>>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) >> The ascendancy of cloud and SAS has shown new light on how organizations think about, pay for, and value hardware. Once sought after skills for practitioners with expertise in hardware troubleshooting, configuring ports, tuning storage arrays, and maximizing server utilization has been superseded by demand for cloud architects, DevOps pros, developers with expertise in microservices, container, application development, and like. Even a company like Dell, the largest hardware company in enterprise tech touts that it has more software engineers than those working in hardware. Begs the question, is hardware going the way of Coball? Well, not likely. Software has to run on something, but the labor needed to deploy, and troubleshoot, and manage hardware infrastructure is shifting. At the same time, we've seen the value flow also shifting in hardware. Once a world dominated by X86 processors value is flowing to alternatives like Nvidia and arm based designs. Moreover, other componentry like NICs, accelerators, and storage controllers are becoming more advanced, integrated, and increasingly important. The question is, does it matter? And if so, why does it matter and to whom? What does it mean to customers, workloads, OEMs, and the broader society? Hello and welcome to this week's Wikibon theCUBE Insights powered by ETR. In this breaking analysis, we've organized a special power panel of industry analysts and experts to address the question, does hardware still matter? Allow me to introduce the panel. Bob O'Donnell is president and chief analyst at TECHnalysis Research. Zeus Kerravala is the founder and principal analyst at ZK Research. David Nicholson is a CTO and tech expert. Keith Townson is CEO and founder of CTO Advisor. And Marc Staimer is the chief dragon slayer at Dragon Slayer Consulting and oftentimes a Wikibon contributor. Guys, welcome to theCUBE. Thanks so much for spending some time here. >> Good to be here. >> Thanks. >> Thanks for having us. >> Okay before we get into it, I just want to bring up some data from ETR. This is a survey that ETR does every quarter. It's a survey of about 1200 to 1500 CIOs and IT buyers and I'm showing a subset of the taxonomy here. This XY axis and the vertical axis is something called net score. That's a measure of spending momentum. It's essentially the percentage of customers that are spending more on a particular area than those spending less. You subtract the lesses from the mores and you get a net score. Anything the horizontal axis is pervasion in the data set. Sometimes they call it market share. It's not like IDC market share. It's just the percentage of activity in the data set as a percentage of the total. That red 40% line, anything over that is considered highly elevated. And for the past, I don't know, eight to 12 quarters, the big four have been AI and machine learning, containers, RPA and cloud and cloud of course is very impressive because not only is it elevated in the vertical access, but you know it's very highly pervasive on the horizontal. So what I've done is highlighted in red that historical hardware sector. The server, the storage, the networking, and even PCs despite the work from home are depressed in relative terms. And of course, data center collocation services. Okay so you're seeing obviously hardware is not... People don't have the spending momentum today that they used to. They've got other priorities, et cetera, but I want to start and go kind of around the horn with each of you, what is the number one trend that each of you sees in hardware and why does it matter? Bob O'Donnell, can you please start us off? >> Sure Dave, so look, I mean, hardware is incredibly important and one comment first I'll make on that slide is let's not forget that hardware, even though it may not be growing, the amount of money spent on hardware continues to be very, very high. It's just a little bit more stable. It's not as subject to big jumps as we see certainly in other software areas. But look, the important thing that's happening in hardware is the diversification of the types of chip architectures we're seeing and how and where they're being deployed, right? You refer to this in your opening. We've moved from a world of x86 CPUs from Intel and AMD to things like obviously GPUs, DPUs. We've got VPU for, you know, computer vision processing. We've got AI-dedicated accelerators, we've got all kinds of other network acceleration tools and AI-powered tools. There's an incredible diversification of these chip architectures and that's been happening for a while but now we're seeing them more widely deployed and it's being done that way because workloads are evolving. The kinds of workloads that we're seeing in some of these software areas require different types of compute engines than traditionally we've had. The other thing is (coughs), excuse me, the power requirements based on where geographically that compute happens is also evolving. This whole notion of the edge, which I'm sure we'll get into a little bit more detail later is driven by the fact that where the compute actually sits closer to in theory the edge and where edge devices are, depending on your definition, changes the power requirements. It changes the kind of connectivity that connects the applications to those edge devices and those applications. So all of those things are being impacted by this growing diversity in chip architectures. And that's a very long-term trend that I think we're going to continue to see play out through this decade and well into the 2030s as well. >> Excellent, great, great points. Thank you, Bob. Zeus up next, please. >> Yeah, and I think the other thing when you look at this chart to remember too is, you know, through the pandemic and the work from home period a lot of companies did put their office modernization projects on hold and you heard that echoed, you know, from really all the network manufacturers anyways. They always had projects underway to upgrade networks. They put 'em on hold. Now that people are starting to come back to the office, they're looking at that now. So we might see some change there, but Bob's right. The size of those market are quite a bit different. I think the other big trend here is the hardware companies, at least in the areas that I look at networking are understanding now that it's a combination of hardware and software and silicon that works together that creates that optimum type of performance and experience, right? So some things are best done in silicon. Some like data forwarding and things like that. Historically when you look at the way network devices were built, you did everything in hardware. You configured in hardware, they did all the data for you, and did all the management. And that's been decoupled now. So more and more of the control element has been placed in software. A lot of the high-performance things, encryption, and as I mentioned, data forwarding, packet analysis, stuff like that is still done in hardware, but not everything is done in hardware. And so it's a combination of the two. I think, for the people that work with the equipment as well, there's been more shift to understanding how to work with software. And this is a mistake I think the industry made for a while is we had everybody convinced they had to become a programmer. It's really more a software power user. Can you pull things out of software? Can you through API calls and things like that. But I think the big frame here is, David, it's a combination of hardware, software working together that really make a difference. And you know how much you invest in hardware versus software kind of depends on the performance requirements you have. And I'll talk about that later but that's really the big shift that's happened here. It's the vendors that figured out how to optimize performance by leveraging the best of all of those. >> Excellent. You guys both brought up some really good themes that we can tap into Dave Nicholson, please. >> Yeah, so just kind of picking up where Bob started off. Not only are we seeing the rise of a variety of CPU designs, but I think increasingly the connectivity that's involved from a hardware perspective, from a kind of a server or service design perspective has become increasingly important. I think we'll get a chance to look at this in more depth a little bit later but when you look at what happens on the motherboard, you know we're not in so much a CPU-centric world anymore. Various application environments have various demands and you can meet them by using a variety of components. And it's extremely significant when you start looking down at the component level. It's really important that you optimize around those components. So I guess my summary would be, I think we are moving out of the CPU-centric hardware model into more of a connectivity-centric model. We can talk more about that later. >> Yeah, great. And thank you, David, and Keith Townsend I really interested in your perspectives on this. I mean, for years you worked in a data center surrounded by hardware. Now that we have the software defined data center, please chime in here. >> Well, you know, I'm going to dig deeper into that software-defined data center nature of what's happening with hardware. Hardware is meeting software infrastructure as code is a thing. What does that code look like? We're still trying to figure out but servicing up these capabilities that the previous analysts have brought up, how do I ensure that I can get the level of services needed for the applications that I need? Whether they're legacy, traditional data center, workloads, AI ML, workloads, workloads at the edge. How do I codify that and consume that as a service? And hardware vendors are figuring this out. HPE, the big push into GreenLake as a service. Dale now with Apex taking what we need, these bare bone components, moving it forward with DDR five, six CXL, et cetera, and surfacing that as cold or as services. This is a very tough problem. As we transition from consuming a hardware-based configuration to this infrastructure as cold paradigm shift. >> Yeah, programmable infrastructure, really attacking that sort of labor discussion that we were having earlier, okay. Last but not least Marc Staimer, please. >> Thanks, Dave. My peers raised really good points. I agree with most of them, but I'm going to disagree with the title of this session, which is, does hardware matter? It absolutely matters. You can't run software on the air. You can't run it in an ephemeral cloud, although there's the technical cloud and that's a different issue. The cloud is kind of changed everything. And from a market perspective in the 40 plus years I've been in this business, I've seen this perception that hardware has to go down in price every year. And part of that was driven by Moore's law. And we're coming to, let's say a lag or an end, depending on who you talk to Moore's law. So we're not doubling our transistors every 18 to 24 months in a chip and as a result of that, there's been a higher emphasis on software. From a market perception, there's no penalty. They don't put the same pressure on software from the market to reduce the cost every year that they do on hardware, which kind of bass ackwards when you think about it. Hardware costs are fixed. Software costs tend to be very low. It's kind of a weird thing that we do in the market. And what's changing is we're now starting to treat hardware like software from an OPEX versus CapEx perspective. So yes, hardware matters. And we'll talk about that more in length. >> You know, I want to follow up on that. And I wonder if you guys have a thought on this, Bob O'Donnell, you and I have talked about this a little bit. Marc, you just pointed out that Moore's laws could have waning. Pat Gelsinger recently at their investor meeting said that he promised that Moore's law is alive and well. And the point I made in breaking analysis was okay, great. You know, Pat said, doubling transistors every 18 to 24 months, let's say that Intel can do that. Even though we know it's waning somewhat. Look at the M1 Ultra from Apple (chuckles). In about 15 months increased transistor density on their package by 6X. So to your earlier point, Bob, we have this sort of these alternative processors that are really changing things. And to Dave Nicholson's point, there's a whole lot of supporting components as well. Do you have a comment on that, Bob? >> Yeah, I mean, it's a great point, Dave. And one thing to bear in mind as well, not only are we seeing a diversity of these different chip architectures and different types of components as a number of us have raised the other big point and I think it was Keith that mentioned it. CXL and interconnect on the chip itself is dramatically changing it. And a lot of the more interesting advances that are going to continue to drive Moore's law forward in terms of the way we think about performance, if perhaps not number of transistors per se, is the interconnects that become available. You're seeing the development of chiplets or tiles, people use different names, but the idea is you can have different components being put together eventually in sort of a Lego block style. And what that's also going to allow, not only is that going to give interesting performance possibilities 'cause of the faster interconnect. So you can share, have shared memory between things which for big workloads like AI, huge data sets can make a huge difference in terms of how you talk to memory over a network connection, for example, but not only that you're going to see more diversity in the types of solutions that can be built. So we're going to see even more choices in hardware from a silicon perspective because you'll be able to piece together different elements. And oh, by the way, the other benefit of that is we've reached a point in chip architectures where not everything benefits from being smaller. We've been so focused and so obsessed when it comes to Moore's law, to the size of each individual transistor and yes, for certain architecture types, CPUs and GPUs in particular, that's absolutely true, but we've already hit the point where things like RF for 5g and wifi and other wireless technologies and a whole bunch of other things actually don't get any better with a smaller transistor size. They actually get worse. So the beauty of these chiplet architectures is you could actually combine different chip manufacturing sizes. You know you hear about four nanometer and five nanometer along with 14 nanometer on a single chip, each one optimized for its specific application yet together, they can give you the best of all worlds. And so we're just at the very beginning of that era, which I think is going to drive a ton of innovation. Again, gets back to my comment about different types of devices located geographically different places at the edge, in the data center, you know, in a private cloud versus a public cloud. All of those things are going to be impacted and there'll be a lot more options because of this silicon diversity and this interconnect diversity that we're just starting to see. >> Yeah, David. David Nicholson's got a graphic on that. They're going to show later. Before we do that, I want to introduce some data. I actually want to ask Keith to comment on this before we, you know, go on. This next slide is some data from ETR that shows the percent of customers that cited difficulty procuring hardware. And you can see the red is they had significant issues and it's most pronounced in laptops and networking hardware on the far right-hand side, but virtually all categories, firewalls, peripheral servers, storage are having moderately difficult procurement issues. That's the sort of pinkish or significant challenges. So Keith, I mean, what are you seeing with your customers in the hardware supply chains and bottlenecks? And you know we're seeing it with automobiles and appliances but so it goes beyond IT. The semiconductor, you know, challenges. What's been the impact on the buyer community and society and do you have any sense as to when it will subside? >> You know, I was just asked this question yesterday and I'm feeling the pain. People question, kind of a side project within the CTO advisor, we built a hybrid infrastructure, traditional IT data center that we're walking with the traditional customer and modernizing that data center. So it was, you know, kind of a snapshot of time in 2016, 2017, 10 gigabit, ARISTA switches, some older Dell's 730 XD switches, you know, speeds and feeds. And we said we would modern that with the latest Intel stack and connected to the public cloud and then the pandemic hit and we are experiencing a lot of the same challenges. I thought we'd easily migrate from 10 gig networking to 25 gig networking path that customers are going on. The 10 gig network switches that I bought used are now double the price because you can't get legacy 10 gig network switches because all of the manufacturers are focusing on the more profitable 25 gig for capacity, even the 25 gig switches. And we're focused on networking right now. It's hard to procure. We're talking about nine to 12 months or more lead time. So we're seeing customers adjust by adopting cloud. But if you remember early on in the pandemic, Microsoft Azure kind of gated customers that didn't have a capacity agreement. So customers are keeping an eye on that. There's a desire to abstract away from the underlying vendor to be able to control or provision your IT services in a way that we do with VMware VP or some other virtualization technology where it doesn't matter who can get me the hardware, they can just get me the hardware because it's critically impacting projects and timelines. >> So that's a great setup Zeus for you with Keith mentioned the earlier the software-defined data center with software-defined networking and cloud. Do you see a day where networking hardware is monetized and it's all about the software, or are we there already? >> No, we're not there already. And I don't see that really happening any time in the near future. I do think it's changed though. And just to be clear, I mean, when you look at that data, this is saying customers have had problems procuring the equipment, right? And there's not a network vendor out there. I've talked to Norman Rice at Extreme, and I've talked to the folks at Cisco and ARISTA about this. They all said they could have had blowout quarters had they had the inventory to ship. So it's not like customers aren't buying this anymore. Right? I do think though, when it comes to networking network has certainly changed some because there's a lot more controls as I mentioned before that you can do in software. And I think the customers need to start thinking about the types of hardware they buy and you know, where they're going to use it and, you know, what its purpose is. Because I've talked to customers that have tried to run software and commodity hardware and where the performance requirements are very high and it's bogged down, right? It just doesn't have the horsepower to run it. And, you know, even when you do that, you have to start thinking of the components you use. The NICs you buy. And I've talked to customers that have simply just gone through the process replacing a NIC card and a commodity box and had some performance problems and, you know, things like that. So if agility is more important than performance, then by all means try running software on commodity hardware. I think that works in some cases. If performance though is more important, that's when you need that kind of turnkey hardware system. And I've actually seen more and more customers reverting back to that model. In fact, when you talk to even some startups I think today about when they come to market, they're delivering things more on appliances because that's what customers want. And so there's this kind of app pivot this pendulum of agility and performance. And if performance absolutely matters, that's when you do need to buy these kind of turnkey, prebuilt hardware systems. If agility matters more, that's when you can go more to software, but the underlying hardware still does matter. So I think, you know, will we ever have a day where you can just run it on whatever hardware? Maybe but I'll long be retired by that point. So I don't care. >> Well, you bring up a good point Zeus. And I remember the early days of cloud, the narrative was, oh, the cloud vendors. They don't use EMC storage, they just run on commodity storage. And then of course, low and behold, you know, they've trot out James Hamilton to talk about all the custom hardware that they were building. And you saw Google and Microsoft follow suit. >> Well, (indistinct) been falling for this forever. Right? And I mean, all the way back to the turn of the century, we were calling for the commodity of hardware. And it's never really happened because you can still drive. As long as you can drive innovation into it, customers will always lean towards the innovation cycles 'cause they get more features faster and things. And so the vendors have done a good job of keeping that cycle up but it'll be a long time before. >> Yeah, and that's why you see companies like Pure Storage. A storage company has 69% gross margins. All right. I want to go jump ahead. We're going to bring up the slide four. I want to go back to something that Bob O'Donnell was talking about, the sort of supporting act. The diversity of silicon and we've marched to the cadence of Moore's law for decades. You know, we asked, you know, is Moore's law dead? We say it's moderating. Dave Nicholson. You want to talk about those supporting components. And you shared with us a slide that shift. You call it a shift from a processor-centric world to a connect-centric world. What do you mean by that? And let's bring up slide four and you can talk to that. >> Yeah, yeah. So first, I want to echo this sentiment that the question does hardware matter is sort of the answer is of course it matters. Maybe the real question should be, should you care about it? And the answer to that is it depends who you are. If you're an end user using an application on your mobile device, maybe you don't care how the architecture is put together. You just care that the service is delivered but as you back away from that and you get closer and closer to the source, someone needs to care about the hardware and it should matter. Why? Because essentially what hardware is doing is it's consuming electricity and dollars and the more efficiently you can configure hardware, the more bang you're going to get for your buck. So it's not only a quantitative question in terms of how much can you deliver? But it also ends up being a qualitative change as capabilities allow for things we couldn't do before, because we just didn't have the aggregate horsepower to do it. So this chart actually comes out of some performance tests that were done. So it happens to be Dell servers with Broadcom components. And the point here was to peel back, you know, peel off the top of the server and look at what's in that server, starting with, you know, the PCI interconnect. So PCIE gen three, gen four, moving forward. What are the effects on from an interconnect versus on performance application performance, translating into new orders per minute, processed per dollar, et cetera, et cetera? If you look at the advances in CPU architecture mapped against the advances in interconnect and storage subsystem performance, you can see that CPU architecture is sort of lagging behind in a way. And Bob mentioned this idea of tiling and all of the different ways to get around that. When we do performance testing, we can actually peg CPUs, just running the performance tests without any actual database environments working. So right now we're at this sort of imbalance point where you have to make sure you design things properly to get the most bang per kilowatt hour of power per dollar input. So the key thing here what this is highlighting is just as a very specific example, you take a card that's designed as a gen three PCIE device, and you plug it into a gen four slot. Now the card is the bottleneck. You plug a gen four card into a gen four slot. Now the gen four slot is the bottleneck. So we're constantly chasing these bottlenecks. Someone has to be focused on that from an architectural perspective, it's critically important. So there's no question that it matters. But of course, various people in this food chain won't care where it comes from. I guess a good analogy might be, where does our food come from? If I get a steak, it's a pink thing wrapped in plastic, right? Well, there are a lot of inputs that a lot of people have to care about to get that to me. Do I care about all of those things? No. Are they important? They're critically important. >> So, okay. So all I want to get to the, okay. So what does this all mean to customers? And so what I'm hearing from you is to balance a system it's becoming, you know, more complicated. And I kind of been waiting for this day for a long time, because as we all know the bottleneck was always the spinning disc, the last mechanical. So people who wrote software knew that when they were doing it right, the disc had to go and do stuff. And so they were doing other things in the software. And now with all these new interconnects and flash and things like you could do atomic rights. And so that opens up new software possibilities and combine that with alternative processes. But what's the so what on this to the customer and the application impact? Can anybody address that? >> Yeah, let me address that for a moment. I want to leverage some of the things that Bob said, Keith said, Zeus said, and David said, yeah. So I'm a bit of a contrarian in some of this. For example, on the chip side. As the chips get smaller, 14 nanometer, 10 nanometer, five nanometer, soon three nanometer, we talk about more cores, but the biggest problem on the chip is the interconnect from the chip 'cause the wires get smaller. People don't realize in 2004 the latency on those wires in the chips was 80 picoseconds. Today it's 1300 picoseconds. That's on the chip. This is why they're not getting faster. So we maybe getting a little bit slowing down in Moore's law. But even as we kind of conquer that you still have the interconnect problem and the interconnect problem goes beyond the chip. It goes within the system, composable architectures. It goes to the point where Keith made, ultimately you need a hybrid because what we're seeing, what I'm seeing and I'm talking to customers, the biggest issue they have is moving data. Whether it be in a chip, in a system, in a data center, between data centers, moving data is now the biggest gating item in performance. So if you want to move it from, let's say your transactional database to your machine learning, it's the bottleneck, it's moving the data. And so when you look at it from a distributed environment, now you've got to move the compute to the data. The only way to get around these bottlenecks today is to spend less time in trying to move the data and more time in taking the compute, the software, running on hardware closer to the data. Go ahead. >> So is this what you mean when Nicholson was talking about a shift from a processor centric world to a connectivity centric world? You're talking about moving the bits across all the different components, not having the processor you're saying is essentially becoming the bottleneck or the memory, I guess. >> Well, that's one of them and there's a lot of different bottlenecks, but it's the data movement itself. It's moving away from, wait, why do we need to move the data? Can we move the compute, the processing closer to the data? Because if we keep them separate and this has been a trend now where people are moving processing away from it. It's like the edge. I think it was Zeus or David. You were talking about the edge earlier. As you look at the edge, who defines the edge, right? Is the edge a closet or is it a sensor? If it's a sensor, how do you do AI at the edge? When you don't have enough power, you don't have enough computable. People were inventing chips to do that. To do all that at the edge, to do AI within the sensor, instead of moving the data to a data center or a cloud to do the processing. Because the lag in latency is always limited by speed of light. How fast can you move the electrons? And all this interconnecting, all the processing, and all the improvement we're seeing in the PCIE bus from three, to four, to five, to CXL, to a higher bandwidth on the network. And that's all great but none of that deals with the speed of light latency. And that's an-- Go ahead. >> You know Marc, no, I just want to just because what you're referring to could be looked at at a macro level, which I think is what you're describing. You can also look at it at a more micro level from a systems design perspective, right? I'm going to be the resident knuckle dragging hardware guy on the panel today. But it's exactly right. You moving compute closer to data includes concepts like peripheral cards that have built in intelligence, right? So again, in some of this testing that I'm referring to, we saw dramatic improvements when you basically took the horsepower instead of using the CPU horsepower for the like IO. Now you have essentially offload engines in the form of storage controllers, rate controllers, of course, for ethernet NICs, smart NICs. And so when you can have these sort of offload engines and we've gone through these waves over time. People think, well, wait a minute, raid controller and NVMe? You know, flash storage devices. Does that make sense? It turns out it does. Why? Because you're actually at a micro level doing exactly what you're referring to. You're bringing compute closer to the data. Now, closer to the data meaning closer to the data storage subsystem. It doesn't solve the macro issue that you're referring to but it is important. Again, going back to this idea of system design optimization, always chasing the bottleneck, plugging the holes. Someone needs to do that in this value chain in order to get the best value for every kilowatt hour of power and every dollar. >> Yeah. >> Well this whole drive performance has created some really interesting architectural designs, right? Like Nickelson, the rise of the DPU right? Brings more processing power into systems that already had a lot of processing power. There's also been some really interesting, you know, kind of innovation in the area of systems architecture too. If you look at the way Nvidia goes to market, their drive kit is a prebuilt piece of hardware, you know, optimized for self-driving cars, right? They partnered with Pure Storage and ARISTA to build that AI-ready infrastructure. I remember when I talked to Charlie Giancarlo, the CEO of Pure about when the three companies rolled that out. He said, "Look, if you're going to do AI, "you need good store. "You need fast storage, fast processor and fast network." And so for customers to be able to put that together themselves was very, very difficult. There's a lot of software that needs tuning as well. So the three companies partner together to create a fully integrated turnkey hardware system with a bunch of optimized software that runs on it. And so in that case, in some ways the hardware was leading the software innovation. And so, the variety of different architectures we have today around hardware has really exploded. And I think it, part of the what Bob brought up at the beginning about the different chip design. >> Yeah, Bob talked about that earlier. Bob, I mean, most AI today is modeling, you know, and a lot of that's done in the cloud and it looks from my standpoint anyway that the future is going to be a lot of AI inferencing at the edge. And that's a radically different architecture, Bob, isn't it? >> It is, it's a completely different architecture. And just to follow up on a couple points, excellent conversation guys. Dave talked about system architecture and really this that's what this boils down to, right? But it's looking at architecture at every level. I was talking about the individual different components the new interconnect methods. There's this new thing called UCIE universal connection. I forget what it stands answer for, but it's a mechanism for doing chiplet architectures, but then again, you have to take it up to the system level, 'cause it's all fine and good. If you have this SOC that's tuned and optimized, but it has to talk to the rest of the system. And that's where you see other issues. And you've seen things like CXL and other interconnect standards, you know, and nobody likes to talk about interconnect 'cause it's really wonky and really technical and not that sexy, but at the end of the day it's incredibly important exactly. To the other points that were being raised like mark raised, for example, about getting that compute closer to where the data is and that's where again, a diversity of chip architectures help and exactly to your last comment there Dave, putting that ability in an edge device is really at the cutting edge of what we're seeing on a semiconductor design and the ability to, for example, maybe it's an FPGA, maybe it's a dedicated AI chip. It's another kind of chip architecture that's being created to do that inferencing on the edge. Because again, it's that the cost and the challenges of moving lots of data, whether it be from say a smartphone to a cloud-based application or whether it be from a private network to a cloud or any other kinds of permutations we can think of really matters. And the other thing is we're tackling bigger problems. So architecturally, not even just architecturally within a system, but when we think about DPUs and the sort of the east west data center movement conversation that we hear Nvidia and others talk about, it's about combining multiple sets of these systems to function together more efficiently again with even bigger sets of data. So really is about tackling where the processing is needed, having the interconnect and the ability to get where