much. >> Yeah. >> Really appreciate it. >> Yeah, thank you. >> Thank you Paul. >> Cheers. All right. Keep it right there everybody. Don't forget, go to thecube.net, you'll see all these videos. Go to siliconangle.com, We've got features with Adam Selipsky, we got my breaking analysis, we have another feature with MongoDB's, Dev Ittycheria, Ali Ghodsi, as well Frank Sluman tomorrow. So check that out. Keep it right there. You're watching theCUBE, the leader in enterprise and emerging tech, right back. (soft techno upbeat music)

>>When Oracle acquired my SQL via the Sun acquisition, nobody really thought the company would put much effort into the platform preferring to focus all the wood behind its leading Oracle database, Arrow pun intended. But two years ago, Oracle surprised many folks by announcing my SQL Heatwave a new database as a service with a massively parallel hybrid Columbia in Mary Mary architecture that brings together transactional and analytic data in a single platform. Welcome to our latest database, power panel on the cube. My name is Dave Ante, and today we're gonna discuss Oracle's MySQL Heat Wave with a who's who of cloud database industry analysts. Holgar Mueller is with Constellation Research. Mark Stammer is the Dragon Slayer and Wikibon contributor. And Ron Westfall is with Fu Chim Research. Gentlemen, welcome back to the Cube. Always a pleasure to have you on. Thanks for having us. Great to be here. >>So we've had a number of of deep dive interviews on the Cube with Nip and Aggarwal. You guys know him? He's a senior vice president of MySQL, Heatwave Development at Oracle. I think you just saw him at Oracle Cloud World and he's come on to describe this is gonna, I'll call it a shock and awe feature additions to to heatwave. You know, the company's clearly putting r and d into the platform and I think at at cloud world we saw like the fifth major release since 2020 when they first announced MySQL heat wave. So just listing a few, they, they got, they taken, brought in analytics machine learning, they got autopilot for machine learning, which is automation onto the basic o l TP functionality of the database. And it's been interesting to watch Oracle's converge database strategy. We've contrasted that amongst ourselves. Love to get your thoughts on Amazon's get the right tool for the right job approach. >>Are they gonna have to change that? You know, Amazon's got the specialized databases, it's just, you know, the both companies are doing well. It just shows there are a lot of ways to, to skin a cat cuz you see some traction in the market in, in both approaches. So today we're gonna focus on the latest heat wave announcements and we're gonna talk about multi-cloud with a native MySQL heat wave implementation, which is available on aws MySQL heat wave for Azure via the Oracle Microsoft interconnect. This kind of cool hybrid action that they got going. Sometimes we call it super cloud. And then we're gonna dive into my SQL Heatwave Lake house, which allows users to process and query data across MyQ databases as heatwave databases, as well as object stores. So, and then we've got, heatwave has been announced on AWS and, and, and Azure, they're available now and Lake House I believe is in beta and I think it's coming out the second half of next year. So again, all of our guests are fresh off of Oracle Cloud world in Las Vegas. So they got the latest scoop. Guys, I'm done talking. Let's get into it. Mark, maybe you could start us off, what's your opinion of my SQL Heatwaves competitive position? When you think about what AWS is doing, you know, Google is, you know, we heard Google Cloud next recently, we heard about all their data innovations. You got, obviously Azure's got a big portfolio, snowflakes doing well in the market. What's your take? >>Well, first let's look at it from the point of view that AWS is the market leader in cloud and cloud services. They own somewhere between 30 to 50% depending on who you read of the market. And then you have Azure as number two and after that it falls off. There's gcp, Google Cloud platform, which is further way down the list and then Oracle and IBM and Alibaba. So when you look at AWS and you and Azure saying, hey, these are the market leaders in the cloud, then you start looking at it and saying, if I am going to provide a service that competes with the service they have, if I can make it available in their cloud, it means that I can be more competitive. And if I'm compelling and compelling means at least twice the performance or functionality or both at half the price, I should be able to gain market share. >>And that's what Oracle's done. They've taken a superior product in my SQL heat wave, which is faster, lower cost does more for a lot less at the end of the day and they make it available to the users of those clouds. You avoid this little thing called egress fees, you avoid the issue of having to migrate from one cloud to another and suddenly you have a very compelling offer. So I look at what Oracle's doing with MyQ and it feels like, I'm gonna use a word term, a flanking maneuver to their competition. They're offering a better service on their platforms. >>All right, so thank you for that. Holger, we've seen this sort of cadence, I sort of referenced it up front a little bit and they sat on MySQL for a decade, then all of a sudden we see this rush of announcements. Why did it take so long? And and more importantly is Oracle, are they developing the right features that cloud database customers are looking for in your view? >>Yeah, great question, but first of all, in your interview you said it's the edit analytics, right? Analytics is kind of like a marketing buzzword. Reports can be analytics, right? The interesting thing, which they did, the first thing they, they, they crossed the chasm between OTP and all up, right? In the same database, right? So major engineering feed very much what customers want and it's all about creating Bellevue for customers, which, which I think is the part why they go into the multi-cloud and why they add these capabilities. And they certainly with the AI capabilities, it's kind of like getting it into an autonomous field, self-driving field now with the lake cost capabilities and meeting customers where they are, like Mark has talked about the e risk costs in the cloud. So that that's a significant advantage, creating value for customers and that's what at the end of the day matters. >>And I believe strongly that long term it's gonna be ones who create better value for customers who will get more of their money From that perspective, why then take them so long? I think it's a great question. I think largely he mentioned the gentleman Nial, it's largely to who leads a product. I used to build products too, so maybe I'm a little fooling myself here, but that made the difference in my view, right? So since he's been charged, he's been building things faster than the rest of the competition, than my SQL space, which in hindsight we thought was a hot and smoking innovation phase. It kind of like was a little self complacent when it comes to the traditional borders of where, where people think, where things are separated between OTP and ola or as an example of adjacent support, right? Structured documents, whereas unstructured documents or databases and all of that has been collapsed and brought together for building a more powerful database for customers. >>So I mean it's certainly, you know, when, when Oracle talks about the competitors, you know, the competitors are in the, I always say they're, if the Oracle talks about you and knows you're doing well, so they talk a lot about aws, talk a little bit about Snowflake, you know, sort of Google, they have partnerships with Azure, but, but in, so I'm presuming that the response in MySQL heatwave was really in, in response to what they were seeing from those big competitors. But then you had Maria DB coming out, you know, the day that that Oracle acquired Sun and, and launching and going after the MySQL base. So it's, I'm, I'm interested and we'll talk about this later and what you guys think AWS and Google and Azure and Snowflake and how they're gonna respond. But, but before I do that, Ron, I want to ask you, you, you, you can get, you know, pretty technical and you've probably seen the benchmarks. >>I know you have Oracle makes a big deal out of it, publishes its benchmarks, makes some transparent on on GI GitHub. Larry Ellison talked about this in his keynote at Cloud World. What are the benchmarks show in general? I mean, when you, when you're new to the market, you gotta have a story like Mark was saying, you gotta be two x you know, the performance at half the cost or you better be or you're not gonna get any market share. So, and, and you know, oftentimes companies don't publish market benchmarks when they're leading. They do it when they, they need to gain share. So what do you make of the benchmarks? Have their, any results that were surprising to you? Have, you know, they been challenged by the competitors. Is it just a bunch of kind of desperate bench marketing to make some noise in the market or you know, are they real? What's your view? >>Well, from my perspective, I think they have the validity. And to your point, I believe that when it comes to competitor responses, that has not really happened. Nobody has like pulled down the information that's on GitHub and said, Oh, here are our price performance results. And they counter oracles. In fact, I think part of the reason why that hasn't happened is that there's the risk if Oracle's coming out and saying, Hey, we can deliver 17 times better query performance using our capabilities versus say, Snowflake when it comes to, you know, the Lakehouse platform and Snowflake turns around and says it's actually only 15 times better during performance, that's not exactly an effective maneuver. And so I think this is really to oracle's credit and I think it's refreshing because these differentiators are significant. We're not talking, you know, like 1.2% differences. We're talking 17 fold differences, we're talking six fold differences depending on, you know, where the spotlight is being shined and so forth. >>And so I think this is actually something that is actually too good to believe initially at first blush. If I'm a cloud database decision maker, I really have to prioritize this. I really would know, pay a lot more attention to this. And that's why I posed the question to Oracle and others like, okay, if these differentiators are so significant, why isn't the needle moving a bit more? And it's for, you know, some of the usual reasons. One is really deep discounting coming from, you know, the other players that's really kind of, you know, marketing 1 0 1, this is something you need to do when there's a real competitive threat to keep, you know, a customer in your own customer base. Plus there is the usual fear and uncertainty about moving from one platform to another. But I think, you know, the traction, the momentum is, is shifting an Oracle's favor. I think we saw that in the Q1 efforts, for example, where Oracle cloud grew 44% and that it generated, you know, 4.8 billion and revenue if I recall correctly. And so, so all these are demonstrating that's Oracle is making, I think many of the right moves, publishing these figures for anybody to look at from their own perspective is something that is, I think, good for the market and I think it's just gonna continue to pay dividends for Oracle down the horizon as you know, competition intens plots. So if I were in, >>Dave, can I, Dave, can I interject something and, and what Ron just said there? Yeah, please go ahead. A couple things here, one discounting, which is a common practice when you have a real threat, as Ron pointed out, isn't going to help much in this situation simply because you can't discount to the point where you improve your performance and the performance is a huge differentiator. You may be able to get your price down, but the problem that most of them have is they don't have an integrated product service. They don't have an integrated O L T P O L A P M L N data lake. Even if you cut out two of them, they don't have any of them integrated. They have multiple services that are required separate integration and that can't be overcome with discounting. And the, they, you have to pay for each one of these. And oh, by the way, as you grow, the discounts go away. So that's a, it's a minor important detail. >>So, so that's a TCO question mark, right? And I know you look at this a lot, if I had that kind of price performance advantage, I would be pounding tco, especially if I need two separate databases to do the job. That one can do, that's gonna be, the TCO numbers are gonna be off the chart or maybe down the chart, which you want. Have you looked at this and how does it compare with, you know, the big cloud guys, for example, >>I've looked at it in depth, in fact, I'm working on another TCO on this arena, but you can find it on Wiki bod in which I compared TCO for MySEQ Heat wave versus Aurora plus Redshift plus ML plus Blue. I've compared it against gcps services, Azure services, Snowflake with other services. And there's just no comparison. The, the TCO differences are huge. More importantly, thefor, the, the TCO per performance is huge. We're talking in some cases multiple orders of magnitude, but at least an order of magnitude difference. So discounting isn't gonna help you much at the end of the day, it's only going to lower your cost a little, but it doesn't improve the automation, it doesn't improve the performance, it doesn't improve the time to insight, it doesn't improve all those things that you want out of a database or multiple databases because you >>Can't discount yourself to a higher value proposition. >>So what about, I wonder ho if you could chime in on the developer angle. You, you followed that, that market. How do these innovations from heatwave, I think you used the term developer velocity. I've heard you used that before. Yeah, I mean, look, Oracle owns Java, okay, so it, it's, you know, most popular, you know, programming language in the world, blah, blah blah. But it does it have the, the minds and hearts of, of developers and does, where does heatwave fit into that equation? >>I think heatwave is gaining quickly mindshare on the developer side, right? It's not the traditional no sequel database which grew up, there's a traditional mistrust of oracles to developers to what was happening to open source when gets acquired. Like in the case of Oracle versus Java and where my sql, right? And, but we know it's not a good competitive strategy to, to bank on Oracle screwing up because it hasn't worked not on Java known my sequel, right? And for developers, it's, once you get to know a technology product and you can do more, it becomes kind of like a Swiss army knife and you can build more use case, you can build more powerful applications. That's super, super important because you don't have to get certified in multiple databases. You, you are fast at getting things done, you achieve fire, develop velocity, and the managers are happy because they don't have to license more things, send you to more trainings, have more risk of something not being delivered, right? >>So it's really the, we see the suite where this best of breed play happening here, which in general was happening before already with Oracle's flagship database. Whereas those Amazon as an example, right? And now the interesting thing is every step away Oracle was always a one database company that can be only one and they're now generally talking about heat web and that two database company with different market spaces, but same value proposition of integrating more things very, very quickly to have a universal database that I call, they call the converge database for all the needs of an enterprise to run certain application use cases. And that's what's attractive to developers. >>It's, it's ironic isn't it? I mean I, you know, the rumor was the TK Thomas Curian left Oracle cuz he wanted to put Oracle database on other clouds and other places. And maybe that was the rift. Maybe there was, I'm sure there was other things, but, but Oracle clearly is now trying to expand its Tam Ron with, with heatwave into aws, into Azure. How do you think Oracle's gonna do, you were at a cloud world, what was the sentiment from customers and the independent analyst? Is this just Oracle trying to screw with the competition, create a little diversion? Or is this, you know, serious business for Oracle? What do you think? >>No, I think it has lakes. I think it's definitely, again, attriting to Oracle's overall ability to differentiate not only my SQL heat wave, but its overall portfolio. And I think the fact that they do have the alliance with the Azure in place, that this is definitely demonstrating their commitment to meeting the multi-cloud needs of its customers as well as what we pointed to in terms of the fact that they're now offering, you know, MySQL capabilities within AWS natively and that it can now perform AWS's own offering. And I think this is all demonstrating that Oracle is, you know, not letting up, they're not resting on its laurels. That's clearly we are living in a multi-cloud world, so why not just make it more easy for customers to be able to use cloud databases according to their own specific, specific needs. And I think, you know, to holder's point, I think that definitely lines with being able to bring on more application developers to leverage these capabilities. >>I think one important announcement that's related to all this was the JSON relational duality capabilities where now it's a lot easier for application developers to use a language that they're very familiar with a JS O and not have to worry about going into relational databases to store their J S O N application coding. So this is, I think an example of the innovation that's enhancing the overall Oracle portfolio and certainly all the work with machine learning is definitely paying dividends as well. And as a result, I see Oracle continue to make these inroads that we pointed to. But I agree with Mark, you know, the short term discounting is just a stall tag. This is not denying the fact that Oracle is being able to not only deliver price performance differentiators that are dramatic, but also meeting a wide range of needs for customers out there that aren't just limited device performance consideration. >>Being able to support multi-cloud according to customer needs. Being able to reach out to the application developer community and address a very specific challenge that has plagued them for many years now. So bring it all together. Yeah, I see this as just enabling Oracles who ring true with customers. That the customers that were there were basically all of them, even though not all of them are going to be saying the same things, they're all basically saying positive feedback. And likewise, I think the analyst community is seeing this. It's always refreshing to be able to talk to customers directly and at Oracle cloud there was a litany of them and so this is just a difference maker as well as being able to talk to strategic partners. The nvidia, I think partnerships also testament to Oracle's ongoing ability to, you know, make the ecosystem more user friendly for the customers out there. >>Yeah, it's interesting when you get these all in one tools, you know, the Swiss Army knife, you expect that it's not able to be best of breed. That's the kind of surprising thing that I'm hearing about, about heatwave. I want to, I want to talk about Lake House because when I think of Lake House, I think data bricks, and to my knowledge data bricks hasn't been in the sites of Oracle yet. Maybe they're next, but, but Oracle claims that MySQL, heatwave, Lakehouse is a breakthrough in terms of capacity and performance. Mark, what are your thoughts on that? Can you double click on, on Lakehouse Oracle's claims for things like query performance and data loading? What does it mean for the market? Is Oracle really leading in, in the lake house competitive landscape? What are your thoughts? >>Well, but name in the game is what are the problems you're solving for the customer? More importantly, are those problems urgent or important? If they're urgent, customers wanna solve 'em. Now if they're important, they might get around to them. So you look at what they're doing with Lake House or previous to that machine learning or previous to that automation or previous to that O L A with O ltp and they're merging all this capability together. If you look at Snowflake or data bricks, they're tacking one problem. You look at MyQ heat wave, they're tacking multiple problems. So when you say, yeah, their queries are much better against the lake house in combination with other analytics in combination with O ltp and the fact that there are no ETLs. So you're getting all this done in real time. So it's, it's doing the query cross, cross everything in real time. >>You're solving multiple user and developer problems, you're increasing their ability to get insight faster, you're having shorter response times. So yeah, they really are solving urgent problems for customers. And by putting it where the customer lives, this is the brilliance of actually being multicloud. And I know I'm backing up here a second, but by making it work in AWS and Azure where people already live, where they already have applications, what they're saying is, we're bringing it to you. You don't have to come to us to get these, these benefits, this value overall, I think it's a brilliant strategy. I give Nip and Argo wallet a huge, huge kudos for what he's doing there. So yes, what they're doing with the lake house is going to put notice on data bricks and Snowflake and everyone else for that matter. Well >>Those are guys that whole ago you, you and I have talked about this. Those are, those are the guys that are doing sort of the best of breed. You know, they're really focused and they, you know, tend to do well at least out of the gate. Now you got Oracle's converged philosophy, obviously with Oracle database. We've seen that now it's kicking in gear with, with heatwave, you know, this whole thing of sweets versus best of breed. I mean the long term, you know, customers tend to migrate towards suite, but the new shiny toy tends to get the growth. How do you think this is gonna play out in cloud database? >>Well, it's the forever never ending story, right? And in software right suite, whereas best of breed and so far in the long run suites have always won, right? So, and sometimes they struggle again because the inherent problem of sweets is you build something larger, it has more complexity and that means your cycles to get everything working together to integrate the test that roll it out, certify whatever it is, takes you longer, right? And that's not the case. It's a fascinating part of what the effort around my SQL heat wave is that the team is out executing the previous best of breed data, bringing us something together. Now if they can maintain that pace, that's something to to, to be seen. But it, the strategy, like what Mark was saying, bring the software to the data is of course interesting and unique and totally an Oracle issue in the past, right? >>Yeah. But it had to be in your database on oci. And but at, that's an interesting part. The interesting thing on the Lake health side is, right, there's three key benefits of a lakehouse. The first one is better reporting analytics, bring more rich information together, like make the, the, the case for silicon angle, right? We want to see engagements for this video, we want to know what's happening. That's a mixed transactional video media use case, right? Typical Lakehouse use case. The next one is to build more rich applications, transactional applications which have video and these elements in there, which are the engaging one. And the third one, and that's where I'm a little critical and concerned, is it's really the base platform for artificial intelligence, right? To run deep learning to run things automatically because they have all the data in one place can create in one way. >>And that's where Oracle, I know that Ron talked about Invidia for a moment, but that's where Oracle doesn't have the strongest best story. Nonetheless, the two other main use cases of the lake house are very strong, very well only concern is four 50 terabyte sounds long. It's an arbitrary limitation. Yeah, sounds as big. So for the start, and it's the first word, they can make that bigger. You don't want your lake house to be limited and the terabyte sizes or any even petabyte size because you want to have the certainty. I can put everything in there that I think it might be relevant without knowing what questions to ask and query those questions. >>Yeah. And you know, in the early days of no schema on right, it just became a mess. But now technology has evolved to allow us to actually get more value out of that data. Data lake. Data swamp is, you know, not much more, more, more, more logical. But, and I want to get in, in a moment, I want to come back to how you think the competitors are gonna respond. Are they gonna have to sort of do a more of a converged approach? AWS in particular? But before I do, Ron, I want to ask you a question about autopilot because I heard Larry Ellison's keynote and he was talking about how, you know, most security issues are human errors with autonomy and autonomous database and things like autopilot. We take care of that. It's like autonomous vehicles, they're gonna be safer. And I went, well maybe, maybe someday. So Oracle really tries to emphasize this, that every time you see an announcement from Oracle, they talk about new, you know, autonomous capabilities. It, how legit is it? Do people care? What about, you know, what's new for heatwave Lakehouse? How much of a differentiator, Ron, do you really think autopilot is in this cloud database space? >>Yeah, I think it will definitely enhance the overall proposition. I don't think people are gonna buy, you know, lake house exclusively cause of autopilot capabilities, but when they look at the overall picture, I think it will be an added capability bonus to Oracle's benefit. And yeah, I think it's kind of one of these age old questions, how much do you automate and what is the bounce to strike? And I think we all understand with the automatic car, autonomous car analogy that there are limitations to being able to use that. However, I think it's a tool that basically every organization out there needs to at least have or at least evaluate because it goes to the point of it helps with ease of use, it helps make automation more balanced in terms of, you know, being able to test, all right, let's automate this process and see if it works well, then we can go on and switch on on autopilot for other processes. >>And then, you know, that allows, for example, the specialists to spend more time on business use cases versus, you know, manual maintenance of, of the cloud database and so forth. So I think that actually is a, a legitimate value proposition. I think it's just gonna be a case by case basis. Some organizations are gonna be more aggressive with putting automation throughout their processes throughout their organization. Others are gonna be more cautious. But it's gonna be, again, something that will help the overall Oracle proposition. And something that I think will be used with caution by many organizations, but other organizations are gonna like, hey, great, this is something that is really answering a real problem. And that is just easing the use of these databases, but also being able to better handle the automation capabilities and benefits that come with it without having, you know, a major screwup happened and the process of transitioning to more automated capabilities. >>Now, I didn't attend cloud world, it's just too many red eyes, you know, recently, so I passed. But one of the things I like to do at those events is talk to customers, you know, in the spirit of the truth, you know, they, you know, you'd have the hallway, you know, track and to talk to customers and they say, Hey, you know, here's the good, the bad and the ugly. So did you guys, did you talk to any customers my SQL Heatwave customers at, at cloud world? And and what did you learn? I don't know, Mark, did you, did you have any luck and, and having some, some private conversations? >>Yeah, I had quite a few private conversations. The one thing before I get to that, I want disagree with one point Ron made, I do believe there are customers out there buying the heat wave service, the MySEQ heat wave server service because of autopilot. Because autopilot is really revolutionary in many ways in the sense for the MySEQ developer in that it, it auto provisions, it auto parallel loads, IT auto data places it auto shape predictions. It can tell you what machine learning models are going to tell you, gonna give you your best results. And, and candidly, I've yet to meet a DBA who didn't wanna give up pedantic tasks that are pain in the kahoo, which they'd rather not do and if it's long as it was done right for them. So yes, I do think people are buying it because of autopilot and that's based on some of the conversations I had with customers at Oracle Cloud World. >>In fact, it was like, yeah, that's great, yeah, we get fantastic performance, but this really makes my life easier and I've yet to meet a DBA who didn't want to make their life easier. And it does. So yeah, I've talked to a few of them. They were excited. I asked them if they ran into any bugs, were there any difficulties in moving to it? And the answer was no. In both cases, it's interesting to note, my sequel is the most popular database on the planet. Well, some will argue that it's neck and neck with SQL Server, but if you add in Mariah DB and ProCon db, which are forks of MySQL, then yeah, by far and away it's the most popular. And as a result of that, everybody for the most part has typically a my sequel database somewhere in their organization. So this is a brilliant situation for anybody going after MyQ, but especially for heat wave. And the customers I talk to love it. I didn't find anybody complaining about it. And >>What about the migration? We talked about TCO earlier. Did your t does your TCO analysis include the migration cost or do you kind of conveniently leave that out or what? >>Well, when you look at migration costs, there are different kinds of migration costs. By the way, the worst job in the data center is the data migration manager. Forget it, no other job is as bad as that one. You get no attaboys for doing it. Right? And then when you screw up, oh boy. So in real terms, anything that can limit data migration is a good thing. And when you look at Data Lake, that limits data migration. So if you're already a MySEQ user, this is a pure MySQL as far as you're concerned. It's just a, a simple transition from one to the other. You may wanna make sure nothing broke and every you, all your tables are correct and your schema's, okay, but it's all the same. So it's a simple migration. So it's pretty much a non-event, right? When you migrate data from an O LTP to an O L A P, that's an ETL and that's gonna take time. >>But you don't have to do that with my SQL heat wave. So that's gone when you start talking about machine learning, again, you may have an etl, you may not, depending on the circumstances, but again, with my SQL heat wave, you don't, and you don't have duplicate storage, you don't have to copy it from one storage container to another to be able to be used in a different database, which by the way, ultimately adds much more cost than just the other service. So yeah, I looked at the migration and again, the users I talked to said it was a non-event. It was literally moving from one physical machine to another. If they had a new version of MySEQ running on something else and just wanted to migrate it over or just hook it up or just connect it to the data, it worked just fine. >>Okay, so every day it sounds like you guys feel, and we've certainly heard this, my colleague David Foyer, the semi-retired David Foyer was always very high on heatwave. So