>>And good afternoon. Welcome back here on the Cub as to continue our coverage at aws Reinvent 22, win the Venetian here in Las Vegas, day two, it's Wednesday. Thanks. Still rolling. Quite a along. We have another segment for you as part of the Global Startup program, which is under the AWS Startup Showcase. I'm joined now by Vink at Viera, who is the CEO and co-founder of R Set. And good to see you, >>Sir. Thanks for having me here. Yeah, >>No, a real pleasure. Looking forward to it. So first off, for some of, for yours who might not be familiar with Roxette, I know you've been on the cube a little bit, so you're, you're an alum, but, but why don't you set the stage a little bit for Rock set and you know, where you're engaged with in terms of, with aws? >>Definitely. Rock Set is a realtime analytics database that is built for the cloud. You know, we make realtime applications possible in the cloud. You know, realtime applications need high concurrency, low latency query processing data needs to be fresh, your analytic needs to be fast. And, you know, we built on aws and that's why we are here. We are very, very proud partners of aws. We are in the AWS Accelerate program, and also we are in the startup program of aws. We are strategic ISV partner. And so yeah, we make real time analytics possible without all the cost and complexity barriers that are usually associated with it. And very, very happy to be part of this movement from batch to real time that is happening in the world. >>Right. Which is certainly an exciting trend. Right. I know great news for you, you made news yesterday, had an announcement involved with the intel with aws, who wants to share some of that >>With us too? Definitely. So, you know, one, one question that I always ask people is like, you know, if you go perspective that I share is like, if you go ask a hundred people, do you want fast analytics on fresh data or slow analytics on stale data? You know, a hundred out of a hundred would say fast and fresh, right? Sure. So then the question is, why hasn't this happened already? Why is this still a new trend that is emerging as opposed to something that everybody's taking for granted? It really comes down to compute efficiency, right? I think, you know, at the end of the day, real time analytics was always in using, you know, technologies that are, let's say 10 years ago using let's say processors that were available 10 years ago to, you know, three cloud, you know, days. There was a lot of complexity barriers associated with realtime analytics and also a lot of cost and, and performance barriers associated with it. >>And so Rox said from the, you know, from the very beginning, has been obsessing about building the most compute efficient realtime database in the world. And, you know, AWS on one hand, you know, allows us to make a consumption based pricing model. So you only pay for what you use. Sure. And that shatters all the cost barriers. But in terms of computer efficiency, what we announced yesterday is the Intel's third generation Zon scalable processors, it's code named Intel Ice Lake. When we port it over Rock said to that architecture, taking advantage of some of the instructions sets that Intel has, we got an 84% performance boost, 84, 84, 84. >>It's, it's incredible, right? >>It's, it's an incredible charts, it's an incredible milestone. It reduces the barrier even more in terms of cost and, you know, and, and pushes the efficiency and sets a, a really new record for how efficient realtime, you know, data processing can be in the cloud. And, and it's very, very exciting news. And so we used to benchmark ourselves against some of our other, you know, realtime, you know, did up providers and we were already faster and now we've set a, a much, much higher bar for other people to follow. >>Yep. And, and so what is, or what was it about real time that, that, you know, was such a barrier because, and now you've got the speed of, of course, obviously, and maybe that's what it was, but I think cost is probably part of that too, right? That's all part of that equation. I mean, real time, so elusive. >>Yeah. So real time has this inherent pattern that your data never stops coming. And when your data never stops coming, and you can now actually do analytics on that. Now, initially people start with saying, oh, I just want a real time dashboard. And then very quickly they realize, well, the dashboard is actually in real time. I'm not gonna be staring at the 24 7. Can you tap on my shoulder when something is off, something needs to be looked at. So in which case you're constantly also asking the question, is everything okay? Is everything all right? Do I need to, is is that something that I need to be, you know, double clicking on and, and following up on? So essentially very quickly in real time analytics, what happens is your queries never stop. The questions that you're asking on your data never stops. And it's often a program asking the question to detect anomalies and things like that. >>And your data never stops coming. And so compute is running 24 7. If you look at traditional data warehouses and data lakes, they're not really optimized for these kinds of workloads. They're optimized to store massive volumes of data and in a storage efficient format. And when an analyst comes and asks a question to generate a report, you can spin up a whole bunch of compute, generate the report and tear it all down when you're done. Well, that is not compute running 24 7 to continuously, you know, you know, keep ingesting the data or continuously keep answering questions. So the compute efficiency that is needed is, is much, much, much higher. Right? And that is why, you know, Rox was born. So from the very beginning, we're only built, you know, for these use cases, we have a, an extremely powerful SQL engine that can give you full feature SQL analytics in a very, very compute efficient way in the cloud. >>Right. So, so let's talk about the leap that you've made, say in the last two years and, and, and what's been the spur of that? What has been allowed you to, to create this, you know, obviously a, a different kind of an array for your customers from which to choose, but, but what's been the spark you think >>We touched upon this a little earlier, right? This spark is really, you know, the world going from batch to real time. So if you look at mainstream adoption of technologies like Apache, Kafka and Confluent doing a really good job at that. In, in, in growing that community and, and use cases, now businesses are now acquiring business data, really important business data in real time. Now they want to operationalize it, right? So, you know, extract based static reports and bi you know, business intelligence is getting replaced in all modern enterprises with what we call operational intelligence, right? Don't tell me what happened last quarter and how to plan this quarter better. Tell me what's happening today, what's happening right now. And it's, it's your business operations using data to make day to day decisions better that either grows your top line, compresses your bottom line, eliminates risk that are inherently creeping up in your business. >>Sure. You know, eliminate potential churn from a customer or fraud, you know, deduction and, and getting on top of, you know, that, you know, a minute into this, into, into an outage as opposed to an hour into the outage. Right? And so essentially I think businesses are now realizing that operational intelligence and operational analytics really, you know, allows them to leverage data and especially real time data to make their, you know, to grow their businesses faster and more efficiently. And especially in this kind of macro environment that is, you know, more important to have better unit economics in your business than ever before. Sure. And so that is really, I think that is the real market movement happening. And, and we are here to just serve that market. We are making it much, much easier for companies that have already adopted, you know, streaming technologies like Kafka and, and, and knows Canis MSK and all these technologies. Now businesses are acquiring these data in real time now. They can also get realtime analytics on the other end of it. Sure. >>You know, you just touched on this and, and I'd like to hear your thoughts about this, about, about the economic environment because it does drive decisions, right? And it does motivate people to look for efficiencies and maybe costs, you know, right. Cutting costs. What are you seeing right now in terms of that, that kind of looming influence, right? That the economy can have in terms of driving decisions about where investments are being made and what expectations are in terms of delivering value, more value for the buck? >>Exactly. I think we see across the board, all of our customers come back and tell us, we don't want to manage data infrastructure and we don't want to do kind of DIY open source clusters. We don't wanna manage and scale and build giant data ops and DevOps teams to manage that, because that is not really, you know, in their business. You know, we have car rental companies want to be better at car rentals, we want airlines to be a better airline, and they don't, don't want their, you know, a massive investment in DevOps