the data you need to the right place at the right time. And because those needs are diversifying, we're just going to continue to see an explosion of different choices and options, which is going to make hardware even more essential I would argue than it is today. And so I think what we're going to see not only does hardware matter, it's going to matter even more in the future than it does now. >> Great, yeah. Great discussion, guys. I want to bring Keith back into the conversation here. Keith, if your main expertise in tech is provisioning LUNs, you probably you want to look for another job. So maybe clearly hardware matters, but with software defined everything, do people with hardware expertise matter outside of for instance, component manufacturers or cloud companies? I mean, VMware certainly changed the dynamic in servers. Dell just spun off its most profitable asset and VMware. So it obviously thinks hardware can stand alone. How does an enterprise architect view the shift to software defined hyperscale cloud and how do you see the shifting demand for skills in enterprise IT? >> So I love the question and I'll take a different view of it. If you're a data analyst and your primary value add is that you do ETL transformation, talk to a CDO, a chief data officer over midsize bank a little bit ago. He said 80% of his data scientists' time is done on ETL. Super not value ad. He wants his data scientists to do data science work. Chances are if your only value is that you do LUN provisioning, then you probably don't have a job now. The technologies have gotten much more intelligent. As infrastructure pros, we want to give infrastructure pros the opportunities to shine and I think the software defined nature and the automation that we're seeing vendors undertake, whether it's Dell, HP, Lenovo take your pick that Pure Storage, NetApp that are doing the automation and the ML needed so that these practitioners don't spend 80% of their time doing LUN provisioning and focusing on their true expertise, which is ensuring that data is stored. Data is retrievable, data's protected, et cetera. I think the shift is to focus on that part of the job that you're ensuring no matter where the data's at, because as my data is spread across the enterprise hybrid different types, you know, Dave, you talk about the super cloud a lot. If my data is in the super cloud, protecting that data and securing that data becomes much more complicated when than when it was me just procuring or provisioning LUNs. So when you say, where should the shift be, or look be, you know, focusing on the real value, which is making sure that customers can access data, can recover data, can get data at performance levels that they need within the price point. They need to get at those datasets and where they need it. We talked a lot about where they need out. One last point about this interconnecting. I have this vision and I think we all do of composable infrastructure. This idea that scaled out does not solve every problem. The cloud can give me infinite scale out. Sometimes I just need a single OS with 64 terabytes of RAM and 204 GPUs or GPU instances that single OS does not exist today. And the opportunity is to create composable infrastructure so that we solve a lot of these problems that just simply don't scale out. >> You know, wow. So many interesting points there. I had just interviewed Zhamak Dehghani, who's the founder of Data Mesh last week. And she made a really interesting point. She said, "Think about, we have separate stacks. "We have an application stack and we have "a data pipeline stack and the transaction systems, "the transaction database, we extract data from that," to your point, "We ETL it in, you know, it takes forever. "And then we have this separate sort of data stack." If we're going to inject more intelligence and data and AI into applications, those two stacks, her contention is they have to come together. And when you think about, you know, super cloud bringing compute to data, that was what Haduck was supposed to be. It ended up all sort of going into a central location, but it's almost a rhetorical question. I mean, it seems that that necessitates new thinking around hardware architectures as it kind of everything's the edge. And the other point is to your point, Keith, it's really hard to secure that. So when you can think about offloads, right, you've heard the stats, you know, Nvidia talks about it. Broadcom talks about it that, you know, that 30%, 25 to 30% of the CPU cycles are wasted on doing things like storage offloads, or networking or security. It seems like maybe Zeus you have a comment on this. It seems like new architectures need to come other to support, you know, all of that stuff that Keith and I just dispute. >> Yeah, and by the way, I do want to Keith, the question you just asked. Keith, it's the point I made at the beginning too about engineers do need to be more software-centric, right? They do need to have better software skills. In fact, I remember talking to Cisco about this last year when they surveyed their engineer base, only about a third of 'em had ever made an API call, which you know that that kind of shows this big skillset change, you know, that has to come. But on the point of architectures, I think the big change here is edge because it brings in distributed compute models. Historically, when you think about compute, even with multi-cloud, we never really had multi-cloud. We'd use multiple centralized clouds, but compute was always centralized, right? It was in a branch office, in a data center, in a cloud. With edge what we creates is the rise of distributed computing where we'll have an application that actually accesses different resources and at different edge locations. And I think Marc, you were talking about this, like the edge could be in your IoT device. It could be your campus edge. It could be cellular edge, it could be your car, right? And so we need to start thinkin' about how our applications interact with all those different parts of that edge ecosystem, you know, to create a single experience. The consumer apps, a lot of consumer apps largely works that way. If you think of like app like Uber, right? It pulls in information from all kinds of different edge application, edge services. And, you know, it creates pretty cool experience. We're just starting to get to that point in the business world now. There's a lot of security implications and things like that, but I do think it drives more architectural decisions to be made about how I deploy what data where and where I do my processing, where I do my AI and things like that. It actually makes the world more complicated. In some ways we can do so much more with it, but I think it does drive us more towards turnkey systems, at least initially in order to, you know, ensure performance and security. >> Right. Marc, I wanted to go to you. You had indicated to me that you wanted to chat about this a little bit. You've written quite a bit about the integration of hardware and software. You know, we've watched Oracle's move from, you know, buying Sun and then basically using that in a highly differentiated approach. Engineered systems. What's your take on all that? I know you also have some thoughts on the shift from CapEx to OPEX chime in on that. >> Sure. When you look at it, there are advantages to having one vendor who has the software and hardware. They can synergistically make them work together that you can't do in a commodity basis. If you own the software and somebody else has the hardware, I'll give you an example would be Oracle. As you talked about with their exit data platform, they literally are leveraging microcode in the Intel chips. And now in AMD chips and all the way down to Optane, they make basically AMD database servers work with Optane memory PMM in their storage systems, not MVME, SSD PMM. I'm talking about the cards itself. So there are advantages you can take advantage of if you own the stack, as you were putting out earlier, Dave, of both the software and the hardware. Okay, that's great. But on the other side of that, that tends to give you better performance, but it tends to cost a little more. On the commodity side it costs less but you get less performance. What Zeus had said earlier, it depends where you're running your application. How much performance do you need? What kind of performance do you need? One of the things about moving to the edge and I'll get to the OPEX CapEx in a second. One of the issues about moving to the edge is what kind of processing do you need? If you're running in a CCTV camera on top of a traffic light, how much power do you have? How much cooling do you have that you can run this? And more importantly, do you have to take the data you're getting and move it somewhere else and get processed and the information is sent back? I mean, there are companies out there like Brain Chip that have developed AI chips that can run on the sensor without a CPU. Without any additional memory. So, I mean, there's innovation going on to deal with this question of data movement. There's companies out there like Tachyon that are combining GPUs, CPUs, and DPUs in a single chip. Think of it as super composable architecture. They're looking at being able to do more in less. On the OPEX and CapEx issue. >> Hold that thought, hold that thought on the OPEX CapEx, 'cause we're running out of time and maybe you can wrap on that. I just wanted to pick up on something you said about the integrated hardware software. I mean, other than the fact that, you know, Michael Dell unlocked whatever $40 billion for himself and Silverlake, I was always a fan of a spin in with VMware basically become the Oracle of hardware. Now I know it would've been a nightmare for the ecosystem and culturally, they probably would've had a VMware brain drain, but what does anybody have any thoughts on that as a sort of a thought exercise? I was always a fan of that on paper. >> I got to eat a little crow. I did not like the Dale VMware acquisition for the industry in general. And I think it hurt the industry in general, HPE, Cisco walked away a little bit from that VMware relationship. But when I talked to customers, they loved it. You know, I got to be honest. They absolutely loved the integration. The VxRail, VxRack solution exploded. Nutanix became kind of a afterthought when it came to competing. So that spin in, when we talk about the ability to innovate and the ability to create solutions that you just simply can't create because you don't have the full stack. Dell was well positioned to do that with a potential span in of VMware. >> Yeah, we're going to be-- Go ahead please. >> Yeah, in fact, I think you're right, Keith, it was terrible for the industry. Great for Dell. And I remember talking to Chad Sakac when he was running, you know, VCE, which became Rack and Rail, their ability to stay in lockstep with what VMware was doing. What was the number one workload running on hyperconverged forever? It was VMware. So their ability to remain in lockstep with VMware gave them a huge competitive advantage. And Dell came out of nowhere in, you know, the hyper-converged market and just started taking share because of that relationship. So, you know, this sort I guess it's, you know, from a Dell perspective I thought it gave them a pretty big advantage that they didn't really exploit across their other properties, right? Networking and service and things like they could have given the dominance that VMware had. From an industry perspective though, I do think it's better to have them be coupled. So. >> I agree. I mean, they could. I think they could have dominated in super cloud and maybe they would become the next Oracle where everybody hates 'em, but they kick ass. But guys. We got to wrap up here. And so what I'm going to ask you is I'm going to go and reverse the order this time, you know, big takeaways from this conversation today, which guys by the way, I can't thank you enough phenomenal insights, but big takeaways, any final thoughts, any research that you're working on that you want highlight or you know, what you look for in the future? Try to keep it brief. We'll go in reverse order. Maybe Marc, you could start us off please. >> Sure, on the research front, I'm working on a total cost of ownership of an integrated database analytics machine learning versus separate services. On the other aspect that I would wanted to chat about real quickly, OPEX versus CapEx, the cloud changed the market perception of hardware in the sense that you can use hardware or buy hardware like you do software. As you use it, pay for what you use in arrears. The good thing about that is you're only paying for what you use, period. You're not for what you don't use. I mean, it's compute time, everything else. The bad side about that is you have no predictability in your bill. It's elastic, but every user I've talked to says every month it's different. And from a budgeting perspective, it's very hard to set up your budget year to year and it's causing a lot of nightmares. So it's just something to be aware of. From a CapEx perspective, you have no more CapEx if you're using that kind of base system but you lose a certain amount of control as well. So ultimately that's some of the issues. But my biggest point, my biggest takeaway from this is the biggest issue right now that everybody I talk to in some shape or form it comes down to data movement whether it be ETLs that you talked about Keith or other aspects moving it between hybrid locations, moving it within a system, moving it within a chip. All those are key issues. >> Great, thank you. Okay, CTO advisor, give us your final thoughts. >> All right. Really, really great commentary. Again, I'm going to point back to us taking the walk that our customers are taking, which is trying to do this conversion of all primary data center to a hybrid of which I have this hard earned philosophy that enterprise IT is additive. When we add a service, we rarely subtract a service. So the landscape and service area what we support has to grow. So our research focuses on taking that walk. We are taking a monolithic application, decomposing that to containers, and putting that in a public cloud, and connecting that back private data center and telling that story and walking that walk with our customers. This has been a super enlightening panel. >> Yeah, thank you. Real, real different world coming. David Nicholson, please. >> You know, it really hearkens back to the beginning of the conversation. You talked about momentum in the direction of cloud. I'm sort of spending my time under the hood, getting grease under my fingernails, focusing on where still the lions share of spend will be in coming years, which is OnPrem. And then of course, obviously data center infrastructure for cloud but really diving under the covers and helping folks understand the ramifications of movement between generations of CPU architecture. I know we all know Sapphire Rapids pushed into the future. When's the next Intel release coming? Who knows? We think, you know, in 2023. There have been a lot of people standing by from a practitioner's standpoint asking, well, what do I do between now and then? Does it make sense to upgrade bits and pieces of hardware or go from a last generation to a current generation when we know the next generation is coming? And so I've been very, very focused on looking at how these connectivity components like rate controllers and NICs. I know it's not as sexy as talking about cloud but just how these opponents completely change the game and actually can justify movement from say a 14th-generation architecture to a 15th-generation architecture today, even though gen 16 is coming, let's say 12 months from now. So that's where I am. Keep my phone number in the Rolodex. I literally reference Rolodex intentionally because like I said, I'm in there under the hood and it's not as sexy. But yeah, so that's what I'm focused on Dave. >> Well, you know, to paraphrase it, maybe derivative paraphrase of, you know, Larry Ellison's rant on what is cloud? It's operating systems and databases, et cetera. Rate controllers and NICs live inside of clouds. All right. You know, one of the reasons I love working with you guys is 'cause have such a wide observation space and Zeus Kerravala you, of all people, you know you have your fingers in a lot of pies. So give us your final thoughts. >> Yeah, I'm not a propeller heady as my chip counterparts here. (all laugh) So, you know, I look at the world a little differently and a lot of my research I'm doing now is the impact that distributed computing has on customer employee experiences, right? You talk to every business and how the experiences they deliver to their customers is really differentiating how they go to market. And so they're looking at these different ways of feeding up data and analytics and things like that in different places. And I think this is going to have a really profound impact on enterprise IT architecture. We're putting more data, more compute in more places all the way down to like little micro edges and retailers and things like that. And so we need the variety. Historically, if you think back to when I was in IT you know, pre-Y2K, we didn't have a lot of choice in things, right? We had a server that was rack mount or standup, right? And there wasn't a whole lot of, you know, differences in choice. But today we can deploy, you know, these really high-performance compute systems on little blades inside servers or inside, you know, autonomous vehicles and things. I think the world from here gets... You know, just the choice of what we have and the way hardware and software works together is really going to, I think, change the world the way we do things. We're already seeing that, like I said, in the consumer world, right? There's so many things you can do from, you know, smart home perspective, you know, natural language processing, stuff like that. And it's starting to hit businesses now. So just wait and watch the next five years. >> Yeah, totally. The computing power at the edge is just going to be mind blowing. >> It's unbelievable what you can do at the edge. >> Yeah, yeah. Hey Z, I just want to say that we know you're not a propeller head and I for one would like to thank you for having your master's thesis hanging on the wall behind you 'cause we know that you studied basket weaving. >> I was actually a physics math major, so. >> Good man. Another math major. All right, Bob O'Donnell, you're going to bring us home. I mean, we've seen the importance of semiconductors and silicon in our everyday lives, but your last thoughts please. >> Sure and just to clarify, by the way I was a great books major and this was actually for my final paper. And so I was like philosophy and all that kind of stuff and literature but I still somehow got into tech. Look, it's been a great conversation and I want to pick up a little bit on a comment Zeus made, which is this it's the combination of the hardware and the software and coming together and the manner with which that needs to happen, I think is critically important. And the other thing is because of the diversity of the chip architectures and all those different pieces and elements, it's going to be how software tools evolve to adapt to that new world. So I look at things like what Intel's trying to do with oneAPI. You know, what Nvidia has done with CUDA. What other platform companies are trying to create tools that allow them to leverage the hardware, but also embrace the variety of hardware that is there. And so as those software development environments and software development tools evolve to take advantage of these new capabilities, that's going to open up a lot of interesting opportunities that can leverage all these new chip architectures. That can leverage all these new interconnects. That can leverage all these new system architectures and figure out ways to make that all happen, I think is going to be critically important. And then finally, I'll mention the research I'm actually currently working on is on private 5g and how companies are thinking about deploying private 5g and the potential for edge applications for that. So I'm doing a survey of several hundred us companies as we speak and really looking forward to getting that done in the next couple of weeks. >> Yeah, look forward to that. Guys, again, thank you so much. Outstanding conversation. Anybody going to be at Dell tech world in a couple of weeks? Bob's going to be there. Dave Nicholson. Well drinks on me and guys I really can't thank you enough for the insights and your participation today. Really appreciate it. Okay, and thank you for watching this special power panel episode of theCube Insights powered by ETR. Remember we publish each week on Siliconangle.com and wikibon.com. All these episodes they're available as podcasts. DM me or any of these guys. I'm at DVellante. You can email me at David.Vellante@siliconangle.com. Check out etr.ai for all the data. This is Dave Vellante. We'll see you next time. (upbeat music)

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

hey welcome to analytics unleashed i'm robert christensen your host today thank you for joining us today we have three quick wins that drive big gains in the enterprise workloads and today we have olaf with erickson we have john with orok and we have dragon with dxc welcome thank you for joining me gentlemen yeah good to be here thank you thank you good to have you hey olaf let's start off with you what big problems are you trying to solve today that are doing for those quick wins what are you trying to do today top top of mind yeah when we started looking into this microservices for our financial platform we immediately saw the challenges that we have and we wanted to have a strong partner and we have a good relationship with hp before so we turned to hp because we know that they have the technical support that we need the possibilities that we need in our platform to fulfill our requirements and also the reliability that we would need so tell me i think this is really important you guys are starting into a digital wallet space that correct yeah that's correct so we are in a financial platform so we are spanning across the world and delivering our financial services to our end customers well that's not classically what you hear about ericsson diving into what's really started you guys down that path and specifically these big wins around this digitization no what what we could see earlier was that we have a mobile networks right so we have a lot of a strong user base within them uh both kind of networks and in the where we started in the emerging markets uh you normally they have a lot of unbanked people and that people also were the ones that you want to target so be able to instead of going down and use your cash for example to buy your fruits or your electricity bill etc you could use your mobile wallet and and that's how it all started and now we're also turning into the emerged markets also like the western side part of worlds etc that's fantastic and i hey i want to talk to john here john's with o'rock and he's the one of those early adopters of those container platforms for the uh in the united states here the federal government tell us a little bit about that program and what's going on with that john yeah sure absolutely appreciate it yeah so with orock what we've done is we developed one of the first fedramp authorized container platforms that runs in our moderate and soon to be high cloud and what that does is building on the israel platform gave us the capability of offering customers both commercial as well as federal the capability and the flexibility of running their workloads in a you know as a service model where they can customize and typically what customers have to do is they have to either build it internally or if they go to the cloud they have to be able to take what resources are available then tweak to those designs to make what they need so in this architecture built on open source and with our own infrastructure we offer you know very low cost zero egress capability but the also the workload processing that they would need to run data analytics machine language and other types of high performance processing that typically they would need as we move forward in this computer age so john you you touched on a topic that's i think is really critical and you had mentioned open source why is open source a key aspect for this transformation that we're seeing coming up in like the next decade yeah sure yeah with open source we shifted early on to the company to move to open source only to offer the flexibility we didn't want to be set on one particular platform to operate within so we took and built the cloud infrastructure we went with open source as an open architecture that we can scale and grow within because of that we were one of the very first fedramp authorizations built on open source not on a specific platform and what we've seen from that is the increased performance capability that we would get as well as the flexibility to add additional components that typically you don't get on other platforms so it was a it was a good move we went with and one that the customer will definitely benefit from that that's that's huge actually because performance leads to better cost and better cost leads better performance around that i i'm just super super happy with all the advanced work that you always are doing there is fantastic and dragon so so you're in a space that i think is really interesting you're dealing with what everybody likes to talk about that's autonomous vehicles you're working with automobile manufacturers you're dealing with data at a scale that is unprecedented can you just open that door for us to talk to about these big big wins that you're trying to get over the line with these enterprises yeah absolutely and um thank you robert we approach uh leveraging esmeral from the data fabric angle we practically have a fully integrated the esmeral data fabric into our robotic drive solution rewarding drive solution is actually a game changer as you've mentioned in accelerating the development of autonomous driving vehicles it's a an end-to-end hyper-scale machine learning and ai platform as i mentioned based on the esmeralda data fabric which is used by the some of the largest manufacturers in the world for development of their autonomous driving algorithms and i think we all in technology i think and following up at the same type of news and research right across the globe in in this area so we're pretty proud that we're one of the leaders in actually providing uh hyperscale machine learning platforms for uh kind manufacturers some of them i cannot talk about but bmw is one of uh one of the current manufacturers that we provide uh these type of solutions and they have publicly spoken about their uh d3 platform uh data driven development platform uh just to give you an idea um of the scale as robert mentioned uh daily we collect over 1.5 petabytes of data of raw data did you say daily data daily the storage capacity is over 250 petabytes and growing uh there's over 100 000 cores and over 200 gpus in the in in the compute area um over 50 50 petabytes of data is delivered every two weeks into a hardware in loop right for testing and we have daily uh thousands of engineers and data scientists accessing the relevant data and developing machine learning models on the daily basis right part of it is the simulation right simulation cuts the cost as well as the uh time right for developing of the autonomous uh driving algorithms and uh the the simulations are taking probably 75 percent of the research uh that's being done on this platform that's amazing dragon i i i i the more i get involved with that and i've been part of these conversations with a number of the folks that are involved with it i i computer science me my geekiness my little propeller head starts coming out i might just blows my mind and i think so i'm going to pivot back over to olaf oh left so you're talking about something that is a global network of financial services okay correct and the flow of transactional typically non-relational transactional data flows to actual transactions going through you have issues of potential fraud you have issues a safety and you have multi-geographic regional problems with data and data privacy how are you guys addressing that today so so to answer that question today we have managed to solve that using the container platform to together with the data fabric but as you say we need to span across different regions we need to have the data as secure as possible because we have a lot of legal aspects to look into because if our data disappears but your money is also disappearing so it's a really important area for us with the security and the reliability of the platforms so so that's why we also went this way to make sure that we have this strong partner that could help us with this because just looking at where we are deployed in in more than 23 countries today and and we it's processing more than 900 million us dollars per day in our systems currently so it is a lot of money passing through and you need to take security in a it's as it's a very important point right it really is it really is and so uh john i mean you you uh obviously are dealing with you know a lot of folks that have three letters as acronyms around the government agencies and uh they range in various degrees of certa of security when you say fedramp i mean what could you just uh articulate why the esmerald platform was something that you selected to go to that fedrak compliant container platform because i think that's that that kind of speaks to the to the industrial strength of what we're talking about yeah it all comes down to being able to offer a product that's secure that the customers can trust and when we went with fedramp fedramp has very stringent security requirements that have monthly poems which are performance reviews and and updates that need to be done if not on a daily basis on a monthly basis so the customers there's a lot that goes on behind the scenes that they don't are able to articulate and what by selecting the hp esmerald platform for containers um one of the key strengths that we looked at was the esmo fabric and it's all about the data it's all about securing the data moving the data transferring the data and from a customer's perspective they want to be able to operate in an environment that they can trust no different than being able to turn on their lights or making sure there's water in their utilities you know containers with the israel platform built on orok's infrastructure gives that capability fedramp enables the security tied to the platform that we're able to follow so it's government uh guided which includes this and many and over hundreds of controls that typically you know the customers don't have time or the capability to address so our commercial customers benefit our federal customers you know that you discuss they're able to follow and check the box to meet those requirements and the container platform gives us a capability where now we're able to move files which we'll hear about through the optimal fabric and then we're able to run the workloads in the containers themselves and give isolation and the security element of fed wrapping esmeral gave us that capability in order to paint that environment fedramp authorized that the customers benefit from from security so they have confidence in running their workloads using their data and able to focus on their core job at hand and not worry about their infrastructure the fundamental requirement isn't it that that isolation between that compute and storage and going up a layer there in in a way that provides them a set of services that they can i wouldn't say set it and forget it but really had the confidence that what they're getting is the best performance for the dollars that they're spending uh john my hat's off to what the work that you all do in there thank you we appreciate it yeah yeah and dragon i want to i wanted to pivot a little bit here because you are primarily the the operator what i consider one of the largest data fabrics on the on the planet for that matter um and i just want to talk a little bit about the openness of our architecture right of all the multiple protocols that we support that allow for you know you know some people may have selected a different set of application deployment models and virtualization models that allow to plug into the data fabric you know it did can you talk a little bit about that yeah and i i think um in my mind right um to operate uh such a uh data fabric at scale right um there were three key elements that we were looking for right uh that we found in uh esmeralda fabric ring the first one was a speed cost and scalability right the second one was the globally distributed data lake or ability to distribute data globally and third was certainly the strength of our partnership with with hpe in this case right so if you look at the uh as well data fabric it's it's fast it's cost effective and it's certainly highly scalable because we as you just mentioned stretch the uh sort of the capabilities of the data fabric to hundreds of petabytes and over a million the data points if you will and it important what was important for us was that the esmeralda fabric actually eliminates the need for multiple vendor solutions which would be otherwise required right because it provides integrated file system database or or a data lake right and the data management on top of it right usually you would probably need to incorporate multiple tools right from different vendors and the file system itself it's it's so important right when you're working at scale like this right and honestly in our research maybe there are three file systems in the world that can support uh this kind of size of the auto data fabric the distributed data lake was also important to us and the reason for that is you can imagine that these large car manufacturers are testing and have testing vehicles all around the world right they're not just doing it locally around the uh their data their id centers right so uh collecting the data and this 1.5 petabytes example right uh for for bmw on a daily basis it's it's it's really challenging unless you have the ability to actually leverage the data in a distributed data like fashion right so data can basically reside in different data centers globally or even on-premise and in cloud environments which became uh very important later because a lot of this car manufacturers actually have oems right that would like to get either portions of the data or get access to the data in a in different environments not necessarily in their data center um and truly i think uh to build something at this scale right uh you you need a strong partner and we certainly had that in hpe and uh we got the comprehensive support right for uh for the software um but but more importantly i think uh partner that clearly understood uh criticality of the data fabric trend and the need for the vice fast response right to our clients and you know jointly i think we met all the challenges and it's so doing i think we made the esmo data fabric a much better and stronger product over the over the last few years that's fantastic thank you dragon appreciate it uh hey so if we're going to wrap up here any last words olaf do you want to share with us no looking forward now in from our perspective on helping out with the kobe 19 situation that we have uh enabling people to still be in the market without actually touching each other and and and leaving maybe for action market and being at home etc doing those transactions that's great thank you john in last comment yeah thanks yeah uh look for uh a joint offering announcement coming up between hpe and orok where we're going to be offering sandbox as a service where the data analytics and machine language where people can actually test drive the actual environment as a service and if they like it then they can move into a production-wise environment so stay tuned for that that's great john thank you for that and hey dragon last words yeah last words um we're pretty happy what we have done already for car manufacturers we're taking this solution right in terms of the uh distributed data-like capabilities as well as the uh hyperscale machine learning and ai platform to other industries and we hope to do it jointly with you well we hope that you do it with us as well so thank you very much everybody gentlemen thank you so much for joining us i appreciate it thank you very much thank you very much hey this is robert christensen with analytics unleashed i want to thank all of our guests here today and we'll catch you next time thank you for joining us bye [Music] [Music] [Music] easy [Music] you