I think you knows got some real legitimacy here coming from a standing start, but I wanna talk about the competition, how they're likely to respond. I mean, if your AWS and you got heatwave is now in your cloud, so there's some good aspects of that. The database guys might not like that, but the infrastructure guys probably love it. Hey, more ways to sell, you know, EC two and graviton, but you're gonna, the database guys in AWS are gonna respond. They're gonna say, Hey, we got Redshift, we got aqua. What's your thoughts on, on not only how that's gonna resonate with customers, but I'm interested in what you guys think will a, I never say never about aws, you know, and are they gonna try to build, in your view a converged Oola and o LTP database? You know, Snowflake is taking an ecosystem approach. They've added in transactional capabilities to the portfolio so they're not standing still. What do you guys see in the competitive landscape in that regard going forward? Maybe Holger, you could start us off and anybody else who wants to can chime in, >>Happy to, you mentioned Snowflake last, we'll start there. I think Snowflake is imitating that strategy, right? That building out original data warehouse and the clouds tasking project to really proposition to have other data available there because AI is relevant for everybody. Ultimately people keep data in the cloud for ultimately running ai. So you see the same suite kind of like level strategy, it's gonna be a little harder because of the original positioning. How much would people know that you're doing other stuff? And I just, as a former developer manager of developers, I just don't see the speed at the moment happening at Snowflake to become really competitive to Oracle. On the flip side, putting my Oracle hat on for a moment back to you, Mark and Iran, right? What could Oracle still add? Because the, the big big things, right? The traditional chasms in the database world, they have built everything, right? >>So I, I really scratched my hat and gave Nipon a hard time at Cloud world say like, what could you be building? Destiny was very conservative. Let's get the Lakehouse thing done, it's gonna spring next year, right? And the AWS is really hard because AWS value proposition is these small innovation teams, right? That they build two pizza teams, which can be fit by two pizzas, not large teams, right? And you need suites to large teams to build these suites with lots of functionalities to make sure they work together. They're consistent, they have the same UX on the administration side, they can consume the same way, they have the same API registry, can't even stop going where the synergy comes to play over suite. So, so it's gonna be really, really hard for them to change that. But AWS super pragmatic. They're always by themselves that they'll listen to customers if they learn from customers suite as a proposition. I would not be surprised if AWS trying to bring things closer together, being morely together. >>Yeah. Well how about, can we talk about multicloud if, if, again, Oracle is very on on Oracle as you said before, but let's look forward, you know, half a year or a year. What do you think about Oracle's moves in, in multicloud in terms of what kind of penetration they're gonna have in the marketplace? You saw a lot of presentations at at cloud world, you know, we've looked pretty closely at the, the Microsoft Azure deal. I think that's really interesting. I've, I've called it a little bit of early days of a super cloud. What impact do you think this is gonna have on, on the marketplace? But, but both. And think about it within Oracle's customer base, I have no doubt they'll do great there. But what about beyond its existing install base? What do you guys think? >>Ryan, do you wanna jump on that? Go ahead. Go ahead Ryan. No, no, no, >>That's an excellent point. I think it aligns with what we've been talking about in terms of Lakehouse. I think Lake House will enable Oracle to pull more customers, more bicycle customers onto the Oracle platforms. And I think we're seeing all the signs pointing toward Oracle being able to make more inroads into the overall market. And that includes garnishing customers from the leaders in, in other words, because they are, you know, coming in as a innovator, a an alternative to, you know, the AWS proposition, the Google cloud proposition that they have less to lose and there's a result they can really drive the multi-cloud messaging to resonate with not only their existing customers, but also to be able to, to that question, Dave's posing actually garnish customers onto their platform. And, and that includes naturally my sequel but also OCI and so forth. So that's how I'm seeing this playing out. I think, you know, again, Oracle's reporting is indicating that, and I think what we saw, Oracle Cloud world is definitely validating the idea that Oracle can make more waves in the overall market in this regard. >>You know, I, I've floated this idea of Super cloud, it's kind of tongue in cheek, but, but there, I think there is some merit to it in terms of building on top of hyperscale infrastructure and abstracting some of the, that complexity. And one of the things that I'm most interested in is industry clouds and an Oracle acquisition of Cerner. I was struck by Larry Ellison's keynote, it was like, I don't know, an hour and a half and an hour and 15 minutes was focused on healthcare transformation. Well, >>So vertical, >>Right? And so, yeah, so you got Oracle's, you know, got some industry chops and you, and then you think about what they're building with, with not only oci, but then you got, you know, MyQ, you can now run in dedicated regions. You got ADB on on Exadata cloud to customer, you can put that OnPrem in in your data center and you look at what the other hyperscalers are, are doing. I I say other hyperscalers, I've always said Oracle's not really a hyperscaler, but they got a cloud so they're in the game. But you can't get, you know, big query OnPrem, you look at outposts, it's very limited in terms of, you know, the database support and again, that that will will evolve. But now you got Oracle's got, they announced Alloy, we can white label their cloud. So I'm interested in what you guys think about these moves, especially the industry cloud. We see, you know, Walmart is doing sort of their own cloud. You got Goldman Sachs doing a cloud. Do you, you guys, what do you think about that and what role does Oracle play? Any thoughts? >>Yeah, let me lemme jump on that for a moment. Now, especially with the MyQ, by making that available in multiple clouds, what they're doing is this follows the philosophy they've had the past with doing cloud, a customer taking the application and the data and putting it where the customer lives. If it's on premise, it's on premise. If it's in the cloud, it's in the cloud. By making the mice equal heat wave, essentially a plug compatible with any other mice equal as far as your, your database is concern and then giving you that integration with O L A P and ML and Data Lake and everything else, then what you've got is a compelling offering. You're making it easier for the customer to use. So I look the difference between MyQ and the Oracle database, MyQ is going to capture market more market share for them. >>You're not gonna find a lot of new users for the Oracle debate database. Yeah, there are always gonna be new users, don't get me wrong, but it's not gonna be a huge growth. Whereas my SQL heatwave is probably gonna be a major growth engine for Oracle going forward. Not just in their own cloud, but in AWS and in Azure and on premise over time that eventually it'll get there. It's not there now, but it will, they're doing the right thing on that basis. They're taking the services and when you talk about multicloud and making them available where the customer wants them, not forcing them to go where you want them, if that makes sense. And as far as where they're going in the future, I think they're gonna take a page outta what they've done with the Oracle database. They'll add things like JSON and XML and time series and spatial over time they'll make it a, a complete converged database like they did with the Oracle database. The difference being Oracle database will scale bigger and will have more transactions and be somewhat faster. And my SQL will be, for anyone who's not on the Oracle database, they're, they're not stupid, that's for sure. >>They've done Jason already. Right. But I give you that they could add graph and time series, right. Since eat with, Right, Right. Yeah, that's something absolutely right. That's, that's >>A sort of a logical move, right? >>Right. But that's, that's some kid ourselves, right? I mean has worked in Oracle's favor, right? 10 x 20 x, the amount of r and d, which is in the MyQ space, has been poured at trying to snatch workloads away from Oracle by starting with IBM 30 years ago, 20 years ago, Microsoft and, and, and, and didn't work, right? Database applications are extremely sticky when they run, you don't want to touch SIM and grow them, right? So that doesn't mean that heat phase is not an attractive offering, but it will be net new things, right? And what works in my SQL heat wave heat phases favor a little bit is it's not the massive enterprise applications which have like we the nails like, like you might be only running 30% or Oracle, but the connections and the interfaces into that is, is like 70, 80% of your enterprise. >>You take it out and it's like the spaghetti ball where you say, ah, no I really don't, don't want to do all that. Right? You don't, don't have that massive part with the equals heat phase sequel kind of like database which are more smaller tactical in comparison, but still I, I don't see them taking so much share. They will be growing because of a attractive value proposition quickly on the, the multi-cloud, right? I think it's not really multi-cloud. If you give people the chance to run your offering on different clouds, right? You can run it there. The multi-cloud advantages when the Uber offering comes out, which allows you to do things across those installations, right? I can migrate data, I can create data across something like Google has done with B query Omni, I can run predictive models or even make iron models in different place and distribute them, right? And Oracle is paving the road for that, but being available on these clouds. But the multi-cloud capability of database which knows I'm running on different clouds that is still yet to be built there. >>Yeah. And >>That the problem with >>That, that's the super cloud concept that I flowed and I I've always said kinda snowflake with a single global instance is sort of, you know, headed in that direction and maybe has a league. What's the issue with that mark? >>Yeah, the problem with the, with that version, the multi-cloud is clouds to charge egress fees. As long as they charge egress fees to move data between clouds, it's gonna make it very difficult to do a real multi-cloud implementation. Even Snowflake, which runs multi-cloud, has to pass out on the egress fees of their customer when data moves between clouds. And that's really expensive. I mean there, there is one customer I talked to who is beta testing for them, the MySQL heatwave and aws. The only reason they didn't want to do that until it was running on AWS is the egress fees were so great to move it to OCI that they couldn't afford it. Yeah. Egress fees are the big issue but, >>But Mark the, the point might be you might wanna root query and only get the results set back, right was much more tinier, which been the answer before for low latency between the class A problem, which we sometimes still have but mostly don't have. Right? And I think in general this with fees coming down based on the Oracle general E with fee move and it's very hard to justify those, right? But, but it's, it's not about moving data as a multi-cloud high value use case. It's about doing intelligent things with that data, right? Putting into other places, replicating it, what I'm saying the same thing what you said before, running remote queries on that, analyzing it, running AI on it, running AI models on that. That's the interesting thing. Cross administered in the same way. Taking things out, making sure compliance happens. Making sure when Ron says I don't want to be American anymore, I want to be in the European cloud that is gets migrated, right? So tho those are the interesting value use case which are really, really hard for enterprise to program hand by hand by developers and they would love to have out of the box and that's yet the innovation to come to, we have to come to see. But the first step to get there is that your software runs in multiple clouds and that's what Oracle's doing so well with my SQL >>Guys. Amazing. >>Go ahead. Yeah. >>Yeah. >>For example, >>Amazing amount of data knowledge and, and brain power in this market. Guys, I really want to thank you for coming on to the cube. Ron Holger. Mark, always a pleasure to have you on. Really appreciate your time. >>Well all the last names we're very happy for Romanic last and moderator. Thanks Dave for moderating us. All right, >>We'll see. We'll see you guys around. Safe travels to all and thank you for watching this power panel, The Truth About My SQL Heat Wave on the cube. Your leader in enterprise and emerging tech coverage.

(upbeat music) >> We're back at AWS re:Invent 2021. It's the biggest hybrid event of the year. One of the few physical events and we're psyched to be here. My name is Dave Vellante, and I'm really pleased to bring back the host emeritus, Stu Miniman, somebody I worked with side-by-side, Stu, for 10 years in a setting much like this, many like this. So, good to have you back. >> Dave, it's great to be here with theCUBE team, family here and re:Invent, Dave. I mean, this show, I remember back, Dave, going to you after the first re:Invent we talked, we were like, "We got to be there." Dave, remember the first year we came, the second year of re:Invent, this is the 10th year now, little card tables, gaming companies, all this stuff. You had Jerry Chen on yesterday and Jerry was comparing like, this is going to be like the next Microsoft. And we bet heavy on this ecosystem. And yeah, we all think this cloud thing, it might be real. 20,000 people here, it's not the 50 or 75,000 that we had in like 2018, 2019, but this ecosystem, what's happening in the cloud, multiple versions of hybrid going on with the event and the services, but yeah, phenomenal stuff. And yeah, it's so nice to see people. >> That's for sure. It's something that we've talked about a lot over the years is, and you remember the early days of re:Invent and to this day, just very a strong developer affinity that AWS has done a tremendous job of building that up and it's their raison d'etre, it's how they approach the market. But now you've been at Red Hat for a bit, obviously as well, developer affinity, what have you learned? Specifically as it relates to the cloud, Kubernetes, hottest thing going, you don't want to do an OpenShift commercial, but it's there, you're in the middle of that mix. What have you learned generally? >> Well, Dave, to the comment that you made about developers here, it's developers and the enterprise. We used to have a joke and say, enterprise developer is an oxymoron, but that line between developers doing stuff, early as a cloud, it was stealth computing. It's they're often doing this stuff and central IT is not managing it. So how do the pieces come together? How do apps and infrastructure, how do those pieces come together? And it's something that Red Hat has been doing a long time. Think about the Linux developer. They might've not have been the app developers, the people building Linux and everything, but they had a decent close tie to it. I'm on the OpenShift team. What we do is cloud, Dave, and we've got a partnership here with Amazon. We GAed our native cloud service earlier this year. Andy Jassy helped name it. It is the beautifully named Red Hat OpenShift Service on AWS or ROSA. But we've done OpenShift on AWS for more than five years, basically since we were doing Kubernetes, it's been here because of course customers doing cloud, where are they? A lot of them are here in Amazon. So I've been loving talking to a lot of customers, understanding how enterprise adoption is increasing, how we can enable developers and help them move faster. And yeah, I mean the quick plug on OpenShift is our service. We've got an SRE team that is going to manage all of that. A friend of the program, Corey Quinn, says, "Hey, an SRE team like that, because you don't want to manage as an enterprise." You don't want to manage Kubernetes. Yeah, you need to understand some of the pieces, but what is important to your business is the applications, your data and all those things and managing the undifferentiated heavy lifting. That's one of the reasons you went to the cloud. So therefore changing your model as to how you consume services in the cloud. And what are we seeing with Amazon, Dave? They're trying to build more solutions, simplify deployments, and offer more solutions including with their ecosystem. >> So I want to ask you. You said enterprise developer is kind of an oxymoron, and I remember, years ago I used to hang around with a lot of heads of application development and insurance companies and financial services, pharmaceutical, and they didn't wear hoodies, but they didn't wear suits either. And then when I talked to guys like Jeff Clark, for instance. He talks about we're building an abstraction layer across clouds, blah, blah, blah, which by the way, I think it is the right strategy. I'm like, "Okay, I'll drink some of that Kool-Aid." And then when I come here, we talked to Adam Selipsky. John flew out and I was on the chime. He goes, "Yeah, that's not hybrid. No, this is nothing like, it's not AWS, AWS is cloud." So, square that circle for me, 'cause you're in both worlds and certainly your strategy is to connect those words. Is that cloud? >> Yeah, right. I mean, Dave, we spent years talking about like is private cloud really a cloud? And when we started coming to the show, there is only one cloud. It is the public cloud and Amazon is the paragon of, I don't know what it was. >> Dave: Fake clouds, cloud washing. >> So today, Amazon's putting lots of things into your data center and extending the cloud out to that environment. >> So that's cloud. >> That's cloud. >> What do we call that cloud? What about the reverse? >> What's happening at the edge is that cloud is that extension of what we said from Amazon. If you look at not only Outpost, but Wavelengths and Local Zones and everything else like that. >> Let's say, yes, that's cloud. The APIs, primitives, check. >> Dave, I've always thought cloud is an operating model, not a location. And the hybrid definition is not the old, I did an ebook on this, Dave earlier this year. It's not the decade old NIS definition of an application that spans because I don't get up in the morning as an enterprise and say, "Oh, let me look at the table of how much Google is charging me or Microsoft or Amazon," or wake up one morning and move from one cloud to the other. Portability, follow the sun type stuff, does it ever happen? Yes, but it is rare thing. Applications oftentimes get pulled apart. So we've seen if you talk about AI, training the cloud, then transact and do things at the edge. If I'm in an autonomous vehicle or in a geosynchronous satellite, I can't be going back to the cloud to process stuff. So I get what I need and I process there. The same thing hybrid, oftentimes I will do my transactional activity in the public cloud because I've got unlimited compute capability, but I might have my repository of data for many different reasons, governance or security, all these things in my own data center. So parts of an application might live there, but I don't just span to go between the public cloud in my data center or the edge, it's specific architectural decisions as to how we do this. And by the way the developer, they don't want to have to think about location. I mean, my background, servers, storage, virtualization, all that stuff, that was very much an infrastructure up look of things. Developers want to worry about their code and make sure that it works in production. >> Okay, let me test that. If it's in the AWS cloud and I think it's true for the other hyperscale clouds too, they don't have to think about location, but they still have to think about location on-prem, don't they? >> Well, Dave, even in a public cloud, you do need to worry about sometimes it's like, "Okay, do I split it between availability zones? How do I build that? How do I do that?" So there are things that we build on top of it. So we've seen Amazon. >> I think that's fair, data sovereignty, you have to think about okay. >> Absolutely, a lot of those things. >> Okay, but the experience in Germany is going to be the same as it is in DC, is it not? >> More or less? There are some differences we'll see off and Amazon will roll things out over time and what's available, you've got cloud. >> For sure, though that's definitely true. That's a maturity thing, right? You've talked a bit, but ultimately they all sort of catch up. I guess my question would be is the delta between, let's say, Fed adoption and East Coast, is that delta narrower, significantly narrow than what you might see on-prem? >> The services are the same, sometimes for financial or political things, there might be some slight differences, but yes, the cloud experience should be the same everywhere from Amazon. >> Is it from a standpoint of hybrid, on-prem to cloud, across cloud? >> Many of the things when they go outside of the Amazon data centers are limited or a little bit different or you might have latency considerations that you have to consider. >> Now it's a tug of war. >> So it's not totally seamless because, David Foyer would tell us there, "You're not going to fight physics." There are certain things that we need to have and we've changed the way we architect things because it's no longer the bottleneck of the local scuzzy connection that you have there, it is now (indistinct). >> But the point I'm making is that gets into a tug of war of "Our way is better than your way." And the answer is depends in terms of your workload and the use case. >> You've looked at some of these new databases that span globes and do things of the like. >> Another question, I don't know if you saw the Goldman Sachs deal this morning, Goldman Sachs is basically turning its business into a SaaS and pointing it to their hedge funds and allowing people to access their data, their tools, their software that they built for their own purposes. And now they're outselling it. Similar to what NASDAQ has done. I can't imagine doing that without containers. >> Yeah, so interesting point, I think. At least six years ago now, Amazon launched serverless and serverless was going to take over the world. I dug into the space for a couple of years. And you had the serverless with camp and you had the container camp. Last year at re:Invent, I really felt a shift from Amazon's positioning that many of the abstraction layers and the tools that help you support those environments will now span between Lambda and containers. The container world has been adding serverless functionality. So Amazon does Fargate. The open-source community uses something called Knative, and just breaking this week. Knative was a project that Google started and it looks like that is going to move over to the CNCF. So be part of the whole Kubernetes ecosystem and everything like that. Oracle, VMware, IBM, Red Hat, all heavily involved in Knative, and we're all excited to see that go into the CNCF. So the reason I say that, I've seen from Amazon, I actually, John and I, when we interviewed Andy Jassy back in 2017, I asked him a follow-up question because he said if he was to build AWS in 2017, "I would start with everything underneath it serverless." I would wonder if following up with Adam or Andy today, I'd said, "Would it be all serverless or would containers be a piece of it?" Because sometimes underneath it doesn't matter or sometimes it can be containers and serverless. It's a single unit in Amazon and when they position things, it's now that spectrum of unit, everything from the serverless through the containers, through... James Hamilton wrote a blog post today about running Xen-on-Nitro and they have a migration service for a mainframe. So what do we know? That one of the only things about IT is almost nothing ever goes away. I mean, it sounded like Amazon declared coming soon the end of life of mainframe. My friends over at IBM might not be quite ready to call that era over but we shall see. All these things take time. Everything in IT is additive. I'm happy to see. It is very much usually an end world when I look at the container and Kubernetes space. That is something that you can have a broad spectrum of applications. So some of my more monolithic applications can move over, my cool new data, AI things, I can build on it, microservices in between. And so, it's a broad platform that spans the cloud, the edge, the data center. So that cloud operating model is easier to have consistency all the places that I go. >> Mainframe is in the cloud. Well, we'll see. Big banks by the next site unseen. So I think Amazon will be able to eat away at the edges of that, but I don't think there's going to be a major migration. They claim it. Their big thing is that you can't get COBOL programmers. So I'm like, "Yeah, call DXC, you'll get plenty." Let's talk about something more interesting. (Stu laughs softly) So the last 10 years was a lot of, a lot about IT transformation and there was a lot more room to grow there. I mean, the four big hyperscalers are going to do 120 billion this year. They're growing at 35%. Maybe it's not a trillion, but there's a $500 billion market that they're going after, maybe more. It looks like there's a real move. You saw that with NASDAQ, the Goldman deal, to really drive into business, deeper business integration in addition to IT transformation. So how do you see the next decade of cloud? What should we be watching? >> So, one of the interesting trends, I mean, Dave, for years we covered big data and big data felt very horizontal in it's approach thing. Hadoop take over the world. When I look at AI solutions, when I look at the edge computing technologies that happen, they're very vertically driven. So, our early customers in edge adoption tend to be like telco with the 5G rollout manufacturing in some of their environments. AI, every single industry has a whole set of use cases that they're using that go very deep. So I think cloud computing goes from, we talked about infrastructure as a service to it needs to be more, it is solution, some of these pieces go together. When Adam got up on stage and talked about how many instance types they have on Amazon, Dave, it's got to be 2X or 4X more different instant types than if I went to go to HPE or Dell and buy a physical server for my environment. So we need to have areas and guidance and blueprints and heck, use some of that ML and AI to help drive people to the right solutions because we definitely have the paradox of choice today. So I think you will find some gravity moving towards some of these environments. Gravatar has been really interesting to watch. Obviously that Annapurna acquisition should be down as one of the biggest ones in the cloud era. >> No lack of optionality to your point. So I guess to the point of deeper business integration, that's the big question, will Amazon provide more solution abstractions? They certainly do with Connect. We didn't hear a ton of that this show. >> Interestingly. (Dave speaking indistinctly) So the article that you and John Furrier wrote after meeting with Adam, the thing that caught my eye is discussion of community and ecosystems. And one of the things coming after, some, big communities out there like, you and I lived through the VMware ecosystem in that very tight community. There are forming little areas of community here in this group, but it's not a single cloud community. There are those focus areas that they have. And I do love to see, I mean, obviously working for Red Hat, talking about the ecosystem support. I was very happy to hear Adam mention Red Hat in the keynote as one of the key hybrid partners there. So, for Amazon to get from the 60 million, the 60 billion to the trillion dollar mark down the road, it's going to take a village and we're happy to be a part of it. >> Hey, great to have you back, enjoy the rest of the show. This is, let's see, day three, we're wrapping up. We're here again tomorrow so check it out. Special thanks to obviously AWS is our anchor sponsor and of course, AMD for sponsoring the editorial segments of our event. You're watching theCUBE, the leader in tech coverage. See you tomorrow. (bright upbeat music)