and data ops, which is not really their core business. And they really want to leverage, you know, you know, fully managed and, you know, cloud offerings like Rock said, you know, built on aws, massively scalable in the cloud with zero operational overhead, very, very easy to get started and scale. >>And so that completely removes all the operational overhead. And so they can invest the resources they have, the manpower, they have, the calories that they have on actually growing their businesses because that is what really gonna allow them to have better unit economics, right? So everybody that is on my payroll is helping me grow my top line or shrink my bottom line, eliminate risk in my business and, and, and, and churn and, and fraud and other, and eliminate all those risks that are inherent in my business. So, so that is where I think a lot of the investments going. So gone are the days where, you know, you're gonna have these in like five to 10% team managing a very hard to operate, you know, open source data management clusters on EC two nodes in, in AWS and, and kind of DIYing it their way because those 10 people, you know, if all they do is just operational maintenance of infrastructure, which is a means to an end, you're way better off, you know, using a cloud, you know, a bond in the cloud built for the cloud solution like rock and eliminate all that cost and, and replace that with an operationally much, much simpler, you know, system to op, you know, to to work with such as, such as rock. >>So that is really the big trend that we are seeing why, you know, not only real time is going more and more mainstream cloud native solutions or the real future even when it comes to real time because the complexity barrier needs to be shattered and only cloud native solutions can actually, >>You get the two Cs cost and complexity, right. That you, you need to address. Exactly. Yeah, for sure. You know, what is it about building trust with your, with your clients, with your partners? Because you, you're talking about this cloud environment that, that everyone is talking about, right? Not everyone's made that commitment. There are still some foot draggers out there. How are you going about establishing confidence and establishing trust and, and, and providing them with really concrete examples of the values and the benefits that you can provide, you know, with, with these opportunities? >>So, you know, I grew up, so there's a few ways to to, to answer this question. I'll, I'll, I'll come, I'll cover all the angles. So in, in order to establish trust, you have to create value. They, you know, your customer has to see that with you. They were able to solve the problem faster, better, cheaper, and they're able to, you know, have a, the business impact they were looking for, which is why they started the project in the first place. And so establishing that and proving that, I think there's no equivalence to that. And, you know, I grew up at, at, you know, at Facebook back in the day, you know, I was managing online data infrastructure, okay. For Facebook from 2007 and 2015. And internally we always had this kind of culture of all the product teams building on top of the infrastructure that my team was responsible for. >>And so they were not ever, there was never a, a customer vendor relationship internally within Facebook that we're all like, we're all part of the same team. We're partnering here to have you, you know, to help you have a successful product launch. There's a very similar DNA that, that exists in Rock said, when our customers work with us and they come to us and we are there to make them successful, our consumption based pricing model also forces us to say they're not gonna really use Rock said and consume more. I mean, we don't make money until they consume, right? And so their success is very much integral part of our, our success. And so that I think is one really important angle on, you know, give us a shot, come and do an evaluation, and we will work with you to build the most efficient way to solve your problem. >>And then when you succeed, we succeed. So that I think is a very important aspect. The second one is AWS partnership. You know, we are an ISV partner, you know, AWS a lot of the time. That really helps us establish trust. And a lot of the time, one of the, the, the people that they look up to, when a customer comes in saying, Hey, what is, who is Rock? Said? You know, who are your friends? Yeah. Who are your friends? And then, you know, and then the AWS will go like, oh, you know, we'll tell you, you know, all these other successful case studies that R has, you know, you know, built up on, you know, the world's largest insurance provider, Europe's largest insurance provider. We have customers like, you know, JetBlue Airlines to Klarna, which is a big bator company. And so, so all these case studies help and, and, and, and platform and partners like AWS helps us, helps you amplify that, that, you know, and, and, and, and, and give more credibility. And last but not least, compliance matters. You know, being Soto type two compliant is, is a really important part of establishing trust. We are hip hop compliant now so that, you know, we can, you know, pi I phi data handling that. And so I think that will continue to be a part, a big part of our focus in improving the security, you know, functionality and, and capabilities that R set has in the cloud, and also compliance and, and the set of com, you know, you know, standards that we are gonna be compliant against. >>Well, I'm glad you hit on the AWS too, cause I did wanna bring that up. I, I appreciate that and I know they appreciate the relationship as well. Thanks for the time here. It's been a pleasure. Awesome. Learning about Rockette and what you're up to. Thank you. >>You bet. >>It's a pleasure. Thank you. Vi ka. All right. You are watching the cube coverage here at AWS Reinvent 22. And on the cube, of course, the leader, the leader in high tech coverage.

(upbeat music) >> Announcer: Live from San Francisco, celebrating 10 years of high-tech coverage, it's theCUBE, covering VMworld 2019. Brought to you by VMware and its ecosystem partners. >> Welcome back to theCUBE. Two sets, wall-to-wall coverage, our 10th year. We actually call this one the Valley set, over on the other side, it's in the middle of a meadow, and this was in the valley. I'm Stu Miniman. My cohost for this segment is, of course, John Furrier, the founder of SiliconANGLE. And joining us, the quintessential Valley guest that we have, Jerry Chen. Long time participant in the program, climbing up the leaderboard here of theCUBE Times at VMworld. Jerry, thank you so much for joining us. >> Stu, John, thanks for having me back. >> All right, so we knew you back when you worked for VMware. >> Jerry: Right. >> You're now a partner at Greylock. We watched some of your amazing startups, we've had many of them on our program. Just a little bit going on in your world this day, maybe we'll start there. >> Sure, it amazes me, both being at VMworld 10 years since you guys started covering. For me, I joined VMware back in 2003. So I was at the first Vmworld, through every single one of them, and seeing this ecosystem reinvent itself, and juxtapose that with every other conference at Moscone. So Dreamforce, Oracle OpenWorld, VMworld. And I would say five years ago, no one would have thought Dreamforce itself, or Salesforce as an ecosystem big enough for investors. But yes, now they can invest in startups. All they do is sell to the Salesforce ecosystem. You can always invest in a startup. All they sell to is the VMware ecosystem. And for sure, when, you and I, three of us go to Amazon or an event, that ecosystem just continues to grow exponentially year over year. >> And this some of the highlights of Datadog, we were talking before we came on camera. They always had a big booth, they bet on the AWS ecosystem, not a lot of Datadog here, but monitoring turns into observability, a key component, which basically was a white space. I mean, monitoring was boring. A little sector, but because of the nature of the data security auditing, this has become kind of a killer category. >> I think last week you saw SignalFX get acquired by Splunk, which is another huge enterprise company, and Datadog filed their S-1. No one thought monitoring would be a big enough market to support multiple billion plus companies, and what we've learned is making a bet on just cloud-native companies like Datadog did, purely in the Amazon Ecosystem, was a great bet because they've grown super fast, and that market turned out to be very big. In addition, it could be Splunk, and they could bet on logging for mostly on-premise companies. That turned out to be a large market. So I think five, 10 years ago, no one thought that these markets would be so big and so gigantic. The cloud itself, you can have a multi-billion dollar company like Datadog purely on a cloud-native application and cloud-native companies, if you will. >> You know, it's interesting, you're a VC and the enterprise specialist at Greylock. Consumer used to be all the rage in venture. "Oh, we're going to consumer against Facebook," Facebook breaks democracy, all kinds of problems. Being regulated. But enterprise became really hot with the cloud, and then