>> Narrator: Live from San Jose, it's theCUBE. Presenting Big Data Silicon Valley. Brought to you by SiliconANGLE Media, and its ecosystem partners. (electronica flourish) >> We're back at Big Data SV. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante. Praveen Kankariya is here. He's the CEO of a company called Impetus. Company's been around the Big Data space before Hadoop, even. Praveen, thanks for back in theCUBE, good to see you. >> Thank you, Dave. >> So, as I said in the open, you've seen a lot. You kind of really got into the Big Data space in 2007, seen it blow through the Hadoop, you know, sort of batch world into the real time world, seen the data management headwinds. From your perspective, you know, what kind of problems are you solving today in the Big Data world? >> So I can go into the details of what we are doing, but at a high level, we are helping companies converge to a singular, enterprise-wide data model. 'Cause I think that is a crisis in the Fortune 500 today, and there'll be have and have-nots. >> Dave: What do you mean a crisis? >> I routinely run into companies who do not have their data model stitched. So they know the same customer, they know me by five different handles, and they don't have it figured out, that I'm the same guy. So, that I think is a major problem. So I think the C-suite is, they would not like to hear this, but they are flying partially blind. >> I have a theory on this, but I want to hear yours-- >> Sure. >> Why is that such a big problem? >> So, the most efficient business in the world is a one-man business, because everything is flowing in the same brain. The moment you hire your first employee, you start having communication breakdowns. And now these companies have hundreds and thousands of employees. Hundreds of thousands of employees. There's a lot of breakdown. There are airlines that, when I'm upgraded to first class, are offering me an economy-plus seat when I go to check in. That's ... they're turning me off, and they're losing an opportunity to, real opportunity to upsell something else to me. So. >> Okay, well, so let's bring this into the world of digital transformation. Everybody talks about those buzzwords, so let's try to put some sort of meat on that bone. If you look at the top five companies by market cap, Amazon, Apple, Facebook, Google. I'm missing somebody. Anyway, they're big. 500 billion, 700 billion dollars. They're all sort of what we would call data-driven. What does that mean? Data is at the core of their enterprise. A lot of the companies you're talking about, human expertise is the core of their enterprise, and they've got data that's sort of in silos, surrounding it. >> Praveen: Yes, yes. >> Is that an accurate description? >> That's-- And how can you help close that gap? >> So they have data in silos, and even that data in silos is not being used at velocity, with velocity. That data is, you know, it's taking much longer for them to even clean up that data, get access to that data, derive insights from that data. >> Dave: Right. >> So there's a lot of sluggishness, overall. >> Dave: So how do you help? >> How do we help? Great question. We help in many different ways. So we actually, so my company provides solutions. So we have some, a few products of our own, and then we work with all kinds of product companies. But we're about solving a problem, so when the customers we engage with, we actually solve a problem, so that there's a business outcome before we walk out. That's the big difference. We're not here to just sell the next sexy platform, or this or that, you know. We're not just here to excite the developers. >> So, maybe you could give me some of your favorite examples of where you've helped some of your clients. >> So there's one fairly large company, it's a household name around the world. And we have helped them create a single source of truth using a Big Data infrastructure. This has about six and a half thousand feeds of data coming in, continuously. Some continuously, some every few minutes, every few hours, whatnot. But then all their data is stitched together, and it's got guardrails, there's full governance. So, and now this platform is available to every business unit, to run their own applications. There's a set of APIs who go in and develop their own applications. So shadow idea is being promoted in this environment. It's not being looked down upon. >> So it's not sitting in one box, presumably, it's distributed throughout the organization? >> It is distributed. And you know, there're are some, you know, as long as you stay within the governance structure, you can derive, you know, somebody wants a graph database, they can derive a graph database from this massive, fully-connected data set, which is an enterprise-wide data set. >> Don't you see as some of the challenges, as well as cultural, there are some industries that might say, or some executives that say, "Well, you know my industry, "healthcare is an example, really hasn't been