(upbeat music) >> The innovation around databases has exploded over the last few years. Not only do organizations continue to rely on database technology to manage their most mission critical business data. But new use cases have emerged that process and analyze unstructured data. They share data at scale, protect data, provide greater heterogeneity. New technologies are being injected into the database equation. Not just cloud which has been a huge force in the space, but also AI to drive better insights and automation, blockchain to protect data and provide better auditability, new file formats to expand the utility of database technology and more. Debates are bound as to who's the best number one, the fastest, the most cloudy, the least expensive, et cetera. But there is no debate, when it comes to leadership and mission critical database technologies. That status goes to Oracle. And with me to talk about the developments of database technology in the market is cube alum Juan Loaiza, who's executive vice president of Mission Critical Database Technology at Oracle. Juan always great to see you, thanks for making some time. >> Thanks, great to see you Dave, always a pleasure to join you. >> Yeah and I hope you have some time because they've got a lot of questions for you. (chuckles) I want to start with- >> All right I love questions. >> Good I want to start and we'll go deep if you're up for it. I want to start with the GoldenGate announcement. We're covering that recent announcement, the service on OCI. GoldenGate it's part of this your super high availability capabilities that Oracle is so well known for. What do we need to know about the new service and what it brings for your customers? >> Yeah, so first of all, GoldenGate is all about creating real time data throughout an enterprise. So it does replication, data integration, moving data into analytic workloads, streaming analytics of data, migrating of databases and making databases highly available. All those are use cases for real-time data movement. And GoldenGate is really the leading product in the market, has been for many years. We have about 80% of the global fortune 500 running GoldenGate today, in addition to thousands and thousands of smaller customers. So it is the premier data integration, replication, high availability, anything involving moving data in real time, GoldenGate is the premier platform. And so we've had that available as a product for many years. And what we just recently done is we've released it as a cloud service, as a fully managed and automated cloud service. So that's kind of the big new thing that's happening right now. >> So is that what's unique about this, is it's now a service, or there are other attributes that are unique to Oracle? >> Yeah, so the service is kind of the most basic part to it. But the big thing about the service is it makes this product dramatically easier to use. So traditionally the data integration, replication products, although very powerful, also are very complex to use. And one of the big benefits of the service is we've made a dramatically simpler. So not just super experts can use it, but anyone can use it. And also as part of releasing it as a cloud service, we've done a number of unique things including making it completely elastically scalable, pay per use and dynamic scalability. So just in time, real time scalability. So as your workload increases we automatically increase the throughput of GoldenGate. So previously you had to figure all this stuff out ahead of time. It was very static. All these products have been very static. Now it's completely dynamic a native cloud product and that's very unique in the market. >> So, I mean, from an availability standpoint, I guess IBM sort of has this with Db2 but it doesn't offer the heterogeneity that GoldenGate has. But at what about like AWS, Microsoft, Google, do they provide services like, like GoldenGate? >> There's really nothing like the GoldenGate service. When you're talking about people like Google and Azure, they really have do it yourself third-party products. So there'll be a third party data integration replication product, and it's kind of available in their marketplace and customers have to do everything. So it's basically a put it together, your own kit. And it's very complicated. I mean these data integration products have always been complicated, and they're even more complicated in the cloud, if you have to do everything yourself. Amazon has a product but it's really focused on basic data migration to their cloud. It doesn't have the same capabilities as Oracle has. It doesn't have the elasticity, it doesn't have pay peruse, so it's really not very clavy at all. >> Well, so I mean the biggest customers have always glommed onto GoldenGate because they need that super ultra high availability. And they're capable of do it yourself. So, tell us how this compares to two DIY. >> Yeah, so you have mentioned the big customers so you're absolutely right. The big customers have been big users of GoldenGate. Smaller customers or users as well, however, it's been challenging because it's complicated. Data integration has been a complicated area of data management. More and most complicated. And so one of the things this does, is that it expands the market. Makes it much dramatically easier for smaller companies that don't have as many it resources to use the product. Also, smaller companies obviously don't have as much data as the really large giants. So they don't have as much data throughput. So traditionally the price has been high for a small customer. But now, with pay per use in the cloud, it eliminates the two big blockers for smaller enterprises. Which are the costs, the high fixed costs and the complexity of the products. So in which, by the way, it's helpful for everyone also. And for big customers they've also struggled with elasticity. So sometimes a huge batch job will kick in, the rate of change increases and suddenly the replication product doesn't keep up. Because on-prem products aren't really very elastic. So it helps large customers as well. Everybody loves these reviews but the elasticity pay per use, on demand nature of it's really helpful for everybody. >> Well, and because it's delivered as a service I would imagine for the large customers that you're giving them more granularity, so they can apply it maybe for a single application, as opposed to trying to have to justify it across a whole suite. And because the cost is higher, but now if you're allowing me to pay by the drink, is that right? I could just sort of apply it in a more granular level. >> Yes, that's exactly right. It's really pay per use. You can use it as much or as little as you want. You just pay for what you use. And as I mentioned, it's not a static payment either. So if you have a lot of data loads going on and right now you pay a little more, at night when you have less going on, you pay a lot less. So you really just paying for what use. It's very easy to set it up for a single application or all your applications. >> How about for things like continuous replication or real-time analytics, is the service designed to support that? >> Yes, so that's the heritage of GoldenGate. GoldenGate has been around for decades and we've worked with some of the most demanding customers in the world on exactly those things. So real time data all over the enterprise is really the goal that everyone wants. Real-time data from OTP and to analytics, from one system to another system, and for availability. That is the key benefit of GoldenGate. And that's the key technology that we've been working on for decades. And now we have it very easy to use in the cloud. >> Well what would be the overheads associated with that? I mean, for instance, you've go it, you need a second copy. You need the other database copies, and where does it make sense to incur that overhead? Obviously the super high availability apps that can exploit real time. Think like fraud detection is the obvious one, but what else can you add there? >> Well, GoldenGate itself doesn't require any extra copies of anything. However, it does enable customers that want to create for example, an analytics system, a data warehouse, to feed data from all their systems in real time into that data warehouse for example. And it also enables the real-time capabilities, enable high availability and you can get high availability within the cloud with it, between on premises in the cloud, between clouds. Also, you can migrate data. Migrate databases without having to take them down. So all these capabilities are available now and they're very easy to use. >> Okay. Thanks for that clarification. What about autonomous? Is that on the roadmap or what you thinking? >> Yeah, the GoldenGate is essentially an autonomous service. And it works with the Oracle Autonomous Database. So you can both use it as a source for data and as a sink for data, as a place you're writing data. So for example, you can have an autonomous OTP database, that's replicating to another autonomous OTP database in real time. And both of them are replicating changes to the autonomous data warehouse. But it doesn't all have to be autonomous. You can have any mix of, autonomous not autonomous, on-prem in cloud, in anybody's cloud. So that's the beauty of GoldenGate, It's extremely flexible. >> Well, you mentioned the plasticity a couple of times. I mean, why is that so important that that GoldenGate on OCI gives you that elastic, whatever billing the auto-scaling talk, talk to me in terms of what that does for the customer. >> Yeah, there's really two big benefits. One benefit is it's very difficult to predict workloads. So normally on an on-prem configuration, you have to say, okay what is the max possible workload that's going to happen here? And then you have to buy the product, configure the product, get hardware, basically size, everything for that. And then if you guess wrong, you're either spending too much because you oversized it or you have a big data real-time problem. The data can't keep up with the real-time because you've undersized the configuration. So that's hard to do. So the beauty of elasticity and the dynamic elasticity, the pay per use, is you don't have to figure all this stuff out. So if you have more workload, we grow it automatically. If you have less workload, we shrink it automatically. And you don't have to guess ahead of time. You don't have to price ahead of time. So you, you just use what, what you use, right? You don't pay for something that you're not using. So it's a very big change in the whole model of how you use these data, replication, integration, high availability technologies. >> Well, I think I'm correct to say GoldenGate primarily has been for big companies. You mentioned that small companies can now take advantage of this service. We talked about the granularity. And I could definitely see, can they afford it? I guess this is part one and then, and then the other part of the question is, I can see GoldenGate really satisfying your on-prem customers and them taking advantage of it, but do you think this will attract new customers beyond your core? So two part question there. >> Yeah, absolutely. So small customers have been challenged by the complexity of data integration. And that's one of the great things about the cloud services is it's dramatically simpler. So Oracle manages everything. Oracle does the patching, the upgrades. Oracle does the monitoring. It takes care of the high availability of the product. So all that management, complexity, all the configuration set up, everything like that, that's all automated, that's owned by Oracle. So small customers were always challenged by the complexity of product, along with everything else that they had to do. And then the other of course benefit is small customers were challenged by the large fixed price. So now with pay per use, they pay only for what they use. It's really usable by easily by small customers also. So it really expands the market and makes it more broadly applicable. >> So kind of same answer for beyond your existing customer base, beyond the on-prem that that's kind of... You answered >> Right. >> my two part question with one answer, so that was pretty efficient, (chuckles) pun intended. So the bottom line for me and squinting through this announcement is you've got the heterogeneity piece with GoldenGate OCI and as such it's going to give you the capability to create what I'll call an architecturally coherent decentralized data mesh. Big on this data mesh these days, could have decentralized data. With the proviso then I going to be able to connect to OCI, which of course you can do with Azure or I guess you could bring cloud to a customer on prem, first of all, is this correct? And can we expect you over time to do this with AWS or other cloud providers? >> It can move data from Amazon or to Amazon. It can actually handle, any data wherever it lives. So, yeah, it's very flexible and it's really just the automation of all the management, that we're running in our public cloud But the data can be from anywhere to anywhere. >> Cool, all right, let's switch topics here a little bit. Just talk about some of the things that you've been working on, some of the innovation. I sat through your blockchain announcement, it was very cool. Of course I love anything blockchain and crypto, NFTs are exploding, so that Coinbase IPO. It's just really an exciting time out there. I think a lot of people don't really appreciate the innovation that's occurring. So you've been making a lot of big announcements last several months. You've been taking your R and D bringing it into product, So that's great, we love to always see that because that's where really the rubber meets the road. Just for the database side of the house, you announced 21c the next generation of the self-driving data warehouse, ADW, blockchain tables, now you got GoldenGate running on OCI. Take us inside the development organizations. What are the underlying drivers other than your boss. >> When we talk about our autonomous database, it is the mission critical Oracle database, but it's dramatically easier to do. So Oracle does all the management all on automation, but also we use machine learning to tune, and to make it highly available, and to make it highly secure. So that that's been one of our biggest products we've been working on for many years. And recently we enhanced our autonomous data warehouse taking it beyond being a data warehouse to complete a data analytics platform. So it includes things like ETL. So we built ETL into the autonomous data warehouse. We're building our GoldenGate replication into autonomous data warehousing. We built machine learning directly natively into the database. So now, if someone wants to run some machine learning they just run a machine learning queries. They no longer have to stand up a separate system. So a big move that we've been making is, taking it beyond just a database to a full analytic platform. And this goes beyond what anyone else in the industry is doing, because we have a lot more technology. So for example, the ML machine learning directly in the database, the ETL directly in the database. The data replication is directly in the database. All these things are very unique to Oracle. And they dramatically simplify for customers how they manage data. In addition to that, we've also been working in our database product. We've enhanced it tremendously. So our big goal there is to provide what we call it converged database. So everything you need, all the data types. Whether it's JSON, relational, spatial, graph, all that different kinds of data types, all the different kinds of workloads. Analytics, OTP, things like blockchain, microservices events, all built into the Oracle database, making it dramatically easier to both develop and deploy new applications. So those are some of our big, big goals. Make it simple, make it integrated. Take the complexity, we'll take on the complexity. So developers and customers find it easy to develop an easy to use. And we've made huge strides in all these areas in the last couple of years. >> That's awesome. I wonder if we could land on blockchain again for now it's kind of jogging, but sort of on crypto. Though you're not about crypto but you are about applying blockchain. Maybe you can help our audience understand what are some of the real use cases where blockchain tech can be used with Oracle database. >> Yeah, so that's a very interesting topic. As you mentioned, blockchain is very currently, we see a lot of cryptocurrencies. I distributed applications for blockchain. So in general, in the past, we've had two worlds. We've had the enterprise data management world and we've had the blockchain world. And these are very distinct, right? And on the blockchain side the applications have mostly centered around, distributed multi-party applications, right? So where you have multiple parties that all want to reach consensus and then that consensus is stored in a blockchain. So that's kind of been the focus of blockchain. And what we've done is very innovative. We're the first company to ever do this. Is we've taken the core architecture, ideas. And really a lot of it has to do with the cryptography of blockchain. And we've built, we've engineered that natively into the mainstream Oracle database. So now in mainstream Oracle database, we have blockchain technology built in. And it's very dramatically simpler to use. And the use cases, you asked about the use case, that's what we've done. And it's taken us about five years to do this. Now it's been released into the market in our mainstream 19c Oracle database. So the use case is different from the conventional blockchain use case. Which I mentioned was really multi-party consensus based apps. We're trying to make blockchain useful for mainstream, enterprise and government applications. So any kind of mainstream government application, or enterprise application. And that idea of blockchain, the core concept of blockchain, is it addresses a different kind of security problem. So when you look at conventional security, it's really trying to keep people out. So we have things like firewalls, passwords, networking cryption, data encryption. It's all about keeping bad people out of the data. And there's really two big problems that it doesn't address well. One problem is that there's always new security exploits being published. So you have hackers out there that are working overtime. Sometimes they're nation States that are trying to attack data providers. And every week, every month there's a new security exploit that's discovered and this happens all the time. So that's one big problem. So we're building up these elaborate walls of protection around our core data assets. And in the meantime, we have basically barbarians attacking on every side.(chuckles) And every once in a while, they get over the walls and this is just what's happening. So that's one big problem. And the second big problem is elicit changes made by people with credentials. So sometimes you have an insider in your, in your company. Whether it's an administrator or a sales person, a support person, that has valid credentials, but then uses those valid credentials in some illicit way. They go out and change somebody's data for their own gain. And even more common than that cause there's not that many bad guys inside the company to they exist, is stolen credentials. So what's happened in many cases is hackers or nation States will steal for example, administrative credentials and then use those administrative credentials to come into a system and steal data. So that's the kind of problem that is not well addressed by security mechanism. So if you have privileges security mechanism says, yeah you're fine. If somebody steals your privileges, again you get the pass through the gate. And so what we've done with blockchain is we've taken the cryptography elements of blockchain. We call it crypto secure data management. And we've built those into the Oracle database. So think of it this way. If someone actually makes it through over the walls that we built, and in into the core data, what we've done with that cryptographic technology of blockchain, is we've made that immutable. So you can't change it. So even if you make it over the gate you can't get into the core data assets and change those assets. And that's not built into Oracle databases is super easy to adopt. And I think it's going to really enhance and expand the community of people that can actually use that blockchain technology. >> I mean, that's awesome. I could talk all day about blockchain. And I mean, when you think about hackers, it's all there. They're all about ROI, value over cost. And if you can increase the denominator they're going to go somewhere else, right? Because the value will will decline. And this is really the intersection of software engineering cryptography. And I guess even when you bring crypto currency into it, it's like sort of the game theory. That's really kind of not what you're all about, but the first two pieces are really critical in terms of just next generation of raising that security hurdle. Love it. Now, go ahead. >> Yeah it's a different approach. I was just going to say, it's a different approach. Because think about trying to keep people out with things like passwords and firewalls, you can have basically bugs in that software that allow people to exploit and get in. When you're talking about cryptography, that's math, it's very difficult. I mean, you really can't fight pass math. Once the data is cryptographically protected on a blockchain, a hacker can't really do anything with that. It's just, math is math. There's nothing you can do to break it, right. It's very different from trying to get through some algorithm. That's really trying to keep you out. >> Awesome. I said, I could talk forever on this topic. But let me, let me go into some competitive dynamics. You recently announced Autonomous Data Warehouse. You've got service capabilities that are really trying to appeal to the line of business. I want to get your take on that announcement and specifically how you think it compares name names. I'm going to name names you don't have to. But Snowflake, obviously a lot of momentum in the marketplace. AWS with Redshift is doing very, very well. Obviously there are others. But those are two prominent ones that we've tracked in our data shows that have momentum. How do you compare? >> Yeah, so there's a number of different ways to look at the comparison. So the most simplest and straightforward is there's a lot more functionality in Oracle data warehousing. Oracle has been doing this for decades. We have a lot of built-in functionality. For example, machine learning natively built into the database makes it super easy to use. We have mixed workloads, we have spatial capabilities. We have graph capabilities. We have JSON capabilities. We have a microservice capabilities. We have-- So there's a lot more capabilities. So that's number one. Number two, our cloud service is dramatically more elastic. So with our cloud service all you really do, is you basically move the slide. You say hey, I want more resources, I want less resources. In fact, we'll do that automatically, that's called auto-scaling. In contrast when you look at people like Snowflake or Redshift they want you to stand up a new cluster. Hey you have some more workload on Monday, stand up another cluster and then we'll have two sets of clusters or maybe you'd want a third cluster, maybe you want a fourth cluster. So you end up with all these different systems which is how they scale. They say, hey, I can have multiple sets of servers access the same data. With Oracle you don't have to even think about those things. We auto scale, you get more workload. We just give it more resources. You don't even have to think about that. And then the other thing is we're looking at the whole data management end to end problem. So starting with capturing the data, moving the data in real time, transforming the data, loading the data, running machine learning and analytics on the data. Putting all kinds of data in a single place that you can do analytics on all of it together. And then having very rich screen capabilities for viewing the data, graphing the data, modeling the data, all those things. So it's all integrated. It makes it super easy to use. So a much easier, much more functionality and much more elastic than any of our competitors in the market. >> Interesting, thank you for those comments. I mean, it's a different world, right? I mean, you guys got all the market share, they got all the growth, those things over time, you've been around, you see it, they come together and you fight it out and may the best approach wins. >> So we'll be watching >> Yeah also I forgot to mention the obvious thing, which is Oracle runs everywhere. So you can run Oracle on premises. You can run Oracle on the public cloud. You can run what we call cloud at customer. Our competitors really are just public cloud only. So you customers don't get the choice of where they want to run their data warehouse. >> Now Juan a while ago I sat down with David foyer and Mark steamer. We reviewed how Gartner looks at the marketplace and it wasn't surprise that when it came to operational workloads, Oracle stood out. I mean, that's kind of an understatement relative to the major competitors. Most of our viewers, I don't think expected for instance Microsoft or AWS to be that far away from you. But at the same time, the database magic quadrant maybe didn't reflect that gap as widely. So there's some dissonance there with the detailed workload drill downs were dramatic. And I wonder what your take on the results. I mean, obviously you're happy with them. You came out leading in virtually every category or you will one and two, and some of that sort of not even non-mission critical operational stuff. But what can you add to my narrative there? >> Yeah, so Gartner, first of all, we're talking about cloud databases. >> Right. >> Right, so this is not on premises databases this is pure cloud databases. And what they did is they did two things. One is, the main thing was a technical rating of the databases, of the cloud databases. And, there's other vendors that have been had database in the cloud for longer than we have. But in the most recent Gartner analysis report, as you mentioned, Oracle came out on top for cloud database technology, in almost every single operational use case including things like Internet of Things, things like JSON data, variable data, analytics as well as a traditional OTP and mixed workloads. So Oracle was rated the highest technology which isn't a big surprise. We've been doing this for decades. Over 90% of the global fortune 500 run Oracle. And there's a reason, because this is what we're good at. This our core strength. Our availability, our security, our scalability, our functionality, both for OTP and analytics. All the capabilities, built-in machine learning, graph analytics, everything. So even when we compare narrowly things like Internet of Things or variable data against niche competitors that that's what all they do. We came up dramatically ahead. But what surprised a lot of people is how far ahead of some of the other cloud vendors like Amazon, like Azure, like Google, Oracle came out ahead in the cloud database category. So a lot of people think, well, some of these other pure cloud vendors must be ahead of Oracle in cloud database. But actually not. I mean, if you look at the Gartner analyst report, it was very clear. It was Oracle was dramatically ahead of their cloud database technologies with our cloud database. >> So I'm pretty much out of time but last question. I've had some interesting discussions lately and we've pointed out for years in our research that of course you're delivering the entire stack, the database, part of the infrastructure the applications, you have the whole engineered system strategy. And for the most part you're kind of unique in this regard. I mean, Dell just announced that it's spinning off VMware and it could have gone the other direction. And become more integrated hardware and software player, for the data center. But look, it's working for Dell based on the reaction, from the street post announcement. Cisco they got a hardware and software model that's sort of integrated but the company's value that peaked back in the .com boom, it's been very slow to bounce back. But my point is for these companies the street doesn't value, the integrated model. Oracle is kind of the exception. You know, it's at trading at all time highs, I know you're not going to comment on the stock price, but I guess in SAP until it missed it guided conservatively, was kind of on the good trajectory. But so I'm wondering, why do you think Oracle strategy resonates with investors, but not so much those companies? Is it, because you have the applications piece? I mean, maybe that's kind of my premise for, for SAP but what's your take? Why is it working for you? >> Well, okay. I think it's pretty simple, which is some of our competitors, for example, they might have a software product and a hardware product. But mostly those are acquired in their separate products that just happen to be in a portfolio. They are not a single company with a single vision and joint engineering going on. It's really, hey, I got the software on over here. I got the hardware over there, but they don't really talk to each other, they don't really work together. They're not trying to develop something where the stack is actually not just integrated but engineered together. And that is really the key. Oracle focuses on data management top to bottom. So we have everything from our ERP, CRM applications talking to our database, talking to our engineered systems, running in our cloud. And it's all completely engineered together. So Oracle doesn't just acquire these things and kind of glue them together. We actually engineer them and that's fundamentally the difference. You can buy two things and have them as two separate divisions in your company but it doesn't really get you a whole lot. >> Juan it's always a pleasure, I love these conversations and hope we can do more in the future. Really appreciate your time. Thanks for coming to the CUBE >> Pleasure, Dave nice to talk to you. >> All right keep it right there, everybody. This is Dave Vellante for theCUBE, we'll see you next time. (upbeat musiC)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> Moore's Law is dead, right? Think again. Massive improvements in processing power combined with data and AI will completely change the way we think about designing hardware, writing software and applying technology to businesses. Every industry will be disrupted. You hear that all the time. Well, it's absolutely true and we're going to explain why and what it all means. Hello everyone, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we're going to unveil some new data that suggests we're entering a new era of innovation that will be powered by cheap processing capabilities that AI will exploit. We'll also tell you where the new bottlenecks will emerge and what this means for system architectures and industry transformations in the coming decade. Moore's Law is dead, you say? We must have heard that hundreds, if not, thousands of times in the past decade. EE Times has written about it, MIT Technology Review, CNET, and even industry associations that have lived by Moore's Law. But our friend Patrick Moorhead got it right when he said, "Moore's Law, by the strictest definition of doubling chip densities every two years, isn't happening anymore." And you know what, that's true. He's absolutely correct. And he couched that statement by saying by the strict definition. And he did that for a reason, because he's smart enough to know that the chip industry are masters at doing work arounds. Here's proof that the death of Moore's Law by its strictest definition is largely irrelevant. My colleague, David Foyer and I were hard at work this week and here's the result. The fact is that the historical outcome of Moore's Law is actually accelerating and in quite dramatically. This graphic digs into the progression of Apple's SoC, system on chip developments from the A9 and culminating with the A14, 15 nanometer bionic system on a chip. The vertical axis shows operations per second and the horizontal axis shows time for three processor types. The CPU which we measure here in terahertz, that's the blue line which you can't even hardly see, the GPU which is the orange that's measured in trillions of floating point operations per second and then the NPU, the neural processing unit and that's measured in trillions of operations per second which is that exploding gray area. Now, historically, we always rushed out to buy the latest and greatest PC, because the newer models had faster cycles or more gigahertz. Moore's Law would double that performance every 24 months. Now that equates to about 40% annually. CPU performance is now moderated. That growth is now down to roughly 30% annual improvements. So technically speaking, Moore's Law as we know it was dead. But combined, if you look at the improvements in Apple's SoC since 2015, they've been on a pace that's higher than 118% annually. And it's even higher than that, because the actual figure for these three processor types we're not even counting the impact of DSPs and accelerator components of Apple system on a chip. It would push this even higher. Apple's A14 which is shown in the right hand side here is quite amazing. It's got a 64 bit architecture, it's got many, many cores. It's got a number of alternative processor types. But the important thing is what you can do with all this processing power. In an iPhone, the types of AI that we show here that continue to evolve, facial recognition, speech, natural language processing, rendering videos, helping the hearing impaired and eventually bringing augmented reality to the palm of your hand. It's quite incredible. So what does this mean for other parts of the IT stack? Well, we recently reported Satya Nadella's epic quote that "We've now reached peak centralization." So this graphic paints a picture that was quite telling. We just shared the processing powers exploding. The costs consequently are dropping like a rock. Apple's A14 cost the company approximately 50 bucks per chip. Arm at its v9 announcement said that it will have chips that can go into refrigerators. These chips are going to optimize energy usage and save 10% annually on your power consumption. They said, this chip will cost a buck, a dollar to shave 10% of your refrigerator electricity bill. It's just astounding. But look at where the expensive bottlenecks are, it's networks and it's storage. So what does this mean? Well, it means the processing is going to get pushed to the edge, i.e., wherever the data is born. Storage and networking are going to become increasingly distributed and decentralized. Now with custom silicon and all that processing power placed throughout the system, an AI is going to be embedded into software, into hardware and it's going to optimize a workloads for latency, performance, bandwidth, and security. And remember, most of that data, 99% is going to stay at the edge. And we love to use Tesla as an example. The vast majority of data that a Tesla car creates is never going to go back to the cloud. Most