you have an interesting dynamic. Now a thousand flowers are blooming on the startup side, so yes, there's a lot of action in startups, but the buyers of startups and the IPO markets is where the liquidity happens, which you care about, right? So now you have liquidity options for IPO for fast-growing flit scalers as you guys call it, and then the M and A market are buying the companies. So I got to ask you, with seeing Splunk as a great example, where they own the log market, log files, bring SignalFX in, former VMware guys and Facebook guys, comes in, they add some servability piece to it. Splunk's got more power now because of the acquisition. It's not just token acquisition. This is the market, product market slash M and A market. What's your thoughts on that? Because that's a key exit opportunity, and the numbers are pretty sizable when you think about it. >> I think just going back to the opportunity, the market's so big that you have multiple multi-billion dollar companies, so like Splunk's a huge company, great company. We're investors in a company called Sumo Logic. That's going to also be a successful company, and also a big-- >> John: And filed for IPO. >> And a big company that's OZA, Amazon, and Vmworld. So I think what you have here is each of these markets are monitoring, APM, the log, infrastructure, are turning out to be multi multi-billion, and larger than we anticipated. So I think before, to your analogy in the consumer, we always knew consumer markets had huge TAMs. Like how many billion in people are on Facebook? How many billion people are on Twitter? What we're learning now is the market and the TAM for these enterprise software companies, be it SAAS, be it LOG, be it Metrics, be it security, those TAMs are actually bigger than we thought beforehand as well. >> And the driver of that is what? Cloud, transformation, just replatforming, modernization? The businesses are businesses still. >> I think the move to cloud is accelerate, I think your last line, "businesses are businesses," is what's key. Like every business now is being touched by software. They all got to go cloud so I'm an investor in a company called Blend that does mortgage software. So the entire financial services industry, from mortgages to car loans and consumer lending, that's all going digital. That's all going online. Jobs that were like mortgage brokers are going to be an app on your phone now. So finance, retail, healthcare, construction, so all these markets now are going to the cloud, going digital, so these TAMs are expanding exponentially. >> Yeah, Jerry, want to get your take on the ecosystem. You know, we look at VMware, they built a big ecosystem, the end user computing space, you know. You've coined the term Virtual Desktop Infrastructure, from that environment there was an ecosystem around there. I see VMware at a lot of shows, and they have a good presence there, and there's some overlap between the public cloud space. Like when I go to this show, and I walk through the expo hall, oh my gosh. Data protection is everywhere, and all of those companies are at a all of the cloud environment, but do you see a transition from, you know, where VMware is in kind of the cloud-native space? Is there a lot of overlap, or what's your thinking on those kind of dynamics? >> I think all above. I think VMware at Vwworld, and like all these tech companies are constantly reinventing themselves and expanding. So you have, as a VC, say it's this company I'm looking at, when it's two individuals, and a dog, and PowerPoint. Is it a feature, is it a product, or is it a company? It's a feature, it's okay. You know, it's probably not worth the investment, but it's worthwhile. It'll get acquired for something. Is it a product? Some companies are just one killer product, right? And you can ride that product for the arc of the company. But then some startups turn out be companies, multi-product companies. And there always have one or two great products, and then you start adding new things as the market evolves, and VMware has done that. And so, as a result of adding server virtualization, desktop virtualization, Cloud Foundry which I helped build, out in the Kubernetes stuff. So they're adding multiple products to their company. I think the great companies can do that. Look at Amazon. They keep launching 10 new products every single month. Microsoft has done a great job reinventing themselves. So I think the great companies can reinvent, but not transform, they just add to what they have, and just to be a multi-product family. >> Stu: All right, so you mentioned Cloud Foundry. >> Yeah. >> Pivotal, of course, is now back in the mothership where it started there. When Cloud Foundry first started it was, "Well, we're not going to take the hypervisor "and put it all of these places." We needed a slightly different footprint. Well, five years later, we're talking about Kubernetes is going to be baked into Vsphere, and Vsphere is going to be a main piece of VMware's cloud-native strategy. Has the market changed or some of those technology pieces, you know, still a challenge? What's your take there? >> You know, it's a great question because I think what we're seeing is there's never ever in technology as you guys know, on platforms, it's a zero-sum game. It's never always going to all mainframe, all client server, all VMs, all microservers, all Serverless, right? And I think we're seeing is it's also never going to be all Amazon, it's never going to be all Google, it's never going to be all Azure, right? I think we talked about early days, it's not a winner take all. It may be, you know, what one-third, two-thirds, or something, 25-40% market share, but it's not going to be all or nothing. And so we're seeing companies now have architectures on multiple clouds, multiple technologies, and so just like 10 years ago, you had a mainframe team, you had a Windows team, you had a Solaris team. Remember Sun and Spark? And a Linux team. Now you have a Google team, and Azure team, an Amazon team, and an on-prem team. And so you just had these different stacks evolve, and I think what's interesting to see is like, we've kind of had this swing of momentum around Docker, Containers, Kubernetes, Serverless, but at the same time you see a bunch of folks realize, okay, what's happening is I'm choosing how much I want to consume. Like an API, a container, or a whole VM, right? And people realizing, yes, maybe consuming the APIs is our right level of consumption, but quite frankly, Stu, John, buying whole VMs also what I want. So you see a bunch of companies say, I'm just going to build better monolithic applications around VMware, I'm going to build better microservices around Docker and Kubernetes, and then we'll use Serverless where I think I need to use Serverless. >> Yeah, that's a good point. One of the things we hear from customers we talk to, and there's two types of enterprise customers, at least in the enterprise infrastructure side, classic CIOs and then CISOs. Two different spectrums. CIOs, old, traditional, multi-vendor means a good thing, no lock in, I know how to deal with that world. CISOs, they want to build their own stacks, manage their own technology, then push APIs out to the suppliers, and rechange the supplier relationship because security is so important they're forced to the cutting edge. So I look at that a kind of canary in the coal mine, and want to get your thought on that, because we're seeing a trend where enterprises are building software. They're saying, hey, you know, I want a stack internally that we're going to do for a variety of different reasons, security or whatever, and that doesn't really blend well for the multi-cloud team approach, because not everyone can have three killer teams building stacks, so you're seeing some people saying, you know, I'm going to pick a cloud here and go all in on certain things, build the stack, and then have a backup cloud there. And then some CIOs say, hey, you know what? I want all the cloud guys in there negotiating their best price maybe, or whatever. >> I think it's great nuance you pointed out. Even just like we had a Windows team and a Linux team, you still had a single database team that ran across both, or storage teams are ran across both. So I think the nuance here is certain parts of the stack should be Azure, Amazon, VMware. Certain parts of the stack should be, I think that the ultimate expression is just an API with service errors. So one of the companies you guys are familiar with, Roxette, it's a search and Serverless analytics company. It's basically an API in the cloud, multi-cloud, to do search and analytics. And just like you had a database team that's independent across all these stacks, for certain parts of the architecture, you're going to want something like Roxette, that's going to be independent of the architecture stacks. And so it's not all isolated, it's not siloed, it's not all horizontal, depending on the part of the stack, you're going to either want a horizontal cross-cloud solution, or a team that's going to go deep on one. >> So it's really a contextual decision based on what the environment looks like, or business. >> And there's certain areas of technology that we know from history that lends themself to either full stacks versus horizontals. Just