>> Announcer: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Hi everyone, this is Dave Vellante and welcome to this CUBE conversation where we're going to dig in to this, the area of cloud databases. And Gartner just published a series of research in this space. And it's really a growing market, rapidly growing, a lot of new players, obviously the big three cloud players. And with me are three experts in the field, two long time industry analysts. Marc Staimer is the founder, president, and key principal at Dragon Slayer Consulting. And he's joined by David Floyer, the CTO of Wikibon. Gentlemen great to see you. Thanks for coming on theCUBE. >> Good to be here. >> Great to see you too Dave. >> Marc, coming from the great Northwest, I think first time on theCUBE, and so it's really great to have you. So let me set this up, as I said, you know, Gartner published these, you know, three giant tomes. These are, you know, publicly available documents on the web. I know you guys have been through them, you know, several hours of reading. And so, night... (Dave chuckles) Good night time reading. The three documents where they identify critical capabilities for cloud database management systems. And the first one we're going to talk about is, operational use cases. So we're talking about, you know, transaction oriented workloads, ERP financials. The second one was analytical use cases, sort of an emerging space to really try to, you know, the data warehouse space and the like. And, of course, the third is the famous Gartner Magic Quadrant, which we're going to talk about. So, Marc, let me start with you, you've dug into this research just at a high level, you know, what did you take away from it? >> Generally, if you look at all the players in the space they all have some basic good capabilities. What I mean by that is ultimately when you have, a transactional or an analytical database in the cloud, the goal is not to have to manage the database. Now they have different levels of where that goes to as how much you have to manage or what you have to manage. But ultimately, they all manage the basic administrative, or the pedantic tasks that DBAs have to do, the patching, the tuning, the upgrading, all of that is done by the service provider. So that's the number one thing they all aim at, from that point on every database has different capabilities and some will automate a whole bunch more than others, and will have different primary focuses. So it comes down to what you're looking for or what you need. And ultimately what I've learned from end users is what they think they need upfront, is not what they end up needing as they implement. >> David, anything you'd add to that, based on your reading of the Gartner work. >> Yes. It's a thorough piece of work. It's taking on a huge number of different types of uses and size of companies. And I think those are two parameters which really change how companies would look at it. If you're a Fortune 500 or Fortune 2000 type company, you're going to need a broader range of features, and you will need to deal with size and complexity in a much greater sense, and a lot of probably higher levels of availability, and reliability, and recoverability. Again, on the workload side, there are different types of workload and there're... There is as well as having the two transactional and analytic workloads, I think there's an emerging type of workload which is going to be very important for future applications where you want to combine transactional with analytic in real time, in order to automate business processes at a higher level, to make the business processes synchronous as opposed to asynchronous. And that degree of granularity, I think is missed, in a broader view of these companies and what they offer. It's in my view trying in some ways to not compare like with like from a customer point of view. So the very nuance, what you talked about, let's get into it, maybe that'll become clear to the audience. So like I said, these are very detailed research notes. There were several, I'll say analysts cooks in the kitchen, including Henry Cook, whom I don't know, but four other contributing analysts, two of whom are CUBE alum, Don Feinberg, and Merv Adrian, both really, you know, awesome researchers. And Rick Greenwald, along with Adam Ronthal. And these are public documents, you can go on the web and search for these. So I wonder if we could just look at some of the data and bring up... Guys, bring up the slide one here. And so we'll first look at the operational side and they broke it into four use cases. The traditional transaction use cases, the augmented transaction processing, stream/event processing and operational intelligence. And so we're going to show you there's a lot of data here. So what Gartner did is they essentially evaluated critical capabilities, or think of features and functions, and gave them a weighting, or a weighting, and then a rating. It was a weighting and rating methodology. On a s... The rating was on a scale of one to five, and then they weighted the importance of the features based on their assessment, and talking to the many customers they talk to. So you can see here on the first chart, we're showing both the traditional transactions and the augmented transactions and, you know, the thing... The first thing that jumps out at you guys is that, you know, Oracle with Autonomous is off the charts, far ahead of anybody else on this. And actually guys, if you just bring up slide number two, we'll take a look at the stream/event processing and operational intelligence use cases. And you can see, again, you know, Oracle has a big lead. And I don't want to necessarily go through every vendor here, but guys, if you don't mind going back to the first slide 'cause I think this is really, you know, the core of transaction processing. So let's look at this, you've got Oracle, you've got SAP HANA. You know, right there interestingly Amazon Web Services with the Aurora, you know, IBM Db2, which, you know, it goes back to the good old days, you know, down the list. But so, let me again start with Marc. So why is that? I mean, I guess this is no surprise, Oracle still owns the Mission-Critical for the database space. They earned that years ago. One that, you know, over the likes of Db2 and, you know, Informix and Sybase, and, you know, they emerged as number one there. But what do you make of this data Marc? >> If you look at this data in a vacuum, you're looking at specific functionality, I think you need to look at all the slides in total. And the reason I bring that up is because I agree with what David said earlier, in that the use case that's becoming more prevalent is the integration of transaction and analytics. And more importantly, it's not just your traditional data warehouse, but it's AI analytics. It's big data analytics. It's users are finding that they need more than just simple reporting. They need more in-depth analytics so that they can get more actionable insights into their data where they can react in real time. And so if you look at it just as a transaction, that's great. If you're going to just as a data warehouse, that's great, or analytics, that's fine. If you have a very narrow use case, yes. But I think today what we're looking at is... It's not so narrow. It's sort of like, if you bought a streaming device and it only streams Netflix and then you need to get another streaming device 'cause you want to watch Amazon Prime. You're not going to do that, you want one, that does all of it, and that's kind of what's missing from this data. So I agree that the data is good, but I don't think it's looking at it in a total encompassing manner. >> Well, so before we get off the horses on the track 'cause I love to do that. (Dave chuckles) I just kind of let's talk about that. So Marc, you're putting forth the... You guys seem to agree on that premise that the database that can do more than just one thing is of appeal to customers. I suppose that makes, certainly makes sense from a cost standpoint. But, you know, guys feel free to flip back and forth between slides one and two. But you can see SAP HANA, and I'm not sure what cloud that's running on, it's probably running on a combination of clouds, but, you know, scoring very strongly. I thought, you know, Aurora, you know, given AWS says it's one of the fastest growing services in history and they've got it ahead of Db2 just on functionality, which is pretty impressive. I love Google Spanner, you know, love the... What they're trying to accomplish there. You know, you go down to Microsoft is, they're kind of the... They're always good enough a database and that's how they succeed and et cetera, et cetera. But David, it sounds like you agree with Marc. I would say, I would think though, Amazon kind of doesn't agree 'cause they're like a horses for courses. >> I agree. >> Yeah, yeah. >> So I wonder if you could comment on that. >> Well, I want to comment on two vectors. The first vector is that the size of customer and, you know, a mid-sized customer versus a global $2,000 or global 500 customer. For the smaller customer that's the heart of AWS, and they are taking their applications and putting pretty well everything into their cloud, the one cloud, and Aurora is a good choice. But when you start to get to a requirements, as you do in larger companies have very high levels of availability, the functionality is not there. You're not comparing apples and... Apples with apples, it's two very different things. So from a tier one functionality point of view, IBM Db2 and Oracle have far greater capability for recovery and all the features that they've built in over there. >> Because of their... You mean 'cause of the maturity, right? maturity and... >> Because of their... Because of their focus on transaction and recovery, et cetera. >> So SAP though HANA, I mean, that's, you know... (David talks indistinctly) And then... >> Yeah, yeah. >> And then I wanted your comments on that, either of you or both of you. I mean, SAP, I think has a stated goal of basically getting its customers off Oracle that's, you know, there's always this urinary limping >> Yes, yes. >> between the two companies by 2024. Larry has said that ain't going to happen. You know, Amazon, we know still runs on Oracle. It's very hard to migrate Mission-Critical, David, you and I know this well, Marc you as well. So, you know, people often say, well, everybody wants to get off Oracle, it's too expensive, blah, blah, blah. But we talked to a lot of Oracle customers there, they're very happy with the reliability, availability, recoverability feature set. I mean, the core of Oracle seems pretty stable. >> Yes. >> But I wonder if you guys could comment on that, maybe Marc you go first. >> Sure. I've recently done some in-depth comparisons of Oracle and Aurora, and all their other RDS services and Snowflake and Google and a variety of them. And ultimately what surprised me is you made a statement it costs too much. It actually comes in half of Aurora for in most cases. And it comes in less than half of Snowflake in most cases, which surprised me. But no matter how you configure it, ultimately based on a couple of things, each vendor is focused on different aspects of what they do. Let's say Snowflake, for example, they're on the analytical side, they don't do any transaction processing. But... >> Yeah, so if I can... Sorry to interrupt. Guys if you could bring up the next slide that would be great. So that would be slide three, because now we get into the analytical piece Marc that you're talking about that's what Snowflake specialty is. So please carry on. >> Yeah, and what they're focused on is sharing data among customers. So if, for example, you're an automobile manufacturer and you've got a huge supply chain, you can supply... You can share the data without copying the data with any of your suppliers that are on Snowflake. Now, can you do that with the other data warehouses? Yes, you can. But the focal point is for Snowflake, that's where they're aiming it. And whereas let's say the focal point for Oracle is going to be performance. So their performance affects cost 'cause the higher the performance, the less you're paying for the performing part of the payment scale. Because you're paying per second for the CPUs that you're using. Same thing on Snowflake, but the performance is higher, therefore you use less. I mean, there's a whole bunch of things to come into this but at the end of the day what I've found is Oracle tends to be a lot less expensive than the prevailing wisdom. So let's talk value for a second because you said something, that yeah the other databases can do that, what Snowflake is doing there. But my understanding of what Snowflake is doing is they built this global data mesh across multiple clouds. So not only are they compatible with Google or AWS or Azure, but essentially you sign up for Snowflake and then you can share data with anybody else in the Snowflake cloud, that I think is unique. And I know, >> Marc: Yes. >> Redshift, for instance just announced, you know, Redshift data sharing, and I believe it's just within, you know, clusters within a customer, as opposed to across an ecosystem. And I think that's where the network effect is pretty compelling for Snowflake. So independent of costs, you and I can debate about costs and, you know, the tra... The lack of transparency of, because AWS you don't know what the bill is going to be at the end of the month. And that's the same thing with Snowflake, but I find that... And by the way guys, you can flip through slides three and four, because we've got... Let me just take a quick break and you have data warehouse, logical data warehouse. And then the next slide four you got data science, deep learning and operational intelligent use cases. And you can see, you know, Teradata, you know, law... Teradata came up in the mid 1980s and dominated in that space. Oracle does very well there. You can see Snowflake pop-up, SAP with the Data Warehouse, Amazon with Redshift. You know, Google with BigQuery gets a lot of high marks from people. You know, Cloud Data is in there, you know, so you see some of those names. But so Marc and David, to me, that's a different strategy. They're not trying to be just a better data warehouse, easier data warehouse. They're trying to create, Snowflake that is, an incremental opportunity as opposed to necessarily going after, for example, Oracle. David, your thoughts. >> Yeah, I absolutely agree. I mean, ease of use is a primary benefit for Snowflake. It enables you to do stuff very easily. It enables you to take data without ETL, without any of the complexity. It enables you to share a number of resources across many different users and know... And be able to bring in what that particular user wants or part of the company wants. So in terms of where they're focusing, they've got a tremendous ease of use, tremendous focus on what the customer wants. And you pointed out yourself the restrictions there are of doing that both within Oracle and AWS. So yes, they have really focused very, very hard on that. Again, for the future, they are bringing in a lot of additional functions. They're bringing in Python into it, not Python, JSON into the database. They can extend the database itself, whether they go the whole hog and put in transaction as well, that's probably something they may be thinking about but not at the moment. >> Well, but they, you know, they obviously have to have TAM expansion designs because Marc, I mean, you know, if they just get a 100% of the data warehouse market, they're probably at a third of their stock market valuation. So they had better have, you know, a roadmap and plans to extend there. But I want to come back Marc to this notion of, you know, the right tool for the right job, or, you know, best of breed for a specific, the right specific, you know horse for course, versus this kind of notion of all in one, I mean, they're two different ends of the spectrum. You're seeing, you know, Oracle obviously very successful based on these ratings and based on, you know their track record. And Amazon, I think I lost count of the number of data stores (Dave chuckles) with Redshift and Aurora and Dynamo, and, you know, on and on and on. (Marc talks indistinctly) So they clearly want to have that, you know, primitive, you know, different APIs for each access, completely different philosophies it's like Democrats or Republicans. Marc your thoughts as to who ultimately wins in the marketplace. >> Well, it's hard to say who is ultimately going to win, but if I look at Amazon, Amazon is an all-cart type of system. If you need time series, you go with their time series database. If you need a data warehouse, you go with Redshift. If you need transaction, you go with one of the RDS databases. If you need JSON, you go with a different database. Everything is a different, unique database. Moving data between these databases is far from simple. If you need to do a analytics on one database from another, you're going to use other services that cost money. So yeah, each one will do what they say it's going to do but it's going to end up costing you a lot of money when you do any kind of integration. And you're going to add complexity and you're going to have errors. There's all sorts of issues there. So if you need more than one, probably not your best route to go, but if you need just one, it's fine. And if, and on Snowflake, you raise the issue that they're going to have to add transactions, they're going to have to rewrite their database. They have no indexes whatsoever in Snowflake. I mean, part of the simplicity that David talked about is because they had to cut corners, which makes sense. If you're focused on the data warehouse you cut out the indexes, great. You don't need them. But if you're going to do transactions, you kind of need them. So you're going to have to do some more work there. So... >> Well... So, you know, I don't know. I have a different take on that guys. I think that, I'm not sure if Snowflake will add transactions. I think maybe, you know, their hope is that the market that they're creating is big enough. I mean, I have a different view of this in that, I think the data architecture is going to change over the next 10 years. As opposed to having a monolithic system where everything goes through that big data platform, the data warehouse and the data lake. I actually see what Snowflake is trying to do and, you know, I'm sure others will join them, is to put data in the hands of product builders, data product builders or data service builders. I think they're betting that that market is incremental and maybe they don't try to take on... I think it would maybe be a mistake to try to take on Oracle. Oracle is just too strong. I wonder David, if you could comment. So it's interesting to see how strong Gartner rated Oracle in cloud database, 'cause you don't... I mean, okay, Oracle has got OCI, but you know, you think a cloud, you think Google, or Amazon, Microsoft and Google. But if I have a transaction database running on Oracle, very risky to move that, right? And so we've seen that, it's interesting. Amazon's a big customer of Oracle, Salesforce is a big customer of Oracle. You know, Larry is very outspoken about those companies. SAP customers are many, most are using Oracle. I don't, you know, it's not likely that they're going anywhere. My question to you, David, is first of all, why do they want to go to the cloud? And if they do go to the cloud, is it logical that the least risky approach is to stay with Oracle, if you're an Oracle customer, or Db2, if you're an IBM customer, and then move those other workloads that can move whether it's more data warehouse oriented or incremental transaction work that could be done in a Aurora? >> I think the first point, why should Oracle go to the cloud? Why has it gone to the cloud? And if there is a... >> Moreso... Moreso why would customers of Oracle... >> Why would customers want to... >> That's really the question. >> Well, Oracle have got Oracle Cloud@Customer and that is a very powerful way of doing it. Where exactly the same Oracle system is running on premise or in the cloud. You can have it where you want, you can have them joined together. That's unique. That's unique in the marketplace. So that gives them a very special place in large customers that have data in many different places. The second point is that moving data is very expensive. Marc was making that point earlier on. Moving data from one place to another place between two different databases is a very expensive architecture. Having the data in one place where you don't have to move it where you can go directly to it, gives you enormous capabilities for a single database, single database type. And I'm sure that from a transact... From an analytic point of view, that's where Snowflake is going, to a large single database. But where Oracle is going to is where, you combine both the transactional and the other one. And as you say, the cost of migration of databases is incredibly high, especially transaction databases, especially large complex transaction databases. >> So... >> And it takes a long time. So at least a two year... And it took five years for Amazon to actually succeed in getting a lot of their stuff over. And five years they could have been doing an awful lot more with the people that they used to bring it over. So it was a marketing decision as opposed to a rational business decision. >> It's the holy grail of the vendors, they all want your data in their database. That's why Amazon puts so much effort into it. Oracle is, you know, in obviously a very strong position. It's got growth and it's new stuff, it's old stuff. It's, you know... The problem with Oracle it has like many of the legacy vendors, it's the size of the install base is so large and it's shrinking. And the new stuff is.... The legacy stuff is shrinking. The new stuff is growing very, very fast but it's not large enough yet to offset that, you see that in all the learnings. So very positive news on, you know, the cloud database, and they just got to work through that transition. Let's bring up slide number five, because Marc, this is to me the most interesting. So we've just shown all these detailed analysis from Gartner. And then you look at the Magic Quadrant for cloud databases. And, you know, despite Amazon being behind, you know, Oracle, or Teradata, or whomever in every one of these ratings, they're up to the right. Now, of course, Gartner will caveat this and say, it doesn't necessarily mean you're the best, but of course, everybody wants to be in the upper, right. We all know that, but it doesn't necessarily mean that you should go by that database, I agree with what Gartner is saying. But look at Amazon, Microsoft and Google are like one, two and three. And then of course, you've got Oracle up there and then, you know, the others. So that I found that very curious, it is like there was a dissonance between the hardcore ratings and then the positions in the Magic Quadrant. Why do you think that is Marc? >> It, you know, it didn't surprise me in the least because of the way that Gartner does its Magic Quadrants. The higher up you go in the vertical is very much tied to the amount of revenue you get in that specific category which they're doing the Magic Quadrant. It doesn't have to do with any of the revenue from anywhere else. Just that specific quadrant is with that specific type of market. So when I look at it, Oracle's revenue still a big chunk of the revenue comes from on-prem, not in the cloud. So you're looking just at the cloud revenue. Now on the right side, moving to the right of the quadrant that's based on functionality, capabilities, the resilience, other things other than revenue. So visionary says, hey how far are you on the visionary side? Now, how they weight that again comes down to Gartner's experts and how they want to weight it and what makes more sense to them. But from my point of view, the right side is as important as the vertical side, 'cause the vertical side doesn't measure the growth rate either. And if we look at these, some of these are growing much faster than the others. For example, Snowflake is growing incredibly fast, and that doesn't reflect in these numbers from my perspective. >> Dave: I agree. >> Oracle is growing incredibly fast in the cloud. As David pointed out earlier, it's not just in their cloud where they're growing, but it's Cloud@Customer, which is basically an extension of their cloud. I don't know if that's included these numbers or not in the revenue side. So there's... There're a number of factors... >> Should it be in your opinion, Marc, would you include that in your definition of cloud? >> Yeah. >> The things that are hybrid and on-prem would that cloud... >> Yes. >> Well especially... Well, again, it depends on the hybrid. For example, if you have your own license, in your own hardware, but it connects to the cloud, no, I wouldn't include that. If you have a subscription license and subscription hardware that you don't own, but it's owned by the cloud provider, but it connects with the cloud as well, that I would. >> Interesting. Well, you know, to your point about growth, you're right. I mean, it's probably looking at, you know, revenues looking, you know, backwards from guys like Snowflake, it will be double, you know, the next one of these. It's also interesting to me on the horizontal axis to see Cloud Data and Databricks further to the right, than Snowflake, because that's kind of the data lake cloud. >> It is. >> And then of course, you've got, you know, the other... I mean, database used to be boring, so... (David laughs) It's such a hot market space here. (Marc talks indistinctly) David, your final thoughts on all this stuff. What does the customer take away here? What should I... What should my cloud database management strategy be? >> Well, I was positive about Oracle, let's take some of the negatives of Oracle. First of all, they don't make it very easy to rum on other platforms. So they have put in terms and conditions which make it very difficult to run on AWS, for example, you get double counts on the licenses, et cetera. So they haven't played well... >> Those are negotiable by the way. Those... You bring it up on the customer. You can negotiate that one. >> Can be, yes, They can be. Yes. If you're big enough they are negotiable. But Aurora certainly hasn't made it easy to work with other plat... Other clouds. What they did very... >> How about Microsoft? >> Well, no, that is exactly what I was going to say. Oracle with adjacent workloads have been working very well with Microsoft and you can then use Microsoft Azure and use a database adjacent in the same data center, working with integrated very nicely indeed. And I think Oracle has got to do that with AWS, it's got to do that with Google as well. It's got to provide a service for people to run where they want to run things not just on the Oracle cloud. If they did that, that would in my term, and my my opinion be a very strong move and would make make the capabilities available in many more places. >> Right. Awesome. Hey Marc, thanks so much for coming to theCUBE. Thank you, David, as well, and thanks to Gartner for doing all this great research and making it public on the web. You can... If you just search critical capabilities for cloud database management systems for operational use cases, that's a mouthful, and then do the same for analytical use cases, and the Magic Quadrant. There's the third doc for cloud database management systems. You'll get about two hours of reading and I learned a lot and I learned a lot here too. I appreciate the context guys. Thanks so much. >> My pleasure. All right, thank you for watching everybody. This is Dave Vellante for theCUBE. We'll see you next time. (upbeat music)