of it doesn't even get persisted. I think Tesla saves like five minutes of data. But some data will connect occasionally back to the cloud to train AI models and we're going to come back to that. But this picture says if you're a hardware company, you'd better start thinking about how to take advantage of that blue line that's exploding, Cisco. Cisco is already designing its own chips. But Dell, HPE, who kind of does maybe used to do a lot of its own custom silicon, but Pure Storage, NetApp, I mean, the list goes on and on and on either you're going to get start designing custom silicon or you're going to get disrupted in our view. AWS, Google and Microsoft are all doing it for a reason as is IBM and to Sarbjeet Johal said recently this is not your grandfather's semiconductor business. And if you're a software engineer, you're going to be writing applications that take advantage of all the data being collected and bringing to bear this processing power that we're talking about to create new capabilities like we've never seen it before. So let's get into that a little bit and dig into AI. You can think of AI as the superset. Just as an aside, interestingly in his book, "Seeing Digital", author David Moschella says, there's nothing artificial about this. He uses the term machine intelligence, instead of artificial intelligence and says that there's nothing artificial about machine intelligence just like there's nothing artificial about the strength of a tractor. It's a nuance, but it's kind of interesting, nonetheless, words matter. We hear a lot about machine learning and deep learning and think of them as subsets of AI. Machine learning applies algorithms and code to data to get "smarter", make better models, for example, that can lead to augmented intelligence and help humans make better decisions. These models improve as they get more data and are iterated over time. Now deep learning is a more advanced type of machine learning. It uses more complex math. But the point that we want to make here is that today much of the activity in AI is around building and training models. And this is mostly happening in the cloud. But we think AI inference will bring the most exciting innovations in the coming years. Inference is the deployment of that model that we were just talking about, taking real time data from sensors, processing that data locally and then applying that training that has been developed in the cloud and making micro adjustments in real time. So let's take an example. Again, we love Tesla examples. Think about an algorithm that optimizes the performance and safety of a car on a turn, the model take data on friction, road condition, angles of the tires, the tire wear, the tire pressure, all this data, and it keeps testing and iterating, testing and iterating, testing iterating that model until it's ready to be deployed. And then the intelligence, all this intelligence goes into an inference engine which is a chip that goes into a car and gets data from sensors and makes these micro adjustments in real time on steering and braking and the like. Now, as you said before, Tesla persist the data for very short time, because there's so much of it. It just can't push it back to the cloud. But it can now ever selectively store certain data if it needs to, and then send back that data to the cloud to further train them all. Let's say for instance, an animal runs into the road during slick conditions, Tesla wants to grab that data, because they notice that there's a lot of accidents in New England in certain months. And maybe Tesla takes that snapshot and sends it back to the cloud and combines it with other data and maybe other parts of the country or other regions of New England and it perfects that model further to improve safety. This is just one example of thousands and thousands that are going to further develop in the coming decade. I want to talk about how we see this evolving over time. Inference is where we think the value is. That's where the rubber meets the road, so to speak, based on the previous example. Now this conceptual chart shows the percent of spend over time on modeling versus inference. And you can see some of the applications that get attention today and how these applications will mature over time as inference becomes more and more mainstream, the opportunities for AI inference at the edge and in IOT are enormous. And we think that over time, 95% of that spending is going to go to inference where it's probably only 5% today. Now today's modeling workloads are pretty prevalent and things like fraud, adtech, weather, pricing, recommendation engines, and those kinds of things, and now those will keep getting better and better and better over time. Now in the middle here, we show the industries which are all going to be transformed by these trends. Now, one of the point that Moschella had made in his book, he kind of explains why historically vertically industries are pretty stovepiped, they have their own stack, sales and marketing and engineering and supply chains, et cetera, and experts within those industries tend to stay within those industries and they're largely insulated from disruption from other industries, maybe unless they were part of a supply chain. But today, you see all kinds of cross industry activity. Amazon entering grocery, entering media. Apple in finance and potentially getting into EV. Tesla, eyeing insurance. There are many, many, many examples of tech giants who are crossing traditional industry boundaries. And the reason is because of data. They have the data. And they're applying machine intelligence to that data and improving. Auto manufacturers, for example, over time they're going to have better data than insurance companies. DeFi, decentralized finance platforms going to use the blockchain and they're continuing to improve. Blockchain today is not great performance, it's very overhead intensive all that encryption. But as they take advantage of this new processing power and better software and AI, it could very well disrupt traditional payment systems. And again, so many examples here. But what I want to do now is dig into enterprise AI a bit. And just a quick reminder, we showed this last week in our Armv9 post. This is data from ETR. The vertical axis is net score. That's a measure of spending momentum. The horizontal axis is market share or pervasiveness in the dataset. The red line at 40% is like a subjective anchor that we use. Anything above 40% we think is really good. Machine learning and AI is the number one area of spending velocity and has been for awhile. RPA is right there. Very frankly, it's an adjacency to AI and you could even argue. So it's cloud where all the ML action is taking place today. But that will change, we think, as we just described, because data's going to get pushed to the edge. And this chart will show you some of the vendors in that space. These are the companies that CIOs and IT buyers associate with their AI and machine learning spend. So it's the same XY graph, spending velocity by market share on the horizontal axis. Microsoft, AWS, Google, of course, the big cloud guys they dominate AI and machine learning. Facebook's not on here. Facebook's got great AI as well, but it's not enterprise tech spending. These cloud companies they have the tooling, they have the data, they have the scale and as we said, lots of modeling is going on today, but this is going to increasingly be pushed into remote AI inference engines that will have massive processing capabilities collectively. So we're moving away from that peak centralization as Satya Nadella described. You see Databricks on here. They're seen as an AI leader. SparkCognition, they're off the charts, literally, in the upper left. They have extremely high net score albeit with a small sample. They apply machine learning to massive data sets. DataRobot does automated AI. They're super high in the y-axis. Dataiku, they help create machine learning based apps. C3.ai, you're hearing a lot more about them. Tom Siebel's involved in that company. It's an enterprise AI firm, hear a lot of ads now doing AI and responsible way really kind of enterprise AI that's sort of always been IBM. IBM Watson's calling card. There's SAP with Leonardo. Salesforce with Einstein. Again, IBM Watson is right there just at the 40% line. You see Oracle is there as well. They're embedding automated and tele or machine intelligence with their self-driving database they call it that sort of machine intelligence in the database. You see Adobe there. So a lot of typical enterprise company names. And the point is that these software companies they're all embedding AI into their offerings. So if you're an incumbent company and you're trying not to get disrupted, the good news is you can buy AI from these software companies. You don't have to build it. You don't have to be an expert at AI. The hard part is going to be how and where to apply AI. And the simplest answer there is follow the data. There's so much more to the story, but we just have to leave it there for now and I want to summarize. We have been pounding the table that the post x86 era is here. It's a function of volume. Arm volumes are a way for volumes are 10X those of x86. Pat Gelsinger understands this. That's why he made that big announcement. He's trying to transform the company. The importance of volume in terms of lowering the cost of semiconductors it can't be understated. And today, we've quantified something that we haven't really seen much of and really haven't seen before. And that's that the actual performance improvements that we're seeing in processing today are far outstripping anything we've seen before, forget Moore's Law being dead that's irrelevant. The original finding is being blown away this decade and who knows with quantum computing what the future holds. This is a fundamental enabler of AI applications. And this is most often the case the innovation is coming from the consumer use cases first. Apple continues to lead the way. And Apple's integrated hardware and software model we think increasingly is going to move into the enterprise mindset. Clearly the cloud vendors are moving in this direction, building their own custom silicon and doing really that deep integration. You see this with Oracle who kind of really a good example of the iPhone for the enterprise, if you will. It just makes sense that optimizing hardware and software together is going to gain momentum, because there's so much opportunity for customization in chips as we discussed last week with Arm's announcement, especially with the diversity of edge use cases. And it's the direction that Pat Gelsinger is taking Intel trying to provide more flexibility. One aside, Pat Gelsinger he may face massive challenges that we laid out a couple of posts ago with our Intel breaking analysis, but he is right on in our view that semiconductor demand is increasing. There's no end in sight. We don't think we're going to see these ebbs and flows as we've seen in the past that these boom and bust cycles for semiconductor. We just think that prices are coming down. The market's elastic and the market is absolutely exploding with huge demand for fab capacity. Now, if you're an enterprise, you should not stress about and trying to invent AI, rather you should put your focus on understanding what data gives you competitive advantage and how to apply machine intelligence and AI to win. You're going to be buying, not building AI and you're going to be applying it. Now data as John Furrier has said in the past is becoming the new development kit. He said that 10 years ago and he seems right. Finally, if you're an enterprise hardware player, you're going to be designing your own chips and writing more software to exploit AI. You'll be embedding custom silicon in AI throughout your product portfolio and storage and networking and you'll be increasingly bringing compute to the data. And that data will mostly stay where it's created. Again, systems and storage and networking stacks they're all being completely re-imagined. If you're a software developer, you now have processing capabilities in the palm of your hand that are incredible. And you're going to rewriting new applications to take advantage of this and use AI to change the world, literally. You'll have to figure out how to get access to the most relevant data. You have to figure out how to secure your platforms and innovate. And if you're a services company, your opportunity is to help customers that are trying not to get disrupted are many. You have the deep industry expertise and horizontal technology chops to help customers survive and thrive. Privacy? AI for good? Yeah well, that's a whole another topic. I think for now, we have to get a better understanding of how far AI can go before we determine how far it should go. Look, protecting our personal data and privacy should definitely be something that we're concerned about and we should protect. But generally, I'd rather not stifle innovation at this point. I'd be interested in what you think about that. Okay. That's it for today. Thanks to David Foyer, who helped me with this segment again and did a lot of the charts and the data behind this. He's done some great work there. Remember these episodes are all available as podcasts wherever you listen, just search breaking it analysis podcast and please subscribe to the series. We'd appreciate that. Check out ETR's website at ETR.plus. We also publish a full report with more detail every week on Wikibon.com and siliconangle.com, so check that out. You can get in touch with me. I'm dave.vellante@siliconangle.com. You can DM me on Twitter @dvellante or comment on our LinkedIn posts. I always appreciate that. This is Dave Vellante for theCUBE Insights powered by ETR. Stay safe, be well. And we'll see you next time. (bright music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is Braking Analysis with Dave Vellante. >> Intel's big announcement this week underscores the threat that the United States faces from China. The US needs to lead in semiconductor design and manufacturing. And that lead is slipping because Intel has been fumbling the ball over the past several years, a mere two months into the job, new CEO Pat Gelsinger wasted no time in setting a new course for perhaps, the most strategically important American technology company. We believe that Gelsinger has only shown us part of his plan. This is the beginning of a long and highly complex journey. Despite Gelsinger's clear vision, his deep understanding of technology and execution ethos, in order to regain its number one position, Intel we believe we'll need to have help from partners, competitors and very importantly, the US government. Hello everyone and welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis we'll peel the onion Intel's announcement of this week and explain why we're perhaps not as sanguine as was Wall Street on Intel's prospects. And we'll lay out what we think needs to take place for Intel to once again, become top gun and for us to gain more confidence. By the way this is the first time we're broadcasting live with Braking Analysis. We're broadcasting on the CUBE handles on Twitch, Periscope and YouTube and going forward we'll do this regularly as a live program and we'll bring in the community perspective into the conversation through chat. Now you may recall that in January, we kind of dismissed analysis that said Intel didn't have to make any major strategic changes to its business when they brought on Pat Gelsinger. Rather we said the exact opposite. Our view at time was that the root of Intel's problems could be traced to the fact that it wasn't no longer the volume leader. Because mobile volumes dwarf those of x86. As such we said that Intel couldn't go up the learning curve for next gen technologies as fast as its competitors and it needed to shed its dogma of being highly vertically integrated. We said Intel needed to more heavily leverage outsourced foundries. But more specifically, we suggested that in order for Intel to regain its volume lead, it needed to, we said at the time, spin out its manufacturing, create a joint venture sure with a volume leader, leveraging Intel's US manufacturing presence. This, we still believe with some slight refreshes to our thinking based on what Gelsinger has announced. And we'll talk about that today. Now specifically there were three main pieces and a lot of details to Intel's announcement. Gelsinger made it clear that Intel is not giving up its IDM or integrated device manufacturing ethos. He called this IDM 2.0, which comprises Intel's internal manufacturing, leveraging external Foundries and creating a new business unit called Intel Foundry Services. It's okay. Gelsinger said, "We are not giving up on integrated manufacturing." However, we think this is somewhat nuanced. Clearly Intel can't, won't and shouldn't give up on IDM. However, we believe Intel is entering a new era where it's giving designers more choice. This was not explicitly stated. However we feel like Intel's internal manufacturing arm will have increased pressure to serve its designers in a more competitive manner. We've already seen this with Intel finally embracing EUV or extreme ultraviolet lithography. Gelsinger basically said that Intel didn't lean into EUV early on and that it created more complexity in its 10 nanometer process, which dominoed into seven nanometer and as you know the rest of the story and Intel's delays. But since mid last year, it's embraced the technology. Now as a point of reference, Samsung started applying EUV for its seven nanometer technology in 2018. And it began shipping in early 2020. So as you can see, it takes years to get this technology into volume production. The point is that Intel realizes it needs to be more competitive. And we suspect, it will give more freedom to designers to leverage outsource manufacturing. But Gelsinger clearly signaled that IDM is not going away. But the really big news is that Intel is setting up a new division with a separate PNL that's going to report directly to Pat. Essentially it's hanging out a shingle and saying, we're open for business to make your chips. Intel is building two new Fabs in Arizona and investing $20 billion as part of this initiative. Now well Intel has tried this before earlier last decade. Gelsinger says that this time we're serious and we're going to do it right. We'll come back to that. This organizational move while not a spin out or a joint venture, it's part of the recipe that we saw as necessary for Intel to be more competitive. Let's talk about why Intel is doing this. Look at lots has changed in the world of semiconductors. When you think about it back when Pat was at Intel in the '90s, Intel was the volume leader. It crushed the competition with x86. And the competition at the time was coming from risk chips. And when Apple changed the game with iPod and iPhone and iPad, the volume equation flipped to mobile. And that led to big changes in the industry. Specifically, the world started to separate design from manufacturing. We now see firms going from design to tape out in 12 months versus taking three years. A good example is Tesla and his deal with ARM and Samsung. And what's happened is Intel has gone from number one in Foundry in terms of clock speed, wafer density, volume, lowest cost, highest margin to falling behind. TSMC, Samsung and alternative processor competitors like NVIDIA. Volume is still the maker of kings in this business. That hasn't changed and it confers advantage in terms of cost, speed and efficiency. But ARM wafer volumes, we estimate are 10x those of x86. That's a big change since Pat left Intel more than a decade ago. There's also a major chip shortage today. But you know this time, it feels a little different than the typical semiconductor boom and bust cycles. Semiconductor consumption is entering a new era and new use cases emerging from automobiles to factories, to every imaginable device piece of equipment, infrastructure, silicon is everywhere. But the biggest threat of all is China. China wants to be self-sufficient in semiconductors by 2025. It's putting approximately $60 billion into new chip Fabs, and there's more to come. China wants to be the new economic leader of the world and semiconductors are critical to that goal. Now there are those poopoo the China threat. This recent article from Scott Foster lays out some really good information. But the one thing that caught our attention is a statement that China's semiconductor industry is nowhere near being a major competitor in the global market. Let alone an existential threat to the international order and the American way of life. I think Scotty is stuck in the engine room and can't see the forest of the trees, wake up. Sure. You can say China is way behind. Let's take an example. NAND. Today China is at about 64 3D layers whereas Micron they're at 172. By 2022 China's going to be at 128. Micron, it's going to be well over 200. So what's the big deal? We say talk to us in 2025 because we think China will be at parody. That's just one example. Now the type of thinking that says don't worry about China and semi's reminds me of the epic lecture series that Clay Christiansen gave as a visiting professor at Oxford University on the history of, and the economics of the steel industry. Now if you haven't watched this series, you should. Basically Christiansen took the audience through the dynamics of steel production. And he asked the question, "Who told the steel manufacturers that gross margin was the number one measure of profitability? Was it God?" he joked. His point was, when new entrance came into the market in the '70s, they were bottom feeders going after the low margin, low quality, easiest to make rebar sector. And the incumbents nearly pulled back and their mix shifted to higher margin products and their gross margins went up and life was good. Until they lost the next layer. And then the next, and then the next, until it was game over. Now, one of the things that got lost in Pat's big announcement on the 23rd of March was that Intel guided the street below consensus on revenue and earnings. But the stock went up the next day. Now when asked about gross margin in the Q&A segment of the announcement, yes, gross margin is a if not the key metric in semi's in terms of measuring profitability. When asked Intel CFO George Davis explained that with the uptick in PCs last year there was a product shift to the lower margin PC sector and that put pressure on gross margins. It was a product mix thing. And revenue because PC chips are less expensive than server chips was affected as were margins. Now we shared this chart in our last Intel update showing, spending momentum over time for Dell's laptop business from ETR. And you can see in the inset, the unit growth and the market data from IDC, yes, Dell's laptop business is growing, everybody's laptop business is growing. Thank you COVID. But you see the numbers from IDC, Gartner, et cetera. Now, as we pointed out last time, PC volumes had peaked in 2011 and that's when the long arm of rights law began to eat into Intel's dominance. Today ARM wafer production as we said is far greater than Intel's and well, you know the story. Here's the irony, the very bucket that conferred volume adventures to Intel PCs, yes, it had a slight uptick last year, which was great news for Dell. But according to Intel it pulled down its margins. The point is Intel is loving the high end of the market because it's higher margin and more profitable. I wonder what Clay Christensen would say to that. Now there's more to this story. Intel's CFO blame the supply constraints on Intel's revenue and profit pressures yet AMD's revenue and profits are booming. So RTSMCs. Only Intel can't seem to thrive when there's this massive chip shortage. Now let's get back to Pat's announcement. Intel is for sure, going forward investing $20 billion in two new US-based fabrication facilities. This chart shows Intel's investments in US R&D, US CapEx and the job growth that's created as a result, as well as R&D and CapEx investments in Ireland and Israel. Now we added the bar on the right hand side from a Wall Street journal article that compares TSMC CapEx in the dark green to that of Intel and the light green. You can see TSMC surpass the CapEx investment of Intel in 2015, and then Intel took the lead back again. And in 2017 was, hey it on in 2018. But last year TSMC took the lead, again. And appears to be widening that lead quite substantially. Leading us to our conclusion that this will not be enough. These moves by Intel will not be enough. They need to do more. And a big part of this announcement was partnerships and packaging. Okay. So here's where it gets interesting. Intel, as you may know was late to the party with SOC system on a chip. And it's going to use its packaging prowess to try and leap frog the competition. SOC bundles things like GPU, NPU, DSUs, accelerators caches on a single chip. So better use the real estate if you will. Now Intel wants to build system on package which will dis-aggregate memory from compute. Now remember today, memory is very poorly utilized. What Intel is going to do is to create a package with literally thousands of nodes comprising small processors, big processors, alternative processors, ARM processors, custom Silicon all sharing a pool of memory. This is a huge innovation and we'll come back to this in a moment. Now as part of the announcement, Intel trotted out some big name customers, prospects and even competitors that it wants to turn into prospects and customers. Amazon, Google, Satya Nadella gave a quick talk from Microsoft to Cisco. All those guys are designing their own chips as does Ericsson and look even Qualcomm is on the list, a competitor. Intel wants to earn the right to make chips for these firms. Now many on the list like Microsoft and Google they'd be happy to do so because they want more competition. And Qualcomm, well look if Intel can do a good job and be a strong second sourced, why not? Well, one reason is they compete aggressively with Intel but we don't like Intel so much but it's very possible. But the two most important partners on this slide are one IBM and two, the US government. Now many people were going to gloss over IBM in this announcement, but we think it's one of the most important pieces of the puzzle. Yes. IBM and semiconductors. IBM actually has some of the best semiconductor technology in the world. It's got great architecture and is two to three years ahead of Intel with POWER10. Yes, POWER. IBM is the world's leader in terms of dis-aggregating compute from memory with the ability to scale to thousands of nodes, sound familiar? IBM leads in power density, efficiency and it can put more stuff closer together. And it's looking now at a 20x increase in AI inference performance. We think Pat has been thinking about this for a while and he said, how can I leave leap frog system on chip. And we think he thought and said, I'll use our outstanding process manufacturing and I'll tap IBM as a partner for R&D and architectural chips to build the next generation of systems that are more flexible and performant than anything that's out there. Now look, this is super high end stuff. And guess who needs really high end massive supercomputing capabilities? Well, the US military. Pat said straight up, "We've talked to the government and we're honored to be competing for the government/military chips boundary." I mean, look Intel in my view was going to have to fall down into face not win this business. And by making the commitment to Foundry Services we think they will get a huge contract from the government, as large, perhaps as $10 billion or more to build a secure government Foundry and serve the military for decades to come. Now Pat was specifically asked in the Q&A section is this Foundry strategy that you're embarking on viable without the help of the US government? Kind of implying that it was a handout or a bailout. And Pat of course said all the right things. He said, "This is the right thing for Intel. Independent of the government, we haven't received any commitment or subsidies or anything like that from the US government." Okay, cool. But they have had conversations and I have no doubt, and Pat confirmed this, that those conversations were very, very positive that Intel should head in this direction. Well, we know what's happening here. The US government wants Intel to win. It needs Intel to win and its participation greatly increases the probability of success. But unfortunately, we still don't think it's enough for Intel to regain its number one position. Let's look at that in a little bit more detail. The headwinds for Intel are many. Look it can't just flick a switch and catch up on manufacturing leadership. It's going to take four years. And lots can change in that time. It tells market momentum as well as we pointed out earlier is headed in the wrong direction from a financial perspective. Moreover, where is the volume going to come from? It's going to take years for Intel to catch up for ARMS if it never can. And it's going to have to fight to win that business from its current competitors. Now I have no doubt. It will fight hard under Pat's excellent leadership. But the Foundry business is different. Consider this, Intel's annual CapEx expenditures, if you divide that by their yearly revenue it comes out to about 20% of revenue. TSMC spends 50% of its revenue each year on CapEx. This is a different animal, very service oriented. So look, we're not pounding the table saying Intel's worst days are over. We don't think they are. Now, there are some positives, I'm showing those in the right-hand side. Pat Gelsinger was born for this job. He proved that the other day, even though we already knew it. I have never seen him more excited and more clearheaded. And we agreed that the chip demand dynamic is going to have legs in this decade and beyond with Digital, Edge, AI and new use cases that are going to power that demand. And Intel is too strategic to fail. And the US government has huge incentives to make sure that it succeeds. But it's still not enough in our opinion because like the steel manufacturers Intel's real advantage today is increasingly in the high end high margin business. And without volume, China is going to win this battle. So we continue to believe that a new joint venture is going to emerge. Here's our prediction. We see a triumvirate emerging in a new joint venture that is led by Intel. It brings x86, that volume associated with that. It brings cash, manufacturing prowess, R&D. It brings global resources, so much more than we show in this chart. IBM as we laid out brings architecture, it's R&D, it's longstanding relationships. It's deal flow, it can funnel its business to the joint venture as can of course, parts of Intel. We see IBM getting a nice licensed deal from Intel and or the JV. And it has to get paid for its contribution and we think it'll also get a sweet deal and the manufacturing fees from this Intel Foundry. But it's still not enough to beat China. Intel needs volume. And that's where Samsung comes in. It has the volume with ARM, has the experience and a complete offering across products. We also think that South Korea is a more geographically appealing spot in the globe than Taiwan with its proximity to China. Not to mention that TSMC, it doesn't need Intel. It's already number one. Intel can get a better deal from number two, Samsung. And together these three we think, in this unique structure could give it a chance to become number one by the end of the decade or early in the 2030s. We think what's happening is our take, is that Intel is going to fight hard to win that government business, put itself in a stronger negotiating position and then cut a deal with some supplier. We think Samsung makes more sense than anybody else. Now finally, we want to leave you with some comments and some thoughts from the community. First, I want to thank David Foyer. His decade plus of work and knowledge of this industry along with this collaboration made this work possible. His fingerprints are all over this research in case you didn't notice. And next I want to share comments from two of my colleagues. The first is Serbjeet Johal. He sent this to me last night. He said, "We are not in our grandfather's compute era anymore. Compute is getting spread into every aspect of our economy and lives. The use of processors is getting more and more specialized and will intensify with the rise in edge computing, AI inference and new workloads." Yes, I totally agree with Sarbjeet. And that's the dynamic which Pat is betting and betting big. But the bottom line is summed up by my friend and former IDC mentor, Dave Moschella. He says, "This is all about China. History suggests that there are very few second acts, you know other than Microsoft and Apple. History also will say that the antitrust pressures that enabled AMD to thrive are the ones, the very ones that starved Intel's cash. Microsoft made the shift it's PC software cash cows proved impervious to competition. The irony is the same government that attacked Intel's monopoly now wants to be Intel's protector because of China. Perhaps it's a cautionary tale to those who want to break up big tech." Wow. What more can I add to that? Okay. That's it for now. Remember I publish each week on wikibon.com and siliconangle.com. These episodes are all available as podcasts. All you got to do is search for Braking Analysis podcasts and you can always connect with me on Twitter @dvellante or email me at david.vellante, siliconangle.com As always I appreciate the comments on LinkedIn and in clubhouse please follow me so that you're notified when we start a room and start riffing on these topics. And don't forget to check out etr.plus for all the survey data. This is Dave Vellante for theCUBE insights powered by ETR, be well, and we'll see you next time. (upbeat music)