like I said, there was a storage team and a database team, right? That's Oracle, or something that ran across Windows and Linux and Sun, you're going to see someone like Roxette become this search and Serverless analytics team across multiple cloud stacks. >> This is why the investment is such a great opportunity for the enterprise VCs right now because, I mean, there's so many dimensions of opportunities for companies to grow and become pretty large, and the markets are shifting so the TAM is pretty big. Michael Dell was just on the other side, I interviewed him. He says, you know, he was getting kind of in Dave's grill saying, "Well, the TAM for enterprise is bigger than cloud TAM." I go, "Well that TAM is going to be replatformized, so like that's going away and moving, shifting, so the numbers are big but they're shifting so tons of opportunities. >> It depends if you're a big company like Dell versus a small startup. Oftentimes, this true that the TAM for enterprise is still much larger than cloud, but your point is what's shifting were the dollars growing fast. >> The TAM for horses was huge at one point, and then, you know, cars came along, right? So you know. >> Every startup, what you want to do, you want to attach to a growing budget. You don't want to attach to a flat to shrinking budget. And so right now, if you're a founder, and say, "Okay, where are the budget dollars flowing to?" Everyone's got a kind of a cloud strategy, just like they had a VMware virtualization strategy, so if I'm like a startup G, metrics, or data analytics, I'm going to try to attach to where the dollars are flowing. That's a cloud strategy, that's an AI application strategy, security strategy. >> So let me ask you one question. So if I'm going to start up, this is a hypothetical startup, startups got an opportunity. It's a SaaS-based startup, they say, "You know what? "This is a feature in the market "that's part of a bigger system, "but I'm going to innovate on that." I think that with the markets shifting, that could evolve into a large TAM to your point about Datadog. What's the strategy, from an investment standpoint, that you would take? Would you say go all in on the single product? Do you want to have one or two features? What's the makeup of that approach, because you want to have some maybe defensibility, is it go all in on the one thing and hope that you return into like a Salesforce, then you bolt stuff on, or do you go in and try to do a little platform play underneath? >> It depends where you are in the startup world. We're in lifecycle. Look, startups succeed because they do one thing better, right? And so focus, focus, focus. And you have to have something that's like 10 times faster, 10 times better, 10 times cheaper, or something different. Something the world hasn't seen before. But if you do that one thing well, either A, you're taking budget dollars from incumbents, or B, you're something net new, the world hasn't seen, people will come to you when they see utility. As an investor I like to see that focus, I like to see, you know, some founders you get say, hey, Stu, think bigger. Some founders like John think smaller. Like what's your wedge? What's that initial entry point to the customer you're going to hit? Because once you land that, you get the right to do the next product, the next feature. >> That's the land, adopt, expand, like Xoom did. Or they picked video, >> Correct, voice, et cetera. >> I mean who the hell thought that was going to be a big market? It's a legacy market but they innovated with the cloud. >> Absolutely. I have all these sayings that I try to say like, "You don't get to play the late innings, "if you don't make it out the early innings," right? You know, and so if you want and have this strategy for this large platform, that's great, and every VC wants to see a path there. But they want to see execute from we're going to land, and we're expand. Now, startups fail because either where they land, they picked incorrectly. Like you decided to storm the wrong beach, right? Or it's either to small, or it's too big. The initial landing spot is too big, and they can't hold that ground. And so part of the art of navigating from Point A to Point B, or where I say, Act one, Act two, Act three of a lifecycle is make sure that you land correctly, earn your keep, show a lot of value, win that first battle, if you will, Act one, and then they move to Act two, Act three, and you can see a company like VMware clearly on their second, third act, right? And they've done a nice job of owning one product category, server virtualization, desktop virtualization, now expanding to other adjacent categories, buying companies like Carbon Black, right? In terms of security. So it doesn't happen overnight. I mean, VMware started in 1998. I was there when there was about 200 employees. People forget Amazon's been, gosh 27, 1998, when Bezos started selling books. Now they're selling books, movies, food, groceries, video, right? >> When did you first use AWS? Was it when the EC2 launched? I mean, everyone kicked the tires on that puppy. >> We all kicked the tires. I was at VMware as a Product Manager, I think it was '06 when they launched, right? And we all kind of kicked the tires on it. And it was a classic innoverse dilemna. We saw this thing that you thought was small and a very narrow surface area. Amazon started with an EC2, >> Two building blocks, storage and EC2. >> S-3, right, that's it. And then they said, "Okay, we're going to give a focus, focus on basic compute and basic object storage," and people were like, "What can you do with S-3? "Nothing," right? It's not a Sand, it's an availability. It's going to fail all the time, but people just started innovating and working their way through it. >> All right, so Jerry, when you look at the overall marketscape out there today, it seems like you still feel pretty confident that it's a good time for startups. Would you say that's true? >> Absolutely. >> All right, I want to get your final word here. 10 years in theCUBE at Vmworld, you know, you've known John for a long time. Did you think we'd make it? Any big memories as to what you've seen as we've changed over the years. >> I've plenty, let's go back to, >> John: Okay, now you can embarrass us. >> 10 year anniversary of VMworld. For your first Vmworld 10 years ago, I was like a Product Manager, and John Furrier, I think I met at a Press dinner, and he's like, "Hey, Chen," walking by, "come here, sit down," and they turn the camera on, and we had no idea what was going on, and he just started asking a bunch of random questions. I'm like, sure, I haven't cleared this with marketing or anyone else, but why not? >> John: Hijack interview, we call that. >> Hijack interview, and then it's been amazing to watch the two of you, Dave, John, everybody, grow SiliconANGLE and theCUBE in particular, and to this, the immediate franchise, in terms of both having a presence at all these shows, like Amazon, Oracle World, DreamForce, Vmworld, etc. But also the content you guys have, right? So now you have 10 years of deep content, and embarrassingly enough, 10 years, I guess, of videos of yours truly, which is always painful to watch, like either what I was saying, or you know, what my hair looked like back then. >> Stu: Jerry, you still have hair though, so. (laughing) >> Well, the beautiful thing is that we can look at the reputation trajectory of what people say and what actually happens. You always had good picks, loved the post you did on MOATs. That turned out to be very timeless content, and yeah, sometimes you miss it, we sometimes cringe. >> We miss a bunch. >> I remember starting one time with no headset on. Lot of great memories, Jerry. Great to have you in the community. Thanks for all your contribution. >> I look forward to the next 10 years of theCUBE, so I got to be here for the 20th anniversary, and now if I walk away, come back on right away, do I get another notch on my CUBE attending list so I can go up and catch Hared in the best? >> If you come on the other set, that counts as another interview. >> Perfect, so I got to catch up with Steve and the rest of the guys. >> Steve just lost it to Eric Herzog just a minute ago. We had a ceremony. It was like a walk through the supermarket, the doors thing, and the confetti came down. 11th time so you got to get to 11 now. So 12 is the high water mark. >> Done, we need t-shirts. (laughing) >> Well Jerry, thanks so much for joining us again. For John Furrier, I'm Stu Miniman, and you can go to theCUBE.net, if you search for Jerry Chen, there's over 16 interviews on there. I know I've gone back and watched some of them. Some great discussions we've had over the years. Thanks so much, and stay tuned for lots more coverage here at Vmworld 2019. Thanks for watching theCUBE. (upbeat music)