>> From the heart of Silicon Valley, it's theCUBE covering Comcast Innovation Day. (smooth music) Brought to you by Comcast. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at the Comcast Silicon Valley Innovation Center here in Sunnyvale. Very cool facility right off the runway from Moffett. They got a ton of cool toys downstairs which I get to go play with, which I'm looking forward to, but today the conversation was all about CX, customer experience, and you know, Comcast is there. A lot of people like to watch their TVs, interacting with their cable systems for a long, long time, but there's a whole range of new and innovative things that are coming out from Comcast, and we're excited to have an engineer who's kind of down in the bowels here in the engine room building all this stuff. So like to welcome Mike Fine. He's a cable software architect for Comcast. Mike, great to see you. >> Likewise. >> So you had a really cool demo earlier, which is not a demo, right? I think this thing is-- >> Production. >> Now in production, it's called the X1 Eye Control. I think most people know what X1 is. What's X1 Eye Control? >> Yeah. X1 Eye Control is a web application that integrates with off-the-shelf accessibility hardware, so that could be a Tobii eye gaze rig, it could be something called a sip-and-puff, which let's users use their inhalation and exhalation to control the application, or any other off-the-shelf accessibility hardware that can mimic a mouse to a piece of software. >> Too, it's-- >> Yeah. The goal of the project was pretty simple. It was to let people with ALS and other conditions control their TVs independently. >> That's amazing, and you showed a great video. The gentleman on the video is using I think an eye gaze method, but you said you've got integrations to a number of different, you know, kind of ADA-approved interface devices. >> That's right, the journey that this project has taken has been interesting. We started with just the ALS use case, which was the eye gaze, but it turned out that one of our early users had control over his voice, which is somewhat unusual for ALS patients, and so he asked whether he could control it with his voice, so we did that work through he had Dragon NaturallySpeaking, which was nice, so we did that work, and then of course given that we have the voice remote we decided could we make voice work for everybody, which we did, so now the application is on par with a physical remote, and then we even went further and let people type in voice commands, so in case somebody who's perhaps mute or had a speech impediment, or some sort of speech pathology issue that prevented them from using a voice, they could do that as well. >> It's really interesting, I mean you guys have so many kind of interface points to an ecosystem broader than simply what's available at Comcast, whether it's on the front end, as you said, with some of these interfaces with ADA devices, or on the backend if I want to watch my Netflix or I want to watch YouTube, or I want to watch, you know, a different service. You guys have really taken, you know, kind of an open, integrated approach to all these, one might argue, competitive threats to really bring it in as the customer wants to experience. Why did you do that, what's kind of the philosophy driving that? >> Yeah, well, the first thought that comes to mind is that none of it's possible without the right cloud APIs, so somebody very visionary years ago made the decision that everything you can do on your TV or on the mobile app you can do through the cloud, and so a project like this couldn't happen unless it was possible for a piece of software that somebody invented well after the fact to cause a TV to change channels unless there was that underpinning, so like any other piece of software it's a bit of an iceberg. There's a lot of stuff underneath that you don't realize as a user-- >> Right. >> But it's there and that's what makes it possible. >> Right, I'm just curious about some of the challenges in terms of moving UI and UX forward into places that people are not familiar with. And I've joked about it on a number of these interviews that, you know, I still get an email, not only from Comcast, but from Google and from Alexa, suggesting to me ways in which I might use voice. You know, as you sit back from a technologist what are some of the challenges you guys, you know, kind of anticipate, what are some of the ones you didn't anticipate, and how do you help us old people, you know, find new ways to interact with the technology? >> Yeah, it's a great question. I mean there's a lot of us here that spend our days solving that exact problem, right? Part of it is is notifying you of interesting things through SMS or through mobile push, or the messages on the TV, so your team is playing in a game that you want to see, a movie that you've declared interest in has become cheaper, become free, or maybe even buyable if you wanted to do that. Obviously there's lots of AI and ML in terms of putting recommendations in front of you based on your viewing habits, based on broader trends across, you know, because you watch this, other people watch this, so we know this is probably a good solution for you as well, but yeah, we're all, there's a large number of us trying to optimize what we call "time to joy," from the time you pick up your remote to think about what you want to watch to the time you're actually watching something you want to watch; make that as seamless as possible. >> Preston said you guys get like a billion voice commands, what was the period of time? >> A month. >> A month. >> A month, yeah. (chuckles) >> So obviously a big, giant new dataset for you guys now to have at your disposal. >> What are some of the things that you're learning from that inbound, what can you do with it, how do you, you know, now use this direct touch with the customer to, again, kind of recycle and have another iteration on improved experience? >> Right, so voice is a lot like a text chat, like a bot interface in that it's an experience where users are telling you exactly what they want to do, so if a user sits in front of a traditional web application or mobile application and has trouble finding what they want to do, they can't figure out what button to press, what screen to go to, you have no idea, right? You can't infer that they're having a problem, but with voice or somebody interacting with a bot, they type exactly what they mean, or they say exactly what they mean, so we can mine those voice commands and find the popular ones that we don't at that point have implemented, and if we can iterate on that cycle fast enough we can quickly introduce new voice commands that our users are literally asking for as quickly as possible. >> Right. What about the stuff that customers are not asking for, because right? There's one line of thought, which is the customer knows best, but the customer doesn't know-- >> That's right. >> What they don't know. So how do you guys continue to look for more kind of cutting edge stuff that isn't necessarily coming back through a feedback loop? >> Right, yeah, so it's an interesting question. So we're trying to add other non-TV use cases into the mix, right, so controlling your IoT devices at home, controlling your security, seeing your cameras through the Set-Top Box, and so on. So you know, until those use cases exist nobody's asking for them, and so you do have to be a bit visionary in terms of what you want to put out there as voice commands. You know, luckily we have people who, well, we're all customers of the platform generally, so we know what it means to be a user, but you know, we have people that talk with users and have a general sense of what they want to do, and then we figure out what the right commands are. >> Right, not voice specifically, but let's unpack a little bit deeper into the impact of IoT. You know, Nest probably was the first kind of broadly accepted kind of IoT device in the home, and now you got Ring, which everybody loves to take pictures of people stealing their boxes from the front porch, but that puts you guys with the internet connectivity in a very different place than simply providing a football game or the entertainment. So as you think of your role changing in the house, specifically with now these connected devices, how do you think about new opportunities, new challenges that being the person in the middle of that is different than just sending a TV signal? >> Yeah, there's a lot of talk about trying to be the home OS. Certainly we are in a unique position being in the home, both in terms of the router and the internet, but also, you know, often frankly you know when your system's setup a human being came in and helps you understand how to best position the physical devices in your house, and so on, that other companies don't have, right? Those vendors just don't have that builtin advantage. Clearly security has become a big thing for us. Home automation, I sit very close to that group. They're doing amazing things with automating rules like, you know, "Tell me when my door's been open too long," and these sort of things, and so more and more the use cases start to converge, that, for example, when you say, "Good morning," we have this idea of scenes, all right. So when your morning starts you not only want to tune the TV, but you also want to crank up the lights and unlock the door and open the windows, or whatever, and when you go to bed, so the actions that are involved in those use cases span not just TV and not just internet, but all of it. >> Right, it's just funny because I don't think Comcast would be the first name that people would say when they're talking about voice technology and the transformational impact of voice technology, right? They're probably going to say Siri was the first and Alexa's probably the most popular, and you know-- >> Right. >> Google's got Lord knows how many inputs they have, but you guys are really sitting at a central place, and I might argue it's one of the more used voice applications-- >> Absolutely. >> Out there, so from kind of a technology leadership perspective you guys have a bunch of really unique assets in terms of where you are, what you control, what you're sitting on in terms of that internet. You know, how does that really help you and the team think about Comcast as an innovation company, Comcast as a cool tech company, not necessarily Comcast as what used to be just a cable company? >> Right, right. Well you know, as somebody in the valley with friends in the valley it's always interesting to try to differentiate reality from the view that many people have. You know, this is definitely much more than your dad's cable company. It's a consumer and electronic company as much as anything else. We very much position ourselves with all the, you know, with the FAANG companies, et cetera, so you know, when we talked about CX it's no longer the case that whatever's passable for a stodgy cable company passes as CX anymore. Now you're being compared to a set of customers, companies that are providing fantastic user experiences for their customers, and you're being held to that standard, so you know, there's a lot of pressure on us, which is great; we like that. We want to produce fantastic products, and yeah, I don't know if I have a great answer in terms of how to move forward in terms of melding it all together, but we have a lot of smart people in the hallways making that happen. (chuckles) >> So last question is really the impact of AI, because you know, we cover a lot of tech events and a lot of talk about AI, but you know, I think those of us around know that really where AI shines is applied AI in specific applications for specific U cases. So how are you guys, you know, kind of implementing AI, where are some of the opportunities that you see that you can do in the future that you couldn't do the past, whether it be just with much better datasets, whether it be with much faster connectivity and much better compute so that you can ultimately deliver a better customer experience using some of these really modern tools? >> Right, so some of the work is just making what you already do or experience better, so for example showing you recommendations, right? Just make that algorithm better, and so there's a great deal of effort, as you might expect, at a company like this on that problem, but there's also work being done to just take any interactivity between you and the system out of the picture completely. We talked a little bit about this earlier, that, for example, we're working on technology that when you turn your TV on in the morning it should probably tune to the channel that you normally tune to in the morning. That's a pretty simple problem, in a sense, but you know, if I watch your viewing patterns and I see that you turn on a particular news show in the morning, why should you have to pick up the remote and change it from what you watched the night before to that channel? It should just happen. We talked about the Smart Resume stuff, that's obviously a fantastic use case for end users, so there's, you know, it's not surprising it's being used all over the technology set. It's in the home automation world. You know, it's in A/B testing, so trying to figure out the right cohorts to try different things in front of, so it's everywhere as you would expect. >> Right, right, it's pretty amazing. I mean there's just so many things going on, you know, kind of under the covers, some that we can see, some that we can't see where you guys are really kind of progressing, you know kind of the leading edge, cutting edge customer experience with something that people interact with every single day. >> That's right. >> Yeah, cool stuff. Well Mike, thanks for taking a few minutes. Congratulations on the Eye Control; really a cool story, and look forward to more publicity around that because that's a really important piece of technology. >> Thank you very much. It's been a pleasure. >> All right. He's Mike, I'm Jeff, you're watching theCUBE. We're at Comcast Silicon Valley Innovation Center. Thanks for watching, we'll see you next time. (smooth music)

>>From Miami beach, Florida. It's the queue covering a chronics global cyber summit 2019 brought to you by Acronis. >>Okay, welcome back. Everyone's the cubes covers two days here in Miami beach. The Fontainebleau hotel for the Kronos has global cyber summit 2019. It's inaugural event around a new category emerging called cyber protection. Um, this isn't a wave that's going to be part of the modernization a week we've been calling cloud 2.0 or whatever you want to call it. A complete modernization of the it technology stack and development environment includes core data center to the edge and beyond. Our next guest is Dan havens, chief growth officer per Chronis. Dan, thanks for coming on. Appreciate it. And thank you for having me, Dan. So, uh, what does chief growth officer mean? You guys obviously are growing, so obviously we see some growth there. Yeah, numbers are there. What she, what she, we have a couple of divisions in the company where we see we can really accelerate the business. >>So we came in and we wanted to make some large investments here. One of those areas was sports. You're seeing race cars out here on the floor, you're seeing all kinds of baseball teams, soccer teams, and we're talking to everybody. We have 40 teams now that are using our technology for competitive advantage on the field. Uh, the other areas, OEM, so, uh, original equipment manufacturers, everybody from making a camera to a server somewhere, having a Cronus be embedded, that's a big angle for us and we just didn't have a lot of focus. So I came into to build those divisions. I've actually joined the CEO before in a prior life in his last company and did something similar for him on a similar, uh, back there and we had violent success. So yeah, it's been a lot of fun. I've been here a year and a half and we're killing it. >>We got triple digit growth in the sporting category and similar in the OEM. It's interesting, you know, I look at a lot of these growth companies and the kind of a formula. You see, you guys have a very efficient and strong product platform engineering group. A lot of developers, a lot of smart people in the company, and a strong customer facing for the lack of a better word, field. The group you're in, you're involved, this is not, and you got marketing supporting it in the middle. Yep. So nice, efficient organizational structure on a massive way. But cyber, because this isn't your grandfather's data projection, this is a platform. What's the pitch? So the key here for us is we have to always say, and, and it, it's, it's hard to simplify and we're easy. In fact, we're cost-effective. Sometimes I'll even say I'm cheap and I'm easy. >>And that does not go out of style for an enterprise, right? So our ability to take good old fashioned backup and these things that other people need and basically extend that across. Now I can have one window where I can control, keep 'em out. If somebody gets in or from the inside or a disaster happens. I from this one place can recover my data. I'm secure with my data. I have the ability to notarize my data. So this one, and by the way, key simple interface. Customers love simple. This one simple interface to be able to do that. Now it takes a lot of engineering that goes behind that. I have plenty of, I have fancy engineering degrees and all that, but I try forget that when I'm talking to a customer because at the end of the day it's gotta make sense. A mind that doesn't know, says no. >>And I think we do a pretty good job of simplifying the message, but as they get under the covers and they roll it out, they recognize that there's, you know, we, we, we have more engineers per employee capita than any company that would have 1600 employees. Simple, easy to use. It reduces the steps it takes to do something as a winning business model. You kind of come from that school you mentioned, you know, cheap and easy. That's what is key. Yeah. But we're in a world where complexity is increasing and costs are increasing. Yep. These are two dynamics that are facing every enterprise, cyber it everywhere. What's your story when you want to educate that person so they can get to that? Yes. I want to work with you guys. What's that? What's that getting to? Yes. Processed motion look like. So the beautiful part is is we sell software right now. >>Software can be purchased complex. You install it, you can figure, you do everything yourself. We also can sell that from a cloud standpoint. So now you consume it like a service. Just like you consume Netflix at home, right? I can now consume this protection as a service. You have bolts spectrums covered. Most enterprises are somewhere in the middle. We call that hybrid. So the idea here is that there's going to be components where this data's not leaving these four walls. It might be government agency, it might be some compliance factor, but the ability to be able to say yes anywhere on that spectrum, it makes it very easy for an executive to say, okay, but we have a very, as you leverage the cloud, the OnRamp for this can be as simple as turning on the surface and pointing it at a data source. I mean, you're a student of history, obviously even in this business for awhile, you've done been there longer than you'd think. >>Data protection was kind of like that. Afterthought, backup data recovery all based upon, yeah, we might have an outage or a flood or hurricane Sandy who knows what's going to happen. You know, some force majority out there might happen, but security is a constant disrupter of business continuity. The data's being hijacked and ransomware to malware attacks. This is a major disruption point of a world that was supposed to be a non disruptive operational value proposition. Yeah, so the world has changed. They went from a niche, well, we've got their architecture of throwing back up. You've got to think about it from day one at the beginning. This seems to be your, your story for the company. You think about security from the beginning with data protection. There's only one club in the bag, so to speak. Talk about that dynamic and how's that translating into your customer's storytelling customer engagements to show you, you used an interesting word at the beginning, disaster recovery years ago, I started my tech industry in 1992 right? >>Disaster recovery is when we're going to have a flood or a hurricane and the building's going to burn down. What we find is most of our customers, that's certainly happens, but that's not the driver. The driver now is somebody after my data because the world has changed. Not only has the amount of data we're collecting change, but the ability to illegally monetize somebody else's data has become reality and you have social media that is socializes if you get breached and so forth. So there's a number of drivers. Number one, I don't want to be turned out of business. Number two, I don't want to be ransom. Then number three, I certainly don't want to do the cover of the wall street journal tomorrow morning as a top executive who looked past data. We literally watch brands, I won't mention the brand now, but a very large fortune 1000 what's called out yesterday. >>We see it every few days and we watched the carnage of their brand get deluded because they weren't protected. So I think it's the perfect storm up. I've got a ton of data, so it's coming in from all directions. Secondly, I I'm concerned about, you know, my brand and been able to protect that data and then you know, what do I do? And the disaster in this case is not necessarily flood or fire. It's that somebody from the inside or outside got in the gym. Pretend that I'm a decision maker. I'm like, my head's exploding. I'm got all this carnage going on. I don't want to get fired yet. I know I'm exposed. Nothing's yet happened yet. Maybe I settled the ransomware thing, but I know I'm not in a good place. What's your story to any, what's your pitch to me? What's in it for me? Tell me. >>Tell me the posture and the, well, we're halfway home. If you say, I know I'm not in a good place, right? Cause oftentimes somebody has to get bit first or they have to see their neighbor get bit first and then they say, Hey come in. One of my first plays would be let's find out what place you really are. I can do that very quickly and an assessment, we can gather your systems, we can get a sense for our, where's your data? Where it's flowing from. What are you doing? What are you doing to protect it? We typically will come back and there's going to be spots where there's blind spots. Sometimes they're fully naked, right? But the good news is is now we know the problem, so let's not waste any time, but you can get onboard and baby steps or you know, we can bandaid it or we can really go into full surgery however you want to move forward. >>But the idea is recognizing this has to be addressed because it's a beast. Every single device that's out there on the floor, in any enterprise, any company is a way in and a POC are critical for your business model. You want to get them certainly candy taste, show the value quickly has a POC, gets structured unit assessment. You come in on a narrow entry nail something quick, get a win. What's the, what's the playbook? Love PLCs because we're so fast and easy meaning oftentimes you do PLCs cause you're complex software and you're trying to prove your point and so forth. I love to push a POC cause I can do it inside of days, but I get the customer to take the drive. It's just on the car lot. If I get you to drive it down the block, you're not bringing it back. You're bringing it home to the neighbors. >>Right. That is the case with our software and our hit rate is key. But again it's because it's straightforward and it's easy. So though most sales cycles don't push for pilot. I can't wait to get a pilot but we don't need 30 days to do it in a couple of days. They're going to recognize I can do this too. You have a good track record of POC. If I get, this is going to be the most conceding. You might have to edit this out. If I get an audience, I will win. That is the most conceited statement on the planet. And if I get the audience and they will look, and this is why we use the sports teams. Sports teams are the cool kids using this. And if I get an executive to say, what are you guys doing with the red Sox? If I could get him or her to look, it's game over. >>Hey being bad ass and having some swagger. It's actually a good thing if you got the goods to back it up. That's not fun. Piece here is that the product works well and it's not this massive mountain to hurdle. It is. We can get started today and take bites as we go, but you mentioned sports. Let's get into that talk track. As we have been covering sports data for now six years on the cube in San Francisco. We were briefly talking about it last night at the reception, but I think sports teams encapsulates probably the most acute use case of digital transformation because they have multiple theaters that are exploding. They got to run their business, they got a team to manage and they got fan experience and their consumers, so you've got consumerization of it. You got security of your customers either in a physical venue from a potential terrorist disaster could happen to just using analytics to competitive venture from the Moneyball model to whatever sports really encapsulates what I call the poster child of using digital into a business model that works. >>You've been successful with sports. We interviewed Brian shield yesterday. Yup. Red Sox, vice-president technology. He was very candid. He's like, look it, we use analytics. It helps us get a competitive, not going to tell you the secrets, but we have other issues that people not thinking about drone strikes while the games going on, potential terrorist attacks, gathering the people, you know, adding on East sports stadium to Fenway park. They have a digital business model integrating in real time with a very successful consumer product and business in sports. This has been a good market for you guys. What's been the secret to success? >> Explosive market? Couple things. First off, you summarized well, sports teams are looking for competitive advantage, so anything that can come in under that guys is gonna get some attention plus data, fan data, system data, ticket data. Um, in baseball, they're studying every single pitch of pictures ever thrown. >>They have video on everything. This is heavy lift data, right? So a place to put it saved money, a place to protect it, a pace to access it so that all of my Scouts that are out in the field with a mobile device have the ability to upload or evaluate a player while they're out still on them and on the field somewhere maybe in another country. And then add the added caveat in our sexiest piece. And that's artificial intelligence. You mentioned Moneyball, right? Uh, the, the entire concept of, of stat of statistics came out in the Moneyball concept and you know, we all saw the movie and we all read the book, but at the end of the day, this is the next step to that, which is not just written down statistics. Now we can analyze data with machine learning and we have very, we have unique baseball examples where there's absolutely no doubt they have the data. >>It's the ability to, how do I turn that to where I can be more competitive on our racing team. So we're actually working with teams improving, changing the car on the track during the race, using our software fact. We always look forward to opportunities where somebody says, Hey, come in and talk about that because it's incredibly sexy to see. Um, but sports are fun because first off they're the cool kids. Secondly, they're early adopters. If it's gonna give competitive advantage, uh, and third, they hit all the vectors. Tons of data have to protect it. >> It's our life in the business models digital too. So the digital transformation is in prime time. We cannot ignore the fact that people want wifi. They got Instagram, Facebook, all of these, they're all conscious of social media. There are all kinds of listening sports club, they have to be, they have to be hip, right? >>And being out front like that, think about the data they have come in at. And so not just to be smart on the field, they have to be smart with our customer. They're competing with that customer for four of their major sports or whatever. Major sports in the, in the, in the, in our case in this fashionable to be hip is cool for the product, but now you think about how they run their business. They've got suppliers, um, that have data and trusting suppliers with data's. There's a difficult protection formula. They've got national secure security issues. They have to protect, well they have to protect as a big part, but they have to protect, well first off these, these archives of data that are of 20 races ago or of this pitcher pitched three years ago and I have a thousand of his pitches and I'm looking for towels. >>That is, that's mission critical. But also, uh, to boot you have just business functions where I'm a, I'm a team and I have a huge telco sponsor and we are shifting back and forth and designing what their actual collateral is going to be in the stadium. They're actually using a Chronis to be able to do that up in the cloud where they can both collaborate on that. Not only doing it, but being able to protect it that way. It's, it's more efficient for them. It's interesting. I asked Brian shield this question, I asked her how does baseball flex and digital with the business model of digital with the success of the physical product or their actual product baseball. And he said an interesting thing. He's like the ROI models just get whacked out because what's the ROI of an investment in technology? It used to be total cost of ownership. >>The class that's right under the under the iceberg to sharpen whatever you use, you use that. We don't use that. We think about other consequences like a terrorist attack. That's right. So so the business model, ROI calculation shifting, do you have those kinds of conversations with some of these big teams and these sports teams? Because you know they win the world series, their brand franchise goes up if they win the national championship, but whatever their goal is has real franchise value. There's numbers on that. There's also the risk of say an attack or some sort of breach. >> Well, I won't mention the names, I won't mention the teams by name, but I have a half a dozen teams right now and two that are actually rolling out that are doing facial recognition just for security, a fan's entering their stadium. So they are taking the ownership of the safety of their fan to the level of doing visual or facial recognition coming into their stadium. >>Obviously the archive to measure against is important and we can archive that, but they're also using artificial intelligence for that. So you're absolutely right. They owe their fan a safe experience, not only a safe experience with good experience and so forth. And we love to be associated whenever we can with wins and losses. But to your point, how do you get, or how do you show a TCO on a disaster and nobody wants to, and by the way, we've seen enough of that to know it's looming. And there's also the supply chain too. I can buy a hotdog and a beer from Aramark, which is the red socks. They say supplier that's not owned by the red Sox. They have a relationship. But my data's in, I'm a consumer of the red Sox. I'm procuring a, you know, some food or service from a vendor. Yeah, yeah. My data's out there. >>So who protects that? Well, these are unique questions that come up all the time. Again, that's a business decision for the customer. The idea is with cloud collaboration, it's technically quite easy, but again, they have to decide where they're gonna commingle their data, how they're going to share. But the idea here is, again, back to the spectrum, fully cloud and accessible and locked down airtight government's scenario where we have a, you know, a lock bottom line is you get to pick where you want to be on there and there's going to be times where my example of talking to the, uh, the telco vendor, we're, we're actually going to share our data together and we're going to make us faster, make a quicker return and design this collateral for our stadium faster. Those are business decisions, but they're allowed because it, Coronas can be as hybrid as you need to be along the site. >>And again, that resonates with an executive. They never want to be wearing handcuffs and they don't want to pay overpay for stuff to not use our stuff. And if you decide to consume cloud, you, you just pay as you go. It's like your electricity bill. All right. So the red Sox are a customer of you guys. You have or they use your service. What other sports teams have you guys engaged with who you're talking to? Give a taste of some of the samples. So European, we have a couple of formula one teams. We have a racing point. We have the Williams team and formula E we have to cheetah the dragon team. We have a adventury, we also have Neo. So we have a good presence in the racing clubs. We have a ton of a world rally cars and, and, and motorcycle motorcross and so forth. >>Then you step over into European football. So we, we, we started in cars and recognize this is hot. So then we got our first, uh, European team, uh, and we had arsenal. As a matter of fact, we have one of the legends here signing with us today. And you know, I mean, they're rock stars, right? People follow them. Anyway, so we have arsenal and we did man city. Um, and we just landed, uh, Liverpool just did that this quarter, two weeks ago. I literally just, the ink is still drying. Um, and then you move into the United States, which I brought the, you know, I brought the circus to town on January one, 2019. First when was the Boston red Sox. We quickly followed that up. You'll see us on the home run fence at San Diego Padres. Volts bought for different reasons, but both very sexy reasons. So it's the reason. >>What were the main drivers? So in the case of the Boston red Sox, it was, it was a heavy lift on video. A lot of on the protection side. Um, the, uh, San Diego was file sync and share. So the example I was giving of, um, being able to share with your largest telco vendor or with your largest investors slash sponsor for your stadium, um, that was the driver. Now what's funny about both is as they get started, he's always expanding, right? So we have the baseball teams, we did land this quarter, the Dallas stars. So that's our first hockey club. I really want. And my goal is to try to get a couple in each of the main four categories and then some of the subs, um, just cause you get the cool kids, you get a tipping point. Everybody then wants to know what's going on. I have a hundred and play. >>And so we, we typically try to qualify regional where it makes sense. Um, uh, we're, you know, we're very close with a team here in the region. So, you know, they, in the feedback from, from the, from the successes you had implementations, why, what's uh, what's been the feedback from the customers. So here's the file in this. Sounds like I'm just tripping with sales guy and I apologize. Warning signs. Okay. If they use it, we're home free. So when you get Brian or any one of these guys that are using it, all I have to do is make sure that a new customer hears this person who has no reason to say anything else and just expose them to it. Because it's this unknown, scary thing that we're trying to protect against and being able to do that and have the freedom of how aggressive or you know, what metaphor am I going to cover that? >>And then also, uh, you know, the, obviously the economics work is you pay as you go. Um, it's, you know, it's a good story. Well, Dan, congratulations on the success. Um, great to see you guys really digging in and getting those PLCs and being successful. We watching your growth. Final question for you yes. Is all the data and the patterns that you see and all of customers. What's the number one reason why a Cronus is selected and why you women? I think that's an interesting question and I think that it's a couple of reasons. Number one, we work, we're easy. We have an enormous footprint. So there's a lot to reference from. Many people have already used us on the consumer side, so we're safe. So that's one reason I would also tell you however, that we have a great ecosystem because a Kronos is different than most software companies. >>Most software companies have a huge outside sales force that sells direct to customer a Chronis. Everybody here is a partner. We sell through a service provider to a channel member through a, through a, a, a, an ISV. Um, and then we have some direct enterprise. But the idea is there's a variety of solutions that can be baked on this foundation. And I think people like that variety. I, they, they like the, like the freedom of I'm not just trapped with this one thing. I can buy it and all options are available and I will tell you an it, nobody wants to be locked down. Everybody wants options, safety in numbers. They want their data protected with the whole cyber land lens. And they know everything's changing every six months. Something's different. And I don't want to be handcuffed in my desk. I want all options available. I think that's our best value from all right, Dan, thanks for coming on. Dan havens, chief growth officer, but Krohn is weird. The Chronis global cyber summit. I'm John Ford. Stay tuned for more cube coverage after this short break.