>>from around the globe. It's the Cube covering HP. Discover Virtual experience Brought to you by HP. >>Welcome back to the Cube's coverage of HP Discover. 2020. The virtual experience. The Cube. The Cube has been virtualized. My name is Dave Vellante. I'm here with Stuart Minuteman and our good friend Tim Crawford is here. He's a strategic advisor to see Io's with boa. Tim, Great to see you. Stuart. Thanks for coming on. >>Great to see you as well, Dave. >>Yes. So let's unpack. What's going on in that Discover Antonio's, He notes, Maybe talk a little bit about the prospects for HP of coming forward in this decade. You know, last decade was not a great one for HP, HP. I mean, there was a lot of turmoil. There was a botched acquisitions. There was breaking up the company and spin merges and a lot of distractions. And so now that companies really and you hear this from Antonio kind of positioning for innovation for the next decade. So So I think this is probably a lot of excitement inside the company, but I want to touch on a couple of points and then you get your guys reaction, I guess, you know, to start off. Obviously, Antonio's talking about Cove in the role that they played in that whole, you know, pandemic and the transition toe the the isolation economy. But so let me start with you, Tim. I mean, what is the sort of posture amongst cios that you talk to? How strategic is HB H B two? The folks that you talk to in your community? >>Well, I think if you look at how CIOs are thinking, especially as we head into covert it into Corona virus and kind of mapping through that, that price, um, it really came down to Can they get their hands on technology? Can they get people back to work working from home? Can they do it in a secure fashion? Um, keeping people productive. I mean, there was a lot of block and tackling, and even to this day, there's still a fair amount of that was taking place. Um, we really haven't seen the fallout from the cybersecurity impact of expanding our foot print. Um, quite. But we'll see that, probably in the coming months. There are some initial inklings there when it comes to HP specifically I think it comes back to just making sure that they had the product on hand, that they understood that customers are going through dramatic change. And so all bets are off. You have to kind of step back and say, Okay, those plans that I had 60 9100 and 20 days ago those strategies that I may have already started down the path with those are up for grabs. I need to step back from those and figure out What do I do now? And I think each company, HP included, needs to think about how do they start to meld themselves, to be able to address those changing customer needs? And I think that's that's where this really kind of becomes the rubber hits the road is is HP capable of doing that? And are they making the right changes? And quite frankly, that starts with empathy. And I think we've heard pretty clearly from Antonio that he is sympathetic to the plight of their customers and the world >>on the whole. >>Yeah, and I think culturally 10 minutes do I mean I think you know HP is kind of getting back to some of its roots, and Tony has been there for a long time. I think people I think is very well liked. Andi, I think, ease of use, and I'm sure he's tough. But he's also a very fair individual, and he's got a vision and he's focused. And so, you know, I think again, as they said, looking forward to this decade, I think could be one that is, you know, one of innovation. Although, you know, look, you look at the stock price, you know, it's kind of piqued in November 19. It's obviously down like many stocks, so there's a lot of work to do there, and it's too. We're certainly hearing from HP. This notion of everything is a service that we've talked about green like a lot. What's your sense of their prospects going forward in this, you know, New Era? >>Yeah, I mean, Dave, one of the biggest attacks we've heard about H E in the last couple of years, you know the line Michael Dell would use is you're not going to grow by, say, abstraction. But as a platform company, HP is much more open. From what I've seen in the HP that I remember from, you know, 5 to 10 years ago. So you look at their partner ecosystem. It's robust. So, you know, years ago, it seemed to be if it didn't come out of HP Labs, it wasn't a product, you know. That was the services arm all wanted to sell HP here. Now, in this software defined world working in a cloud environment, they're much more open to finding that innovation and enabling it. So, you know, we talk about Green Lake Day. Three lakes got about 1000 customers right now, and a big piece of that is a partner. Port Police, whether it's VM Ware Amazon Annex, were H B's full stack themselves. They have optionality in there, and that's what we hear from from users is that they want flexibility they don't want. You know, you look at the cloud providers, it's not, you know, here's a solution. You look at Amazon. There's dozens of databases that you can use from Amazon or, if you use on top of Amazon, so H p e. You know, not a public cloud provider, but looking more like that cloud experience. They've done so many acquisitions over the years. Many of them were troubled. They got rid of some of the pieces that they might have over paid for. But you look at something like CTP them in this multi cloud world in the networking space, they've got a really cool, open source company, the company behind spiffy, inspire. And, you know, companies that are looking at containers and kubernetes, you know, really respond to say, Hey, these are projects that were interesting Oh, who's the company that that's driving that it's HP so more open, more of a partner ecosystem definitely feels that there's a lot there that I respect and like that hp >>well, I mean, the intent of splitting the company was so that HP could be more focused but focused on innovation was the intent was to be the growth company. It hasn't fully played out yet. But Tim, when you think about the conversations that CIOs are having with with HPI today versus what they were having with hpe HP, the the conglomerate of that the Comprising e ds and PCs, I guess I don't know, in a way, more more Dell like so Certainly Michael Dell's having strategic conversations, CIOs. But you got to believe that the the conversations are more focused today. Is that a good thing or a jury's still out? >>No, it absolutely is a good thing. And I think one of the things that you have to look at is we're getting back to brass tax. We're getting back to that focus around business objectives. So no longer is that hey, who has the coolest tech? And how can we implement that tax? Kind of looking from a tech business? Ah, spectrum, you're now focused squarely is a C i. O. You have to be squarely focused on what are the business objectives that you are teamed up for, and if you're not, you're on a very short leash and that doesn't end well. And I think the great thing about the split of HP HP e split and I think you almost have to kind of step back for a second. Let's talk about leadership because leadership plays a very significant role, especially for CIOs that are thinking about long term decisions and strategic partners. I don't think that HP necessarily had the right leadership in place to carry them into that strategic world. I think Antonio really makes a change there. I mean, they made some really poor decisions. Post split. Um, that really didn't bode well for HP. Um, and frankly, I talked a bit about that I know wasn't really popular within HP, but quite frankly, they needed to hear it. And I think that actually has been heard. And I think they are listening to their customers. And one of the big changes is they're getting back into the software business. And when you talk about strategic initiatives, you have to get beyond just the hardware and start moving up the proverbial stack, getting closer to those business initiatives. And that is software. >>Yeah, well, Antonio talked about sort of the insights. I mean, something I've said a lot about borrowed from the very Meeker conversations that that data is plentiful. Something I've always said. Insights aren't. And so you're right. You've seen a couple of acquisitions, you know, Matt bahr They picked up, I think pretty inexpensively. Kind of interesting cause, remember, HP hp had an investment in Horton works, which, of course, is now Cloudera and Blue Data. Ah Kumar Conte's company, you know, kind of focusing on maybe automating data, you know, they talked about Ed centric, cloud enabled, data driven. Nobody's gonna argue with those things. But you're right, Tim. I mean, you're talking more software than kind of jettisons the software business and now sort of have to rebuild it. And then, of course, do this cloud. What do you make of HP ease Cloud play? >>Yeah, well, I >>mean, >>Dave, you the pieces. You were just talking about math bar and blue data, where HP connects it together is, you know, ai ops. So you know, where are we going with infrastructure? There needs to be a lot more automation. We heard a great quote. I love from automation anywhere. Dave was, if you talk about digital transformation without automation, it's hallucination. So, you know, HP baking that into what they're doing. So, you know, I fully agree with Tim software software software, you know, is where the innovation is. So it can't just be the infrastructure. How do you have eyes and books into the applications? How are you helping customers build those new pieces? And what's the other software that you build around that? So, you know, absolutely. It's an interesting piece. And you know, HP has got a lot of interesting pieces. You know, you talk about the edge. Aruba is a great asset for that kind of environment and from a partnership, that is a damn point. Dave. They have. John Chambers was in the keynote. John, of course. Long time partners. He's with Cisco for many years Intel. Cisco started eating with HP on the server business, but now he's also the chairman of pensando. HP is an investor in pensando general availability this month of that solution, and that's going to really help build out that next generation edge. So, you know, a chip set that HP E can offer similar to what we see how Amazon builds outpost s. So that is a solution both for the enterprise and beyond. Is as a B >>yeah course. Do. Of course, it's kind of, but about three com toe. Add more fuel to that tension. Go ahead, Tim. >>Well, I was going to pick apart some of those pieces because you know, at edge is not an edge is not an edge. And I think it's important to highlight some of the advantages that HP is bringing to the table where Pensando comes in, where Aruba comes in and also we're really comes in. I think there are a number of these components that I want to make sure that we don't necessarily gloss over that are really key for HP in terms of the future. And that is when you step back and you look at how customers are gonna have to consume services, how they're going to have to engage with both the edge and the cloud and everything in between. HP has a great portfolio of hardware. What they haven't necessarily had was the glue, that connective tissue to bring all of that together. And I think that's where things like Green Lake and Green Lake Central really gonna play a role. And even their, um, newer cloud services are going to play a role. And unlike outposts and unlike some of the other private cloud services that are on the market today, they're looking to extend a cloud like experience all the way to the edge and that continuity creating that simplicity is going to be key for enterprises. And I think that's something that shouldn't be understated. It's gonna be really important because when I look at in the conversations I'm having when we're looking at edge to cloud and everything in between. Oh my gosh, that's really complicated. And you have to figure out how to simplify that. And the only way you're going to do that is if you take it up a layer and start thinking about management tools. You start thinking about autumn, and as companies start to take data from the edge, they start analyzing it at the edge and intermediate points on the way to cloud. It's going to be even more important to bring continuity across this entire spectrum. And so that's one of the things that I'm really excited about that I'm hearing from Antonio's keynote and others. Ah, here at HP Discover. >>Yeah, >>well, let's let's stay on that stupid. Let's stay on that for a second. >>Yeah, I wanted to see oh interested him because, you know, it's funny. You think back. You know, HP at one point in time was a leader in, you know, management solutions. You know, HP one view, you know, in the early days, it was really well respected. I think what I'm hearing from you, I think about outpost is Amazon hasn't really put management for the edge. All they're doing is extending the cloud piece and putting a piece out of the edge. It feels like we need a management solution that built from the ground up for this kind of solution. And do I hear you right? You believe that to be as some of those pieces today? >>Well, let's compare and contrast briefly on that. I think Amazon and the way Amazon is well, is Google and Microsoft, for that matter. The way that they are encompassing the edge into their portfolio is interesting, but it's an extension of their core business, their core public cloud services business. Most of the enterprise footprint is not in public cloud. It's at the other end of that spectrum, and so being able to take not just what's happening at the edge. But what about in your corporate data center in your corporate data center? You still have to manage that, and that doesn't fall under the purview of Cloud. And so that's why I'm looking at HP is a way to create that connective tissue between what companies are doing within the corporate data center today, what they're doing at the edge as well as what they're doing, maybe in private cloud and an extension public cloud. But let's also remember something else. Most of these enterprises, they're also in a multi cloud environment, so they're touching into different public cloud providers for different services. And so now you talk about how do I manage this across the spectrum of edge to cloud. But then, across different public cloud providers, things get really complicated really fast. And I think the hints of what I'm seeing in software and the new software branding give me a moment of pause to say, Wait a second. Is HP really gonna head down that path? And if so, that's great because it is of high demand in the enterprise. >>Well, let's talk about that some more because I think this really is the big opportunity and we're potentially innovation is. So my question is how much of Green Lake and Green Lake services are really designed for sort of on Prem to make that edge to on Prem? No, I want to ask about Cloud, how much of that is actually delivering Cloud Native Services on AWS on Google on Azure and Ali Cloud etcetera versus kind of creating a cloud like experience for on Prem in it and eventually the edge. I'm not clear on that. You guys have insight on how much effort is going into that cloud. Native components in the public cloud. >>Well, I would say that the first thing is you have to go back to the applications to truly get that cloud native experience. I think HP is putting the components together to a prize. This to be able to capitalize on that cloud like experience with cloud native APS. But the vast majority of enterprise app they're not cloud native. And so I think the way that I'm interpreting Green Lake and I think there are a lot of questions Greenland and how it's consumed by enterprises there. There was some initial questions around the branding when it first came out. Um, and so you know it's not perfect. I think HP definitely have some work to do to clarify what it is and what it isn't in a way that enterprises can understand. But from what I'm seeing, it looks to be creating and a cloud like experience for enterprises from edge to cloud, but also providing the components so that if you do have applications that are shovel ready for cloud or our cloud native, you can embrace Public Cloud as well as private cloud and pull them under the Green Lake >>Rela. Yeah, ostensibly stew kubernetes is part of the answer to that, although you know, as we've talked about, Kubernetes is necessary containers and necessary but not sufficient for that experience. And I guess the point I'm getting to is, you know we do. We've talked about this with Red Hat, certainly with VM Ware and others the opportunity to have that experience across clouds at the Edge on Prim. That's expensive from an R and D standpoint. And so I want to kind of bring that into the discussion. HP last year spent about 1.8 billion in R and D Sounds like a lot of money. It's about 6% of its of it's revenues, but it's it's spread thin now. It does are indeed through investments, for instance, like Pensando or other acquisitions. But in terms of organic R and D, you know, it's it's it's not at the top of the heap. I mean, obviously guys like Amazon and Google have surpassed them. I've written about this with regard to IBM because they, like HP, spend a lot on dividends on share buybacks, which they have to do to prop up the stock price and placate Wall Street. But it But it detracts from their ability to fund R and d student your take on that sort of innovation roadmap for the next decade. >>Yeah, I mean, one of the things we look at it in the last year or so there's been what we were talking about earlier, that management across these environments and kubernetes is a piece of it. So, you know, Google laid down and those you've got Microsoft with Azure, our VM ware with EMS. Ooh! And to Tim's point, you know, it feels like Green Lake fits kind of in that category, but there's there's pieces that fall outside of it. So, you know, when I first thought of Green Lake, it was Oh, well, I've got a private cloud stack like an azure stack is one of the solutions that they have there. How does that tie into that full solution? So extending that out, moving that brand I do here, you know good things from the field, the partners and customers. Green Lake is well respected, and it feels like that is, that is a big growth. So it's HB 50 from being more thought of, as you know, a box seller to more of that solution in subscription model. Green Lake is a vehicle for that. And as you pointed out, you know, rightfully so. Software so important. And I feel when that thing I'd say HPI ee feels toe have more embracing of software than, say, they're closest competitors. Which is Dell, which, you know, Dell Statement is always to be the leading infrastructure writer, and the arm of VM Ware is their software. So, you know, just Dell alone without VM ware, HP has to be that full solution of what Dell and VM ware together. >>Yeah, and VM Ware Is that the crown jewel? And of course, HP doesn't have a VM ware, but it does have over 8000 software engineers. Now I want to ask you about open source. I mean, I would hope that they're allocating a large portion of those software engineers. The open source development developing tooling at the edge, developing tooling from multi cloud certainly building hooks in from their hardware. But is HP Tim doing enough in open source? >>Well, I don't want to get on the open source bandwagon, and I don't necessarily want to jump off it. I think the important thing here is that there are places where open source makes sense in places where it doesn't, um, and you have to look at each particular scenario and really kind of ask yourself, does it make sense to address it here? I mean, it's a way to to engage your developers and engage your customers in a different mode. What I see from HP E is more of a focus around trying to determine where can we provide the greatest value for our customers, which, frankly, is where their focus should be, whether that shows up in open source for software, whether that shows up in commercial products. Um, we'll see how that plays out. But I think the one thing that I give HP e props on one of several things I would say is that they are kind of getting back to their roots and saying, Look, we're an infrastructure company, that is what we do really well We're not trying to be everything to everyone. And so let's try and figure out what are customers asking for? How do we step through that? I think this is actually one of the challenges that Antonio's predecessors had was that they tried to do jump into all the different areas, you know, cloud software. And they were really X over, extending themselves in ways that they probably should. But they were doing it in ways that really didn't speak to their four, and they weren't connecting those dots. They weren't connecting that that connective tissue they needed to dio. So I do think that, you know, whether it's open source or commercial software, we'll see how that plays out. Um, but I'm glad to see that they are stepping back and saying Okay, let's be mindful about how we ease into this >>well, so the reason I bring up open source is because I think it's the mainspring of innovation in the industry on that, but of course it's very tough to make money, but we've talked a lot about H B's strength since breath is, we haven't talked much about servers, but they're strong in servers. That's fine We don't need to spend time there. It's culture. It seems to be getting back to some of its roots. We've touched on some of its its weaknesses and maybe gaps. But I want to talk about the opportunities, and there's a huge opportunity to the edge. David Flores quantified. He says that Tam is four. Trillion is enormous, but here's my question is the edge Right now we're seeing from companies like HP and Dell. Is there largely taking Intel based servers, kind of making a new form factor and putting them out on the edge? Is that the right approach? Will there be an emergence of alternative processors? Whether it's our maybe, maybe there's some NVIDIA in there and just a whole new architecture for the edge to authority. Throw it out to you first, get Tim Scott thoughts. >>Yeah, So what? One thing, Dave, You know, HP does have a long history of partnering with a lot of those solutions. So you see NVIDIA up on stage when you think about Moonshot and the machine and some of the other platforms that they felt they've looked at alternative options. So, you know, I know from Wicky Bon standpoint, you know, David Foyer wrote the piece. That arm is a huge opportunity at the edge there. And you would think that HP would be one of the companies that would be fast to embrace that >>Well, that's why I might like like Moonshot. I think that was probably ahead of its time. But the whole notion of you know, a very slim form factor that can pop in and pop out. You know, different alternative processor architecture is very efficient, potentially at the edge. Maybe that's got got potential. But do you have any thoughts on this? I mean, I know it's kind of Yeah, any hardware is, but, >>well, it is a little hardware, but I think you have to come back to the applicability of it. I mean, if you're taking a slim down ruggedized server and trying Teoh essentially take out, take off all the fancy pieces and just get to the core of it and call that your edge. I think you've missed a huge opportunity beyond that. So what happens with the processing that might be in camera or in a robot or in an inch device? These are custom silicon custom processors custom demand that you can't pull back to a server for everything you have to be able to to extend it even further. And, you know, if I compare and contrast for a minute, I think some of the vendors that are looking at Hey, our definition of edge is a laptop or it is this smaller form factor server. I think they're incredibly limiting themselves. I think there is a great opportunity beyond that, and we'll see more of those kind of crop up, because the reality is the applicability of how Edge gets used is we do data collection and data analysis in the device at the device. So whether it's a camera, whether it's ah, robot, there's processing that happens within that device. Now some of that might come back to an intermediate area, and that intermediate area might be one of these smaller form factor devices, like a server for a demo. But it might not be. It might be a custom type of device that's needed in a remote location, and then from there you might get back to that smaller form factor. Do you have all of these stages and data and processing is getting done at each of these stages as more and more resources are made available. Because there are things around AI and ML that you could only do in cloud, you would not be able to do even in a smaller form factor at the edge. But there are some that you can do with the edge and you need to do at the edge, either for latency reasons or just response time. And so that's important to understand the applicability of this. It's not just a simple is saying, Hey, you know, we've got this edge to cloud portfolio and it's great and we've got the smaller servers. You have to kind of change the vernacular a little bit and look at the applicability of it and what people are actually doing >>with. I think those are great points. I think you're 100% right on. You are going to be doing AI influencing at the edge. The data of a lot of data is going to stay at the edge and I personally think and again David Floor is written about this, that it's going to require different architectures. It's not going to be the data center products thrown over to the edge or shrunk down. As you're saying, That's maybe not the right approach, but something that's very efficient, very low cost of when you think about autonomous vehicles. They could have, you know, quote unquote servers in there. They certainly have compute in there. That could be, you know, 2344 $5000 worth of value. And I think that's an opportunity. I'd love to see HP Dell, others really invest in R and D, and this is a new architecture and build that out really infuse ai at the edge. Last last question, guys, we're running out of time. One of the things I'll start with you. Still what things you're gonna watch for HP as indicators of success of innovation in the coming decade. As we said last decade, kind of painful for HP and HP. You know, this decade holds a lot of promise. One of the things you're gonna be watching in terms of success indicators. >>So it's something we talked about earlier is how are they helping customers build new things, So a ws always focuses on builders. Microsoft talks a lot. I've heard somethin double last year's talk about building those new applications. So you know infrastructure is only there for the data, and the applications live on top of it. And if you mention Dave, there's a number of these acquisitions. HP has moved up the stack. Some eso those proof points on new ways of doing business. New ways of building new applications are what I'm looking for from HP, and it's robust ecosystem. >>Tim. Yeah, yeah, and I would just pick you back right on. What's do was saying is that this is a, you know, going back to the Moonshot goals. I mean, it's about as far away as HP ease, and HP is routes used to be and that that hardware space. But it's really changing business outcomes, changing business experiences and experiences for the customers of their customers. And so is far cord that that eight p e can get. I wouldn't expect them to get all the way there, although in conversations I am having with HP and with others that it seems like they are thinking about that. But they have to start moving in that direction. And that's actually something that when you start with the builder conversation like Microsoft has had, an Amazon has had Google's had and even Dell, to some degree has had. I think you missed the bigger picture, so I'm not saying exclude the builder conversation. But you have to put it in the right context because otherwise you get into this siloed mentality of right. We have solved one problem, one unique problem, and built this one unique solution. And we've got bigger issues to be able to address as enterprises, and that's going to involve a lot of different moving parts. And you need to know if you're a builder, you've it or even ah ah, hardware manufacturer. You've got to figure out, How does your piece fit into that bigger picture and you've got to connect those dots very, very quickly. And that's one of the things I'll be looking for. HP as well is how they take this new software initiative and really carry it forward. I'm really encouraged by what I'm seeing. But of course the future could hold something completely different. We thought 2020 would look very different six months ago or a year ago than it does today. >>Well, I wanna I want to pick up on that, I think I would add, and I agree with you. I'm really gonna be looking for innovation. Can h P e e get back to kind of its roots? Remember, H B's router invents it was in the logo. I can't translate its R and D into innovation. To me, it's all about innovation. And I think you know cios like Antonio Neri, Michael Dell, Arvind Krishna. They got a They have a tough, tough position because they're on the one hand, they're throwing off cash, and they can continue Teoh to bump along and, you know, placate Wall Street, give back dividends and share buybacks. And and that's fine. And everybody would be kind of happy. But I'll point out that Amazon in 2007 spent spend less than a $1,000,000,000 in R and D. Google spent about the back, then about the same amount of each B E spends today. So the point is, if the edge is really such a huge opportunity, this $4 trillion tam is David Foyer points out, there's a There's a way in which some of these infrastructure companies could actually pull a kind of mini Microsoft and reinvent themselves in a way that could lead to massive shareholder returns. But it was really will take bold vision and a brave leader to actually make that happen. So that's one of things I'm gonna be watching very closely hp invent turn r and D into dollars. And so you guys really appreciate you coming on the Cube and breaking down the segment for ah, the future of HP be well, and, uh and thanks very much. Alright. And thank you for watching everybody. This is Dave Volante for Tim Crawford and Stupid men. Our coverage of HP ease 2020 Virtual experience. We'll be right back right after this short break. >>Yeah, yeah, yeah, yeah.