[Music] we're on welcome to the special cube conversation we're here with some breaking news we got some startup investment news here in the Q studios palo alto I'm John for your host here at Jerry Chen partnered Greylock and the CEO of rock said Venkat Venkat Rahmani welcome to the cube you guys announcing hot news today series a and seed and Series A funding 21 million dollars for your company congratulations thank you Roxette is a data company jerry great this is one of your nest you kept this secret forever it was John was really hard you know over the past two years every time I sat in this seat I'd say and one more thing you know I knew that part of the advantage was rocks I was a special company and we were waiting to announce it and that's right time so it's been about two and half years in the making I gotta give you credit Jerry I just want to say to everyone I try to get the secrets out of you so hard you are so strong and keeping a secret I said you got this hot startup this was two years ago yeah I think the probe from every different angle you can keep it secrets all the entrepreneurs out there Jerry Chen's your guide alright so congratulations let's talk about the startup so you guys got 21 million dollars how much was the seed round this is the series a the seed was three million dollars both Greylock and Sequoia participating and the series a was eighteen point five all right so other investors Jerry who else was in on this I just the two firms former beginning so we teamed up with their French from Sequoia and the seed round and then we over the course of a year and half like this is great we're super excited about the team bank had Andrew bhai belt we love the opportunity and so Mike for an office coin I said let's do this around together and we leaned in and we did it around alright so let's just get into the other side I'm gonna read your your about section of the press release roxette's visions to Korea to build the data-driven future provide a service search and analytics engine make it easy to go from data to applications essentially building a sequel layer on top of the cloud for massive data ingestion I want to jump into it but this is a hot area not a lot of people are doing this at the level you guys are now and what your vision is did this come from what's your background how did you get here did you wake up one Wednesday I'm gonna build this awesome contraction layer and build an operating system around data make this thing scalable how did it all start I think it all started from like just a realization that you know turning useful data to useful apps just requires lots of like hurdles right you have to first figure out what format the data is in you got to prepare the data you gotta find the right specialized you know data database or data management system to load it in and it often requires like weeks to months before useful data becomes useful apps right and finally you know after I you know my tenure at Facebook when I left the first thing I did was I was just talking you know talking to a lot of people with real-world companies and reload problems and I started walking away from moremore of them thinking that this is way too complex I think the the format in which a lot of the data is coming in is not the format in which traditional sequel based databases are optimized for and they were built for like transaction processing and analytical processing not for like real-time streams of data but there's JSON or you know you know parque or or any of these other formats that are very very popular and more and more data is getting produced by one set of applications and getting consumed by other applications but what we saw it was what is this how can we make it simpler why do we need all this complexity right what is a simple what is the most simple and most powerful system we can build and pulled in the hands of as many people as possible and so we very sort of naturally relate to developers and data scientists people who use code on data that's just like you know kind of like our past lives and when we thought about it well why don't we just index the data you know traditional databases were built when every byte mattered every byte of memory every byte on disk now in the cloud the economics are completely different right so when you rethink those things with fresh perspective what we said was like what if we just get all of this data index it in a format where we can directly run very very fast sequel on it how simple would the world be how much faster can people go from ideas to do experiments and experiments to production applications and how do we make it all faster also in the cloud right so that's really the genesis of it well the real inspiration came from actually talking to a lot of people with real-world problems and then figuring out what is the simplest most powerful thing we can build well I want to get to the whole complexity conversation cuz we were talking before we came on camera here about how complexity can kill and why and more complexity on top of more complexity I think there's a simplicity angle here that's interesting but I want to get back to your background of Facebook and I want to tell a story you've been there eight years but you were there during a very interesting time during that time in history Facebook was I think the first generation we've taught us on the cube all the time about how they had to build their own infrastructure at scale while they're scaling so they were literally blitzscaling as reid hoffman and would say and you guys do it the Greylock coverage unlike other companies at scale eBay Microsoft they had old-school one dotto Technology databases Facebook had to kind of you know break glass you know and build the DevOps out from generation one from scratch correct it was a fantastic experience I think when I started in 2007 Facebook had about 40 million monthly actives and I had the privilege of working with some of the best people and a lot of the problems we were very quickly around 2008 when I went and said hey I want to do some infrastructure stuff the mandate that was given to me and my team was we've been very good at taking open source software and customizing it to our needs what would infrastructure built by Facebook for Facebook look like and we then went into this journey that ended up being building the online data infrastructure at Facebook by the time I left the collectively these systems were surveying 5 plus billion requests per second across 25 plus geographical clusters and half a dozen data centers I think at that time and now there's more and the system continues to chug along so it was just a fantastic experience I think all the traditional ways of problem solving just would not work at that scale and when the user base was doubling early in the early days every four months every five months yeah and what's interesting you know you're young and here at the front lines but you're kind of the frog in boiling water and that's because you are you were at that time building the power DevOps equation automating scale growth everything's happening at once you guys were right there building it now fast forward today everyone who's got an enterprise it's it wants to get there they don't they're not Facebook they don't have this engineering staff they want to get scale they see the cloud clearly the value property has got clear visibility but the economics behind who they hire so they have all this data and they get more increasing amount of data they want to be like Facebook but can't be like Facebook so they have to build their own solutions and I think this is where a lot of the other vendors have to rebuild this cherry I want to ask you because you've been looking at a lot of investments you've seen that old guard kind of like recycled database solutions coming to the market you've seen some stuff in open source but nothing unique what was it about Roxette that when you first talk to them that but you saw that this is going to be vectoring into a trend that was going to be a perfect storm yeah I think you nailed it John historic when we have this new problems like how to use data the first thing trying to do you saw with the old technology Oh existing data warehouses akin databases okay that doesn't work and then the next thing you do is like okay you know through my investments in docker and B and the boards or a cloud aerosol firsthand you need kind of this rise of stateless apps but not stateless databases right and then I through the cloud area and a bunch of companies that I saw has an investor every pitch I saw for two or three years trying to solve this data and state problem the cloud dudes add more boxes right here's here's a box database or s3 let me solve it with like Oh another database elastic or Kafka or Mongo or you know Apache arrow and it just got like a mess because if almond Enterprise IT shop there's no way can I have the skill the developers to manage this like as Beckett like to call it Rube Goldberg machination of data pipelines and you know I first met Venkat three years ago and one of the conversations was you know complexity you can't solve complex with more complexity you can only solve complexity with simplicity and Roxette and the vision they had was the first company said you know what let's remove boxes and their design principle was not adding another boxes all a problem but how to remove boxes to solve this problem and you know he and I got along with that vision and excited from the beginning stood to leave the scene ah sure let's go back with you guys now I got the funding so use a couple stealth years to with three million which is good a small team and that goes a long way it certainly 2021 total 18 fresh money it's gonna help you guys build