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum, World 2019 brought to you by the M Wear and its ecosystem partners. >> Hey, welcome back, everyone. Live Cube coverage of the emerald 2019 were here in San Francisco, California Mosconi North Lobby. Two sets Our 10th year covering the emerald in our 20th year of Of of our seasons of covering Me to be enterprised Tech. I'm Jeffrey Day Volonte student Justin Warren breaking down day to Cube insights segment. Dave's Do You Do You're on Set Valley set this the meadow set because it's got the steamboat chirping birds behind us. Justin, you've been doing some interviews out on the floor as well. Checking the story's out. All the news is out. Day one was all the big corporate stuff. Today was the product technology news stew. I'll go to you first. What's the assessment on your take on the M, where obviously they're reinventing themselves? Jerry Chen, who we interviewed, said this is Act three of'em where they keep on adding more and more prostitute their core, your thoughts on what's going on. >> So the biggest whore I've seen is the discussion of Tom Zoo, which really talking those cloud native applications. And if you break down VM wear, it's like many companies that said, There's the, you know, core product of the company. It is vey sphere. It is the legacy for what we have and it's not going anywhere, and it's changing. But, you know, then there's the modernization project Pacific howto a bridge to the multi cloud world. How do I bridge Kubernetes is going to come into the sphere and do that? But then there's the application world into the thing I've been. You know, the existential threat to VM, where I've been talking about forever is if we sas if I and cloud If I and all the APS go away, the data centers disappear in Vienna, where dominant, the data center is left out in the cold. So, you know, Pivotal was driving down that that path. They've done a lot of acquisitions, so love directionally where towns who's going time will tell whether they can play in that market. This is not a developer conference. We go to plenty of developer events, so, you know, that's you know, some of the places. I see you know, and and still, you know, >> narrator conference. You're right. Exactly Right. And just I want to get your thoughts, too, because you've been blocking heavily on this topic as well. Dev Ops in general, commenting on the Cube. You know, the reality and the reality, Uh, and the reality of situation from the the announcement. That's a vapor. They're doing some demos. They're really product directions. So product directions is always with VM. Where does it? It's not something that their shameful love, that's what they do. That's what they put out. It's not bakery >> company. It's a statement, A statement of >> direction. We were talking hybrid cloud in 2012 when I asked Pet guess it was a halfway house. He blew a gasket. And now, five years later, the gestation period for hybrid was that. But the end was happy to have the data center back in the back. In the play here, your thoughts on >> Yeah. So this conference is is, I think, a refreshing return to form. So, Vienna, where is as you say, this is an operators conference in Vienna. Where is for operators? It's not Four Dev's. There was a period there where cloud was scary And it was all this cloud native stuff in Vienna where tried to appeal to this new market, I guess tried to dress up and as something that it really wasn't and it didn't pull it off and we didn't It didn't feel right. And now Veum Way has decided that Well, no, actually, this is what they and where is about. And no one could be more Veum where than VM wear. So it's returning to being its best self. And I think you >> can software. They know software >> they know. So flick. So the addition of putting predict Enzo in and having communities in there, and it's to operate the software. So it's it's going to be in there an actual run on it, and they wanna have kubernetes baked into the sphere. So that now, yeah, we'll have new a new absent. Yeah, there might be SAS eps for the people who are consuming them, but they're gonna run somewhere. And now we could run them on van. Wait. Whether it's on Silent at the edge could be in the cloud your Veum wear on eight of us. >> David David so I want to get your thoughts just don't want to jump into because, you know, I love pivotal what they've done. I've always felt as a standalone company they probably couldn't compete with Amazon to scale what's going on in the other things. But bring it back in the fold in VM, where you mentioned this a couple of our interviews yesterday, Dave, and still you illuminate to to the fact of the cloud native world coming together. It's better inside VM wear because they can package pivotal and not have to bet the ranch on the outcome in the marketplace where this highly competitive statements out there so you get the business value of Pivotal. The upside now can be managed. Do your thoughts first, then go to date >> about Pivotal. Yeah, as >> an integrated, integrated is better for the industry than trying to bet the ranch on a pier play >> right? So, John, yesterday we had a little discussion about hybrid and multi cloud and still early about there, but the conversation of past five years ago was very different from the discussion. Today, Docker had a ripple effect with Containers and Veum. Where is addressing that and it made sense for Pivotal Cut to come home, if you will. They still have the Pivotal Labs group that can work with customers going through that transformation and a number of other pieces toe put together. But you ve m where is doing a good enough job to give customers the comfort that we can move you forward to the cloud. You don't have to abandon us and especially all those people that do VM Where is they don't have to be frozen where they are >> a business value. >> Well, I think you've got to start with the transaction and provide a historical context. So this goes back to what I used to call the misfit toys. The Federation. David Golden's taking bits and pieces of of of Dragon Pearl of assets in side of E, M. C and V M wear and then creating Pivotal out of whole cloth. They need an I P O. Michael Dell maintained 70% ownership of the company and 96% voting shares floated. The stock stock didn't do well, bought it back on 50 cents on the dollar. A so what the AIPO price was and then took a of Got a Brit, brought back a $4 billion asset inside of the M wear and paid $900 million for it. So it's just the brilliant financial transaction now, having said all that, what is the business value of this? You know, when I come to these shows, I'd liketo compare what they say in the messaging and the keynotes to what practitioners are saying in the practitioners last night were saying a couple of things. First of all, they're concerned about all the salmon. A like one. Practitioners said to me, Look, if it weren't for all these acquisitions that they announced last minute, what would we be hearing about here? It would have been NSX and V san again, so there's sort of a little concerns there. Some of the practitioners I talked to were really concerned about integration. They've done a good job with Nasasira, but some of the other acquisitions that they may have taken longer to integrate and customers are concerned, and we've seen this movie before. We saw the DMC. We certainly saw the tell. We're seeing it again now, at the end where Veum where? Well, they're very good at integrating companies. Sometimes that catches up to you. The last thing I'll say is we've been pushing You just mentioned it, Justin. On Dev's not a deaf show. Pivotal gives VM where the opportunity to whether it's a different show are an event within the event to actually attract the depths. But I would say in the multi cloud world, VM wears sitting in a good position. With the exception of developers pivotal, I think it's designed to solve that problem. Just tell >> your thoughts. >> Do you think that Veum, where is, is at risk of becoming a portfolio company just like a M A. M. C. Watts? Because it certainly looks at the moment to me like we look at all the different names for things, and I just look at the brand architecture of stuff. There are too many brands. There are too many product names, it's too confusing, and there's gonna have to be a culottes some point just to make it understandable for customers. Otherwise, we're just gonna end up with this endless sprawl, and we saw what the damage that did it. At present, I am saying >> it's a great point and Joseph Joe to cheese used to say that overlap is better than gaps, and I and I agree with him to appoint, you know better until it's not. And then Michael Dell came in and Bar came and said, Look, if we're gonna compete with Amazon's cost structure, we have to clean this mess up and that's what they've been doing it a lot of hard work on that. And so, yeah, they do risk that. I think if they don't do that integration, it's hard to do that. Integration, as you know, it takes time. Um, and so I have Right now. All looks good, right? Right down the middle. As you say, John, are >> multi cloud. Big topic gestation period is going to take five years to seven years. When the reality multi cloud a debate on Twitter last night, someone saying, I'm doing multi cloud today. I mean, we had Gelsinger's layout, the definition of multi cloud. >> Well, he laid out his definition definition. Everyone likes to define its. It's funny how, and we mentioned this is a stew and I earlier on the other set, cloud were still arguing about what cloud means exit always at multi cloud, which kind of multi cloud is a hybrid bowl over. And then you compare that to EJ computing, which computing was always going on. And then someone just came along and gave it a name and everyone just went, huh? OK, and go on with their lives. And so why is cloud so different and difficult for people to agree on what the thing is? >> There's a lot of money being made and lost, That's why >> right day the thing I've said is for multi cloud to be a real thing, it needs to be more valuable to a customer than the sum of its pieces on. And, you know, we know we're gonna be an Amazon reinvent later this year we will be talking, you know? Well, they will not be talking multi cloud. We might be talking about it, but >> they'll be hinting to hybrid cloud may or may not say >> that, you know, hybrid is okay in their world with outpost and everything they're doing in there partnering with VM wear. But you know, the point I've been looking at here is you know, management of multi vendor was atrocious. And, you know, why do we think we're going to any better. David, who hired me nine years ago. It was like I could spend my entire career saying, Management stinks and security needs to be, >> you know, So I want to share lawyers definition. They published in Wicked Bon on Multiply Multi Cloud Hybrid Cloudy, Putting together True Hybrid Cloud Multiply Any application application service can run on any node of the hybrid cloud without rewriting, re compiling or retesting. True hybrid cloud architectures have a consistent set of hardware. Software service is a P I is with integrated network security data and control planes that are native to and display the characteristics of public cloud infrastructure is a service. These attributes could be identically resident on other hybrid nodes independent of location, for example, including on public clouds on Prem or at the edge. That ain't happening. It's just not unless you have considered outposts cloud a customer azure stack. Okay, and you're gonna have collections of those. So that vision that he laid out, I just I think it's gonna >> be David. It's interesting because, you know, David and I have some good debates on this. I said, Tell me a company that has been better at than VM wear about taking a stack and letting it live on multiple hardware's. You know, I've got some of those cars are at a big piece last weekend talking about, you know, when we had to check the bios of everything and when blade Service rolled out getting Veum whereto work 15 years ago was really tough. Getting Veum were to work today, but the >> problem is you're gonna have outposts. You're gonna have project dimensions installed. You're gonna have azure stacks installed. You're gonna have roll your own out there. And so yeah, VM where is gonna work on all >> those? And it's not gonna be a static situation because, you know, when I talk to customers and if they're using V M where cloud on AWS, it's not a lift and shift and leave it there, Gonna modernize their things that could start using service is from the public cloud and they might migrate some of these off of the VM where environment, which I think, is the thing that I am talking to customers and hearing about that It's, you know, none of these situations are Oh, I just put it there and it's gonna live there for years. It's constantly moving and changing, and that is a major threat to VM wears multi clouds, >> Traffic pushes. Is it technically feasible without just insanely high degrees of homogeneity? That's that's the question. >> I I don't think it is and or not. I don't think it's a reasonable thing to expect anyway, because any enterprise you have any M and a activity, and all of a sudden you've got more than one that's always been true, and it will always be true. So if someone else makes a different choice and you buy them, then we'll have both. >> So maybe that's not a fair definition, but that's kind of what what? One could infer that. I think the industry is implying that that is hybrid multi club because that's the nirvana that everybody wants. >> Yeah, the only situation I can see where that could maybe come true would be in something like communities where you're running things on as an abstraction on top off everything else, and that that is a common abstraction that everyone agrees on and builds upon. But we're already seeing how that works out in real life. If >> I'm >> using and Google Antos. I can't easily move it to P. K s or open shift. There's English Kubernetes, as Joe Beta says, is not a magic layer, and everybody builds. On top of >> it, is it? Turns out it's actually not that easy. >> Well, and plus people are taken open source code, and then they're forking it and it building their own proprietary systems and saying, Hey, here's our greatest thing. >> Well, the to the to the credit of CNC, if Kubernetes. Does have a kind of standardized, agreed to get away away from that particular issue. So that's where it stands a better chance and say unfortunately, open stack. So because we saw a bit of that change of way, want to go this way? And we want to go that way. So there's a lot of seeing and zagging, at least with communities. You have a kind of common framework. But even just the implementation of that writing it, >> I love Cooper. I think I've been a big fan of committed from Day one. I think it's a great industry initiative. Having it the way it's rolling out is looking very good. I like it a lot. The comments that we heard on the Cube of Support. Some of my things that I'm looking at is for C N C s Q. Khan Come coop con Coming up is what happened with Kay, native and SDO because that's what I get to see the battleground for above Goober Netease. You see, that's what differentiates again. That's where that the vendors are gonna start to differentiate who they are. So I think carbonates. It could be a great thing. And I think what I learned here was virtualization underneath Kubernetes. It doesn't matter if you want to run a lot. Of'em Furat scale No big deal run Cooper's on top. You want to run in that bare metal? God bless you, >> Go for it. I think this use cases for both. >> That's why I particularly like Tenzer is because for those customers who wanna have a bit of this, cupidity is I don't want to run it myself. It's too hard. But if I trust Vienna where to be able to run that in to upgrade it and give me all of the goodness about operating it in the same way that I do the end where again we're in and I'll show. So now I can have stuff I already know in love, and I can answer incriminating on top of it. >> All right, But who's gonna mess up Multi clouds do. Who's the vendor? I'm not >> even saying it s so you can't mess up something that >> who's gonna think vision, this vision of multi cloud that the entire industry is putting forth who's gonna throw a monkey? The rich? Which vendor? Well, screw it. So >> you know, licensing usually can cause issues. You know, our friend Corey Crane with a nice article about Microsoft's licensing changes there. You know, there are >> lots of Amazon's plays. Oh, yeah. Okay. Amazon is gonna make it. >> A multi clock is not in the mob, >> but yet how could you do multi cloud without Amazon? >> They play with >> control. My the chessboard on my line has been Amazon is in every multi cloud because if you've got multiple clouds, there's a much greater than likely chance >> I haven't been. You know, my feeling is in looking at the history of how multi vendor of all from the I T industry from proprietary network operating systems, many computers toe open systems, D c P I P Web, etcetera. What's going on now is very interesting, and I think the sea so ce of the canary in the coal mine, not Cee Io's because they like multi vendor. They want multiple clouds. They're comfortable that they got staff for that si sos have pressure, security. They're the canary in the coal mine and all the seasons lights, while two are all saying multi clouds b s because they're building stacks internally and they want to create their own technology for security reasons and then build a P eyes and make a P. I's the supplier relationship and saying, Hey, supplier, if you want to work with me, me support my stack I think that is an interesting indication. What that means is that the entire multi cloud thing means we're pick one clown build on, have a backup. We'll deal with multiple clouds if there's workloads in there but primary one cloud, we'll be there. And I think that's gonna be the model. Yes, still be multiple clouds and you got azure and get office 3 65 That's technically multi cloud, >> but I want to make a point. And when pats on we joke about The cul de sac is hybrid cloud a cul de sac, and you've been very respectful and basically saying Yap had okay, But But But you were right, Really. What's hybrid would show me a hybrid cloud. It's taken all this time to gestate you where you see Federated Applications. It's happening. You have on prim workloads, and you have a company that has public cloud workloads. But they're not. Hybrid is >> the region. Some we'll talk about it, even multi. It is an application per cloud or a couple of clouds that you do it, but it's right. Did he follow the sun thing? That we might get there 15 years ago? Is >> no. You're gonna have to insist that this >> data moving around, consistent >> security, governance and all the organizational edicts across all those platforms >> the one place, like all week for that eventually and this is a long way off would be if you go with Serverless where it's all functions and now it's about service composition and I don't care where it lives. I'm just consuming a service because I have some data that I want to go on process and Google happens to have the best machine learning that I need to do it on that data. Also use that service. And then when I actually want to run the workload and host it somewhere else, I drop it into a CD in with an application that happens to run in AWS. >> Guys wrapping up day to buy It's just gonna ask, What is that animal? It must be an influence because hasn't said a word. >> Thistles. The famous blue cow She travels everywhere with me, >> has an INSTAGRAM account. >> She used to have an instagram. She now she doesn't. She just uses my Twitter account just in time to time. >> I learned a lot about you right now. Thanks for sharing. Great to have you. Great as always, Great commentary. Thanks for coming with Bay three tomorrow. Tomorrow. I want to dig into what's in this for Del Technologies. What's the play there when I unpacked, that is tomorrow on day three million. If there's no multi cloud and there's a big tam out there, what's in it for Michael Dell and BM where it's Crown Jewel as the main ingredient guys, thanks for coming stupid in Manchester words, David Want them? John, Thanks for watching day, too. Inside coverage here are wrap up. Thanks for watching

>> fly from San Francisco. It's the Cube covering Google Club next nineteen Tio by Google Cloud and its ecosystem partners. >> Hey, welcome back. Everyone live here in San Francisco, California is the cubes coverage of Google Cloud Next twenty nineteen star Third day of three days of wall to wall coverage. John for a maiko stupid demon devil on things out around the floor. Getting stories, getting scoops. Of course, we're here with Sadeer has Bay. Who's the director of product management? Google Cloud. So great to see you again. Go on Back on last year, I'LL see Big Query was a big product that we love. We thought the fifty many times about database with geek out on the databases. But it's not just about the databases. We talked about this yesterday, all morning on our kickoff. There is going to be database explosion everywhere. Okay, it's not. There's no one database anymore. It's a lot of databases, so that means data in whatever database format document relational, Unstructured. What you want to call it is gonna be coming into analytical tools. Yes, this's really important. It's also complex. Yeah, these be made easier. You guys have made their seers announcements Let's get to the hard news. What's the big news from your group around Big Queria Mail Auto ml Some of the news share >> the news. Perfect, I think not. Just databases are growing, but also applications. There's an explosion off different applications. Every organization is using hundreds of them, right from sales force to work today. So many of them, and so having a centralized place where you can bring all the data together, analyze it and make decisions. It's critical. So in that realm to break the data silos, we have announced a few important things that they went. One is clouded effusion, making it easy for customers to bring in data from different sources on Prum Ices in Cloud so that you can go out and as you bring the data and transform and visually just go out and move the data into Big query for for analysis, the whole idea is the board and have Dragon drop called free environment for customers to easily bring daytime. So we have, like, you know, a lot of customers, just bringing in all the data from their compromise. The system's oracle, my sequel whatever and then moving that into into big Query as they analyze. So that's one big thing. Super excited about it. A lot of attraction, lot of good feedback from our customers that they went. The second thing is Big Query, which is our Cloud Skill Data warehouse. We have customers from few terabytes to hundreds of terabytes with it. Way also have an inline experience for customers, like a data analyst who want to analyze data, Let's say from sales force work, they are from some other tools like that if you want to do that. Three. I have made hundred less connectors to all these different sense applications available to our partners. Like five Grand Super Metrics in Macquarie five four Barrel Box out of the box for two five clicks, >> you'LL be able to cloud but not above, but I guess that's afraid. But it's important. Connectors. Integration points are critical table stakes. Now you guys are making that a table stakes, not an ad on service the paid. You >> just basically go in and do five clicks. You can get the data, and you can use one of the partners connectors for making all the decisions. And also that's there. and we also announced Migration Service to migrate from candidate that shift those things. So just making it easy to get data into recipe so that you can unlock the value of the data is the first thing >> this has become the big story here. From the Cube standpoint on DH student, I've been talking about day all week. Data migration has been a pain in the butt, and it's critical linchpin that some say it could be the tell sign of how well Google Cloud will do in the Enterprise because it's not an easy solution. It's not just, oh, just move stuff over And the prizes have unique requirements. There's all kinds of governance, all kinds of weird deal things going on. So how are you guys making it easy? I guess that's the question. How you gonna make migrating in good for the enterprise? >> I think the one thing I'll tell you just before I had a customer tell me one pain. You have the best highways, but you're on grams to the highway. Is that a challenge? Can you pick that on? I'm like here are afraid. Analogy. Yeah, it's great. And so last year or so we have been focused on making the migration really easy for customers. We know a lot of customers want to move to cloud. And as they moved to cloud, we want to make sure that it's easy drag, drop, click and go for migration. So we're making that >> holding the on ramps basically get to get the data in the big challenge. What's the big learnings? What's the big accomplishment? >> I think the biggest thing has Bean in past. People have to write a lot ofthe court to go ahead and do these kind of activities. Now it is becoming Click and go, make it really cold free environment for customers. Make it highly reliable. And so that's one area. But that's just the first part of the process, right? What customers want is not just to get data into cloud into the query. They want to go out and get a lot of value out off it. And within that context, what we have done is way made some announcements and, uh, in the in that area. One big thing is the B I engine, because he'd be a engine. It's basically an acceleration on top of the query you get, like subsequently, agency response times for interactive dash boarding, interactive now reporting. So that's their butt in with that. What we're also announced is connected sheets, so connected sheets is basically going to give you spreadsheet experience on top ofthe big credit data sets. You can analyze two hundred ten billion rose off data and macquarie directly with drag drop weakened upriver tables again. Do visualizations customers love spreadsheets in general? >> Yeah, City area. I'm glad you brought it out. We run a lot of our business on sheep's way of so many of the pieces there and write if those the highways, we're using our data. You know what's the first step out of the starts? What are some of the big use cases that you see with that? >> So I think Andy, she is a good example of so air. Isha has a lot of their users operational users. You needed to have access to data on DH, so they basically first challenge was they really have ah subsequently agency so that they can actually do interact with access to the data and also be an engine is helping with that. They used their story on top. Off half now Big Quit it, Gordon. Make it accessible. Be engine will vote with all the other partner tooling too. But on the other side, they also needed to have spread sheet like really complex analysis of the business that they can improve operation. Last year we announced they have saved almost five to ten percent on operational costs, and in the airline, that's pretty massive. So basically they were able to go out and use our connective sheets experience. They have bean early Alfa customer to go out and use it to go in and analyse the business, optimize it and also so that's what customers are able to do with connected sheets. Take massive amounts of data off the business and analyze it and make better. How >> do we use that? So, for a cost, pretend way want to be a customer? We have so many tweets and data points from our media. I think fifty million people are in our kind of Twitter network that we've thought indexed over the years I tried to download on the C S V. It's horrible. So we use sheets, but also this They've had limitations on the han that client. So do we just go to Big Query? How would we work >> that you can use data fusion with you? Clicks move later into Big Query wants you now have it in big query in sheets. You will have an option from data connectors Macquarie. And once you go there, if you're in extended al far, you should get infection. Alfa. And then when you click on that, it will allow you to pick any table in bickering. And once you link the sheets to be query table, it's literally the spreadsheet is a >> run in >> front and got through the whole big query. So when you're doing a favour tables when you're saying Hey, aggregate, by this and all, it actually is internally calling big credit to do those activities. So you remove the barrier off doing something in the in the presentation layer and move that to the engine that actually can do the lot skill. >> Is this shipping? Now you mention it. Extended beta. What's the product? >> It's an extended out far for connected sheets. Okay, so it's like we're working with few customers early on board and >> make sure guys doing lighthouse accounts classic classic Early. >> If customers are already G sweet customer, we would love to get get >> more criteria on the connected sheets of Alfa sending bait after Now What's what's the criteria? >> I think nothing. If customers are ready to go ahead and give us feedback, that's what we care of. Okay, so you want to start with, like, twenty twenty five customers and then expanded over this year and expand it, >> maybe making available to people watching. Let us let us know what the hell what do they go? >> Throw it to me and then I can go with that. Folks, >> sit here. One of the other announcements saw this week I'm curious. How it connects into your pieces is a lot of the open source databases and Google offering those service maybe even expand as because we know, as John said in the open there, the proliferation of databases is only gonna increase. >> I think open source way announced lot of partnerships on the databases. Customers need different types of operational databases on. This is a great, great opportunity for us to partner with some of our partners and providing that, and it's not just data basis. We also announced announced Partnership with Confident. I've been working with the confident team for last one place here, working on the relationship, making sure our customers haven't. I believe customers should always have choice. And we have our native service with Cloud pops up. A lot of customers liked after they're familiar with CAFTA. So with our relationship with Khan fluent and what we announced now, customers will get native experience with CAFTA on Jessie P. I'm looking forward to that, making sure our customers are happy and especially in the streaming analytic space where you can get real time streams of data you want to be, Oh, directly analytics on top of it. That is a really high value add for us, So that's great. And so so that's the That's what I'm looking forward to his customers being able to go out and use all of these open source databases as well as messaging systems to go ahead and and do newer scenarios for with us. >> Okay, so you got big Big query. ML was announced in G. A big query also has auto support Auto ml tables. What does that mean? What's going what's going on today? >> So we announced aquarium L at Kew Blast next invader. So we're going Ta be that because PML is basically a sequel interface to creating machine learning models at scale. So if you have all your data and query, you can write two lines ofthe sequel and go ahead and create a model tow with, Let's say, clustering. We announced plastering. Now we announced Matrix factory ization. One great example I will give you is booking dot com booking dot com, one of the largest travel portals in the in the world. They have a challenge where all the hotel rooms have different kinds off criteria which says they have a TV. I have a ll the different things available and their problem was data quality. There was a lot of challenges with the quality of data they were getting. They were able to use clustering algorithm in sequel in Macquarie so that they could say, Hey, what are the anomalies in this data? Sets and identify their hotel rooms. That would say I'm a satellite TV, but no TV available. So those claims direct Lansing stuff. They were easily able to do with a data analyst sequel experience so that's that. >> That's a great example of automation. Yeah, humans would have to come in, clean the data that manually and or write scripts, >> so that's there. But on the other side, we also have, Ah, amazing technology in Auto Emma. So we had our primal table are normal vision off thermal available for customers to use on different technologies. But we realized a lot of problems in enterprise. Customers are structured data problems, So I have attained equerry. I want to be able to go in and use the same technology like neural networks. It will create models on top of that data. So with auto Emel tables, what we're enabling is customers can literally go in auto Emel Table Portal say, Here is a big query table. I want to be able to go out and create a model on. Here is the column that I want to predict from. Based on that data, and just three click a button will create an automated the best model possible. You'LL get really high accuracy with it, and then you will be able to go out and do predictions through an FBI or U can do bulk predictions out and started back into Aquarian also. So that's the whole thing when making machine learning accessible to everyone in the organization. That's our goal on with that, with a better product to exactly it should be in built into the product. >> So we know you've got a lot of great tech. But you also talk to a lot of customers. Wonder if you might have any good, you know, one example toe to really highlight. Thie updates that you >> think booking dot com is a good example. Our scent. Twentieth Century Fox last year shared their experience off how they could do segmentation of customers and target customers based on their past movies, that they're watched and now they could go out and protect. We have customers like News UK. They're doing subscription prediction like which customers are more likely to subscribe to their newspapers. Which ones are trying may turn out s o those He examples off how machine learning is helping customers like basically to go out and target better customers and make better decisions. >> So, do you talk about the ecosystem? Because one of things we were riffing on yesterday and I was giving a monologue, Dave, about we had a little argument, but I was saying that the old way was a lot of people are seeing an opportunity to make more margin as a system integrated or global less I, for instance. So if you're in the ecosystem dealing with Google, there's a margin opportunity because you guys lower the cost and increase the capability on the analytic side. Mention streaming analytics. So there's a business model moneymaking opportunity for partners that have to be kind of figured out. >> I was the >> equation there. Can you share that? Because there's actually an opportunity, because if you don't spend a lot of time analyzing the content from the data, talk aboutthe >> money means that there's a huge opportunity that, like global system integrators, to come in and help our customers. I think the big challenges more than the margin, there is lot of value in data that customers can get out off. There's a lot of interesting insights, not a good decision making they can do, and a lot of customers do need help in ramping up and making sure they can get value out of that. And it's a great opportunity for our global Asai partners and I've been meeting a lot of them at the show to come in and help organizations accelerate the whole process off, getting insights from from their data, making better decisions, do no more machine learning, leverage all of that. And I think there is a huge opportunity for them to come in. Help accelerate. What's the >> play about what some other low hanging fruit opportunities I'LL see that on ramping or the data ingestion is one >> one loving fruit? Yes, I think no hanging is just moving migration. Earlier, he said. Break the data silos. Get the data into DCP. There's a huge opportunity for customers to be like, you know, get a lot of value. By that migration is a huge opportunity. A lot of customers want to move to cloud, then they don't want to invest more and more and infrastructure on them so that they can begin level Is the benefits off loud? And I think helping customers my great migrations is going to be a huge Obviously, we actually announced the migration program also like a weak back also way. We will give training credits to our customers. We will fund some of the initial input, initial investment and migration activities without a side partners and all, so that that should help there. So I think that's one area. And the second area, I would say, is once the data is in the platform getting value out ofit with aquarium in auto ml, how do you help us? It must be done. I think that would be a huge opportunity. >> So you feel good too, dear. But, you know, build an ecosystem. Yeah. You feel good about that? >> Yeah, way feel very strongly about our technology partners, which are like folks like looker like tableau like, uh, talent confluence, tri factor for data prep All of those that partner ecosystem is there great and also the side partner ecosystem but for delivery so that we can provide great service to our customers >> will be given good logos on that slide. I got to say, Try facts and all the other ones were pretty good etcetera. Okay, so what's the top story for you in the show here, besides your crew out on the date aside for your area was a top story. And then generally, in your opinion, what's the most important story here in Google Cloud next. >> I think two things in general. The biggest news, I think, is open source partnership that we have announced. I'm looking forward to that. It's a great thing. It's a good thing both for the organizations as well as us on DH. Then generally, you'LL see lot off examples of enterprise customers betting on us from HSBC ends at bank that was there with mean in the session. They talked about how they're getting value out ofthe outof our data platform in general, it's amazing to see a lot more enterprises adopting and coming here telling their stories, sharing it with force. >> Okay, thanks so much for joining us. Look, you appreciate it. Good to see you again. Congratulations. Perfect fusion ingesting on ramps into the into the superhighway of Big Query Big engine. They're they're large scale data. Whereas I'm Jeffers dipping them in. We'LL stay with you for more coverage after this short break