disrupted. "We're maybe insulated from that." I feel as though that's somewhat risky thinking, and it's easy to maybe sit back say, "Well, I'm going to wait, see what happens." What are your thoughts on that? >> Look at the data. The week Jeff Bezos announced that he is tying up with JPMC and Warren Buffet, some of the largest healthcare companies, and I'm talking of Fortune 10 companies, they lost about 20% of their market cap that week. So, you don't have to listen to me. Listen to the markets. >> Well, that's true. We see what happens in grocery, see what happens in... We haven't really seen, as I say, the disruption in healthcare, financial services, but it's all data, and that changes the equation. So why, let's see, not why. How when, if you get to this, so it sounds like step one is to get that sort of single data model across the organization, but there's other steps. You got to figure out how to monetize the data, not necessarily by selling it, but how data contributes to the monetization of the company. You got to it accessible, you got to make it of high quality, you've got to get the right skill sets. So there's a lot to it, and more than just the technology. Maybe you could talk about that. >> So the way, I would like to preach, if I'm allowed to-- >> Dave: Please, it's theCUBE... (laughs) >> No, no, I mean, I don't mean here, but if any CEO was listening to me, what I would like to tell them is, just create a vision of your ultimate connected data model. And then start looking at how do you converge out of that vision. It may not happen in one day, one week, one year. It's going to take time, and you know, every business is in flight, so they have to operate continuously, but they have to keep gravitating. And the biggest casualty is going to be their customer relationship if they don't do this. Because most companies don't know their customers fully. I mean, that little example of the airline which was showing me, flashing an ad for economy seats, premium economy seats when I'm already in first class, they don't know me. Some part of that company doesn't know me. So they're not able to service me well. Here now they lost an opportunity to monetize, but I think from another perspective, they lost an opportunity to really offer me something which would've made my flight way more comfortable. >> Well. >> So. >> Then you wonder if that's the dynamic that you encountered, what's the speed to market, the agility of that organization? They're hampered by their ability to, whether it's roll out new apps, identify new data sources, create new products for the customers. Have you seen, what kind of impacts have you seen within your customers? You gave the example before, of that sort of single data model, the single version of the truth. What business impacts have been able to affect for your customers? >> So, there, I mean I can go on giving you anecdotes from my observations, my front row observations into these companies. >> Yeah, it'd be good to have some kind of proof points, right? Our audience would love to hear that. >> So, you know there's a company not too far from here. They've stitched every click stream, right to product usage data. To support data, to every marketing email opened. And they can tell who's buying, what happened, what is their support experience, who's upgrading, who's upgrading faster because they had a positive support experience, or not. So everything is tied. Any direction you want to look into your customer space, you can go and get visibility from every perspective you can think of. That's customer 360. We worked with a credit card company where they had a massive rules engine, which had been developed over generations to report fraud, to catch fraud, while a transaction's being processed. We actually, once they got all their data together, we could apply a massive machine learning engine. And we started learning from customers' own behavior, so we completely discarded the rules engine, and now we have a learning system which is flagging fraudulent transactions. So they managed to cut down their false positives tremendously, and in turn reduced inconvenience. It used to be embarrassing for me to give out a card and get it declined in front of a customer. >> So, as I said at the top, you've seen sort of the evolution of this whole Big Data meme before it was called Big Data. What are the things that may be exciting you? We seem to be entering a new era we call digital. There's a cognitive era, AI, machine intelligence. What do you see that's exciting, and real? >> So number one, so I like to divide this space into two parts, the whole space of data analytics. There's the data plumbing, which we call data management, and whatnot. I have to plumb all my data together. Only then I can feed this data into my AI models. Now I can do in my silos today, but for me to do at a global level for my entire corporation, I need it all stitched together. And then, of course, these models are very real. My son, my 22-year