out the team and crank whatnot get that later but what did you guys do in the in those two years where are you now sequel obviously is lingua franca cool of sequel but all this data is doesn't need to be scheming up and built out so were you guys that now so since raising the seed I think we've done a lot of R&D I think we fundamentally believe traditional data management systems that have been ported over to run on cloud Williams does not make them cloud databases I think the cloud economics is fundamentally different I think we're bringing this just scratching the surface of what is possible the cloud economics is you know it's like a simple realization that whether you rent 100 CPUs for one minute or or one CPU 400 minutes it's cost you exactly the same so then if you really ask why is any of my query is slow right I think because your software sucks right so basically what I'm trying to say is if you can actually paralyze that and if you can really exploit the fluidity of the hardware it's not easy it's very very difficult very very challenging but it's possible I think it's not impossible and if you can actually build software ground-up natively in the cloud that simplifies a lot of this stuff and and understands the economics are different now and it's system software at the end of the day is how do I get the best you know performance and efficiency for the price being paid right and the you know really building you know that is really what I think took a lot of time for us we have built not only a ground-up indexing technique that can take raw data without knowing the shape of the data we can turn that and index it in ways and store them maybe in more than one way since for certain types of data and then also have built a distributed sequel engine that is cloud native built by ground up in the cloud and C++ and like really high performance you know technologies and we can actually run distributor sequel on this raw data very very fast my god and this is why I brought up your background on Facebook I think there's a parallel there from the ground this ground up kind of philosophy if you think of sequel as like a Google search results search you know keyword it's the keyword for machines in most database worlds that is the standard so you can just use that as your interface Christ and then you using the cloud goodness to optimize for more of the results crafty index is that right correct yes you can ask your question if your app if you know how to see you sequel you know how to use Roxette if you can frame your the question that you're asking in order to answer an API request it could be a micro service that you're building it could be a recommendation engine that you're that you're building or you could you could have recommendations you know trying to personalize it on top of real time data any of those kinds of applications where it's a it's a service that you're building an application you're building if you can represent ask a question in sequel we will make sure it's fast all right let's get into the how you guys see the application development market because the developers will other winners here end of the day so when we were covering the Hadoop ecosystem you know from the cloud era days and now the important work at the Claire merger that kind of consolidates that kind of open source pool the big complaint that we used to hear from practitioners was its time consuming Talent but we used to kind of get down and dirty the questions and ask people how they're using Hadoop and we had two answers we stood up Hadoop we were running Hadoop in our company and then that was one answer the other answer was we're using Hadoop for blank there was not a lot of those responses in other words there has to be a reason why you're using it not just standing it up and then the Hadoop had the problem of the world grew really fast who's gonna run it yeah management of it Nukem noose new things came in so became complex overnight it kind of had took on cat hair on it basically as we would say so how do you guys see your solution being used so how do you solve that what we're running Roxette oh okay that's great for what what did developers use Roxette for so there are two big personas that that we currently have as users right there are developers and data scientists people who program on data right - you know on one hand developers want to build applications that are making either an existing application better it could be a micro service that you know I want to personalize the recommendations they generated online I mean offline but it's served online but whether it is somebody you know asking shopping for cars on San Francisco was the shopping you know was the shopping for cars in Colorado we can't show the same recommendations based on how do we basically personalize it so personalization IOT these kinds of applications developers love that because often what what you need to do is you need to combine real-time streams coming in semi structured format with structured data and you have no no sequel type of systems that are very good at semi structured data but they don't give you joins they don't give you a full sequel and then traditional sequel systems are a little bit cumbersome if you think about it I new elasticsearch but you can do joins and much more complex correct exactly built for the cloud and with full feature sequel and joins that's how that's the best way to think about it and that's how developers you said on the other side because its sequel now all of a sudden did you know data scientist also loved it they had they want to run a lot of experiments they are the sitting on a lot of data they want to play with it run experiments test hypotheses before they say all right I got something here I found a pattern that I don't know I know I had before which is why when you go and try to stand up traditional database infrastructure they don't know how what indexes to build how do i optimize it so that I can ask you know interrogatory and all that complexity away from those people right from basically provisioning a sandbox if you will almost like a perpetual sandbox of data correct except it's server less so like you don't you never think about you know how many SSDs do I need how many RAM do I need how many hosts do I need what configure your programmable data yes exactly so you start so DevOps for data is finally the interview I've been waiting for I've been saying it for years when's is gonna be a data DevOps so this is kind of what you're thinking right exactly so you know you give us literally you you log in to rocks at you give us read permissions to battle your data sitting in any cloud and more and more data sources we're adding support every day and we will automatically cloudburst will automatically interested we will schematize the data and we will give you very very fast sequel over rest so if you know how to use REST API and if you know how to use sequel you'd literally need don't need to think about anything about Hardware anything about standing up any servers shards you know reindex and restarting none of that you just go from here is a bunch of data here are my questions here is the app I want to build you know like you should be bottleneck by your career and imagination not by what can my data employers give me through a use case real quick island anyway the Jarius more the structural and architectural questions around the marketplace take me through a use case I'm a developer what's the low-hanging fruit use case how would I engage with you guys yeah do I just you just ingest I just point data at you how do you see your market developing from the customer standpoint cool I'll take one concrete example from a from a developer right from somebody we're working with right now so they have right now offline recommendations right or every night they generate like if you're looking for this car or or this particular item in e-commerce these are the other things are related well they show the same thing if you're looking at let's say a car this is the five cars that are closely related this car and they show that no matter who's browsing well you might have clicked on blue cars the 17 out of 18 clicks you should be showing blue cars to them right you may be logging in from San Francisco I may be logging in from like Colorado we may be looking for different kinds of cars with different you know four-wheel drives and other options and whatnot there's so much information that's available that you can you're actually by personalizing it you're adding creating more value to your customer we make it very easy you know live stream all the click stream beta to rock set and you can join that with all the assets that you have whether it's product data user data past transaction history and now if you can represent the joins or whatever personalization that you want to find in real time as a sequel statement you can build that personalization engine on top of Roxanne this is one one category you're putting sequel code into the kind of the workflow of the code saying okay when someone gets down to these kinds of interactions this is the sequel query because it's a blue car kind of go down right so like tell me all the recent cars that this person liked what color is this and I want to like okay here's a set