(techno music) >> At Ducati, we create racing bikes and road bikes, and unique experiences for our bikers. The Ducati teams participate in 19 races, in 15 countries, on five continents, as part of Moto GP Championship around the world. When you own a bike, you are part of a new family, the Ducatisti. (engine revving) We have a DNA racing, that we bring into everyday's bike, you can be a racer, or you can be someone who want to go down downtown Bologna, or San Francisco, or Bangkok. Data is at the heart of the Ducati digital strategy, in racing we know how to analyze data, the experience is directly moved to our road bikes. In race bikes and road bikes we have physical sensors, now thanks to machine learning, artificial intelligence, we can bring to data together to create Bitron sensors, that give us information that were not available before. We are looking for a partner that truly understands the value and the power of data, and this happened to be NetAPP. We want to arrange data in new ways, to transform the sport of Moto GP racing, and the road bike experience. NetAPP has controlled data to make experimentation more quickly, the bike we race on Sunday, is the bike we sell on Monday, and we can test the riders sensation through data. I'm Piergiorgio Grossi, and I'm data driven. (techno music) >> Narrator: Live from Las Vegas, it's the Cube, covering NetAPP Insight 2018, brought to you by NetAPP. >> Welcome back the the Cube our continuing coverage today, from the Mandalay Bay of NetAPP Insight 2018, I'm Lisa Martin with Stu Miniman and we have a couple of guests joining us. If you're a Motorsport fan, turn the volume up. First we have, welcoming back to the Cube, Jean English, the SVP and CMO at NetAPP, great to have you back Jean!. >> Oh thank you very much, excited to be here. >> And we have Konstantin Kostenarov, CTO of Ducati Motor, wow Ducati, there is by the way, I encourage you to go to the NetAPP.com web site after the segment here there's a very cool video about how Ducati is working with NetAPP on the racing side, these bikes are like flying IOT devices, as well as the consumer side. So Jean let's kick of things with you, this is day one, record breaking attendance for NetAPP, 5000 attendees, we were in the Keynote this morning, standing room only, talk to us about NetAPP as a Data authority, what's some of the feedback that you're hearing from your wealth of partners and customers that are here this week? >> Absolutely, well we're thrilled to have so many partners and customers and employees here with us, record breaking attendance, more customers and partners that have ever joined us before here at Insight a Data authority, people are asking us what do I need to do to maximize the value of that data, whether it's integrating the data, simplifying the data, they're trying to figure it out, and most of the time it's in a Hybrid role, it's in a multiclout world, and so we're just excited about where we are with our strategy, we're bringing it to life, more and more customers, like Ducati everyday are helping us to see this vision come true and we just can't wait to get started with everyone else. >> And this is a really interesting example, NetAPP has, in it's 26 year history, a massive install base, probably every industry, but when you look at something like Ducati, which probably every guy knows about, I have some Motorsport experience myself, it's much more of a, oh as a consumer, as a fan of the sport, so Konstantin, tell us about Ducati's decision to work with NetAPP, because you guys aim to not only utilize, all of the data, tons of data coming off the two bikes, every race weekend, to improve performance, but you're also wanting to use that speed, which is the new scale as George Curion said this morning, to even improve the consumer experience, and talk to us about Ducati's partnership with NetAPP. >> So we start to work with NetAPP about two years ago, more over, and in these, nowadays, every people around us talk about job thinking, extreme improvement, extreme increase of customer experience so in this world this will be Ducatis very excited challenge and this challenge requires us to respond with the best technology. The best technology that help us to collect the best information from our motorbikes, from our racing teams that we know how to collect the data, how to transformate this data into usable information, and how to generate the opportunity to have data sensors that we can transform in in information but also in knowledge that we hear before, and put all this information inside our fabric, and inside our shop floor, inside our R and D department, in order to be able to extremely increase the experience of our customers. >> I love that we get to work with one of the most innovative companies in the entire world of Motorsports, and I think really from the inception of Ducati, you guys have been really focused on how do you keep innovating through technology, and we talk about transforming the world of racing with data and how are we doing that together, so together with Ducati and NetAPP, how do we help enable them to have the best motors in the whole world, we're really excited! >> Jean, it's a great discussion, we've loved watching from just talking about the storage industry to where we're talking about data, and transformations so maybe explain to our audience that maybe not understand, you know, what's different about the industry today, and what's enabling this, NetAPP to be able to work with companies like Ducati, to help them through these transformations today, that they might not have been able to do a few years ago. >> Absolutely, I think there's just more and more data that we're finding every day, whether it's Ducati, Motorsports, if it happens to be in health care, and thinking about the millions and billions of genomes types of research that they're doing. We know even from banking how they're trying to connect the dots across an entire customer experience. Sure they're using technology like storage, absolutely, they're thinking about computers, they're thinking more and more though about services, and the cloud, APIs, how are they going to gain all this innovation through AI, analytics, but it's about making the customer experience better. What I love about the partnership we have with Ducati is it's not just about the bikes themselves, it's about the community that they have and that they're building and that community is yes, based on data from the bike, it's about the data coming from the riders, and it's about the data they collect so they all become a stronger community as a whole. >> Yeah, Konstantin maybe explain a little bit more to your audience the role of data as Ducati see's it, and how that drives innovation in your company. >> In the world like motorbike racing team, where every millisecond counts and the difference, in how we can collect in, very quickly mode the data, and to transform the information becomes determinate if you win or not because as you know, in Qatar we win with 29 milliseconds, and this is the work that we've done, days before, analyzing data, and set up the motorcycle, in the best way, because for us, the collaboration with NetAPP is not only storage, and is not only data, but is data management, and extremely short time to respond to our business requests and work to transform the paradigm of time, and money the paradigm of data and information, and we talk about performance with our line of business, not from the technical point of view but from the extremely business oriented, the customer oriented point of view, and we collect the data from the more than 60 sensors, from the racing motorbikes and transform it with artificial intelligence and deep machine learning, in vector sensors that give us information that we cannot reach from the normal road bikes, and this improves extremely our competitiveness, and we are able to give this, experience to our riders that becomes our families, because a good thing, a good product to all our customers, and with attention of environment in the behavior of the riders we would think that the good people in the good universe act in a good way. >> And we're happy to be part of that too. >> Before we get into that, the consumer side, so your riders, Andrea Dovizioso, and Jorge Lorenzo, how has their performance improved because you're able to take data, gigs per quali day, race day, analyze it in real time, how has their performance improved as a result of your NetAPP partnership? >> As you know, the racing motorbike is not able to stop in real time during the race, not like in Formula One so you need to use the best technology to connect the bikes to our minidata center inside the box during the race. Make our strategy to set up the bike as better as we can, and the speed which we can reach the, and collect the data, put it in the telemetry software, calibrate it, make the strategy decision is very very important. And with the HCI technology we can do it. >> How are you taking the transformation that you're making on the racing side and applying it to the consumer side so that, as I think I heard on the video, Ducati wants to deliver the bike that a guy or gal rides on a Sunday by Monday, that speed, speed is the new scale as George Curion mentioned this morning, how is the consumer side of Ducati Motorsport being influenced positively to enable those consumers to have exactly what they want? >> If you see our new creation, the Dopra, the Panigale V4, this is the right example how we transform racing motorbikes to the road bikes, and we give to our customers this kind of experience because all information we manage during the Sunday we are able to put in on Monday and sell the bike that have the same performance, safety, and pleasure of riding for the final customers and we have a racing that we bring to everydays motorbike, so when you buy a bike we give you experience that before you're riding, during the riding, and after your riding when you are at your home, with our uplink connection, we use the NetAPP technology to give the best experience of connected bikes. >> So when you think about customers, especially our partnership with Ducati, in order to be customer centric, or rider centric, we really have to be data driven, and so as we think about what are all the connections and the dots of data that happen, whether it's on the bike, the rider, the community itself, how does that bike that's driven or ridden on a Sunday, how is then really performed and given to customer that next day, it's all about the data. >> I'm curious, cause how have you been able to improve that speed of scale meta HCI as part of your data driven foundation, what's kind of a before and after, are you able to deliver bikes faster? Have you transformed the customer experience like Jean was saying? >> So before NetAPP, our production plan is more difficult to be connected to all other line of business and we are not able to collect the information from our final user, our customer. And give this information to our R and D department or the shop floor, in order to be able to transform in real time our production process, and to give the best experience for everyday bikers. >> So significant business impact? >> Exactly, and with our connected bike, this has become a reality. >> Jean, just want to bring it back to NetAPP for a minute here you've been on board for about two years, George Curion talked about the transformation that NetAPP is going through itself, can you speak a little bit to the culture, you know I think back for years and NetAPP has been known for one of the top places to work, it's talking about that transformation, what can you say about what's happening inside NetAPP? >> Sure, so I think the transformation has gone through a couple of different cycles. I mean one was really around the operational efficiency we needed to be as a company to really be focused on what were the customers caring about? What were the technologies and innovations that we needed to shift to that mattered to the customer? Cloud being one of those, whether it was a private cloud, or a public cloud, we also started to think through, is the right leadership that we needed to have in the company to start making those shifts? A big part of it is the culture though and that culture is ground up, it definitely starts across the leadership team we have today, but it is infused across all of NetAPP. It is one of the reason why I joined the company, when I first started interviewing with George, he wanted me to come help him write the new story, but so much a part of a story of a company is the people themselves, and so if you think about any kind of transformation, it is definitely strategy, it's technology, it's around what you do from processes, but culture and people are the biggest part of that, and we think of the brand inside of NetAPP, the people are the biggest part of it. And who we are and what we stand for, really always leaning in to the latest technology, because it's what customers care about, if I think about the history over the last 10 to 15 years, what could have broken NetAPP, moving from Linux to Windows, moving in to virtualization, now with the cloud, we've always leaned in, because we want to care about what the customer cares about. And that's every single person inside of NetAPP that makes that happen. So I love being at NetAPP and it's an exciting place to be! >> Cultural transformation is hard to do, it's essential for IT transformation, digital transformation, security transformation, I'm curious Jean, NetAPP has such a big install base of a lot of enterprise incumbents that weren't born in digital of course you've got some amazing customers like Ducati, talk to us about how your customers, you mentioned NetAPP is good at leaning in, how do you leverage that voice of the customer to help the sustain the cultural transformation you need to really put cloud at the heart of your strategy? >> Absolutely, even with the example of Dreamworks, we just started working with Dreamworks as one of our partners to start co-engineering with them, to help them on their own transformation. And so that's taking right from the customer, what are their requirements, how are they going to take this cutting edge digital content, and then be able to make it into beautiful, engaging films that we all know and love, How To Train Your Dragon's coming out very soon and we're excited about seeing it, but those kind of partnerships really matter, and how people are leaning in to the cloud, and how they're leaning in to hypercloud, multicloud, we want to hear what our customers need and work with them to be able to really build out that technology and innovation for the future. >> Konstantin, last question for you, what are you, I know you had a session yesterday, what are you excited to hear about from you partner NetAPP at the event this week? >> I'm excited to hear about the people, it's a very put attention of the details, of what the NetAPP mean regarding the data management. And the data driven company, what is the real time feedback to the customers, and improvement of the customer experience, and one of the things that I like is the simplicity to use the NetAPP technology that give us the speed of reaction, and transform the information into knowledge, and how can I say in experience to know how to do the things >> Well Konstantin, Jean, thank you so much for stopping by and giving us a really cool, sexy example of how NetAPP is helping a company like Ducati really revolutionize the racing side and the consumer side of the businesses. And we want to encourage you to go to NetAPP.com search Ducati and you will find a very cool video, on how these two companies are working together. For Stu Miniman, I'm Lisa Martin, you're watching the Cube live, all day from NetAPP Insight 2018, Stu and I will be right back with our next guest. (techno music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering NetApp Insight 2018. Brought to you by NetApp. >> Welcome to theCUBE, we are live at NetApp Insight 2018, I'm Lisa Martin and I'm joined by Stu Miniman. Stu and I are going to be here all day. And this is the third annual Insight, with customers and partners and NetAppians and analysts and press. Stu this is the second time theCUBE has been here. We just came from the keynote and the interesting thing that Stu, that you and I both noticed, was at least the first 75 minutes of the keynote that we got to see today, none of the product news was announced. It was really about strategy, #datadriven, how NetApp wants to enable their customers from DreamWorks to oil and gas companies, health care, etc. To use data, develop a data strategy, to move their businesses into the digital age. >> Yeah, Lisa, first of all, great to be working with you again. >> Always. >> And I'm excited, it's second year that we've been at this show, third of the NetApp Insights that we've done. Cause we've done both the U.S. and the European shows. My first time actually coming to a NetApp event. I remember, gosh I'm showing my age, I remember when NetApp started, network storage was becoming a thing. NetApp really rose its ascendancy with file systems and NAS, and FAS was the one operating system to rule them all, really grew into a very sizable business. Company's about $6 billion worth of revenue and I think somewhere about 10,000 employees. Today, NetApp is really the largest independent storage company after Dell took EMC off as an independent now, so it's interesting to watch. George Kurian got on stage and talked about digital transformation. And one of the things I'm really interested in looking at is how is NetApp doing in that transformation? Because, most people when I was talking to some customers at some of the meals and walking the floor and things like that it's, NetApp is my filer company. I buy boxes, sometimes I mine some software and there's some things there, but I'm the guy that runs NetApp Gear, if you will. And that transformation, what is the NetApp of 2019 and beyond? Are they a storage company? Are they a hybrid, multi-cloud software led something something company in the future? Are they a services company? There's a nice ecosystem here, so that's what I'm excited to dig into. George Kurian he in the keynote this morning, laid out the four things that companies need to do for digital transformation. It's something we'll dig into, but yeah, I had to go search NetApp on the news release and be like, oh Cloud Insights, and ONTAP in the Cloud, and HCI and Partnership News and things like that, so there definitely is some news, they just didn't talk about it in the keynote. >> Yeah, it was an interesting keynote for me, and as theCUBE we go to a lot of keynotes, many times a year, and this was an interesting start to it. It's clear from the NetApp messaging on NetApp.com, NetApp Insight, things that are being put out on media that they're really putting cloud at the heart of their strategy. The discussions and the keynote this morning included futurist Gerd Leonhard, who's going to be on the program with us in just a few minutes. Interesting take on data, humanity, the only thing that NetApp talked about was about 75 minutes minutes into they keynote this morning was when Anthony Lye got on, he's going to be on the show later today, talking about the data fabric. And I think some of the messages that NetApp was wanting to get out is that data fabric is transforming from a vision into an architecture kind of foundationally to enable organizations to employ those four principals of digital transformation that George Kurian talked about. Digital transformation requires IT transformation, speed is the new scale, some interesting thoughts and concepts there, more conceptual. I liked the DreamWorks customer, I think she's a great speaker. Kind of talked also about how DreamWorks, everybody knows DreamWorks, "Shrek", "How to Train your Dragon", are becoming more morphing from a customer to an engineering partner. So that was and interesting kind of, I wouldn't even say undertone, but part of the story today. >> You know, Lisa, absolutely. When you look at traditionally, not only NetApp, but all the storage companies, where they sold to. It was the storage budget, and oh how do I manage with the explosion of data, and that growth and what's the performance, the speeds and feeds, the price per terabyte, all that kind of stuff? I thought we could actually take George Kurian's four characteristics and say, how's NetApp doing? First is digital transformation requires IT transformation. >> (Lisa) Right. >> I heard yesterday in some of the sessions they actually had some of NetApp's IT people talk about how they're leveraging and using new technologies. We talked about speed is the new scale, well how fast is NetApp? We have a number of acquisitions. There was the big SolidFire acquisition which is now fully part of the portfolio. They had a Kubernetes company that they bought recently. They've had management companies that they bought. How fast is NetApp keeping up with the pace of what they're doing? Hybrid multi-cloud, I think NetApp first of all was really what you would call software-defined before that was a thing, and they were very early in jumping on this wave of we need to play in the cloud environment. Most of the storage companies really lined up and was like, oh wait, Amazon's the competition, you can't do that, but NetApp was partnering with Amazon for many years, now I'd like to see more proof points as to what customers are doing, how are they doing it differently. But absolutely we're going to have Microsoft Azure on the program with Anthony Lye, this afternoon. I know we're going to be talking about Amazon, we're going to be talking about Kubernetes and Istio, where does NetApp fit into that environment? I've been going to theCUBE Con shows for a couple years, and storage is actually lagging in that space. When you talk about having persistent data, that's not something we're there with. We spent more than a decade trying to fix storage and networking in the virtualized environments, and NetApp played a strong role in helping on the storage piece there. So it would be great to see how they are going to play into the Kubernetes and issue discussion. And the last piece is they said moving from data center to data fabric. >> Right. >> Which is the closest tie to the products as you said. >> (Lisa) Yes, exactly. >> To what they're doing. >> Well, Stu we have a jam-packed schedule today, all day. We're going to be able to unpack a lot of things from NetApp, execs, to their branding folks, to customers, so Stu and I will be right back with our next guest. Again, theCUBE Live from NetApp Insight 2018. We'll be right back. (music)

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape so cube conversations simplifying blockchain for developers remi karpadito is here is the CEO of espresso remy thanks for coming in yeah thanks for having yeah so you guys are in the Seaport we want to hear all the action that's going on there but let's start with espresso CEO founder or co-founder um not a co-founder founder okay good just to clarify with respect to your co-founders voice why did you guys start espresso yeah no it starts back on in a little bit little while ago we originally wanted to and a replace our first company was a company called campus towel and we want to replace student identity with NFC chips and smart phones and it was a really cool concept back in 2010 but at the time there's only one phone that had the technology capable of pulling the south and we built a prototype with that smart phone as a Samsung phone at the time and we brought that around to a dozen plus colleges showing hey you could replace the student ID with the phone you can just tap your phone to it for attendance for events etc and they loved it but everyone had the same question you know when is the iPhone can have the technology and we were three years early the iPhone didn't come up with NFC chips until 2013 and we ended up hitting into a mentoring platform and scaled that company October 70 colleges across the country but ironically enough we came back to the same issue a lot of CIOs and CTOs wants to interface with their single sign-on servers which required us to support this legacy technology you know so AJ and I spun back internally AJ's our co-founder and CTO to identify how can we replace identity again but instead of using hardware and smartphones let's use the blockchain and AJ was an early a Bitcoin adopter back in 2010 mining Bitcoin really I'm passionate about the technology and I started learning a little bit more about it and trying to find a way to incorporate blockchain technology into our student identity solution as a secondary offering for Campus Tau but we quickly realized was that our front-end engineering team who is a little bit underwater in terms of the technical skills that needed to help and participate in the development for the boccie an identity solution so we ended up building up to middleware components to help them with the development and that's where we saw kind of that's where the lightbulb went off and the bigger opportunity came about where a lot of the infrastructure and tooling needed in order to build a production level blockchain application isn't quite there yet ice we ended up hitting and building a new company called espresso to make botching development more accessible so let's talk about that that the challenge that your developers face so you were at the time writing in for aetherium and in solidity right which is explain to our audience why that's so challenging what is solidity yeah and and why is it so complex yes illinit e is a JavaScript based framework for writing smart contracts on in the etherion platform it's not a fully baked or fully developed tools that yet in terms of the language there's some nuances but on top of that you also need to understand how to support things like the infrastructure so the cryptography the network protocols so if you want to sustain your own blockchain there's a lower-level skill set needed so the average JavaScript engineering could be a little bit kind of overwhelmed by what's needed to actually participate in a full-blown botching development yes and they're probably close to 10 million JavaScript engineers worldwide so it sounds like your strategy is to open up blockchain development to that massive you know resource yeah and in JavaScript being a definite core focus out of the gates and will be developing a plethora of SDKs including JavaScript and Python and Ruby etc in the thought process is you know activating these engineers that have coming new code academies or Enterprise engineers that really get a C++ or another language and allowing them to code in the languages they already know and allow them to participate the blockchain development itself okay and so how many developers are on your team so we've it's a small ad product teams three people on a parodic team now but we're actually the process is killing that up yeah so those guys actually had to go on the job training so they kind of taught themselves and then that's where you guys got the idea said okay yeah exactly and we realized that you know if we could build out this infrastructure this tooling layer that just allows you compile the language as you know into the software or the blockchain side it can make it a much more accessible and then also the other thing too that's interesting it's not just kind of writing the languages they already accustomed to but it's also the way you architect these blockchain solutions and one thing we've realized is that a lot of people think that you know every piece of data needs to live on the blockchain where that's really not something I've been teachers for you to do so because it's really expensive to put all the data on the blockchain and it's relatively slow right now with ethereum of 30 transactions per second there's companies like V chain that are looking to remedy some of those solutions with faster write data write times but the thought process is you can also create this data store and with our middleware it's not just an SDK but it's a side chain or a really performant in-memory based data store they'll allow you to store off chain data it's still in a secure fashion through consensus etc that can allow you to write data rich or today's level applications on the blockchain which is really kind of the next step I see coming in the Box chain space so I'm gonna follow up on when coaching there I mean historically distributed database which is what blockchain is it's been you know hard to scale it's like I say low transaction volumes they had to pick the right use cases smart contracts is an obvious one yeah do you feel as though blockchain eventually you mentioned V chain it sounds like they're trying to solve that problem will eventually get there to where it can can compete with the more centralized model head on and some of you know the more mainstream apps yeah and that's and that's kind of where we are because our thought process if we were to move campus topic the kind of private LinkedIn for colleges per se on to the blockchain back when we started it wouldn't be possible so how do you store this non pertinent data this transactional or not even transactional this attribute data within a boxing application and that's really where that second layer solution comes into play and you see things like lightning Network for Bitcoin etc and plasma for aetherium but creating this environment where a developer comes on they create an account they name their application they pick their software language and then they pick their blockchain there's pre-built smart contract we offer them but on top of that they already have this data store that they can leverage these are things that people already accustomed to in the web 2.0 world these are the caching layers that everyone uses things like Redis etcetera that we're bringing into the blockchain space that well I that we believe will allow this kind of large-scale consumer type application well when you think about blockchain you think okay well he thinks it's secure right but at the same time if you're writing in solidity and you're not familiar with it the code could be exposed to inherent security flaws is that so do you see that as one of the problems that you're solving sort of by default yeah I think one thing here is that I kind of as you write a smart contract you need to audit you test it so on and so forth and so we're helping kind of get that core scaffolding put up for the developer so they don't need to start from scratch they don't need to pull a vanilla smart contract off of a open source library they can leverage ones that are kind of battle tested through our through our internal infrastructure so the last part of our kind of offering is this marketplace of pre developed components that developers can leverage to rapidly prototype or build their applications whether it be consumer