>>Live from San Francisco. It's the cube covering my groin. Insight 2019 brought to you by micron. >>Welcome back to pier 27 in San Francisco. I'm your host Dave Vellante with my cohost David foyer and this is the cube, the leader in live tech coverage. This is our live coverage of micron insight 2019 we were here last year talking about some of the big picture trends. Derek ticker is here, he's the general manager and vice president of the storage business unit at micro and great to see you again. Thank you so much for having me here. Welcome. So you know we talk about the super powers a lot, you know, cloud data, AI and these new workloads that are coming in. And this, this, I was talking to David earlier in our kickoff like how real is AI? And it feels like it's real. It's not just a bunch of vendor industry hype and it comes in a lot of different forms. Derek, what are you seeing in terms of the new workloads and the big trends in artificial intelligence? >>I think just on the, on the front end, you guys are absolutely right. The, the role of artificial intelligence in the world is, uh, is absolutely transformational. I was sitting in a meeting in the last couple of days and somebody was walking through a storyline that I have to share with you. That's a perfect example of why this is becoming mainstream. In Southern California at a children's hospital, there were a set of parents that had a few days old baby and this baby was going through seizures and no one could figure out what it was. And during the periods of time of the seizure, the child's brain activity was zero. There was no brain activity whatsoever. And what they did is they performed a CT scan, found nothing, check for infections, found nothing. And can you imagine a parent just sitting there dealing with their child and that situation, you feel hopeless. >>This particular institution is so much on the bleeding edge. They've been investing in personalized medicine and essentially what they were able to do was extract a sample of blood from that sample of blood within a matter of minutes. They were able to run an algorithm that could sift through 5 million genetic variants to go find a potential match for a genetic variant that existed within this child. They found one that was 0.01% of the population found a tiny, tiny, call it a less than a needle in the haystack. And what they were able to do is translate that actual insight into a treatment. And that treatment wasn't invasive. It didn't involve surgery. It involves supplements and providing this shower, just the nutrients that he needed to combat this genetic variant. But all of this was enabled through technology and through artificial intelligence in general. And a big part of the show that we're here at today is to talk about the industry coming together and discussing what are the great advances that are happening in that domain. >>It's just, it's super exciting to see something that touches that close to our life. I love that story and that's, that's why I love this event. I mean, well, obviously micron memories, you know, DRAM, NAND, et cetera, et cetera. But this event is all about connecting to the impacts on our lives. You take, you take that, I used to ask this question a lot of when will machines be able to make better diagnoses than, than doctors. And I think, you know, a lot people say, well they already can, but the real answer is it's really about the augmentation. Yeah. You know, machines helping doctors get to that, you know, very, you know, uh, a small probability 0.1001% yes. And it'd be able to act on it. That's really how AI is affecting our lives every day. >> Wholeheartedly agree. And actually that's a, that's a big part of our mission. >>Our mission is to transform how the world uses information to enrich life. That's the heart and soul of what you just described. Yeah. And we're actually, we're super excited about what we see happening in storage as a result of this. Um, one of the, one of the things that we've noticed as we've gotten engaged with a broad host of customers in the industry is that there's a lot of focus on artificial intelligence workloads being handled based on memory and memory bandwidth and larger amounts of memory being required. If you look at systems of today versus systems of tomorrow, based on the types of workloads that are evolving from machine learning, the need for DRAM is growing dramatically. Multiple factors, we see that, but what nobody ever talks about or rarely talks about is what's going on in the storage subsystem and one of the biggest issues that we've found over time or challenges that exist is as you look at the AI workloads going back to 2014 the storage bandwidth required was a few megabytes per second and called tens of, but if you just look every year, over time we're exceeding at gigabyte, two gigabytes of bandwidth required out of the storage subsystem. >>Forget the memory. The storage is being used as a cash in it flushes, but once you get into a case where you actually want to do more work on a given asset, which of course everybody wants to do from a TCO perspective, you need super high performance and capability. One of the things that that we uncovered was by delivering an SSD. This is our 9,300 drive. We actually balanced both the read IOPS and the ride IOPS at three gigs per second. And what we allow to have happened is not just what you can imagine as almost sequential work. You load up a bunch of data into a, into a training machine, the machine goes and processes on it, comes back with a result, load more data in by actually having a balanced read and write a model. Your ingest times go faster. So while you're working on a sequence, you can actually ingest more data into the system and it creates this overall efficiency. And it's these types of things that I think provided a great opportunity for innovation in the storage domain for these types of that's working >> requiring new architectures in storage, right? I mean, yeah, >>I mean, th th so one of the things that's happened in, in bringing SSDs in is that the old protocols were very slow, etc. And now we all the new protocols within in Vme and potentially even more new protocols coming in, uh, into this area. What's micron? What, how is micron making this thing happen? This speed that's gonna provide these insights? >>It's a fan fan. Fantastic question and you're absolutely right. The, the world of standards is something that we found over the course of time. If you can get a group of industry players wrapped around a given set of standards, you can create a large enough market and then people can innovate on top of that. And for us in the, in the storage domain, the big transitions had been in Sada and NBME. You see that happening today when we talked a little bit about maybe a teaser for what's coming a little later at, at our event, um, in some of the broader areas in the market, we're talking about how fabrics attach storage and infrastructure. And interestingly enough, where people are innovating quite a bit right now is around using the NBME infrastructure over fabrics themselves, which allows for shared storage across a network as opposed to just within a given server there. >>There's some fantastic companies that are out there that are actually delivering both software stacks and hardware accelerators to take advantage of existing NBME SSDs. But the protocol itself gets preserved. But then they can share these SSDs over a network, which takes a scenario where before you were locked with your storage stranded within a server and now you can actually distribute more broad. It's amazing difference, isn't it at that potential of looking at data over as broad an area as you want to. Absolutely. And being able to address it directly and having it done with standards and then having it done with low enough latency such that you aren't feeling severely disadvantaged, taking that SSD out of a box and making it available across a broad network. So you guys have a huge observation space. Uh, you sell storage to the enterprise, you sell storage to the cloud everywhere. >>I want to ask you about the macro because when you look at the traditional storage suppliers, you know, some of them are struggling right now. There aren't many guys that are really growing and gaining share because the cloud is eating away at that. You guys sell to the cloud. So that's fine. Moving, you know, arms dealer, whoever wins it may the best man win. Um, but, but at the same time, customers have ingested so much all flash. It's giving them head room and so they're like, Hey, I'm good for awhile. I used to have this spinning disc. I'd throw spinning disc at it at the problem till I said, give me performance headroom. That has changed. Now we certainly expect a couple of things that that will catch up and there'll be another step function. But there's also elasticity. Yes. Uh, you saw for instance, pure storage last quarter said, wow, hit the price dropped so fast, it actually hurt our revenues. >>And you'd say, well, wait a minute. If the price drops, we want people to buy more. There's no question that they will. It just didn't happen fast enough from the quarter. All of these interesting rip currents going on. I wonder what you're seeing in terms of the overall macro. Yeah. It's actually a fantastic question. If you go back in time and you look at the number of sequential quarters, when we had ASP decreases across the industry, it was more than six. And the duration from peak to trough on the spot markets was high double digit percentages. Not many markets go through that type of a transition. But as you suggested, there's this notion of elasticity that exists, which is once the price gets below a certain threshold, all of a sudden new markets open up. And we're seeing that happen today. We're seeing that happen in the client space. >>So, so these devices actually, they're going through this transition where companies are actually saying, you know what, we're going to design out the hard drive cages for all platforms across our portfolio going into the future. That's happening now. And it's happening largely because these price points are enabling that, that situation and the enterprise a similar nature in terms of average capacities and drives being deployed over time. So it's, I told you, I think the last time we saw John, I told just one of the most exciting times to be in the memory and storage industry. I'll hold true to that today. I, I'm super excited about it, but I just bought a new laptop and, and you know, I have, you know, a half a half a terabyte today and they said for 200 bucks you can get a terabyte. Yes. And so I said, Oh wow, I could take everything from 1983 and bring it, bring it over. >>Yeah. Interestingly, it was back ordered, you know, so I think, wow, it am I the only one, but this is going to happen. I mean, everybody's going to have, you know, make the price lower. Boom. They'll buy more. We, we, we believe that to be the case for the foreseeable future. Okay. Do you see yourself going in more into the capacity market as well with SSTs and I mean, this, this, this drop, let's do big opportunity or, yeah. Actually, you know, one of the areas that we feel particularly privileged to be able to, to engage in is the, the use of QLC technology, right. You know, quad level solar for bits per cell technology. We've integrated this into a family of, uh, of SSDs for the enterprise, or interestingly enough, we have an opportunity to displace hard drives at an even faster rate because the core capability of the products are more power efficient. >>They've got equal to, or better performance than existing hard drives. And when you look at the TCO across a Reed intensive workloads, it's actually, it's a no brainer to go replace those HDD workloads in the client space. There's segments of the market where we're seeing QLC to play today for higher, higher capacity value segments. And then there's another segment for performance. So it's actually each segment is opening up in a more dramatic way. So the last question, I know you got some announcements today. They haven't hit the wire yet, but what, can you show us a little leg, Derrick? What can you tell us? So I, I'll, I'll give you this much. The, um, the market today, if you go look in the enterprise segment is essentially NBME and SATA and SAS. And if you look at MDME in 20 2019 essential wearing crossover on a gigabyte basis, right? >>And it's gonna grow. It's gonna continue to grow. I mentioned earlier the 9,300 product that we use for machine learning, AI workloads, super high performance. There's a segment of the market that we haven't announced products in today that is a, a a mainstream portion of that market that looks very, very interesting to us. In addition, we can never forget that transitions in the enterprise take a really long time, right, and Sada is going to be around for a long time. It may be 15% of the market and 10% out a few years, but our customers are being very clear. We're going to continue to ship Satta for an extended period of time. The beautiful thing about about micron is we have wonderful 96 layer technology. There's a need in the market and both of the segments I described, and that's about as much as I can give you, I don't bet against data. Derek, thanks very much for coming on. Thank you guys so much. You're welcome. There's a lot of facts. Keep it right there, buddy. We'll be back at micron insight 2019 from San Francisco. You're watching the cube.

from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation welcome to the cube studios for the cube conversation where we go in-depth with thought leaders driving business outcomes with technology I'm your host Peter Burris digital business and the need to drive the value of data within organizations is creating an explosion of technology in multiple domains systems networking and storage we've seen advances in flash we've seen advances in HD DS we've seen advances and all kinds of different elements but it's essential that users and enterprises still think in terms not just of these individual technologies piecemeal but as solutions that are applied to use cases now you always have to be aware of what are the underlying technology components but it's still important to think about how systems integration is going to bring them together and apply them to serve business outcomes now to have that conversation we've got David Fleur who's the CTO and co-founder of wiki bond and my colleague David welcome to the cube thank you very much Peter all right so I've just laid out this proposition that systems integration as a discipline is not gonna go away when we think about how to build these capabilities that businesses need in digital business so let's talk about that what are some of the key features of systems integration especially in the storage world that will continue to be a helps differentiate between winners and losers absolutely so you you need to be able to use software to be able to combine all these different layers and it has to be an architect software solution that will work wherever you've got equipment and where have you got data so it needs to work in the cloud it needs to work in a private cloud it needs to work at the edge all of these needs to be architected in a way which is available to the users to put where the data is going to be created as opposed to bring it all in in one super large collection of data and so we've got different types of technology at the very fastest we've got DRAM we've got we've got non-volatile DRAM which is coming very fast indeed we've got flash and there are many different sorts of flash there's obtained from Intel that may be trying to get in between there as well and then there are different HD DS as well so we got a long hierarchy the important thing is that we protect the application and the operations from all of that complexity by having an overall hierarchy and utilizing software from an integration standpoint but it suggests that when an enterprise thinks about a solution for how they store their data they need to think in terms of as you said first off physically where is it going to be secondly what kinds of services at the software level am I going to utilize to ensure that I can have a common administrative experience and the differentiated usage experience based on the physical characteristics of where it's being used and then obviously and very importantly from an administration standpoint I need to ensure that I'm not having to learn new and unique administration practices everywhere because I would just blow everything up absolutely but there is a real there's going to be in my opinion a large number of these solutions out there I mean one data architecture is not going to be sufficient for all applications they're gonna have many different architectures out there I think it's probably useful just to start with one as an example in this area just let's take one as an example and then we can see what the major characteristics of you are so let's take something that would fit in most places a mid-range type solution let's take nimble nimble storage which has a very specific architecture so it was started off by being a virtualization of all those different layers so the application sees that everything is in flash and in cash or whatever it is but where it is is totally different it can be anywhere within that hierarchy so the application sees effectively a pool of resources that it can call yes all it sees and and it doesn't know and nobody and it doesn't need to know that it's on disk or a hard disk or in in memory in in in a cache inside the controller or wherever it is so it starts with using nimble as an example nimble is successfully masking the complexities and specificities of that storage heart and from the application right so so and and that's an advantage because it's simpler but it's also needs to cover more things you need to be able to do everything within that virtualized environment so you need for example to be able to take snapshots and you the snapshots need all the metadata about the snapshots needs to be put in a separate place so one of the things you find that comes from this sort of architecture is that the metadata is separated out completely different from the actual data itself but still proximate to the data because data locality still matters absolutely has to be there but it's in a different part of a hierarchy it's much further up the hierarchy all the metadata so what we've got the metadata we've got the flash high speed we've got the the fastest which is the DRAM itself that when for writes is has a protection mechanism for that that part of the DRAM specialized hardware in that area so that allows you to do writes very very quickly indeed and then you come down to the next layer which is flash and indeed within the in the in taking the nimble example you have two sorts of flash you can have the high-speed flash at the top and if you want to you can have lower performance flash you know using the 3d quad flash or whatever it is you can have lower performance flash if that's what you need and then going lower down then you have HD DS and the architecture combines the benefits of flash with the character and the characteristics of flash with the benefits of HD d which is much lower cost but the characteristics of HD d which are slower but very suited to writing out large volumes or reading in large volumes so that's read out to the disk but where where it's all held is held in the metadata so it's really looking at the workloads that are going to be they're gonna hit the data and then with out of making the application aware of it utilizing the underlying storage hierarchy to so best support those workloads again with a virtualized interface that keeps it really simple from an administration development and runtime perspective actually all right David foyer thanks very much for being on the cube and talking about some of these new solution-oriented requirements for thinking about storage over the next few years once again I'm Peter Burris see you next time you [Music]

>> Live from Las Vegas, it's theCUBE! Covering Dell Technologies World 2019. Brought to you by Dell Technologies and its ecosystem partners. >> Hello everyone, welcome to theCUBE's live coverage here in Las Vegas for Dell Technologies World 2019. I'm John Furrier, Stu Miniman, Dave Vellante. Day two of three days of wall-to-wall coverage. We got two sets called theCube Cannon. We've got the Cannon of Content, interviews all day long, out at night at the analyst briefings, meet-ups, receptions, talking to all the executives at Dell Technologies VMware and across the industry. Stu, Dave, today is product announcements on the keynotes. Yesterday was the grand vision with Michael Dell and the big reveal on the Microsoft partnership with Satya Nadella's surprise visit onstage, unveiling new Azure-VMware integrations with Dell Technologies. Dell announced the Dell Cloud, which is a little bit of Virtustream, but they're trying to position this cloud, I guess it's a cloud if you want to call it a single cloud of glass. Dave, single pane in the glass with a variety of other things, unified workspace and some other things. This is Dell trying to be a supplier end-to-end. This is the pitch from Dell Technologies. We'll be talking to Michael Dell, also Pat Gelsinger, the CO of VMware. Dave, were you impressed, were you shocked, were you surprised with yesterday's big news and as the products start coming online here, what's your analysis? >> Well yesterday, John, was all about the big strategic vision, Michael Dell laying out check for good and then the linchpin of Dell strategy which of course is VMware for cloud, multicloud, hybrid cloud, kind of VMware everywhere. I was surprised that Satya Nadella flew down from Seattle and was here on stage in person. Didn't come in from the big screen. So I thought that was pretty impressive. You had the three power players up on stage. Today of course was all about the products. Both Dell and EMC have always been very practical in terms of their engineering. Stu, you used to work there. Their R&D is a lot of D. It's sort of incremental product improvements to keep the customers happy, to keep ahead of the competition, to keep the lifecycle going. They had like 10 announcements today. I can go through 'em real quick if you want, but they range from new laptops to talking about new branding on servers, new storage devices. You had PowerProtect which is their new rebranded backup and data protection and data manage portfolio, an area where Dell EMC has been behind. So lots of announcements. Another kind of mega launch tradition and again, a lot of incremental but important tactical improvements to the product line. >> Last year, what we heard from Jeff Clarke is they're looking to simplify that portfolio. Back in the EMC days, it was oh my gosh, look at the breadth of this. Every category, they had two or three offerings and you know, the stated goal is to simplify that and that means most categories are going to get one product. It's interesting. You talk about networking just got rebranded with that Power branding. I kind of said there there's marketing behind it. If you know what that product is because it's the Power brand and they put it out there. So you know, PowerMax, has been their tiered storage. They had a good update for Unity. It's Unity XT. Doesn't have a power name yet so maybe there's still some dry powder left in the product portfolio there, but they're making progress going through this 'cause these things don't happen overnight. It's great to spin up the clouds, but in the storage world, customers, they trust, they have the code, they test it out. So going to new generations, making that change, does take time but you've seen that progress. The tail end of that integration between Dell and EMC on the product side. >> Stu, what's your analysis of the products so far 'cause again like Dave said, it's a slew of announcements. What's resonating, what's popping out, what's boiling up to the surface? >> Yeah so look, the area that I spent so much time on, John, that hyper-converged infrastructure. If you look at a lot of the pieces underneath it all, it's VxRail. One of the things we've had a little bit of a challenge squinting through is oh wait, there's this managed service stack, it's VxRail underneath. Oh wait I've taken the appliance and I put VCF. Oh that's VxRail and then I've got this other, it's like I see three or four solutions and I'm like is it all just VxRail with like a VMware stack on top of it? But it's how do I package it, what applications live on it, how is it consumed, manage service, op ex, cap ex. So they've got that a little bit of complexity when VxRail itself is you know, dirt simple and really there so they're making progress on the cloud piece. Dell is the leader in hyper-converged. I'll point out, you don't hear anybody talking about Nutanix here, but Dell still has a partnership on the XC Core. They're going to sell a lot of Dell servers into Nutanix environment so I expect you'll still have the Nutanix show. John you're going to be at that next week. They're still going to talk about Dell. I'm sure you'll talk to Dheeraj. Yes they made a partnership with HP, but that does not kill the relationship with Nutanix just like Microsoft, heck. I'm going to see Satya Nadella on stage at Red Hat Summit next week and you're like oh well VMware and Red Hat. Red Hat's here. Red Hat's a Dell-ready partner. If you want to put open shift on top of their stack, they can do that so hardware and software, everybody's got their pieces, everybody's got their pieces, everybody competes a lot, but they partner across the board. IBM Global Services is here. There's so many companies here. Dell's a broad company, deep partnerships. The question I have is Pat Gelsinger was just on stage saying that this SDDC will be the building block for the future. I said kudos to them. They've got it on AWS, they've got it announced with Azure, we announced it with Google, but that is not necessarily the end state. VMware is a piece of the puzzle. I don't know if VMware will be the leader in multicloud management. vCenter was the leader in virtualization management so how much of that will there or do I get an Amazon and then start moving some stuff over? Do I get to Azure and start modernizing my environment so that I don't need to pay VMware and I don't need virtualization. VMware and Dell are going to containerize everything so in the future, are they containerware, you know? That's the competition kind of post-it note. They are VMware at their core. VMware is centra of the strategy and there's still some work to go, but they're making some good progress. >> I want to get your thoughts, guys, on the role VMware is playing here at the show. Normally they're here, usually they're here, but this year it seems to be much more smoother integration of talking points, messaging, product integrations. The show's got a good beat to it. Pretty packed, but the role of VMware, Dave, Stu, what's your reaction and thoughts? We've seen them dance all the time. Obviously VMware, Dave as you pointed out yesterday, a big part of the valuation of Dell Technologies, but what's your observation on the presence of VMware here at Dell Technologies World? >> I mean I've said many times that this company and I said this about EMC, it's kind of a boring company without VMware. You put VMware in the mix and all of a sudden, it becomes very strategic and very interesting from a lot of standpoints. Certainly from a financial standpoint. Remember, the Class V transaction that took Dell public was the result of an $11 billion dividend because of VMware. They took VMware's cash and they said okay, we're going to give nine billion to the shareholders. Without VMware, that wouldn't have happened. As well, the multicloud strategy, the underpinning of that multicloud strategy is VMWare. What strikes me, John and Stu, is that the cultural change. You had Dell, you had EMC. They said ah yeah the companies are compatible, but they're different companies. They maybe had shared kind of goals and values, but they had different cultures and really in a short timeframe, Michael Dell and his team have put these two companies together and they have aligned in a big way. I mean they are basically saying VMware and Dell, boom. That's how we're going to market and you know, Pat's coming on later today and I'm sure he'll say hey we love NetApp, we love HBE, we love IBM, but it's clear what the preferred partnership is. >> Dave, when the acquisition happened, there was talks of synergies and we were like oh where are they going to cut everything? If I look around here, they've got the seven logos of the primary companies. It's Dell, Dell EMC, Pivotal, RSA, Secureworks, Virtustream and VMware. They're one company. Michael Dell will go on calls for any of them. Friends of mine at Pivotal says you talk to Michael quite a bit. You know, he's out there. We talked about it yesterday. Dell and VMware are closer and tighter aligned than EMC and VMware ever were. Now on the one hand, EMC kept them separate because the growth of virtualization required that. Today in this cloud environment, it's a different world and it's matured so VMware, sure, there's still work on HP and IBM and all this other stuff, but Dell leads that move as you said, Dave. >> John, you're big on culture. This is a founder culture. What's your take on what Michael Dell has accomplished and how does it stand to compare with sort of other great cultural transformations that you've seen? >> Well I think HBE is a great example of a culture that split, was uncharged there. We know what happened there and I think they're hurting, they're losing talent and they're not winning in categories across the board like Dell is. I think Michael Dell, the founder-led approach that he's having 'cause he told us years ago, if you guys remember, here on the record, also privately that I'm going to take this off the table with EMC and I'm going to do all these things. We're going to execute. So he brought his execution mojo and ecos of Dell and become Dell Technologies, as Stu pointed out, a portfolio of multiple companies under one umbrella and he brought the execution discipline and this is a theme, Dave. Last night at the analysts reception, as I was talking to other analysts and talking to some of the execs, both from VMware and Dell Technologies, that the execution performance across the board both on product integration, which was a weak spot as you know, is getting better, the business performance discipline. We're going to have the CFO on here to talk more about it, they're executing. Howard Elias is going to be on this afternoon. He called this three years ago when he was talking about the integration that they saw synergies, they saw opportunities and they were going to unpack those. They stayed relentless on that. So I think this is a great example of keeping the founders around for all the VC-backed companies. You're thinking about getting rid of founders. Never let a founder leave a company. They bring the vision, they bring also some guts and grit and they bring a perspective and you can put great talent and team around that, that attract and retain great executives like Michael's done and he's poaching HPE, other companies and pulling talent in 'cause they're executing. They pay well, it's a great place to work according to the statistics. So again, this is all because of the founder and if the founder's not around, you have all the fiefdoms and the policists who kick in and then it becomes kind of sideways. So that's kind of what I see other companies that don't have founders around and HP lost their founders obviously and then the culture kind of went a little bit sideways. So they're trying to get back in the game, seeing them go back to their roots. We'll see how they do. We don't do that show anymore and again we don't have a lot of visibility into what HP's doing but we do know, Dave, that they do not have a lot of the pieces on the board that Dell does. So if you want to have an end-to-end operating model, and you're missing key value activities of an end-to-end value chain, that's going to be hard to automate, it's hard to be a performant, it's going to be hard to be successful. So I think Dell is showing the playbook of how to be horizontally scalable operationally and offer perspectives and data-driven specialism in any industry in any vertical. >> Yeah Dave, if I can just on the cultural piece 'cause it's really interesting. You talked about EMC, East Coast hard driving versus VMware, software, Silicon Valley company. While they're working together, a lot of it, you know, I talk to VMware people and they're like well it's great the Dell force is just selling our stuff. It's not like I'm having storage shoved down my throat or we have to have our arms twisted. It's the product portfolio that they're selling, the vSAN, NSX, the management software suite and those pieces, things like SD-WAN, there's some good synergies there. So the product portfolio is a nice fit that just jointly go out to market that they just really line up well together and Dell's a very different cultural beast than EMC was. >> Well again, staying on culture for a moment, when I discussed with some of the folks that I know out of Hopkinton the narrative early on was oh Dell's ruining EMC, tearing it apart and so forth. When you talk to people today, they say, you know what, it was painful. Dell came in and said okay, you're going to be accountable, really had an accountability culture, but now they've come out the other side, the narrative is it was the right thing to do. Jeff Clarke came in and sort of forced this alignment. There's like no question about it. People, this is a guy who you know, his calendar's set for the year. People know where he's going to be, what meeting he's going to have, what's expected and they're prepared and it seems to be taking hold. I mean if a $90 billion company that's growing at 14% in revenues, in profitable revenues, that's quite astounding when you think about it and I think it's a big result of the speed at which Dell has brought in its operating model to the broader EMC and transformed itself. It's quite amazing. >> Awesome show, guys. We've got clips out there on the #DellTechWorld on Twitter. We've got a lot of videos. We've got two sets here, three days of wall-to-wall coverage. Final word on this intro for day two, guys. Thoughts on the show? It's not a boring show. It's a lot of activities, a lot of things. They've got an Alienware eSports gaming studio which I think is totally badass. A lot of kind of cool things here. It's not the glitz and glam that we've seen in other EMC Worlds before or Dell Worlds, but it's meat and potatoes and it's got a spring to its step here. I feel it's not, it feels good. That's my takeaway. >> Well the big theme is hybrid cloud and multicloud. Jon Rowe as we were leaving the room today that we were early with that multicloud. Thanks for everybody else in the industry for hopping on board. The reality is the first time I heard the sort of hybrid cloud was called private cloud. Chuck Hollis wrote a blog back in the mid to late 2000s. Now I will make an observation in the customers that I talk to. Multicloud is not thus far, has not thus far has been a deliberate strategy. In my opinion, it's been the outcropping of multivendor, shadow IT, lines of business and I think the corner office is saying hold on, we need to reign this in, we need to have a better understanding of what our cloud strategy is, build a platform that is hybrid and sure, multicloud, to build our digital transformation. We need IT to basically help us build this out to make sure we comply with the corporate edicts and that's what's happening. It is early days. There's a long way to go. >> Yeah, as Dave, as you know, I sat right down the hallway from Chuck Hollis when he wrote that piece and I went and I called up Chuck and I was like hey Chuck, this sure sounds like my next generation virtual data center stuff that I joined the CTO office to work on and he's like yeah, yeah, new marketing branding and I wrote a piece, exactly what you said, Dave, on Wikibon.com, hybrid and multicloud were a bunch of pieces, you know. It's not a cohesive strategy. The management's not there. We're starting to see maturation. Some of the point products, you know, developed really fast. When we talk about VMware on AWS, that happened really fast. I heard if you stop by the VMware booth here at the show, they're showing outposts and I said is a diagram? No, no, I've got customers in production running this. I'm like hold on, I need to hear about this. Outpost in production? But that strategy as you said, hybrid and multicloud, we're starting to get there, starting to pull it together. David Foyer wrote a phenomenal piece about hybridcloud taxonomy. We've spent a lot of time on the research side. Really what does the industry need to do, how should customers think about all of the layers? You know, data and networking and all of these components to help make not just a bunch of pieces but actually drive innovation and help be better than the sum of its parts. >> Well ironic followup on that post, the Chuck Hollis post was around they called it the private cloud and it was all about homogeneity and now multicloud is everything but homogeneous. Outpost, however, is. Same hardware, same software, same control plane, same data plane so interesting juxtaposition. >> We'll see Amazon Outpost. Guys, go to SiliconAngle.com, Wikibon.com. Great hybridcloud, multicloud analysis coverage and news. And some of the headlines hitting the net here. Dell Technologies makes VMware linchpin of hybrid cloud, data center as a service, end user strategies from Zdnet. eWEEK, Dell makes major hybrid cloud push. Obviously great analysis, guys, right on the number. Day two, CUBE coverage here in Las Vegas. I'm John Furrier, Dave Vellante, Stu Miniman. We've got two sets. Rebecca Knight, Lisa Martin and more. Stay tuned for more coverage of day two after the short break. (upbeat music)