of candidate recommendations I have how do I start it what are the four five what are the top five I want to show and then on the data science use case there's a you know somebody building a market intelligence application they get a lot of third-party data sets it's periodic dumps of huge blocks of JSON they want to combine that with you know data that they have internally within the enterprise to see you know which customers are engaging with them who are the persons churning out what are they doing and they in the in the market and trying to bring they bring it all together how do you do that when you how do you join a sequel table with a with a JSON third party dumb and especially for coming and like in the real-time or periodic in a week or week month or one month literally you can you know what took this particular firm that we're working with this is an investment firm trying to do market intelligence it used age to run ad hoc scripts to turn all of this data into a useful Excel report and that used to take them three to four weeks and you know two people working on one person working part time they did the same thing in two days and Rock said I want to get to back to microservices in a minute and hold that thought I won't go to Jerry if you want to get to the business model question that landscape because micro services were all the world's going to Inc so competition business model I'll see you gets are funded so they said love the thing about monetization to my stay on the core value proposition in light of the red hat being bought by by IBM had a tweet out there kind of critical of the transactions just in terms of you know people talk about IBM's betting the company on RedHat Mike my tweet was don't get your reaction will and tie it to the visible here is that it seems like they're going to macro services not micro services and that the world is the stack is changing so when IBM sell out their stack you have old-school stack thinkers and then you have new-school stack thinkers where cloud completely changes the nature of the stack in this case this venture kind of is an indication that if you think differently the stack is not just a full stack this way it's this way in this way yeah as we've been saying on the queue for a couple of years so you get the old guard trying to get a position and open source all these things but the stacks changing these guys have the cloud out there as a tailwind which is a good thing how do you see the business model evolving do you guys talk about that in terms of you can hey just try to find your groove swing get customers don't worry about the monetization how many charging so how's that how do you guys talk about the business model is it specific and you guys have clear visibility on that what's the story on that I mean I think yeah I always tell Bank had this kind of three hurdles you know you have something worthwhile one well someone listen to your pitch right people are busy you like hey John you get pitched a hundred times a day by startups right will you take 30 seconds listen to it that's hurdle one her will to is we spend time hands on keyboards playing around with the code and step threes will they write you a check and I as a as a enter price offered investor in a former operator we don't overly folks in the revenue model now I think writing a check the biz model just means you're creating value and I think people write you checking screening value but you know the feedback I always give Venkat and the founders work but don't overthink pricing if the first 10 customers just create value like solve their problems make them love the product get them using it and then the monetization the actual specifics the business model you know we'll figure out down the line I mean it's a cloud service it's you know service tactically to many servers in that sentence but it's um it's to your point spore on the cloud the one that economists are good so if it works it's gonna be profitable yeah it's born the cloud multi-cloud right across whatever cloud I wanna be in it's it's the way application architects going right you don't you don't care about VMs you don't care about containers you just care about hey here's my data I just want to query it and in the past you us developer he had to make compromises if I wanted joins in sequel queries I had to use like postgrads if I won like document database and he's like Mongo if I wanted index how to use like elastic and so either one I had to pick one or two I had to use all three you know and and neither world was great and then all three of those products have different business models and with rocks head you actually don't need to make choices right yes this is classic Greylock investment you got sequoia same way go out get a position in the market don't overthink the revenue model you'll funded for grow the company let's scale a little bit and figure out that blitzscale moment I believe there's probably the ethos that you guys have here one thing I would add in the business model discussion is that we're not optimized to sell latte machines who are selling coffee by the cup right so like that's really what I mean we want to put it in the hands of as many people as possible and make sure we are useful to them right and I think that is what we're obsessed about where's the search is a good proxy I mean that's they did well that way and rocks it's free to get started right so right now they go to rocks calm get started for free and just start and play around with it yeah yeah I mean I think you guys hit the nail on the head on this whole kind of data addressability I've been talking about it for years making it part of the development process programming data whatever buzzword comes out of it I think the trend is it looks a lot like that depo DevOps ethos of automation scale you get to value quickly not over thinking it the value proposition and let it organically become part of the operation yeah I think we we the internal KPIs we track are like how many users and applications are using us on a daily and weekly basis this is what we obsess about I think we say like this is what excellence looks like and we pursue that the logos in the revenue would would you know would be a second-order effect yeah and it's could you build that core kernels this classic classic build up so I asked about the multi cloud you mention that earlier I want to get your thoughts on kubernetes obviously there's a lot of great projects going on and CN CF around is do and this new state problem that you're solving in rest you know stateless has been an easy solution VP is but API 2.0 is about state right so that's kind of happening now what's your view on kubernetes why is it going to be impactful if someone asked you you know at a party hey thank you why is what's all this kubernetes what party going yeah I mean all we do is talk about kubernetes and no operating systems yeah hand out candy last night know we're huge fans of communities and docker in fact in the entire rock set you know back-end is built on top of that so we run an AWS but with the inside that like we run or you know their entire infrastructure in one kubernetes cluster and you know that is something that I think is here to stay I think this is the the the programmability of it I think the DevOps automation that comes with kubernetes I think all of that is just like this is what people are going to start taking why is it why is it important in your mind the orchestration because of the statement what's the let's see why is it so important it's a lot of people are jazzed about it I've been you know what's what's the key thing I think I think it makes your entire infrastructure program all right I think it turns you know every aspect of you know for example yeah I'll take it I'll take a concrete example we wanted to build this infrastructure so that when somebody points that like it's a 10 terabytes of data we want to very quickly Auto scale that out and be able to grow this this cluster as quickly as possible and it's like this fluidity of the hardware that I'm talking about and it needs to happen or two levels it's one you know micro service that is ingesting all the data that needs to sort of burst out and also at the second level we need to be able to grow more more nodes that we we add to this cluster and so the programmability nature of this like just imagine without an abstraction like kubernetes and docker and containers and pods imagine doing this right you are building a you know a lots and lots of metrics and monitoring and you're trying to build the state machine of like what is my desired state in terms of server utilization and what is the observed state and everything is so ad hoc and very complicated and kubernetes makes this whole thing programmable so I think it's now a lot of the automation that we do in terms of called bursting and whatnot when I say clock you know it's something we do take advantage of that with respect to stateful services I think it's still early days so our our position on my partner it's a lot harder so our position on that is continue to use communities and continue to make things as stateless as possible and send your real-time streams to a service like Roxette not necessarily that pick something like that very separate state and keep it