engineer or enterprise that one and you were developer what's your back my background yeah so I studied entrepreneurship and Information Systems so I do have I was a database analyst at fidelity it was my last job in the corporate world so I do have some experience developing nowhere near that of my co-founder AJ or some of our other but but yeah I understand the core concepts pretty well well speaking blockchain who if she was talking about obviously you you see a lot of mainstream companies obviously the banks are all looking at it you're seeing companies we just you know heard VMware making some noise the other day you're at certainly IBM makes a lot of noise about smart contracts so you're seeing some of these mainstream enterprise tech companies you know commit to it what do you see there in terms of adoption in the mainstream yeah no I think the enterprise space is gonna want to fully embrace this technology first I think the consumer level we're still a little bit ways away there just because this infrastructure and this tooling is needed before developers kind of get there but from the enterprise space what we see I mean obvious things like supply chain being a phenomenal use case the blockchain technology Walmart IBM are already implementing really cool solutions one of them my advisors Rob Dulci is the president of Asia and they've successfully implemented several blockchain projects from car parts manufacturers to track and trace through wine seeds and this from grape seeds and so there's a lot of different use cases in the supply chain side identity is really exciting Estonia is already doing some really cool work with digital identities that's gonna have a big impact voting systems etc but also thinking through some newer concepts like video streaming and decentralization of Network Maps and so there's many different use cases and for us we're not trying to necessary solve like a dis apply chain problem or anything we're trying to give a set of tools that anyone can use for their verticals so we're excited to see kind of what a spreads used for and over the next several months to here I remember you mentioned V chain before so explain what V chain is and now your what you're doing with those guys yes if V chain is another kind of next generation blockchain they're they're v chain Thor is the new platform and actually their main net launch is tomorrow and they're really excited they're introducing heightened security faster block times more transactions per second they have a really interesting governance model that I think is a good balance between pure decentralization in the centralized world which i think is that that intermediate step that a lot of these enterprises are going to need to get to end of the block chain space and we're working with them or lon on their platform so our token sale will be run through V chain which is great in addition we'll be working with them with through strategic partnerships and the goal is have espresso be the entry point for developers coming into V chain so we'll help kind of navigate the waters and kind of have them leverage the pre-built smart contracts and get more developers into the ecosystem okay let's talk about your token sale so you're doing the utility token yep and so that means you've actually got utility in the token so how is that utility token being utilized within your community yeah so the data actually the token is used to meter and mitigate abuse in the platform as well so at every single transaction it'll validate the transaction in addition it will be an abstraction layer since we do speak to multiple block chains that ezpz token will have to abstract up to aetherium to Thor which is the V chain token the future dragon chain etc so that's a really interesting use case and one of the interesting things we're trying to solve right now if you're a developer trying to come in and use it it cryptocurrency for development you need to go to something like a coin base you have to exchange fiat to aetherium you have to push that out to a third party exchange you have to do a trade and then you have to send that digital wallet address where you get easy peasy Oh to our account after that's a ton of friction and that's more friction if you're not a crypto person you're gonna be what is it you're gonna be asking to do it yeah so we're talking to some pretty big potential partners that allow kind of they would be the intermediate intermediary or money service to allow a seamless transition for engineer just to come straight onto espresso put down a credit card bank account verified go through the standard kyc AML process and then be able to get easy peasy in real time and that's something that at a macro level I think is one of the biggest barriers to entry in the botching space today so what do you call you your token easy-peasy okay so you're making that simple transparent done so you're doing a utility token you do in a raise where are you at would that raise give us the details there yeah yes so we just close our friends and family around we're not private sale right now are working closely with the VA in the VA chain foundation helping kick that off right now as well and we're yeah this is gonna be much more strategic capital in this round and then after that we'll be moving into since we are partnered with each a in their community gets a little bit of exclusivity in the next piece of the round so their master note holders will get a bigger discount in the next round and then the last round will be the public round for the general community and that's where we anticipate a lot of developers we already have development shops coming on participating in the first round which is great because the thought process is we want to get as many developers in this platform as possible throughout the summer and I think that's one of the most unique things about the token sales it's not just raising capital it's actually getting people that want to use your product to buy him now and that's that's amazing so okay so you're doing the private sale first right and you open that up to those types of folks that you just mentioned and they get some kind of discount on the on the token because they're there in early and they're backing you guys early and then you guys got a telegram channel I know it was on the recently anything is exploding it looks like a pretty hot you know offering and then then what happens next then you open it up to just a wider audience we start getting the core community members from V chain and then after that the public sale will be really targeted for the unused these are the people that you know need to put in a large substantial amount of capital again and at that point you could put in a couple hundred dollars and actually participate in in the token sale and you'd be getting in the kind of ground Florida sand and the SEC just made a ruling you know recently a week ago or so that Bitcoin and in aetherium were not security so that's a good thing nonetheless you as a CEO and entrepreneur you must have been concerned about you know a utility token and making sure everything's clean that there actually is utility you can't just use the utility token to do a raise and then go build the products you have you had it you have a working product right yeah so there's a lot of functionality already set up and we're going to continue to iterate before we even get close to the actual tokens or the public sale right so we anticipate having full functionality of what we want to get out there to the development world by the end of the sale so it's the thing that we I think one of the biggest things in this space right now in terms of the law and compliance side is a lot of self regulation since in the u.s. in particular it's such a great area you need to one stay up-to-date with every single hearing announcement but also really make sure you're you're taking best practices with kyc AML making sure the people you know good people that are investing into the comm or I've kind of participating in the allocation and and that's something we you know we've spent a lot of time with our legal team I've got pretty intimate with our lawyers and really understanding kind of the nuances of this space over time what about domicile what can you advise people you know based on your experience in terms of domicile yeah I'm not a lawyer but based on our experience I mean there's some great places over in in Europe you know Switzerland Malta Gibraltar we're down on the came in and also Singapore there's a you know these different legislature or jurisdictions are writing new law to support the effort and I think that's gonna continue to happen and I hope it happens in the u.s. too so we remove some of this nuance and gray areas that people can feel more comfortable operating and I think that's gonna happen hopefully soon in the next six months or so we'll see but as long as more guidance continues to come out I think we can operate or people can operate in the US I know a lot of people are moving offshore like we did so just something that's gonna it's a tough area right now well it gives you greater flexibility um and it like you said it's less opaque so you can have more confidence that what you're gonna do is on the up-and-up because as an entrepreneur you don't want you know I'm not gonna worry about compliance you just want to do your job and write great code and execute and build a company and so I mean I feel I don't know if you agree that the u.s. is a little bit behind you know this is kind of really slow to support entrepreneurs like yourselves like like us we'd like more transparency and clarity and you just can't seem to get a decision you're sort of in limbo and you got to move your business ahead so you make a decision you go to the Caymans you go to Switzerland you go to Malta and you move on right so and I think it's interesting too and you know a lot of what the SEC did in the beginning there's a ton of bad actors out there just as well and there's a bunch of good actors too so again if you yourself regulate you play you really understand what you need to do to be compliant you should be fine but again I think the flexibility you get right now is the more kind of defined law and some these other jurisdictions makes a lot of it yeah and I don't mean to be unfair to SEC they are doing a job and they need to protect the little guy and protect the innocent no question I would just like to see them be more proactive and provide more clarity sooner than later so okay last question the Seaport scene in Boston you know we always compare Boston and silicon silicon valley you can't compare the two Silicon Valley's a vortex in and of itself but the Boston scenes coming back there's blockchain there's IOT the Seaport is cranking you guys are in the Seaport you live down there what are you seeing would give us a what's the vibe like ya know watching me just passed about a month ago it may be less and as the great turnouts I spoke at a few events a few hundred people kind of it each one which is great and it's interesting you get a good mix of Enterprise people looking to learn and educate themselves in the space you see the venture capital side moving into the space and participating in a lot of these larger scale events and it's definitely growing rapidly in terms of the blockchain scene in Boston and I spent some time in New York and that's another great spot to and an even think places like Atlanta and I was down in Denver I did a big presentation down in Denver which was awesome and and now the coolest thing about blockchain is it really is global I spent a lot of time in Asia and in Europe and speaking over there the the pure at like the tangible energy in the room is amazing and it's one of the most exciting things about the industry many people that in the space know we're on the cutting edge here we're on the this is a new frontier that we're building along the way being part of that and helping define that is pretty exciting stuff that's cool you know I said last question I lied I forgot to ask you a little bit more about your your team maybe you could you talk a team your team your advisors maybe you could just give us a brief yeah okay there my co-founder and CTO we've been working together since I believe my sophomore year at college so it's been a while and he's their original crypto a blockchain guy and and pushed us in the spaces leading to the product development on that from in the top of that we have Craig Gainsborough our CFO I actually spent a lot of time at PwC he was the North America tax and advisory CFO over there Jalen Lou is the director of product marketing Kevin coos the head of product he worked he was nominated for a Webby and then we have our ops team Kyle who's a former campus - a complete business deaf guy over there that's working on us from some of the other side on the advisory team we have a really good team sunny luke from the CEO and founder of e chain just came on eileen quentin the president of Dragon chain foundation that was the blockchain company spun out of Disney and then David for gamma is the co-founder and had a product at autonomy that's an IOT protocol really really cool stuff happening over there new new new program coming about Rob Dulci as the president of Asia in North America which is the supply chain company and they've already successfully deployed a handful of use cases and mihaela dr. mahele Uluru who is really interesting and in this sense that she was working on decentralized systems before they were called blockchain she worked with the professor in Berkeley that defined decentralized in technology and she speaks in the World Economic Forum frequently and is really just a global presenter so we have we feel like we have a really strong team right now and we're actually getting to the point of scaling so it's gonna be exciting to start bringing in some new people and picking up the momentum it's super exciting well listen congratulations on getting to where you are and best of luck going forward best of luck with the raise and and solving the problem that you're solving it's it's an important one and thanks for coming in the cube of course thank you so much you're welcome all right thanks for watching everybody we'll see you next time this is david onte

>> Narrator: Live from Las Vegas, it's the Cube, covering IBM Think 2018, brought to you by IBM. >> We're back at IBM Think 2018. You're watching the Cube, the leader in live tech coverage. My name is Dave Vellante and I'm here with my co-host, Peter Burris. Ken King is here; he's the general manager of OpenPOWER from IBM, and Sumit Gupta, PhD, who is the VP, HPC, AI, ML for IBM Cognitive. Gentleman, welcome to the Cube >> Sumit: Thank you. >> Thank you for having us. >> So, really, guys, a pleasure. We had dinner last night, talked about Picciano who runs the OpenPOWER business, appreciate you guys comin' on, but, I got to ask you, Sumit, I'll start with you. OpenPOWER, Cognitive systems, a lot of people say, "Well, that's just the power system. "This is the old AIX business, it's just renaming it. "It's a branding thing.", what do you say? >> I think we had a fundamental strategy shift where we realized that AI was going to be the dominant workload moving into the future, and the systems that have been designed today or in the past are not the right systems for the AI future. So, we also believe that it's not just about silicon and even a single server. It's about the software, it's about thinking at the react level and the data center level. So, fundamentally, Cognitive Systems is about co-designing hardware and software with an open ecosystem of partners who are innovating to maximize the data and AI support at a react level. >> Somebody was talkin' to Steve Mills, probably about 10 years ago, and he said, "Listen, if you're going to compete with Intel, "you can copy them, that's not what we're going to do." You know, he didn't like the spark strategy. "We have a better strategy.", is what he said, and "Oh, strategies, we're going to open it up, "we're going to try to get 10% of the market. "You know, we'll see if we can get there.", but, Ken, I wonder if you could sort of talk about, just from a high level, the strategy and maybe go into the segments. >> Yeah, absolutely, so, yeah, you're absolutely right on the strategy. You know, we have completely opened up the architecture. Our focus on growth is around having an ecosystem and an open architecture so everybody can innovate on top of it effectively and everybody in the ecosystem can profit from it and gains good margins. So, that's the strategy, that's how we design the OpenPOWER ecosystem, but, you know, our segments, our core segments, AIX in Unix is still a core, very big core segment of ours. Unix itself is flat to declining, but AIX is continuing to take share in that segment through all the new innovations we're delivering. The other segments are all growth segments, high growth segments, whether it's SAP HANA, our cognitive infrastructure in modern day to platform, or even what we're doing in the HyperScale data centers. Those are all significant growth opportunities for us, and those are all Linux based, and, so, that is really where a lot of the OpenPOWER initiatives are driving growth for us and leveraging the fact that, through that ecosystem, we're getting a lot of incremental innovation that's occurring and it's delivering competitive differentiation for our platform. I say for our platform, but that doesn't mean just for IBM, but for all the ecosystem partners as well, and a lot of that was on display on Monday when we had our OpenPOWER summit. >> So, to talk about more about the OpenPOWER summit, what was that all about, who was there? Give us some stats on OpenPOWER and ecosystem. >> Yeah, absolutely. So, it was a good day, we're up to well over 300 members. We have over 50 different systems that are coming out in the market from IBM or our partners. Over 20 different manufacturers out there actually developing OpenPOWER systems. A lot of announcements or a lot of statements that were made at the summit that we thought were extremely valuable, first of all, we got the number one server vendor in Europe, Atos, designing and developing P9, the number on in Japan, Hitachi, the number one in China, Inspur. We got top ODMs like Super Micro, Wistron, and others that are also developing their power nine. We have a lot of different component providers on the new PCIe gen four, on the open cabinet capabilities, a lot of announcements made by a number of component partners and accelerator partners at the summit as well. The other thing I'm excited about is we have over 70 ISVs now on the platform, and a number of statements were made and announcements on Monday from people like MapD, Anaconda, H2O, Conetica and others who are leveraging those innovations bought on the platform like NVLink and the coherency between GPU and CPU to do accelerated analytics and accelerated GPU database kind of capabilities, but the thing that had me the most excited on Monday were the end users. I've always said, and the analysts always ask me the questions of when are you going to start penetration in the market? When are you going to show that you've got a lot of end users deploying this? And there were a lot of statements by a lot of big players on Monday. Google was on stage and publicly said the IO was amazing, the memory bandwidth is amazing. We are deploying Zaius, which is the power nine server, in our data centers and we're ready for scale, and it's now Google strong which is basically saying that this thing is hardened and ready for production, but we also (laughs) had a number of other significant ones, Tencent talkin' about deploying OpenPOWER, 30% better efficiency, 30% less server resources required, the cloud armor of Alibaba talkin' about how they're putting on their on their X-Dragon, they have it in a piler program, they're asking everybody to use it now so they can figure out how do they go into production. PayPal made statements about how they're using it, but the machine learning and deep learning to do fraud detection, and we even had Limelight, who is not as big a name, but >> CDN, yeah. >> They're a CDN tool provider to people like Netflix and others. We're talkin' about the great capability with the IO and the ability to reduce the buffering and improve the streaming for all these CDN providers out there. So, we were really excited about all those end users and all the things they're saying. That demonstrates the power of this ecosystem. >> Alright, so just to comment on the architecture and then, I want to get into the Cognitive piece. I mean, you guys did, years ago, little Indians, recognizing you got to get software based to be compatible. You mentioned, Ken, bandwidth, IO bandwidth, CAPI stuff that you've done. So, there's a lot of incentives, especially for the big hyperscale guys, to be able to do more with less, but, to me, let's get into the AI, the Cognitive piece. Bob Picciano comes over from running a $15 billion analytics business, so, obviously, he's got some knowledge. He's bringin' in people like you with all these cool buzzwords in your title. So, talk a little bit about infrastructure for AI and why power is the right platform. >> Sure, so, I think we all recognize that the performance advantages and even power advantages that we were getting from Dennard scaling, also known as Moore's law, is over, right. So, people talk about the end of Moore's Law, and that's really the end of gaining processor performance with Dennard scaling and the Moore's Law. What we believe is that to continue to meet the performance needs of all of these new AI and data workloads, you need accelerators, and not just computer accelerators, you actually need accelerated networking. You need accelerated storage, you need high-density memory sitting very close to the compute power, and, if you really think about it, what's happened is, again, system view, right, we're not silicon view, we're looking at the system. The minute you start looking at the silicon you realize you want to get the data to where the computer is, or the computer where the data is. So, it all becomes about creating bigger pipelines, factor of pipelines, to move data around to get to the right compute piece. For example, we put much more emphasis on a much faster memory system to make sure we are getting data from the system memory to the CPU. >> Coherently. >> Coherently, that's the main memory. We put interfaces on power nine including NVLink, OpenCAPI, and PCIe gen four, and that enabled us to get that data either from the network to the system memory, or out back to the network, or to storage, or to accelerators like GPUs. We built and embedded these high-speed interconnects into power nine, into the processor. Nvidia put NVLink into their GPU, and we've been working with marketers like Xilinx and Mellanox on getting OpenCAPI onto their components. >> And we're seeing up to 10x for both memory bandwidth and IO over x86 which is significant. You should talk about how we're seeing up to 4x improvement in training of MLDL algorithms over x86 which is dramatic in how quickly you can get from data to insight, right? You could take training and turn it from weeks to days, or days to hours, or even hours to minutes, and that makes a huge difference in what you can do in any industry as far as getting insight out of your data which is the competitive differentiator in today's environment. >> Let's talk about this notion of architecture, or systems especially. The basic platform for how we've been building systems has been relatively consistent for a long time. The basic approach to how we think about building systems has been relatively consistent. You start with the database manager, you run it on an Intel processor, you build your application, you scale it up based on SMP needs. There's been some variations; we're going into clustering, because we do some other things, but you guys are talking about something fundamentally different, and flash memory, the ability to do flash storage, which dramatically changes the relationship between the processor and the data, means that we're not going to see all of the organization of the workloads around the server, see how much we can do in it. It's really going to be much more of a balanced approach. How is power going to provide that more balanced systems approach across as we distribute data, as we distribute processing, as we create a cloud experience that isn't in one place, but is in more places. >> Well, this ties exactly to the point I made around it's not just accelerated compute, which we've all talked about a lot over the years, it's also about accelerated storage, accelerated networking, and accelerated memories, right. This is really, the point being, that the compute, if you don't have a fast pipeline into the processor from all of this wonderful storage and flash technology, there's going to be a choke point in the network, or they'll be a choke point once the data gets to the server, you're choked then. So, a lot of our focus has been, first of all, partnering with a company like Mellanox which builds extremely high bandwidth, high-speed >> And EOF. >> Right, right, and I'm using one as an example right. >> Sure. >> I'm using one as an example and that's where the large partnerships, we have like 300 partnerships, as Ken talked about in the OpenPOWER foundation. Those partnerships is because we brought together all of these technology providers. We believe that no one company can own the agenda of technology. No one company can invest enough to continue to give us the performance we need to meet the needs of the AI workloads, and that's why we want to partner with all these technology vendors who've all invested billions of dollars to provide the best systems and software for AI and data. >> But fundamentally, >> It's the whole construct of data centric systems, right? >> Right. >> I mean, sometimes you got to process the data in the network, right? Sometimes you got to process the data in the storage. It's not just at the CPU, the GPUs a huge place for processing that data. >> Sure. >> How do you do that all coherently and how do things work together in a system environment is crucial versus a vertically integrated capability where the CPU provider continues to put more and more into the processor and disenfranchise the rest of the ecosystem. >> Well, that was the counter building strategies that we want to talk about. You have Intel who wants to put as much on the die as possible. It's worked quite well for Intel over the years. You had to take a different strategy. If you tried to take Intel on with that strategy, you would have failed. So, talk about the different philosophies, but really I'm interested in what it means for things like alternative processing and your relationship in your ecosystem. >> This is not about company strategies, right. I mean, Intel is a semiconductor company and they think like a semiconductor company. We're a systems and software company, we think like that, but this is not about company strategy. This is about what the market needs, what client workloads need, and if you start there, you start with a data centric strategy. You start with data centric systems. You think about moving data around and making sure there is heritage in this computer, there is accelerated computer, you have very fast networks. So, we just built the US's fastest supercomputer. We're currently building the US's fastest supercomputer which is the project name is Coral, but there are two supercomputers, one at Oak Ridge National Labs and one at Lawrence Livermore. These are the ultimate HPC and AI machines, right. Its computer's a very important part of them, but networking and storage is just as important. The file system is just as important. The cluster management software is just as important, right, because if you are serving data scientists and a biologist, they don't want to deal with, "How many servers do I need to launch this job on? "How do I manage the jobs, how do I manage the server?" You want them to just scale, right. So, we do a lot of work on our scalability. We do a lot of work in using Apache Spark to enable cluster virtualization and user virtualization. >> Well, if we think about, I don't like the term data gravity, it's wrong a lot of different perspectives, but if we think about it, you guys are trying to build systems in a world that's centered on data, as opposed to a world that's centered on the server. >> That's exactly right. >> That's right. >> You got that, right? >> That's exactly right. >> Yeah, absolutely. >> Alright, you guys got to go, we got to wrap, but I just want to close with, I mean, always says infrastructure matters. You got Z growing, you got power growing, you got storage growing, it's given a good tailwind to IBM, so, guys, great work. Congratulations, got a lot more to do, I know, but thanks for >> It's going to be a fun year. comin' on the Cube, appreciate it. >> Thank you very much. >> Thank you. >> Appreciate you having us. >> Alright, keep it right there, everybody. We'll be back with our next guest. You're watching the Cube live from IBM Think 2018. We'll be right back. (techno beat)

>> Announcer: Live from Madrid Spain, it's theCUBE covering HPE Discover Madrid 2017. Brought to you by Hewlett Packard Enterprise. >> We're back. This is theCUBE that you're watching, the leader in live tech coverage. We're at HPE Discover 2017 in Madrid. My name is Dave Vellante, I'm here with my co-host for the week, Peter Burris. Peter, it's been great working with you this week. >> Indeed, it's been great. >> We're winding down, and we're really excited to have Ric Lewis, >> Great ideas. >> Senior Vice President and General Manger of the Software Defined and Cloud Group. Many time CUBE guest with HPE, and Jeff Wike of Dreamworks. CTO, thanks for coming on. >> Yeah. Thank you. Thanks for having me. >> Great to see you. You're welcome. Been a good week? >> It's been a fantastic week. >> Things are coming into focus? >> They are. >> You killed it on the keynote, how are you feeling? >> Feeling really good, feeling really good. I mean, the momentum in the software defined and cloud arena is just fantastic. You know, there were times when I used to visit with you guys and we were only talking about what's coming in the future. Now we're talking a lot about what we have, what customers are buying, where we have momentum. And still introducing new things, so it's just a whole lot of fun. >> Jeff, Senior Vice President, CTO, can we talk a little bit about your role? What the scope is? >> Sure. Sure, so Dreamworks Animation, you may have heard of it. >> Yeah. We do we make animated films. >> Good friend Kate Swanberg's been on a number of times. >> Kate's, love her. We make animated films, we do a lot more than that. We're a digital content creation company. So we, we're the largest TV animation studio in the world. We're doing theme park ride work, cause we've got, we're now under NBC Universal. So we're doing a lot of projects, it's a very busy time for us. >> So, Synergy, we talked about Synergy a lot, there's nothing >> Yeah. >> like Synergy we've heard. >> Yeah, yeah. >> Fluid pools of infrastructure. >> Yeah, it just gets better. >> Wait and see and so, what can you tell us? How's the momentum? >> Yeah let's talk a little bit about that. So the momentum on Synergy is fantastic. We started shipping in volume at this conference last year, basically December of last year. And the response has been fantastic. We've looked at Momentum for new infrastructure plays. You know if you look back at our history, whether it was the C7000 or whether it was UCS from Cisco or whether it was VCEs built on UCS, Nutanix. If you kind of look at the first year of a new infrastructure play, Synergy looks like it's the fastest growing thing ever. It's just fantastic, really growing for us. We have over 1100 customers on Synergy now. You know, and that's in 11 months of shipping. And the business, it just continues to grow quarter by quarter. Just really thrilled with the progress there, so happy. >> And you guys are customers? >> We're big customers, if we're not the biggest customer, we're certainly the biggest fan. >> One of the biggest, one of the biggest customers, maybe the biggest fan. >> Certainly the biggest fan. >> Okay so Jeff, tell us, take us back to sort of pre-Synergy, you know, what was it like before and after and what has it done for your business in particular? >> Well one of the things that that we face going forward is we developed, in our infrastructure, and inner data center, we do a lot of rendering to make a movie. That's our largest high performance compute. You know, 80 million render hours, CPU hours to make one of these films. And we're making a lot of them at the same time. We really defined that work flow, and how we optimize the data center hardware to be able to go through that work flow and be able to be as efficient as possible. The issue came with we have a lot of other projects that are coming in, and since we are now under NBC Universal, there's a lot of other work that's happening there. And also, different types of media that's coming, you know, around the corner. And we want to be able to prepare for that. What we would have done traditionally would be to buy to peak, you know because it is rather cyclical, and that's what we would do that on prem, peak. But if we had a special project, we might buy or segment a portion of that and say, you know, this is for this purpose. This is for that purpose, but that's very inefficient. So with Synergy, the beauty of it is we can purchase you know that hardware, but then if we want to be able to use it for another project, we can do that. And we can do that very very quickly. >> You said you repurpose that across your application portfolio. Or your project portfolio. >> Yeah. Yeah, it gives us, I like to say it future proofs us. Because now no matter what the parent company or our own creative ambitions are, we can handle that. We can't say no, well we never say no. We usually say not right now, or wait a couple of weeks or a couple of months to be able to provision that. And now it's, it's instantaneous. >> And I know what Ric's answer would be to this, but I want to hear from the customers. Is this really different than other products that you've experienced. >> It's totally unique. We haven't experienced it before. And I'll give you, I'll give you a little example. We just got our order. We got about 200 servers of Synergy that arrived a couple of months ago. And within seven working days, we were using it in production. And I just want to say, we took, I don't know if I told you this story, but we were able to provision all of that from the time we mounted in the racks within five hours, which is incredible. It would have taken us easily three weeks