old son is using TensorFlow for some little startup that he's cooking. And it took him just a month to pick it up and start applying it. So why can't our large companies do so? And in turn, bring down the cost of services, cost of products, the velocity of delivering those things to us, and make life better. >> So, the barriers to technology deployment are getting lower. >> And this is all feasible, Dave, right now. >> Yeah. >> You know, I mean, this is all, this is a dream 10 years ago. If somebody had said, you know, for an old corporation to stitch all its data, "What're you talking about? "It's not going to happen." But now, this is possible, and it's feasible. It's not going to require, make a massive hole in their budgets. >> But don't you think it's also table stakes to compete in over, the next 10 years? >> It is, there is table stakes. It's actually kind of late, from my perspective. If I had to go invest in the market, I mean, I would invest in companies who have their data act together. >> Yeah, yeah. So, what's the, how do you tell, when a company has its data act together? When you walk into a prospect, how do you know, what do you see, what're the characteristics of somebody who has that act together? >> It's hard for me to give you a few characteristics, but you know, you can tell what is the mandate they're operating under, if there are clear mandates. Because, for most companies, this is lost because of turf battle. This whole battle is lost due to turf issues. And the moment you see senior executives working together, with a massive willingness to bring everything together. You know, they'll have different turfs, and they're willing to contribute data, and bring it together. That's a phenomenally positive sign, because once that happens, then every large company has the wherewithal to go hire 50 data scientists, or work with all kinds of companies, including mine, to get data science help. >> Yeah, it comes back to the culture, doesn't it? >> Yes, absolutely. >> All right, Praveen, we have to leave it right there. Thanks very much for coming back in theCUBE. >> Thank you Dave, thank you. Thank you for the opportunity. >> You're very welcome. All right, keep it right there, everybody. This is theCUBE. We're live from the Forager in San Jose, Big Data SV. We'll be right back. (electronica flourish)

(upbeat music) >> Tech people love tech. Consumers love to benefit of tech. No consumer opens up their iphone and says, "Oh my gosh, I love the technology behind my iphone". >> What's it been like being on the Shark Tank? >> You know filming is fun. And hanging out is fun, and it's fun to be a celebratory at first. Your head gets really big and you can get tables at restaurants. >> Who says tech isn't got a little pizazz? (laughing) >> Announcer: More skin in the game. In charge of his destiny. >> I mean you guys are exciting? >> Announcer: Robert Herjavec, is Cube Alumni. (upbeat music) Live from Silicon Valley, it's the Cube, covering Google Cloud Next' 17. >> Welcome back to the Cube, we're doing two days of live coverage here of the Google Cloud Next' 2017 here in the center of Silicon Valley from our 4500 sq foot Palo Alto studio. Happy to bring back to the program a multi time guest, but first time in his new role Praveen Akkiraju now the CEO of Viptela. Thank you for joining us. >> Thanks Stu real pleasure to be here. >> Praveen we were joking, it's like you first came on the Cube back in 2012, you've been on the program at many of our shows, but now you're at our place here, we've got the nice studio, so happy. >> Yes it's really impressive. It's a, you guys have come a long way and it's been an awesome show when I was at VC and I'm really excited to be back here with you. >> Awesome, thank you so much. Why don't you give our audience why Vipetla? What was exiting o you about the opportunity? We've has the opportunity of interviewing some of your folks over the last couple of years at shows like the Emerald and alike? >> Absolutely, I think it's interesting, when you think about sort of what's happening in the IT industry as a whole. There's a revolution going on in the cloud. You know the show that you guys are covering as well as what's been happening over the past couple of years. Applications are basically migrating out of the data center, whether it's into the public cloud into into PaaS platforms, SaaS platforms and such like, similarly at the edge right, users have been migrating away from their desktops right, mobility has unleashed the user to be wherever they need to be and be able to still be productive. In addition to that, you have a whole bunch of things happening in the edge in terms of devices and things coming onboard. Now if you think about these two worlds and the revolution that's happening there, the actual connectivity between those two has been frozen in time right. Majority of the enterprises today are still connected using MPLE, VPN technology which is invented 20 years ago to solve the problem of ATM