in a backhand that is very much suited to your micro service and the business logic that needs to live there continue should continue to live there but if you can take a very hard to scale stateful service split it into two and have some kind of an indexing system Roxette is one that you know we are proud of building and have your stateless communal application logic and continue to have that you know maybe use kubernetes scale it in lambdas you know for all we care but you can take something that is very hard to you know manage and scale today break it into the stateful part in the stateless part and the serval is back in like like Roxette will will sort of hopefully give you a huge boost in being able to go from you know an experiment to okay I'm gonna roll it out to a smaller you know set of audience to like I want to do a worldwide you know you can do all of that without having to worry about and think about the alternative if you did it the old way yeah yeah and that's like talent you'd need it would be a wired that's spaghetti everywhere so Jerry this is a kubernetes is really kind of a benefit off your your investment in docker you must be proud and that the industry has gone to a whole nother level because containers really enable all this correct yeah so that this is where this is an example where I think clouds gonna go to a whole nother level that no one's seen before these kinds of opportunities that you're investing in so I got to ask you directly as you're looking at them as a as a knowledgeable cloud guy as well as an investor cloud changes things how does that change how is cloud native and these kinds of new opportunities that have built from the ground up change a company's network network security application era formants because certainly this is a game changer so those are the three areas I see a lot of impact compute check storage check networking early days you know it's it's it's funny it gosh seems so long ago yet so briefly when you know I first talked five years ago when I first met mayor of Essen or docker and it was from beginning people like okay yes stateless applications but stateful container stateless apps and then for the next three or four years we saw a bunch of companies like how do I handle state in a docker based application and lots of stars have tried and is the wrong approach the right approach is what these guys have cracked just suffered the state from the application those are app stateless containers store your state on an indexing layer like rock set that's hopefully one of the better ways saw the problem but as you kind of under one problem and solve it with something like rock set to your point awesome like networking issue because all of a sudden like I think service mesh and like it's do and costs or kind of the technologies people talk about because as these micro services come up and down they're pretty dynamic and partially as a developer I don't want to care about that yeah right that's the value like a Roxanna service but still as they operate of the cloud or the IT person other side of the proverbial curtain I probably care security I matters because also India's flowing from multiple locations multiple destinations using all these API and then you have kind of compliance like you know GDP are making security and privacy super important right now so that's an area that we think a lot about as investors so can I program that into Roxette what about to build that in my nap app natively leveraging the Roxette abstraction checking what's the key learning feature it's just a I'd say I'm a prime agent Ariane gdpr hey you know what I got a website and social network out in London and Europe and I got this gdpr nightmare I don't we don't have a great answer for GDP are we are we're not a controller of the data right we're just a processor so I think for GDP are I think there is still the controller still has to do a lot of work to be compliant with GDP are I think the way we look at it is like we never forget that this ultimately is going to be adding value to enterprises so from day one we you can't store data and Roxette without encrypting it like it's just the on you know on by default the only way and all transit is all or HTTPS and SSL and so we never freaked out that we're building for enterprises and so we've baked in for enterprise customers if they can bring in their own custom encryption key and so everything will be encrypted the key never leaves their AWS account if it's a you know kms key support private VP ceilings like we have a plethora of you know security features so that the the control of the data is still with the data controller with this which is our customer but we will be the the processor and a lot of the time we can process it using their encryption keys if I'm gonna build a GDP our sleeves no security solution I would probably build on Roxette and some of the early developers take around rocks at our security companies that are trying to track we're all ideas coming and going so there the processor and then one of the companies we hope to enable with Roxette is another generation security and privacy companies that in the past had a hard time tracking all this data so I can build on top of rocks crack okay so you can built you can build security a gbbr solution on top rock set because rock set gives you the power to process all the data index all the data and then so one of the early developers you know stolen stealth is they looking at the data flows coming and go he's using them and they'll apply the context right they'll say oh this is your credit card the Social Security is your birthday excetera your favorite colors and they'll apply that but I think to your point it's game-changing like not just Roxette but all the stuff in cloud and as an investor we see a whole generation of new companies either a to make things better or B to solve this new category problems like pricing the cloud and I think the future is pretty bright for both great founders and investors because there's just a bunch of great new companies and it's building up from the ground up this is the thing I brought my mother's red hat IBM thing is that's not the answer at the root level I feel like right now I'd be on I I think's fastenings but it's almost like you're almost doubling down to your your comment on the old stack right it's almost a double down the old stack versus an aggressive bet on kind of what a cloud native stack will look like you know I wish both companies are great people I was doing the best and stuff do well with I think I'd like to do great with OpenStack but again their product company as the people that happen to contribute to open source I think was a great move for both companies but it doesn't mean that that's not we can't do well without a new stack doing well and I think you're gonna see this world where we have to your point oh these old stacks but then a category of new stack companies that are being born in the cloud they're just fun to watch it all it's all big all big investments that would be blitzscaling criteria all start out organically on a wave in a market that has problems yeah and that's growing so I think cloud native ground-up kind of clean sheet of paper that's the new you know I say you're just got a pic pick up you got to pick the right way if I'm oh it's gotta pick a big wave big wave is not a bad wave to be on right now and it's at the data way that's part of the cloud cracked and it's it's been growing bigger it's it's arguably bigger than IBM is bigger than Red Hat is bigger than most of the companies out there and I think that's the right way to bet on it so you're gonna pick the next way that's kind of cloud native-born the cloud infrastructure that is still early days and companies are writing that way we're gonna do well and so I'm pretty excited there's a lot of opportunities certainly this whole idea that you know this change is coming societal change you know what's going on mission based companies from whether it's the NGO to full scale or all the applications that the clouds can enable from data privacy your wearables or cars or health thing we're seeing it every single day I'm pretty sad if you took amazon's revenue and then edit edit and it's not revenue the whole ready you look at there a dybbuk loud revenue so there's like 20 billion run which you know Microsoft had bundles in a lot of their office stuff as well if you took amazon's customers to dinner in the marketplace and took their revenue there clearly would be never for sure if item binds by a long shot so they don't count that revenue and that's a big factor if you look at whoever can build these enabling markets right now there's gonna be a few few big ones I think coming on they're gonna do well so I think this is a good opportunity of gradual ations thank you thank you at 21 million dollars final question before we go what are you gonna spend it on we're gonna spend it on our go-to-market strategy and hiding amazing people as many as we can get good good answer didn't say launch party that I'm saying right yeah okay we're here Rex at SIA and Joe's Jerry Chen cube cube royalty number two all-time on our Keeble um nine list partner and Greylock guy states were coming in I'm Jeffrey thanks for watching this special cube conversation [Music]