(electronic music) >> Hi, I'm Peter Burris. Welcome to Wikibon action item from theCUBE Studios in Palo Alto, California. So today we've got a great conversation and what we're going to be talking about is hybrid cloud. Hybrid cloud's been in the news a lot, lately. Larger consequences, from changes made by AWS, as they announced Outpost, and acknowledged for the first time that there's going to be a greater distribution of data and a greater distribution of function as enterprises, move to the cloud. We've been on top of this for quite some time, and have actually coined what we called true hybrid cloud. Which is the idea that increasingly we're going to see a need for a common set of capabilities and services, in multiple locations, so that the cloud can move to the data, and not the data automatically being presumed to move to the cloud. Now to have that conversation and to reveal some new research on what the cost and value propositions of the different options are that are available today. We've got David Foyer, David welcome to theCUBE. >> Thank you. >> So David, let's start, when we talk about hybrid cloud, we are seeing, a continuum of different options starting to emerge. What are the defining characteristics? >> So, yes, we're seeing a continuum emerging. We have a what we call stand alone of course at one end of the spectrum, and then we have multi cloud, and then we have loosely and tightly coupled, and then we have true, and as you go up the spectrum. So the dependents upon data depend on the data plain, dependents upon low latency, dependents on writing a systems of record, records. All of those increase as we're going from high latency and high bandwidth all the way up to low latency. >> So let me see if I got that right. So true hybrid cloud is at one end. >> Yes. >> And true hybrid cloud is, low latency, right on your work loads, simple as possible administration. That means we are typically going to have, a common stack in all locations. >> Yes. >> Next to that is this notion of tightly coupled, hybrid cloud, which could be higher latency, write oriented, could probably has a common set of software, on all nodes, that handles state. And then kind of this notion of loosely coupled. Multi well hybrid cloud, which is high latency, read oriented, which may have just API level coordination and commonality on all nodes. >> Yep that's right, and then you go down even further to just multi cloud, where you're just connecting things and each of them is independent of each other. >> So if I'm a CIO and I'm looking at a move to a cloud, I have to think about green field applications and the natural distribution of data for those green field applications, and that's going to help me choose which class of hybrid cloud, I'm going to use. But let's talk about the more challenging set of scenarios for most CIO's, which is the existing legacy applications. >> The systems of record. >> Yeah, the systems of record as I try to bring those, those cloud like experience to those applications, how am I going through that thought process? >> So, we have some choices, the choices are I could move it up too lift and shift, up to one of the cloud's, one of the large cloud's, many of them are around, and what if I, if I do that, what I need to be looking at is, what is the cost of moving that data, and what is the cost of pushing that up into the cloud, and what's the conversion cost, if I needed to move, to another database. >> And I think that's the biggest one, so that's just the cost of moving the data, which is just an ingress cost, it's a cost of format changes. >> Absolutely >> You know, migration and all the other elements, conversion changes et cetera. >> Right, so what I did in my research was focus on systems of record, the highly expensive, very, very important systems of record, which obviously are fed by a lot of other things, you know, systems of engagements, analytics et cetera. But those systems of record have to work. You need to know if you've taken an order. You need to have consistency about that order. You need to know always that you can recover any data, you need in your financials et cetera, all of that is mission critical systems of record. And that's the piece that I focused on here, and I focused on. >> So again these are low latency. >> Very, low latency, yes. >> Write oriented. >> Very write oriented, types of applications, and, I focused on Oracle because the majority, of systems of record, run on Oracle databases, the large scale ones at least. So, that's what we are focusing on here. So I, looking at the different options for a CIO, of how they would go, and there are three main options open at the moment, there's Oracle, Cloud, Cloud at customer, which gives the cloud experience. There is Microsoft Azure Stack, which has a Oracle database version of it, and Outposts, but we eliminated Outposts not because, it's not going to be any good, but because it's not there yet. >> You can't do research on it if it doesn't exist yet. >> (laughs) That's right. So, we focused on Oracle and Azure, and we focused on, what was the benefit of moving from a traditional environment, where you've got best of breed essentially on site, to this cloud environment. >> So, if we think about it, the normal way of thinking about this kind of a research, is that people talk about R.O.I, and historically that's been done by looking, by keeping the amount of work that's performed, as given, constant and then looking at how the different technology components compare from a call standpoint. But a move to Cloud, the promise of a move to Cloud is not predicated on lowering costs per say. You may have other financial considerations of course but, it's really predicated on the notion of the cloud experience. Which is intended to improve business results, so if we think about R.O.I, as being a numerator question, with the value is the amount of work you do, versus a denominator question which is what resources are consumed to perform that work. It's not just the denominator side, we really need to think about the numerator side as well. >> The value you are creating, yes. >> So, what kind of thing's are we focused on when we think about that value created, as a consequence of possibilities and options of the Cloud. >> Right, so both are important, so obviously when you move, to a cloud environment, you can simplify operations in particular, you can simplify recovery, you can simplify a whole number of things within the IT shop and those give you extra resources. And then the question is, do you just cash in on those resources and say okay I've made some changes, or do you use those resources to improve the ability of your systems to work. One important characteristic of IT, all IT and systems of record in particular, is that you get depreciation of that asset. Over time it becomes less fitted, to the environment, that it started with, so you have to do maintenance on it. You have to do maintenance and work, and as you know, most work done in an IT shop is on the maintenance side. >> Meaning it's an enhancement. >> It's maintenance and enhancement, yes. So making more resources available, and making it easier to do that maintenance, and making less things that are going to interfere with that, faster time to maintenance, faster time to new applications or improvements. Is really fundamental to systems of record. So that is the value that you can bring to it and you also bring value with lower better availability, higher availability as well. So those are the thing's we have put into the model, to see how the different approaches, and we were looking at really a total, one supplier being responsible for everything, which was the Oracle environment, and Oracle Cloud at Customer, to a sort of hybrid environment, more hybrid environment, where you had. >> Or mixed, or mixed. >> Mixed environment, yes. Where you had the equipment coming from different places. >> One vendor. >> The service, the Oracle, the Azure service, coming from Microsoft, and of course the database coming then from Oracle itself. And we found tremendous improvement in the value that you could get because of the single source. We found that a better model. >> So, the common source lead to efficiencies, that then allowed a business to generate new classes, of value >> Correct. >> Cause' as you said, you know, 70 plus percent of an IT or business is spent on technology, is associated with maintaining what's there, enhancing what's there, and a very limited amount is focused on new green field, and new types of applications. So if you can reduce the amount of time and energy, that goes into that heritage set of applications, those systems of record, then that opens up, that frees up resources to do some other things. >> And, having the flexibility now with things like Azure Stack and in the future AWS, of putting that resource either on premise or in the cloud, means that you can make decisions about where you process these things, about where the data is, about where the data needs to be, the best placement for the data for what you're trying to do. >> That decision is predicated on things like latency, but also regulatory environment, intellectual property control. >> And the cost of moving data up and down. So the three laws of the cloud, so having that flexibility of keeping it where you want to is a tremendous value in again, in terms of, the speed of deployment and the speed of improvement. >> So we'll get to the issues surrounding the denominator side of this. I want to come back to that numerator side. So the denominator again is, the resources consume, to deliver the work to the business, but when we talk about that denominator side, perhaps opening up additional monies, to do new types of development, new types of work. But, take us through some of the issues like what is a cloud experience associated with, single vendor, faster development, give us some of the issues that are really driving the value proposition above the line. >> The whole issue about Cloud is that you take away all of the requirements to deal with the hardware, deal with the orchestration of the storage, deal with all of these things, so instead of taking weeks, months to put in extra resources, you say, I want them, and it's there. >> So you're taking administrative tasks, out of the flow. >> Out of the flow yes. >> And as a consequence, things happen faster, so time of value is one of the first ones, give us another one. >> So, obviously the ability to have. It's a cloud environment, so if you're a vendor, of that cloud, what you want to be able to do, is to make incremental changes, quickly as opposed to waiting for a new release and work on the release basis. So that fundamental speed to change, speed to improve, bring in new features, bring in new services, a cloud first type model, that is a very powerful way for the vendor to push out new things, and for the consumer to absorb them. >> Right, so the first one is time to value, but also it's lower cost to innovation. >> Yes, faster innovation, ability to innovate. And then the third most important part is, if you re-invest those resources that you have saved into new services, new capabilities of doing that, to me the most important thing, long term for systems of record is to be able to make them go faster, and use that extra latency time there to bring in systems of analytics, AI systems, other systems, and provide automation of individual business processes, increased automation. That is going to happen overtime, that's a slow adding to it, but it means you can use those cloud mechanisms, those additional resources, wherever they are. You can use those to provide, a clear path to, improving the current systems of record. And that is a more faster and more cost effective way, than going in for a conversion, or moving the data up to the cloud or lift and shift, for these types of applications. >> So these are all kind of related, so I get superior innovation speeds, because I'm taking new technology and faster, I get faster time to value, because, I'm not having to perform a bunch of tasks, and I can get, I can imbue additional types of work, in support of automation, without dramatically, expanding the transactional latency and a rival way of transactions within the system of record. Okay so, how did Oracle and Azure, with Oracle, stack up in your analysis? >> So first of all important is both are viable solutions, they both would work. Okay, but the impact in terms of the total business value including obviously any savings on people and things like that, was 290 nearly, $300 million additional, this was for a >> For how big a company? >> For a fortune 2000 customer, so it was around two billion dollars, so a lot of money, over five years, a lot of money. Either way, you would save 200 million, if you were with the Azure, but 300 with the Oracle. So that to me is far, far higher than the costs of IT, for that particular company, it's a strategic decision, to be able to get more value out quicker, and for this class of work load, on Oracle, then Oracle at Cloud was the best decision, to be absolutely fair, if you were on Microsoft's database, and you wanted to go to Microsoft Azure, that would be the better bet. You would get back a lot of those benefits. >> So stay within the stack if you can. >> Correct. >> Alright, so, two billion dollars a year, five years. $10 billion revenue, roughly. >> Between 200 million in saving, for One Microsoft, Azure, plus Oracle. 300 million so a 1% swing, talk to us about speed, value what happens in, a numerator side of that equation? >> So, it is lower in cost, but you have a higher, the cost of the actual cloud, is a little higher, so, overall the pure hardware, equipment class is a wash, it's not going to change much. >> Got it. >> It might be a little bit more expensive. You make the savings, as well because of the people, less operators, simpler environment. Those are the savings you're going to make, and then you are going to push those back, into the organization, as increase value that can be given to the line of the business. >> So the conclusion to the research is that if you are a CIO, you look at your legacy application, it's going to be difficult to move and you go with the stack that's best for those, legacy applications. >> Correct. >> So the vast majority of systems of record, are running on Oracle. >> Large scale. >> Large scale, then that means Oracle Cloud at Customers, is the superior fit for most circumstances. >> For a lot of those. >> If you're not there though then look at other options. >> Absolutely. >> Alright, David Foyer. >> Thank you. >> Thanks, very much for being on the cube today. And you've been watching another Wikibon action item, from theCUBE Studios in Palo Alto California, I'm Peter Burris, thanks very much for watching. (electronic music)

>> Hi, I'm Peter Burroughs Wellcome to wicked bon action >> item from the Cube Studios in Palo Alto, California So today we've got a great conversation, and what we're going to be talking about is hybrid cloud hybrid. Claude's been in the news a lot lately. Largest consequences from changes made by a Ws is they announced Outpost and acknowledged for the first time that there's going to be a greater distribution of data on a greater distribution of function as enterprise has moved to the cloud. We've been on top of this for quite some time, and it actually coined what we call true hybrid cloud, which is the idea that increasingly, we're going to see a need for a common set of capabilities and services in multiple locations so that the cloud could move to the data and not the data automatically being presumed to move to the cloud. >> Now to have that >> conversation and to reveal some new research on what the cost in value propositions of the different options are available. Today. We've >> got David Foyer. David. Welcome to the Cube. Thank you. So, David, let's start. When we talk about Hybrid Cloud, we're seeing a continuum of different options start to emerge. What are the defining characteristics? >> Yes, we're seeing it could continue him emerging. We have what we've called standalone off course. That one is end of the spectrum on DH. There we have multi cloud, and then we have loosely and tightly coupled, and then we have true and as you go up the spectrum. So the dependence upon data depends on the data plane dependence upon low latent see dependance on writing does a systems of record records. All of those increase as we going from from lonely for High Leighton Sea and High Band with all way up to low late. >> So let me see if I got this right. It's true. I've a cloud is at one end and true. Either cloud is low late and see right on into workloads simplest possible administration. That means we're typically goingto have a common stack in all locations. Next to that is this notion of tightly coupled hybrid cloud, which could be higher late. And see, right oriented could probably has a common set of software on all no common mental state. And then, kind of this. This notion of loosely coupled right multi or hybrid cloud, which is low, high late and see, write or read oriented, which may have just a P I level coordination and commonality and all >> that's right. And then you go down even further to just multi cloud, where you're just connecting things, and each of them is independent off each other. >> So if I'm a CEO and I'm looking at a move to a cloud, I have to think about Greenfield applications and the natural distribution of data for those Greenfield applications. And that's going to help me choose which class of hybrid clawed him and he used. But let's talk about the more challenging from a set of scenarios for most CEOs, which is the existing legacy applications as I cry that Rangel yeah, systems of record. As I try to bring those those cloud like experience to those applications, how am I going through that thought process? >> So we have some choices. The choices are I could move it up to lift and shift up to on a one of the clouds by the large clouds, many of them around. And what if I if I do that what I'm need to be looking at is, what is the cost of moving that data? And what is the cost of pushing that up into the cloud and lost the conversion cast if I need to move to another database, >> and I think that's the biggest one. So it just costs of moving the data, which is just uninterested. It's a cost of format changes at our migration and all the other out conversion changes. >> So what I did in my research was focus on systems of record, the the highly expensive, very, very important systems of record, which obviously are fed by a lot of other things their systems, the engagement analytics, etcetera. But those systems of record have to work. They you need to know if you've taken on order, you need to have consistency about that order. You need to know always that you can recover any data you need in your financials, etcetera. All of that is mission critical systems of record. Andi, that's the piece that I focused on here, and I focused on >> sort of. These are loaded and she >> low, very low, latent, right oriented, very right orientated types of applications. And I focused on the oracle because the majority ofthe systems of record run on Oracle databases on the large scale ones, at least so that's what we're we're focusing on here. So I looking at the different options for a C I O off. How they would go on DH. There are three main options open at the moment. There's there's Arkalyk Cloud Cloud, a customer, which gives thie the cloud experience. There is Microsoft as your stack, which has a a Oracle database version of it on DH outposts. But we eliminated outposts not because it's not going to be any good, but because it's not there yet, is >> you get your Razor John thing. >> That's right. So we focused on Oracle on DH as you and we focused on what was the benefit of moving from a traditional environment where you've got best of breed essentially on site to this cloud environment. >> So if we think about it, the normal way of thinking about this kind of a research is that people talk about R. A Y and historically that's been done by looking by keeping the amount of work that's performed has given constant and then looking at how the different technology components compare from a call standpoint. But a move to cloud the promise of a move to cloud is not predicated on lowering costs per se, but may have other financial considerations, of course, but it's really predicated on the notion of the cod experience, which is intended to improve business results. So we think about our lives being a numerator question. Value is the amount of work you do versus the denominator question, which is what resources are consumed to perform that work. It's not just the denominator side we really need to think about. The numerator side is well, you create. So what? What kind of things are we focused >> on? What we think about that value created his consequence of possibilities and options of the cloud. >> Right? So both are important. So so Obviously, when you move to a cloud environment, you can simplify operations. In particular, you can simplify recovery. You, Khun simplify a whole number of things within the shop and those give you extra resources on. Then the question is, Do you just cash in on those resources and say OK, I've made some changes, Or do you use those resources to improve the ability of your systems to work and one important characteristic off it alight and systems of record in particular is that you get depreciation of that asset. Over time, it becomes less fitted to the environment it has started with, so you have to do maintenance on it. You have to do maintenance and work, and as you know most means most work done in my tea shop is on the maintenance side minutes. An enhancement. It's maintenance. An enhancement, yes. So making more resources available on making it easier to do that maintenance are making less, less things that are going to interfere with that faster time to to to maintenance faster time. Two new applications or improvements is really fundamental to systems of record, so that is the value that you can bring to it. And you also bring value with lower of better availability, higher availability as well. So those are the things that we put into the model to see how the different approaches. And we were looking at really a total one. One supplier being responsible for everything, which was the Oracle environment of Oracle clouded customer to a sort of hybrid invite more hybrid environment where you had the the the work environment where you had the equipment coming from different place vendor that the service, the oracle, the as your service coming from Microsoft and, of course, the database coming then from Arkham itself. And we found from tremendous improvement in the value that you could get because of this single source. We found that a better model. >> So the common source led to efficiencies that then allowed a business to generate new classes of value. Because, as you said, you know, seventy plus percent of a night organ orb business is spending. Biology is associate with maintaining which they're enhancing. What's there in a very limited amount is focused on new greenfield or new types of applications. So if you can reduce the amount of time energy that goes into that heritage set of applications those systems of record, the not opens up that frees up resources to do some of the things >> on DH Having inflexibility now with things like As your stack conned in the future E. W. S off. Putting that resource either on premise or in the cloud, means that you can make decisions about where you process things things about where the data is about, where the data needs to be, the best placement of the data for what you're trying to do >> and that that decision is predicated on things like late in sea, but also regulatory, environment and intellectual property, controlling >> the custom moving data up and down. So the three laws of off off the cloud so having that flexibility of moving, keeping it where you want to, is a tremendous value in again in terms ofthe the speed of deployment on the speed of improved. >> So we'll get to the issues surrounding the denominator side of this. I want to come back to that numerator sites that the denominator again is the resources consumed to deliver the work to the business. But when we talk about that denominator side, know you perhaps opening up additional monies to do new types of development new times of work. But take us through some of the issues like you know what is a cloud experience associated with single vendor Faster development. Give us some of the issues that are really driving the value proposition. Look above the line. >> I mean, the whole issue about cloud is that you go on, take away all of the requirements to deal with the hardware deal with the orchestration off the storage deal with all of these things. So instead of taking weeks, months to put in extra resources, you say I want them on is there. >> So you're taking out administrate your taking administrative tasks out of the flow out of the flow, and as a consequence, things happen. Faster is the time of values. One of the first one. Give us another one. >> So obviously the ability to no I have it's a cloud environment. So if you're a vendor of that cloud, what you want to be able to do is to make incremental changes quickly, as opposed to awaiting for a new release and work on a release basis. So that fundamental speed to change speed to improve, bring in new features. Bringing new services a cloud first type model that is a very powerful way for the vendor to push out new things. And for the consumer, too, has absorbed them. >> Right? So the first one is time to value, but also it's lower cost to innovation. >> Yes, faster innovation ability to innovate. And then the third. The third most important part is if you if you re invest those resources that you've saved into new services new capabilities of doing that. To me, the most important thing long term for systems of record is to be able to make them go faster and use that extra Leighton see time there to bring in systems off systems of analytics A. I systems other systems on provide automation of individual business processes, increased automation that is gonna happen over time. That's that's a slow adding to it. But it means you can use those cloud mechanisms, those additional resources, wherever they are. You can use those to provide a clear path to improving the current systems of record. And that is a much faster and more cost effective way than going in for a conversion or moving the data upto the cloud or shifting lift and shift. For these types of acts, >> what kind of they're all kind of related? So I get, I get. I get superior innovation speeds because I'm taking new technology and faster. I get faster time to value because I'm not having to perform much of tasks, and I could get future could imbue additional types of work in support of automation without dramatically expanding the transactional wait and see on arrival rate of turns actions within the system of record. Okay, So how did Oracle and Azure with Oracle stack up in your analysis? >> So first of all, important is both a viable solutions. They both would work okay, but the impact in terms of the total business value, including obviously any savings on people and things like that, was two hundred nineteen eighty three hundred million dollars additional. This was for Robert to come in for a a Fortune two thousand customer, so it was around two billion dollars. So a lot of money over five years, a lot of money. Either way, you would save two hundred million if you were with with the zero but three hundred with the oracle, so that that to me, is far, far higher than the costs of I T. For that particular company, it's It is a strategic decision to be able to get more value out quicker. And for this class of workload on Oracle than Arkalyk, Cloud was the best decision to be absolutely fair If you were on Microsoft's database. And you wanted to go to Microsoft as you. That would be the better bet you would. You would get back a lot of those benefits, >> so stay with him. The stack, if you can't. Correct. All right, So So two billion dollars a year. Five years, ten billion dollars in revenue, roughly between two hundred million and saving for one Congress all around three. Treasure Quest. Oracle three hundred millions were one percent swing. Talk to us about speed value. What >> happens in the numerator side of that equation >> S Oh, so it is lower in caste, but you have a higher. The cast of the actual cloud is a little a little higher. So overall, the pure hardware equipment Cass is is awash is not going to change much. It might be a little bit more expensive. You make the savings a cz? Well, because of the people you less less operators, simpler environment. Those are the savings you're going to make. And then you're going to push those back into into the organization a cz increased value that could be given to the line of business. >> So the closure of the researchers If your CEO, you look at your legacy application going to be difficult to move, and you go with stack. That's best for those legacy applications. And since the vast majority of systems of record or running all scale large scale, then that means work. A cloud of customers is a superior fit for most from a lot of chances. So if you're not there, though, when you look at other options, all right, David Floy er thank you. Thanks very much for being on the Cube today, and you've been watching other wicked bon action >> item from the Cube Studios and Power Rialto, California on Peter Burke's Thanks very much for watching.