before. In fact, it took us longer to take it out of the cartons than it did to provision. >> Well, so let me see if I... You're talking about maybe 200 servers. You're probably talking about 8,000 individual tasks configured. To get it done in five hours you probably perform what, 40, 50 tasks? Administrative steps? >> By the way, first time doing it. And our engineers were saying, we could've used more parallelism. We could've done it faster. You know, it's almost a challenge to see just how easy you can do this. >> But I got that right? Is it really like 98 percent reduction in the administrative tasks? >> Absolutely. >> Really? >> That's incredible. >> It is. >> Huh, alright. >> That's before you start flexing work, flexing resources against different workloads and dynamically reprovisioning. This is just provisioning the first time. But it, if you think about it, if you're gonna do it dynamically, it can't take forever, so you've gotta make it, the first time it's gotta be super fast. >> Okay. >> So, I have to admit I'm a little stunned, I didn't know that. So, and as you said, the whole point is that you can reprovision >> Yes. >> Over and over. Which means that the... There's something in economics and technology that's known as an asset specificity. And an asset has high specificity when you buy it and can appropriate it to a specific purpose. And about the only thing in tech that makes something an asset specificity is the administrative tasks of changing it to prepare it to do something else. And you just told me that I can remove nearly 100% of the transaction costs associated with taking an asset from this and applying it to that. >> If you're gonna destroy silos in the data center, that's what you have to do. >> But that's... >> Right, so silo is this asset specificity. If you can repurpose it immediately. >> So I'm excited, that's my second question. How did your people respond to this? Because I talked to a lot of other CIOs that say one of the biggest challenges I'm having, or CTOs, one of the biggest challenges I'm having is I'm able to converge hardware, I'm able to converge to some software, I'm able to converge Administrative tasks, but my people don't like converge. What, they don't like to converge. How are you walking your people through some of these changes to liberate these opportunities? >> Well we've been moving toward, from more traditional, we'll call it IT for now. From traditional IT to dev ops environment and, you know what, it's change. So we've been bringing people along in that you know, to, and some people adapt to it. They say wow this is gonna be great for my career. And engineers want to always use the new stuff, so from that aspect of I know how I work, and I know what I do, to here's a better way of doing it to be more automated, it's been a good experience for people. And you know what, the chance of human error in configuring things... If I look to my long history at Dreamworks, 21 years, I look at any down time we've had or any problems, 90% of that has been from misconfiguration. And it's usually from somebody fat fingering, you know a parameter in the set up of the servers. And now, that's virtually eliminated. >> Did you have to go through some kind of organizational, internal sort of discussion, transformation, whatever you want to call it to actually get to the point where you could buy this way, buy a sort of single SKU of Synergy? Because you maybe previously you were buying bespoke, kind of roll your own components. A little server here, maybe some storage over there, maybe some networking here. Now maybe it's all HP that made it simpler, but you probably had specialist in each of those areas, did you not? >> We did. >> How did you deal with that organizational friction? >> You know, that was an issue as and by the way, there's so many, there's so much technology that's being developed some of it open source, some of it in this partner ecosystem that you have. And trying to stay abreast of that has been a real challenge. And one of the things that we always dreamed of is wouldn't it be nice if there was one way that you could control that. The single pane of glass, which is you know, to be able to have an API layer that everybody could hook in to. I think you've got a company like Hewlett Packard Enterprise that has that dominance in the market place to be able to dictate, I'm using that word. >> Yeah. >> Maybe dictate isn't the right word. >> Offer. >> Offer. (group laughing) >> That's the word we use. Enable. >> Enable, you know those APIs. And all of those are being developed you know almost in parallel. >> Yeah, yeah, yeah. >> So this stuff is really coming in. Now we have our own... We're a snowflake like everybody else is to your point. And what we've done is we brought in the Pointnext team to go in and write those northbound APIs so that we can hook in to one view. To be able to manage all of our legacy, I'll call it legacy, our previous infrastructure along with you know, the new tech that we're buying. So that it makes it easy to manage. >> They made it match the composable API that we put into Synergy. It's natively integrated. All the ecosystem partners are adapting to it. And they said we'll just use that as our standard to even manage our legacy infrastructure. Plus, since Oneview runs on legacy infrastructure, all of the HPE stuff, it just adapts like that. So it's been a very good, good project. >> So you've got a lot of experience with this now. Can you share with, maybe you can quantify it, maybe you can't, but even subjectively the developer impact or the animator impact, the business impact to Dreamworks? >> So the biggest impact... Well I have three things that are my, actually I got this from Meg Whitman, I had a list of 12 objectives for the studio for technology and she said at one of the CIO summits, you've gotta have three. So I said okay, I've gotta pare it down to three. And one of those is provide the technology, the software and infrastructure to meet the creative needs. The second one was innovate for competitive advantage. And the third one was drive efficiency into operations. And if you look at what Synergy provides, it hits every single one of those. So we've actually, you know, over the past year or two, we've actually reduced the number of people that we have maintaining our infrastructure, which is amazing if you consider the fact that this year we doubled the size of our infrastructure. In what other business, in what other area can you actually reduce the amount of people that are maintaining something while you're doubling the amount that you're maintaining. That never happens. And I think it's because of this software defined infrastructure and the fact that you can write these recipes or profiles, whatever you want to call them, personalities. >> Yep, yep, yep. >> To be able to... And test them and harden them. And by the way, that reminds me, one of the things I really like about this is our ability to do proofs of concept, to try different workflows and all that without having to take away resources from the main thing that we're doing which is the artistic community. So we can actually say, you know what? We're gonna go in, reimage these servers. We're gonna do that at night to run this test, in the morning they're back, they're back in the pool. And that's an amazing thing. >> That's dynamic provisioning. No one else can dynamically provision. >> Yeah. >> All the converge systems, all the hyper converge, they're provisioned a certain way. They run VMs a certain way. They stay that way for their lifetime. This stuff dynamically reprovisions, and you guys, you're not even talking about kind of doing containers with VMs and containers with your bare metal, you can dynamically reprovision across that as well. >> Yeah, what he said. (laughter) >> Listen, we're just getting started so just relax, okay. These guys are telling me we gotta wrap. We're not gonna wrap. >> No. >> We haven't even gotten to One Sphere yet. >> We have other topics. Exactly. >> So let's get to One Sphere. >> Yeah. >> Yeah I want to talk about One Sphere. But I do want to say. >> Go ahead, last thought. >> One more thing, so you talked about artists, but the other part of it is for developers so one of the things we don't want the engineering teams to be a hindrance to the developers. Because they want to be able to move quickly, they want to be able to be assessing, and I think one of the things that's not just an impact on our artists, to be able to do these new projects, but also it makes our developers more efficient. They don't have to wait. >> Yeah. >> Okay, great. Now let's talk multi cloud. >> Yep. >> A lot of complexity, the more things get simple, the more complex they seem to get. So, One Sphere. You guys announced yesterday. >> Yeah, so. A core pillar of the HP strategy, make hybrid IT simple, right. And you can see from this conversation we're making hybrid IT simple on-prem. Not only do we have Synergy, but we have a fantastic offering in our Simplivity space. And that platform's over 2,000 customers and growing like crazy as well. But after we did that, we said look, we've got fantastically simple virtualization clusters in Simplivity, we've got great dynamic reprovisioning and composable infrastructure, but customer are not... That's part of their hybrid IT problem, that's the on-prem part. They're also wrestling with I've got multiple cloud instances, I need to get insights into where I'm spending my money, where workloads are deployed and all that. So we started this program, HPE OneSphere. We've had it going for almost three years. We had a small team on it early on. We ramped up the staffing a couple years ago. And what it really does, it's pretty simple. It allows you to build clouds, deploy apps, and gain insights extremely fast. So it's designed for IT ops to be able to build and deploy a private cloud as fast as they can and assemble that with their public cloud assets. And provide one place to look at all of those. For developers, it provides a common multi-tenant environment that has all the services and tools they need to be able to deploy an application whether it's on-prem or off-prem, and you can choose, you can build applications that have some of both inside that developer environment. And then for the business, it shows insights into where's the money being spent? Where are those workloads running and what's it costing me? So, think of it almost as composable at that next level where it's not just resources within chassis, now it's resources across the hybrid IT estate. It actually is public cloud assets from any of the public clouds, whether it's AWS, Azure, Google, Cloud28+, as well as your private cloud assets. And it automates the life cycle stuff that we were just talking about through this application into OneView. It's a SaaS environment, so actually OneSphere is software as a service. It lives in the cloud, it's a subscription that our customers buy, and it does all of this capability to simplify their hybrid environment and taps into the capabilities we just talked about. It's fantastic, nobody has anything like it. >> Okay well we've heard that before, but now... >> Exactly. >> You're putting your money where your mouth is. >> So I was right on that one. >> Okay but it's early days for OneSphere. >> Okay. >> And your private cloud is what we call a true private cloud. >> Which you said on stage yesterday. >> I did that's exactly right. >> It's evidence by your ability to reduce staff to manage infrastructure. >> It's a con experience wherever the data requires is how we put it. >> Yes, yes. We want the simplicity of management and the availability of apps that you get in public cloud in the private cloud. >> And the pricing. Yeah? >> Well, yeah, well... No, cause it's actually more expensive to go public cloud. >> I mean pricing models. >> Oh yes, yeah. >> The consumption is what you're basically talking about, yeah. >> And so you, Jeff you guys are OneSphere or OneSphere betas? >> Yeah, you bet. >> So what were you trying to learn? What were you kicking the tires on, testing? Where'd you focus? >> We, you know, if we look at the future, we're not gonna be on-prem forever, and I certainly don't want to be on-prem forever, I want to take advantage of flexing to public cloud, but again, for our films, you know, we want to be able to provide the producers of those movies, what is that gonna cost me? What is that, how can I tell you what that costs? And where can we move as we start to do more different types of projects? Which ones should go to the public cloud? Which ones should stay inside? And be able to understand that. The other thing that made us nervous about public cloud. Was what they call the zombie cloud instances, you know where you went in, you provision something and then you forget about, and you, but you're paying, you know. And that's, a lot of money is made. >> Kind of like app subscriptions. >> Group: Yes, exactly. >> I'm still paying for that? (laughter) >> Exactly but this gives you all of that... >> 4,000 dollars a month. >> A little different right. >> Or 15,000 a month. (laughter) >> Yeah, that's for sure. That visibility is something that all... We talk about it, CFOs hate this thing... Some of the consumption model is shifting from cap ex to op ex, but CFOs hate surprise op ex. And that's where they're actually surprised by oh my gosh look at that bill. Well this provides visibility into all of those assets, whether they're on-prem or off-prem and what they're costing you. And it's always up to date, and it's always consistent across your entire farm, so you can choose and say that's costing me too much, I want to move those apps over here. And immediately do it. And for a lot of our customers, they're over-provisioned so they have spare capacity on-prem they're not taking advantage of. Why not use some of that and it's instantly provisioned. >> And that's where you initially, anyway, see the business value of OneSphere. >> Well, look, it's OneSphere to rule them all. And I believe whether it's private, public, you know we really want to have what is my total resource availability? So in the future, we never say no anymore. Really, we can tell them how much, but you don't have to say no. And the other thing is we can do this stuff instantly. So, we don't even say when, we just go now here's what you have to pay if you want to do it, we can provide those options. It's a new world. >> I love the demo of, I don't know if you guys saw it, there's a demo with Pong, you know, it's the IT guy of the past. >> Yeah the guy saying no. >> And then they made it vertical. It's the IT guy of the future. So, alright my last question. What cool movies can we anticipate? What's coming? >> Well you know what, How to drain... How to Train, how to drain your tragon I was gonna say. (laughter) How to Train Your Dragon 3 is our next film out and it's gonna be unbelievable. >> I'll bet. >> So my last question. Am I gonna have to continue to sit through 15 minutes of IT credits at the end of future Dreamworks movies as a consequence of Synergy? >> There's less, cause there's less resources required to manage your Synergy hardware. So it's less people. >> I know you don't sit through the credits. (laughter) >> I do. (laughter) I love credits. Alright guys, thanks very much for coming on. >> Thank you. >> It's been a great pleasure. >> Thank you, always fun. >> Alright keep it there everybody, Peter and I will be back to wrap up HPE Discover 2017 from Madrid, you're watching theCUBE. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCUBE. Covering HPE Discover 2017. Brought to you by Hewlett-Packard Enterprise. >> Okay, welcome back everyone. We are here live in Las Vegas for SiliconANGLE Media's, theCUBE's exclusive coverage for three days for HPE Discover 2017. We're on day three, down to the wire here. I'm John Furrier with SiliconANGLE with my co-host Dave Vellante, my partner in crime with Wikibon. Our next guest, Ric Lewis. Software Defined Cloud Senior Vice President, President and GM of HPE, welcome back to theCUBE. >> Thank you. >> And Kate Swanborg, Senior Vice-President Tech Communications and Strategic Alliances, DreamWorks Animation. Welcome back as well. >> Thank you. >> John: Great to have you guys back. >> It's good to be here. >> So obviously DreamWorks, you guys are a big customer, Ric you are now leading up the team for Software Defined infrastructure, as we call it programmable infrastructure, a lot of great things. >> Ric: Yeah. >> Synergy we talked heavily about last year. >> Ric: Yeah. >> I kind of was geeking out with you on that in terms of all that programming ability and automation. Meg story this week was simplifying hybrid IT, which is the key part of where Software's coming in. >> That's exactly right. >> And so we got DreamWorks here, what's your vision in how that's going to happen? How do you take that simple message and put it into practice? >> Yeah so, we're completely about making hybrid IT simple, and we have three primary vectors that we're driving in order to make that happen. The first is our hyperconverged appliances that we deliver, and the second is HPE Synergy, our composable, and the third is our hybrid IT management stacked software that we have. And we've got momentum across all of those. In Hyper Converged, you guys know we acquired SimpliVity, it closed in February. Got a lot of customers on that. We had Red Bull on-stage here at Discover talking about their use case of that in their racing. It was a packed house, people completely interested in all the things we're doing in hybrid IT. That's SimpliVity. Synergy, we now have almost 400 customers that have adopted Synergy. We started shipping in volume in December, and DreamWorks Animation is one of those customers, and real excited for you to hear a little bit about how they're using it, but we had, I think we had around 10 customers from Synergy across all kinds of verticals and use cases, including service providers that were on-stage here. And the final thing is our hybrid IT management stack, a program that we introduced here at Discover called Project New Stack. So, that's what's going on in Software Defined & Cloud, it's a lot right now. >> And we had a SimpliVity customer on by the way, they were really glowing. >> Yeah. >> Great to see that happen. >> That was a great story. >> Great story, Kate, so DreamWorks, you guys have a business, you've got to put a product out there and so you got to look at technology, make it work for you, and sometimes you got to get in the weeds, there's pieces and pieces, at the end of the day you got a product to deliver. How are you guys taking some of the things that are coming out at HPE and putting them into action? What are some of the things you're doing? >> Well, I think one of the things that is often surprising to people is just how much technology we consume to make a CG feature animated film. These films take 80 million compute hours to render the images, petabytes of storage and we're typically working on five or six active films in production because they take us four or five years to make. And so we want to be able to have the capability of releasing two or three films a year, we must have simultaneous production. But of course, not all of the productions are exactly the same, and we've also got other media opportunities, whether it's television or theme park. And so, what's critical to us is that we're actually able to provision the right amount of digital resource to the right project quickly and easily so that as those creative inspirations are growing and burgeoning at the studio, we've got the resource behind it in an effortless fashion. >> And how are you making that happen with the Synergy for example, because last year we were looking at thinking well this has got a lot of potential. I mean you can do it through the orchestration, making the management work kind of takes that, abstracts away a lot of the complexity. How are you guys dealing with that, I mean how have you put that into action? >> Well, we've been working within a hybrid environment for years now, so the idea of a hybrid environment isn't new to us. The key however, is that it's labor intensive. It's time-consuming. In order to get all of the right configurations of the networking and the storage, the compute to actually work in a realtime environment for our artists, that has taken us an enormous amount of effort over the years. What we're looking for in the Synergy deployment is to reduce those weeks down to days and those days down to hours. Once we're able to do that, our engineers can go off and focus on the niche technology solutions that actually matter to the artists. And that's where we want to get the business benefit. >> And with Synergy, compute, storage and fabric all managed under the same management domain. >> That's right. >> Single API that you can get access to all those resources, so it makes it super easy. It's the world's easiest way to do infrastructure as a service, it's built into the platform natively. >> That's right, and one of the things that's been so impressive to us is that we've been working with the Pointnext team to come in and actually configure this for our environment. Everybody uses a high-performance compute environment, but nobody's is exactly the same. The configure ability of this and the customability of this to our environment has been critical, and we've seen incredible benefits from that. >> So Ric, we kind of pushed you in theCUBE last year, cause you were saying "there's nothing like this in the marketplace". We said, okay define what's different. (John laughs) One of the things you touched on was the fluid pools of infrastructure. >> Yes. >> And Kate, what you just described is bringing technology to different digital teams. >> The dynamicism if you will. >> Absolutely. >> Being able to dynamically configure the thing, yes. >> So, let's test it. I mean, it sounds like that's exactly what you're doing, and how is this different than the infrastructure that you used to have? >> So, the reason that it's different is that we've got, we've got a simply said, a single infrastructure. We've got a compute farm, we've got storage, and historically what we had to do was actually partition off certain pieces of that for certain productions in order to protect their resources. The problem with that is that any given day, particularly in a creative environment, maybe they're using all of it, maybe they need more, maybe they need less. The challenge is is that historically if they needed less we can't reprovision that to another production in order to take advantage of their inspiration and their business motivations. Now we can. Now we have the opportunity to actually have the infrastructure be as dynamic as our creative environment, and that's saying a lot. >> And you can reconfigure those resources three clicks, five minutes, you literally can deprovision -- >> Kate: That's it. >> So the old way they're like bitchin and moanin, where's the servers? >> Absolutely. >> Right. >> And running around scrambling. >> They're on order. (all laugh) >> Six weeks. No this what we're talking about. >> Yeah. >> This is about speed, right? I mean this is -- >> It absolutely is. >> Alright, so I want to ask you a question about the HPE event. You mentioned you're here. So, a lot of people go to these events and they try and extract all the action. You've heard a lot of firsts, last year was Synergy first, big claim there. We're hearing some security stuff with servers here. >> Ric: Yeah. >> As a practitioner that comes to these shows, what's your strategy when you come to an event like HPE Discover, and obviously the schmooze is going on and getting wined and dined by HP, a big customer, but like when you go in there, what are you looking for, how do you connect the dots, what tea leaves do you read, what's your strategy? >> Well, I'll tell you, one of the things that really interests me about Discover is we've got a deep partnership with Hewlett-Packard Enterprise. We're talking to Hewlett-Packard Enterprise all the time. So we might actually think that we know what's going on. It's not true, there's so much innovation happening that when we bring our team to this show, we learn things that could really help our business. I'll give you a great example, so we learned this week about SimpliVity. Now, we had sort of heard about it, but we had not taken our time out of our schedules to really understand how that could help our VM environment. Our team's sitting in one of the panels this week, and he's texting other engineers on our team going "We have got to look at this next week at DreamWorks Animation". That's the kind of environment this is. I'll tell you something else, New Stack, we're going to lean heavy into New Stack because we believe that the innovation that we're seeing in that space is really, finally going to deliver on this promise of cloud that's been out there. >> What specifically about New Stack do you like? I want to just double down on that. Is it the rule of your own, is it the flexibility, what's the big thing there? >> Well, again this is one of those things where our team today is actually writing code and creating architectures that are sort of New Stack-like, but we're having to do it, we're having to invest our own time. It's trial and error, some of the things work some of the things don't, and that time is not being spent focused on our animation productions. The fact of the matter is, here's Hewlett-Packard actually doubling down and making sure that there is going to be a robust solution that works, that we can bring into our environment. >> We're in enterprises across the world every day. We're having these conversations, and most enterprises are doing kind of a roll-your-own cloud kind've thing. >> That's right. >> They're playing with OpenStack, they're playing with Kubernetes, they're playing with all these tools, they got a bunch of custom code, but we're really what we're trying to do with New Stack is take the best of what they're all trying to do, constrain that down, take our standard Software Defined infrastructure as the base, put a stack on top of that that they can count on to do a private cloud with bridge-to-hybrid capabilities, that's standard, that ships, that delivers and has updates, so that they're not messing around with it. Their developers don't want to spend time doing that, they just want to have a private cloud installation that has hybrid capabilites and have it installed. >> This is super relevant, this is super relevant, and we call you a tech athlete because you want to go out there and deliver value to your group and actually build products, right? >> That's right. >> The film. But Dave's team just put out the True Private Cloud Report which shows on PRAM, cloud-like environment, $260 billion dollar TAM, but the notable thing is that the labor costs were non-differentiated spend is going up by a $150 billion shifting in 10 years. >> Yeah. >> That's exactly the point here that you're talking about, is my guy's aren't working on the product that they need to be building. They're doing the R&D, so the OpenStack and all these things you're talking about, they're doing the R&D. Here, you're doing the R&D, delivering the product to the customer. >> Well and when we deliver that, we're still going to leverage all of those technologies. OpenStack is a key part of New Stack. Kubernetes is a key part of New Stack, but what we're doing is pulling that together so that they don't have to curate their own private cloud. >> Kate: That's right. >> We create that, deliver it in a way that's an appliance-like way, just like we deliver Hyper Converged today, in a controlled plane that manages that hybrid IT estate and gives them visibility into public cloud uses and private cloud, and it's really going to help them a lot, and it's going to help a whole lot of other customers cause we're making it standard and easily deployable. >> Well, we've seen this story unfold over this decade, where the corner office has said I don't want to spend money on that caching and provisioning. Okay, so go to the cloud. And then IT said, well, eh, we can't do that. (laughs) Okay, and so they get in with Hewlett-Packard Enterprise and others say what's the answer? Okay, but what you've described is this horizontal infrastructure capability that you can throw any workload at. >> That's right. >> And so my question is, what does it mean for the business? Does it mean you can do things faster, you have happier animators, you can do more movies, what does it mean? >> I think it means a couple of things. First of all, opportunity cost. In our business, a new opportunity for a creative endeavor, that comes up all the time, and the key is is that you want to be able to explore that as quickly as possible. Creative ideas work out sometimes, sometimes they don't, but they key is is that if takes you time and effort and money to just explore it, you've got an opportunity cost you don't want. >> Yeah, yep. >> Something like Synergy will allow us to provision resources to new ideas and new potentials quickly enough, easily enough, and at a cost-effective measure, so that we can actually determine which creative endeavors are going to work more quickly in our environment. That's a huge deal. >> So you were missing opportunities because of the infrastructure limitations, is that right? >> That's -- >> The mockups and everything have to get done. >> That's right! >> All the CG work. >> Again, when our filmmakers have a new idea for a new sequence, a new character, those types of characters, they take tremendous amounts of resources. I often talk about the dragon in Shrek. Back in 2001 we released Shrek, and it had this beautiful, huge pink dragon in it. And she was fantastic, but frankly she was so complex and so computationally heavy, we actually had to cut her out of parts of the film because we couldn't produce the shots she was in. Fast forward a few years, and we decide to make a movie called How to Train Your Dragon that's nothing but dragons. The key is is that we never want to be in a position again where we're tabling a great creative idea because we can't resource for it. And solutions like SimpliVity and Synergy and particularly where we're going with New Stack and the ability to actually harness the cloud without having to do all the work ourselves, that's going to bring that potential to reality. >> John: And then you know, your application in this opportunity cost is for your business. Other companies have apps, right? So their opportunity costs are very similar. >> That's right. >> John: This is the classic how shadow IT was born. >> Oh, yes! >> And people want to experiment, show proof of concept. Not a PowerPoint, an actual demo of real working product. It may not have the scale there, but you get to that point of where it's workable. >> Look, every business is facing some element of this right now, and I will tell you the other reason of the two reasons that I think that this is going to make a difference. It's future-proofing our environment. >> Ric: Yeah. >> The world is so dynamic right now, things are changing so quickly. Even in our environment with media and entertainment, the world of what people want to consume and how they want to consume it and the nature of how we're looking at innovation in both filmmaking techniques, as well as new media opportunities, the key in all of that is is that we have to be dynamic in order to be future-proofed. These types of solutions give us the confidence that we're actually putting the money in the right place. It's an investment in our future. >> Earlier you mentioned Pointnext services, and the narrative from Hewlett-Packard Enterprise is my inference is it's more cloud-like. Do different types of business models. Are you seeing that? I mean, is it more than just a new name, a new brand, are you starting to see an evolution of the way in which you engage with Hewlett-Packard services? >> We absolutely are, and it's one thing to talk about strategy, but at the end of the day, you don't call up your technology and have a conversation with it, you call up people. And what we're seeing is that Hewlett-Packard Enterprise is investing in a level of expertise within the Pointnext services organization that is unparalleled. That is a massive change over the course of the last five, six, 10 years. These folks are coming into our environment now and we're finding that we are inspired by their strategies. We're not having to teach them about our business, they're actually coming in with all of these other learnings that they've gotten from all of these corporations and they're looking at our ambitions and going hey, we think we've got some ideas here. I'll tell you, our engineers are hard to impress. >> That's the truth. >> They are used to, what was your phrase, rolling it on their own. >> Yeah. >> They are used to being responsible, and they have very little tolerance for actually giving other people time within our organization. Pointnext has blown them away. We could not be doing the work that we're doing on Synergy as quickly and as effectively, installation and strategy around that without the Pointnext team. >> Well, that's the proof, that is the proof in the pudding in my opinion when your people who are, I won't say cocky, but they're kind of, sounds like they're pretty cocky. (laughs) >> Ric: Confident. >> But that you're in a, you're in media entertainment. It is one of the most disruptive, being disrupted markets right now. Smart Cities, IoT, media entertainment it's, you're the leading trend in IT right now, media entertainment. >> And in our team, there's simply no tolerance at DreamWorks Animation for technology getting in the way of the business. The fact of the matter is technology always has to be enabling the storytellers, enabling the filmmakers, enabling the business and ambition. And the key is is that our engineering team, they feel responsible to that. One of the things that we're finding with the new Hewlett-Packard Enterprise, the Pointnext team, Ric's team with the Synergy deployments, is that we actually feel like we've got a partner that can up our own game. >> John: Good. >> And we do deep beta programs with them on everything that we're doing to make sure that we're meeting that next generation of what they need. It's a fantastic partnership. >> Well Ric, congratulations on the success, and Kate thanks for sharing all the great stories and your experience DreamWorks Animation. Great to see that trend, again media entertainment, you guys are doing great stuff. We're doing our share with digital TV here, we're not a, we live on the edge of the network with theCUBE here at HP Discover. With DreamWorks Animation, I'm John Furrier, Dave Vellante, stay with us for more day three coverage here in Las Vegas at HP Discover. We'll be right back. (tech music)