from Las Vegas it's the queue covering VMworld 2018 brought to you by VMware and its ecosystem partners and we're back here at the Mandalay Bay in somewhat beautiful Las Vegas where we're doing third day of VMworld on the cube and on Peterborough and I'm joined by my two lead analysts here at Ricky bond with me Jim Camilo's who's looking at a lot of the software stuff David floor who's helping to drive a lot of our hardware's research guys you've spent an enormous amount of time talking to an enormous number of customers a lot of partners and we all participated in the Analyst Day on Monday let me give you my first impressions and I want to ask you guys some questions here you thought so I have it this is you know my third I guess VMworld in or in a row and and my impression is that this has been the most coherent of the VM worlds I've seen you can tell when a company's going through a transition because they're reaching to try to bring a story together and that sets the tone but this one hot calendar did a phenomenal job of setting up the story it makes sense it's coherent possibly because it aligns so well with what we think is going to happen in the industry so I want to ask you guys based on three days of one around and talking to customers David foyer what's been the high point what have you found is the most interesting thing well I think the most interesting thing is the excitement that there is over VMware if you if you contrast that with a two three years ago the degree of commitment of customers to viennois the degree of integration they're wanting to make the degree rate of change and ideas that have come out of VMware it's like two different companies totally different companies some of the highlights for me were the RDS the bringing from AWS to on site as well as on the AWS cloud RDS capabilities I think that's a very very interesting thing that's the relational database is services the Maria DB and all the other services that's a very exciting thing to me and a hint to me that AWS is going to have to get serious about well Moore's gone out I think it's a really interesting point that after a lot of conversations with a lot of folks saying all AWS it's all going to go up to the cloud and wondering whether that also is a one-way street for VMware Casta Moore's right but now we're seeing it's much more of a bilateral relationship it's a moving it to the right place and that's the second thing the embracing of multi-cloud by everybody one cloud is not going to do everything they're going to be SAS clouds they're going to be multiple places where people are gonna put certain workloads because that's the best strategic fit for it and the acceptance in the marketplace that that is where it's going to go I think that again is a major change so hybrid cloud and multi cloud environments and then the third thing is I think the richness of the ecosystem is amazing the the going on the floor and the number of people that have come to talk to us with new ideas really fascinating ideas is something I haven't seen at all for the last last three four years and so I'm gonna come back to you on that but it goes back to the first point that you make that yeah there is a palpable excitement here about VMware that two-three years ago the conversation was how much longer is the franchise gonna be around Jim but now it's clear yeah it's gonna be around Jim how about you yeah actually I'm like you guys I'm a newbie to VM world this is my very first remember I'm a big data analyst I'm a data science an AI guy but obviously I've been aware of VMware and I've had many contacts with them over the years my take away my prime and I like Pat Gail singers I agree with you Peter they're really coherent take and I like that phrase even though it sounds clucking impact kind of apologize they are the dial tone to the multi-cloud if the surgery really gives you a strong sense or who else can you character is in this whole market space cloud computing has essentially a multi cloud provider who provide the unifying virtualization glue to help their custom to help customers who are investing in an AWS and maybe in a bit of you know you're adopting Google and Microsoft Azure and so forth providing a virtualization layer that's the above server virtualization network virtualization VDI all the way to the edge nobody can put it all is putting it all together and quite the way that VMware is one of the my chief takeaways is similar to David's which is that in terms of the notion of a hybrid cloud VMware with its whole what's it's doing with RDS but also projects like this project dimension which is in project in progress taking essentially the entire VMware virtualization stack and putting it onto an appliance for deployment on the edges and then for them to manage it VMware of this their plans as an end-to-end managed edge cloud service and so forth Wow the blurring of public and private cloud I don't even think the term hybrid cloud applies it's just a blurry the common cloud yeah it's moving to the workload the clouds moving to the data which is exactly what we say they are halfway there in terms of that vision halfway in a sense that RDS has been announced the you know on the VMware and this project dimension they're well along with that if there was a briefings for the analyst space I'm really impressed for how they're architecting this I think they've got a shot to really dominate well I'll tell you so I would agree with you just to maybe provide a slightly different version of one of the things you said I definitely agree I think what's VMware hopes to do and I think they're not alone is to have AWS look like an appliance to their console to have as you look like an appliance of their Khan so through free em where you can get access to whatever services you need including your VMware machines your VMs inside those clouds but that increasingly their their goal is to be that control point that management point for all of these different resources that are building and it is very compelling I think that there's one area that I still think we need more from as analysts and we always got to look through no and what's yeah what was more required and I hear what you say about project dimension but I think that the edge story still requires a fair amount of work oh yeah it's a project in place but that's going to be an increasingly important locus of how architectures get laid out how people think about applications in the future how design happens how methodologies for building software work David what do you think what when you look out what what is what what is more is needed for you so really I think there are two things that give me a small concern the the edge that's a long term view so they got time to get that right but the edge view is very much an IT view top-down and they are looking to put in place everything that they think the OT people should fit in with I think that is personally not going to be a winning strategy you you have to take it from the bottom up the world is going to go towards devices very rich devices and sensors lots of software right on that device the inference work on those devices and the job of IT will be to integrate those devices it won't be those devices taking on the standards of IT it'll be IT that has to shape itself to look after all those devices there so that's a that's the main viewpoint I think that needs adjustment and it will come I'm sure over time but as you said there's a lot of computer science it's going to be an enormous amount of new partnerships are gonna be fabricate exactly to make this happen Jim what do you think yeah I agree terms of partnerships one big gap from both VMware and Dell technologies partnerships and romance and technology proposes AI now they have a project VMware call from another project called project Magna which is really AI ops in fact I published a wiki about reports this week on AI ops AI to drive IT Service Management and to and they're doing some stuff they're working on that project it's just you know the beginning stages I think what's going to happen is that vmware dell technologies they're gonna have to make strategic acquisitions of AI solution providers to build up that capability because that's going to be fundamental to their ability to manage this complex multi called fabric from end to end continuously they need that competency internally that can't be simply a partner providing that that's got to be their core competencies so you know I'm gonna push it I'll give you the contrarian point of view okay we actually had Khamsin VMware we've had a lot of conversations about this does that is that a reflection of David's point about top-down buying things and pushing it down as opposed to other conversations we've had about how the edge is going to evolve where a lot of OT guys are going to combine with business expertise and technology expertise to create specialized solutions and is and then VMware is gonna have to reach out to them and make VMware relevant to them do you think it's going to be VMware buying a bunch of stuff or an a-grade no solution or is it going to be the solutions coming from elsewhere and VM at VMware I just becoming more relevant to them now you can still be buying a bunch of stuff to get that horizontal in place but which way you think it's going to go I think it's gonna be the top-down they're gonna buy stuff because if I talk to the channel one of the channel people this morning about well you know but they've got an IOT connected bundle and so forth they announced this show you know I think they agree with me that the core AI technology needs to be built into the fundamentals like the IOT stack bundle that they then provide to the channel partners for with you know with channel specific content that they can then tweak and customize to their specific needs but you know the core requirements for a I are horizontal you know it's the ability to run neural networks to do predictive analysis anomaly detection and so forth this is all cross-cutting across all domains it has to be in the core application stack they can't be simply something they source for particular channel opportunities it has to be leveraged across you know the same core tensorflow models for anomaly detection for manufacturing for logistics for you know customer relationship management whatever it's or are you saying essentially that then VMware becomes that horizontal play even though even if the solution providers are increasingly close to the actual action where the edges III I'm gonna disagree we can gently on that but we'd still be friends [Music] no it's you know I'm I'm an OT guy of hearth I suppose and I think that that is going to be a stronger force in terms of VMware but there will be some places where you it will be top-down but other places that where it's going to be need needed to adjust but I think there's one other there very interesting area I'd like to bring up in terms of of this question of acquisition what what we heard about beforehand was excellent results and VMware has been adding a you know a billion dollars a year in terms of free cash there and they have thirteen billion in short term cash there and the the refinancing from Dell is gonna take eleven of that thirteen and put it towards the towards the the company now you can work towards deltek yes well just Dell Dell as a hold and and silver later towards those partners I I personally believe that there is such a lot of opportunity that's going to be out there if you take NSX for example it has the potential to do things in new areas they're gonna need to provide solutions in those new areas and aggressively go after those new areas and that's going to mean big investments and many other areas where I think they are going to need acquisitions to strengthen the whole story they have the whole multi-cloud story about this real-time operating system in a sexy has a network routing virtualization backplane I mean it needs to go real-time so sensitive guaranteed ladies if they need that big investments guarantee yeah they need to go there yeah so what we're agreeing on that and I get concerned that it's not going to be given the right resources you know to be able to actually go after the opportunities that they have genuinely created it's gonna mean from you see how that plays out so I think all drugs in the future I think saying though is that there is going to be a solution a set of solution players that VMware is going to have to make significant moves to make them relevant and then the question is where it's the values story what's the value proposition it's probably gonna be like all partnerships yeah some are gonna claim that they are doing it also some are gonna DM where it's gonna claim that they do more of it but at the end of the day VMware has to make themself relevant to the edge however that happens I want to pick up on NSX because I'm a pretty big believer that NSX may be the very special crown jewel and a lot of the stuff this notion of hybrid cloud whatever we call it let's just call it extended cloud let me talk of a better word like it is predicated on the idea that I also have a network that can naturally and easily not just bridge but truly multi network interoperate internet work with a lot of different cloud sources but also all different cloud locations and there's not a lot of technologies out there that are great candidates to do that and it's and I look at NSX and I'm wondering is that gonna be kind of a I want to take the metaphor too far but is that gonna be kind of a new tcp/ip for the cloud in the sense that you're still gonna run over tcp/ip and you're still gonna run over the Internet but now we're gonna get greater visibility into jobs into workloads into management infrastructures into data locations and data placement predictive movement and NSX is going to be the at the vanguard of showing how that's gonna work and the security side of that especially to be able to know what is connected to what and what shouldn't be connected to what and to be able to have that yeah they need stateful structured streaming others Kafka flink whatever they need that to be baked into the whole nsx virtualization layer that much more programmable and that provides that much better a target for applications all right last question then we got a wrap guys David as you walk out the door get in the plane what are you taking away what's your last impression my last impression is one of genuine excitement wanting to work wanting to follow up with so many of the smaller organizations the partners that have been here and who are genuinely providing in this ecosystem a very rich tapestry of of capability that's great Jim my takeaway is I want to see their roadmap for kubernetes and serverless there wasn't a hole last year they made an announcement of a serverless project I forgot what the code name is didn't hear a whole lot about it this year but they're going up the app stack they got a coop you know distribution you know they're if they need a developer story I mean developers are building functional apps and so forth you know you can and they're also containerized they need they need a developer story and they need a server list story and they need to you need to bring us up to speed on where they're going in that regard because AWS their predominant partner I mean they got lambda functions and all that stuff you know that's that's the development platform of the present and future and I'm not hearing an intersection of that story with VMware's a story yeah my last thing that I'll say is that I think that for the next five years VMware is gonna be one of the companies that shapes the future of the cloud and I don't think we would have said that a couple of names no they wouldn't I agree with you so you said yes all right so this has been the wiki bond research leadership team talking about what we've heard at VMware this year VMworld this year a lot of great conversation feel free to reach out to us and if you want to spend more time with rookie bond love to have you once again Peter burrows for David floor and Jim Kabila's thank you very much for watching the cube we'll talk to you again [Music]

(upbeat orchestral music) >> Hi I'm Peter Burris and welcome to another CUBE Conversation from our wonderful Palo Alto Studios. Great conversation today with Jeremy Werner who is the vice president of SSD Marketing at Toshiba Memory, Jeremy welcome to theCUBE. >> Thank you Peter, great to be here. >> You know Jeremy, one of the reasons why I find you being here so intriguing interesting is there's a lot going on in the industry. We talk about new types of workloads: AI, cloud, deep learning, all these other things, all these technologies are-- all these applications and workloads are absolutely dependent on the idea that the infrastructure has to start focusing less on just persisting memory and focusing more on delivering memory-- delivering data to these very advanced applications. That's where flash comes in. Tell us a little bit about the role that flash has had in the industry. >> It's amazing, thank you for recognizing that. So, flash has a long history. 30 years ago actually Toshiba invented flash memory, and it's had a transformation on people's lives everywhere, on all kinds of products starting with the very first application for flash being-- for NAND flash being kind of removable memory cards. You had the digital camera revolution, then it found its way into cell phones, that enabled smart phones and people carrying around all their media etc. And now we're in kind of this large third phase adoption which is, like you mentioned, the transition from persistent storage with a hard drive where, your data was available but not really available to do a lot with. To now storage on an SSD, which allows artificial intelligence, business analytics, and all the new workloads that are changing business paradigms. >> So clearly flash adoption is increasing in the data center. Wikibon has been talking about this for quite some time. My colleague David Foyer was one of the first people out there to project the role that flash was going to play within the data center. How are you seeing as you talk to customers, as you talk to some of the big systems manufacturers and some of the hyperscalers. How are you hearing or what are they saying about how they are applying and will intend to apply flash in the market today? >> It's amazing when we talk to customers they really can't get enough flash. As an industry we just came out of a major shortage of flash memory, and now a lot of new technologies are coming online. So, we at Toshiba, just announced our 96 layer 3D flash, our QLC flash. This is all in an attempt to get more flash storage into the hands of these customers so that they can bring these new applications to market. And this transformation, it's happening quickly although maybe not as quickly as people think because there's a very long road ahead of us. Still you look out 10 years into the future, you're talking about 40 or 50% growth per year, at least for the next decade. >> So I want to get to that in a second, but I want to touch upon something that you said that many of the naysayers about flash predicted that there would be shortfalls and they were very Chicken Little like. Oh my gosh, the sky is going to fall, the prices are going to go out of control. We did have a shortage, and it was a pretty significant one, but we were able to moderate some of the price increases so it didn't lead to a whole bunch of design losses or a disruption in how we thought about new workloads, did it? >> True, no it didn't, and I think that's the value of flash memory. Basically what we saw was the traditional significant decline in pricing took a pause, and you look back 20 years ago, I mean flash was 1000 times more expensive. And as we move down that cost curve, it enables more and more applications to adopt it. Even in today's pricing, flash is an amazingly valuable tool to data centers and enterprise as they roll out new workloads and particularly around analytics, and artificial intelligence, machine learning, kind of all the interesting new technologies that you hear about. >> Yeah, and I think that's probably going to be the way that these kinds of blips in supply are going to be-- it'll perhaps lead to a temporary moderation in how fast the prices drop. >> That's right. >> It's not going to lead to massive disruption and craziness. And I will also say this, you mentioned 20 years ago stuff was really expensive and I cut my teeth on mainframe stuff. And I remember when disk drives on the mainframe were $3500 a megabyte, so it could be a lot worse. So, let's now-- flash is a great technology, SSD is a great technology, but it's made valuable by an overall ecosystem. >> That's right. >> There's a lot of other supporting technologies that are really crucial here. Disk has been dominated by interfaces like SATA for a long time. Done very well by us. Allowed for a fair amount of parallelism, a lot of pathing to mainly disk, but that's starting to change as we start thinking about flash coming on and being able to provide much much faster access times. What's going on with SATA and what's on the horizon? >> Yeah, so great question. Really what we saw with SATA in about 2010 was the introduction of a six gigabit SATA interface, and that was a doubling of the prior speed that was available, and then zero progress since then, and actually the SATA roadmap has nothing forward. So people have been stuck effectively with that SATA interface for the last eight years. Now they've had some choices. You look at the existing ecosystem, the existing infrastructure, SATA and SAS drives were both choices, and SAS is a faster interface today up to 12 gigabit. It's full duplex where SATA is half duplex, so you can read and write in parallel, so actually you can get four times the speed on a SAS drive that you would get on a SATA drive today. The challenge with SAS, why everyone went to SATA-- I won't say everyone went to SATA, but maybe three or four times the adoption rate of SATA versus SAS was the SAS products that were available on the market really didn't deliver the most economical deployment of-- >> They were more expensive. >> They were more expensive. >> Alright, but that's changing. >> That is changing, so what we've been trying to do is prepare and work with our customers for a life after SATA. And it's been a long time coming, like I said eight years on this current interface. Recently we introduced what we call a value SAS product line. The value SAS product line brings a lot of the benefits of SAS, so the faster performance, the better reliability, and the better manageability, into the existing infrastructure, but at SATA-like economics. And that I think is going to be critical as customers look at the long-term life after SATA, which is the transition to NVMe and a flash-only world without having to be fully dependent on changing everything that they've ever done to move from SATA to NVMe. So, the life after SATA preparation on customers is how do I make the most out of my existing knowledge, my existing infrastructure capabilities. What's readily available from a support perspective as I prepare for that eventual transition to NVMe. >> Yeah I want to pick up on that notion of higher performance at improving cost of SAS and just make sure that we're clear here that SATA is an electrical interface. It has certain performance characteristics, but these new systems are putting an enormous amount of stress on that interface. And that means you can't put more work on top of that, not only from an application standpoint, but as you said crucially also from a management standpoint. When you put more reporting or you put more automation or your put more AI on some of these devices, that creates new load on those drives. Going to SAS releases that headroom, so now we can bring more management workloads. That's important, and this is what I want to test. That's important because as we do these more complex applications, we're pushing more work down closer to the data, and we're using a lot more data, it's going to require more automation. Is SAS going to provide the headroom that we need to actually bring new levels of reliability to more complex work? >> I believe it will, absolutely. SAS is the world's most trusted interface. So, when it comes to reliability, our SAS drives in the field are the most reliable product that our customers purchase today. And we take that same core technology and package in a way to make it truly an economical replacement for SATA. >> So we at Wikibon now have observed NVMe, so I want to turn a little bit of attention to that. We have observed that NVMe is in fact going to have a significant impact. But when Toshiba Memory is looking at what kinds of things customers are looking for, you're saying not so much SATA, let's focus on SAS, and let's bring NVMe online as the system designs are there. Is that kind of what it's about? >> You know I think it's a complicated situation. Not everyone is ready for everything at the same time. Even today, there's some major cloud providers that have just about fully transitioned to NVMe SSDs. And that transition has been challenging. So what we see is customers over the course of the next four or five years, their readiness for that transition from today to five years from now, that's happening based on the complexity of what they need to manage from a physical infrastructure, a software ecosystem perspective. So some customers have already migrated, and other customers are years away. And that is really what we're trying to help customers with. We have a very broad NVMe offering. Actually we have more NVMe SSDs than any other product line, but for a lot of those customers who want to continue with the digital transformation in to data analytics, in to realizing the value of all the data that they have available and transforming that into improved business processes, improved business results. Those customers don't want to have to wait for their infrastructure to catch up for NVMe. Value SAS gives them a means to make that transition, while continuing on to take advantage of all the capabilities of flash. One of the things that we always talk about, one of my responsibilities is product planning product definition, and one of the things that we always talk about is our ideal SSD, the bottleneck is the flash. In other words if you look at a drive there's so many things that could bottleneck performance. It could be the interface, it could be the power that you can consume and dissipate, it could be the megahertz in your controller >> You sound like an electrical engineer. >> I am an electrical engineer, but I'm a marketing guy, right? So, there's all kinds of bottlenecks, and when we design an SSD we want the flash to be the bottleneck cause at the end of the day, that's fundamentally what people need and want. And so, you look at SATA, and it's like, not only is it a bottleneck, but it's clamping the performance at 50% or less than 50% of what's achievable in the same power footprint, in the same cost footprint, so it's just not practical I mean the thing's eight years old so-- >> Yeah. Yeah. >> In technology eight years is a lot of time. >> Especially these days, and so to simplify that perhaps, or say that a little bit differently, bottom line is SAS is a smaller step for existing customers who don't have the expertise necessary to re-engineer an entire system and infrastructure. >> That's right, it gives them that stepping stone. >> So you also mentioned that there' a difference between the flash and the SSD, and that difference is an enormous amount of value-wide engineering that leads to automation, reliability, types of things you can do down at the drive. Talk to us a little bit about Toshiba, Toshiba Memory, as a supplier of that differentiating engineering that's going to lead to even superior performance at better cost and greater manageability and time to value on some of these new flash-based workloads. >> So I'm amazed at the quality of our engineering team and the challenges that they face to constantly be bringing out new technologies that keep up with the flash memory curve. And I actually joke sometimes, I say it's like being on a hamster wheel. It never stops, the second that you release a product you're developing the next product. I mean it's one of the fastest product life cycles in the entire industry, and you're talking about extremely complicated, complex systems with tight firmware development. So what we do at Toshiba Memory, we actually engineer our own SOCs and controllers, develop the RTL, manage that from basically architecture to production. We write all our own firmware, we assemble our own drives, we put it all together. The process for actually defining a product to when we release it is about five years. So we have meetings now, we're talking about what are we going to release in 2023? And that is one of the big challenges, because these design cycles are very long so anticipating where innovation is going, and today's innovation is at the speed of software, right? Not the speed of hardware. So how do you build that kind of flexibility and capability into your product so that you can keep up with new innovations no one might have seen five years ago? That's where Toshiba Memory's engineering team really shows its mettle. >> So let's get your back in theCUBE in the not-to-distant future to talk about what 2023 is going to look like, but for right now Jeremy Werner, Vice President of SSD Marketing at Toshiba Memory, thank you very much for being on theCUBE. >> Thank you, Peter. >> And once again, thanks for watching this CUBE Conversation. (upbeat orchestral music)

>> Announcer: Live from Chicago, Illinois. It's the Cube, covering Veeamon 2018. Brought to you by Veeam. >> Welcome back to Chicago everybody, this is the Cube, the leader in live tech coverage. My name is Dave Vellante, and I'm joined by my co-host Stewart Miniman, Ratmir Timashev is here, he's the cofounder of Veeam and in my opinion, the man who brought Veeam into the modern era, created the persona of Veeam, allowed it to punch above its way, Ratmir thanks for coming back in the Cube, great to see you again. >> Thank you Dave, thanks. >> So congratulations on another kickoff to another great event, you painted Chicago green. Love it, first of all how do you feel. >> Fantastic, awesome. It's great being here, great city, the weather is finally nice, so spring is here finally, so we are great time. >> Yeah we had a little trouble getting in, but everybody's here, everybody's here safely which is the most important thing. I want you to talk about the evolution of Veeam, you started out as a virtualization specialist, generally VMware specialists, especially focusing on small business. We used to see you everywhere, now you're extending into the enterprise. What's that all about, what's the vision, give us your perspective. >> You're absolutely right, Veeam started with the single focus to be the best for VMware, for VMware, data protection, cap replication, and we started as the easy to use, simple, powerful solution for SMB, moved into mid-enterprise and now we added lots of enterprise features, and moving into the large enterprise. And last year was really the most important and most successful year, 2017, in the history of Veeam, so we finally admitted that we'd be lying to our customers for 10 years. >> Dave: You've been lying? >> Yeah, we've been lying. >> What do you mean by that. >> For 10 years we've been saying, Veeam is VMware only, Veeam is high B only, we will never do physical. So last year we introduced the comprehensive M2M platform to do everything, virtual, physical, and cloud. So we integrated our agent-based technology into our flagship product, to provide a single panel blast to manage all your data across the cloud, M2M. >> Why lie for a decade? >> That's a good question. You know, when you deal with sales people, smart sales people, they constantly ask you, hey, when I will do that, I will go and do physical, I was going to do physical. You have to tell them no, never, because once you say yeah, we will do physical, the next question is when. >> Dave: Yeah, when can I sell it, right. >> So we don't want to give our sales people an excuse to lose a deal because we've got the best virtual, go and sell the best virtual, and make our customers happy. >> You don't want to head fake the customers either. >> Maybe explain, what were the core principles back from the early days that are still holding true, what is the same and what's different now that you're doing cloud and virtual. >> Again, the core principle. >> Stu: Or physical, I should say. >> For principle, again, in terms of the product design, think customer first, make it easy for the customer and really stick to your core customer, that customer that is using your product every day. So make it easy, powerful, and affordable. That was our core principles in designing the product, and the whole business model behind Veeam. >> Talk about the metrics a little bit. Stu and I were talking at the open, 820 some odd million in booking, so you can see a billion dollars. We said, software companies that are a billion dollars are few and far between so that's a huge milestone if and when you hit that. But talk about that and the growth, share with us whatever metrics you can. >> Again, 2017 was one of the most successful years in our history, yeah, like you mention, we recorded bookings revenue of 830 million and that was 36% growth. Actually, our growth is accelerating as we become bigger. So we just celebrated 300,000 customers, we are adding 4,000 new customers every day, and Peter Mackay, our president and co COO mentioned this morning at the keynote, that we're adding 133 customers every single day, so that's very impressive. >> Yeah, it's awesome. So yeah, just to give you a sense, 300,000 customers, VMware, who basically owns the enterprise, says slightly over half a million customers. >> So we probably are on 50% of VMware, so we own 50% of VMware market in terms of data protection. >> So one of the challenges that we mentioned upfront was okay, so you drove a truck through the opportunity when virtualization VMware came in, and a lot of the incumbents were caught flat footed. They didn't have the architecture, they didn't have the go to market, et. Cetera. Now things are changing, moving to cloud, moving to this digital world, how does Veeam retain its edge in that new world. >> That's an excellent question, so that's the big opportunities that we see for the next five years. So we won the first battle, the battle of on pram, highly virtualized modern data center. We are the leader, we are number one data protection and ideal ability for that market, right. So the next battle, the next opportunity that we see for the next five years is to dominate the, what we call intelligent data management market in the multi cloud world. So we have to think how we approach that, once you win the market, like there is a saying, the winner takes it all. Once you win the market, you are going to dominate that, so for us the next two or three years are the most critical in dominating this multi cloud world for the next decade. >> Ratmir, I'd love to hear, you wrote that virtualization wave, which really was about creating virtualization admin, huge shift going from silos to admins. And we're seeing that change from architects in the cloud and the like, talk to, who you're selling to, and the partners that you have to grow. There's just so much change happening in that kind of environment. >> Yeah we see the change as we are moving from VMware administrator, so originally the product was designed for VMware administrator, now we are moving to the infrastructure person that is responsible not just for private part of your infrastructure, but for the multi cloud strategy, which includes the public cloud, SAS, physical servers, everything than an enterprise has as far as the infrastructure. >> Okay, so I want to go through just a couple of things that we talked about earlier and get your reaction to this. So some of the things that we've seen in our research is that data protection and orchestration are becoming much much more important in the list of CXO concerns. And that's something that your messaging is going after. But there's a dissonance between the business expects out of data protection and what IT is actually delivering, and I wonder if you can comment on that. >> Sure, so yeah, we are introducing our new message. So our previous message was focused on VMware administrator, now we are moving into the enterprise, and our message is about the importance of data. We see the three characteristics of the modern data, hyper critical, hyper sprawled, and hyper growth. So this leads to the need of creating a new type of solution what we call is intelligent data management solution. To manage the hyper available enterprise. So we're using the word hyper a lot because the data is now hyper critical, it's over distributed, hyper distributed, and is growing exponentially. That's part of our new message, that as we go into the C level people, about how important this data, and what with all the things that going on, in terms of the security compliance and how we're going to extend this platform to solve other business issues and provide more value and more business outcomes of using your late. Veeam's emporium has grown within this enterprise customers. However, as we mentioned, we are moving further, we are not standing still, so we have added lots of capabilities in terms of protecting cloud, native cloud, AWS, Azure, as well as a physical servers. So we are moving more into the end to end strategic data management platform provider from being just a niche point solution. >> I want to give you another stat that came out of our research, which I think you'll love, is that our David Foyer calculated that on average, a Fortune 1000 company over I think a three or a four year period, loses about a billion and a half dollars in value because of poorly architected data protection approaches, whether it's they're not end to end, or they're not protecting their cloud data properly, or they're not doing, whether it's backup or disaster recovery properly, well over a billion dollars over a four year period, your thoughts. >> Yeah, that's similar to what our research shows as well. So we do annual research and ask all customers how much down time and data loss costs them annually or through hour, that research shows that average enterprise can lose as much as over 10 million dollars per hour, so if you add it up over four years, that might be close to that number. But with all the compliance and the new security risks and security threat, and reason where this is becoming more and more of a critical business critical problem to solve. >> So this is a huge opportunity for Veeam, because when you think about your total available market, what a lot of time analysts will do is they'll add up all the spending on let's say data protection solutions, but to me your tam is actually quite a bit larger because of this lost revenue opportunity. It's many tens of billions, maybe 30 to 50 billion, I don't know if you have any thoughts on that. >> Yeah definitely, so data protection is just part of that core market right, so that data management is much bigger, by data management we mean not just the protection of data, but using this data to help businesses, to accelerate the innovation rate, so to reduce risk, to comply with the new regulations. So all these challenges are much bigger part of not just the data backup and recovery, overall data management market which is much bigger and probably is larger than 20, 30 billion range. >> So okay, so you have 2,500, 3,000 of your favorite people here gathered this week. As always I expect that you're going to have a big sendoff, a big party, what can we expect this week. >> As always, that's part of the Veeam culture, is work hard, play hard, and so Veeam is known for having the best parties. Yeah we, now Peter runs the company day to day, but culturally we still remain young entrepreneurial spirited company right, so we like party and we like to work hard. >> Well you know, if you've never been to a Veeam party, you're missing it. I don't usually stay for these things, I get out of here, we have to do so many Cubes, but we'll be at the Veeam party this week. >> Awesome, awesome. >> Thanks very much, always a pleasure seeing you, and congratulations on all your success. >> Thank you very much. >> Alright you're welcome. Keep it right there everybody, we'll be back with our next guest, you're watching the Cube from Veeamon 2018. We're in the Windy City and we'll be right back.