like emulation or IP. So I think what was really interesting to me about Viptela is it's truly about redefining the network connectivity between users and applications for the could era. And that's really what our mission is and that's what we're really excited about. >> Yeah Praveen it reminds me a lot of you know, what we saw in the data centers when it came to networking. There was that big shift for a number of years in saying, "Well it was the client to server "and then that machine to machine". Everything that happened with virtualization. We went from north south traffic to east west traffic. We talked about forever. Now as cloud pulls in those connectivity. Reinventing what's happening in WAN. >> And absolutely and think about it, if you're a user, you might be accessing your applications in the data center, But you might need to access a something on a SaaS platform well if you're sitting at a branch office do you want to go back to the data center and then head out to the Cloud? Or do you want to be able to take the best path out? Most branches today, have internet connections that our faster than anything MPLS can provide. In fact, there's a data point, one of our customers gave us. The per megabit cost for MPLS VPN is about $200. The per megabit cost for internet is about $2. And you think about the speed as symmetry and obviously the SLA's are different right. So you want to be able to make sure that you can leverage the best connectivity, but also make sure the applications are mapped to the appropriate SLA's transport. So, what we do is essentially, we think about ourselves as the next generation overlay. So we can, the Viptela fabric essentially encompasses MPLS, VPN, internet, LTE connectivity, and we're able to understand what happens in the underlay. But enterprises can just focus on how they want their users to connect to their applications without having to understand what's happening underneath. So that's truly the power of the software refined world if you will right. >> Yeah so, we've been talking for a few years. That whole SDN wave that came out, Google talks about themselves as the largest SDN company out there. But most of the discussion seems to have moved beyond SDN. You're area of SD WAN is definitely one of the hot conversations. Where are customers in kind of understanding this transition and where do things fit? >> Yeah it's a great point, I mean the first wave of software defined networking was essentially was about solving the data center connectivity problem. So how you connect machines more dynamically. How you connect do you connect capacity more dynamically. So application can migrate, you know this notion of sort of machine to machine communication in a dynamic fashion. And being able to potentially even stripe it out to the could. But the first wave did not address hard users connect to their applications. So we think of ourselves from an SDN perspective, kind of leading that second wave of software defined networking, which truly is about user experience an application experience. Connecting users wherever they are to applications wherever they are right. In a scalable secure and dynamic fashion. >> Very different discussion from what I think of. The guys from Nicira that turned into the NXS, that seemed very tied into how VMware talks about hybrid environment. When you talk about, when VMware on AWS goes in. I need that NXS in there. You know you worked at Cisco for a number of years, what they're doing with ACI now is talking more about that as opposed to the client the application layer. >> Exactly right. And I think that at the end of the day. We optimized how applications can migrate and move. And how they can get the best capacity. But the whole purpose is to really deliver those applications to the users. And the WAN has been kind of this, it's frozen in time for 20 years, primarily because it's hard right. It's really hard to be able to figure out what the underlay actually looks like. I mean some of these, some of our customers are global. I mean we have sights in Vietnam. In India, in the US obviously, But it's a global or it's a global footprint and being able to overlay something on top that still give you the predictable performance and be is secure, is something that's been a hard problem to solve. And that's what's really exiting about what we're doing at Viptela. >> It's really interesting stuff. Talk about how you guys partner with, interact with the public cloud environments? >> Yeah you know so we, we're obviously most of our controller are hosted in AWS as well as Verzion which is another, which is a key partner. These are the two big two big sort of partners for us in our in terms of our controllers. But we think about, we partner with AWS, we partner with Microsoft from a Open from an Office 365 perspective. And there a lot of our customer who want to have a much more predictable, high, low leniency access to Office 365. A lot of our customer have workloads in AWS. So we're able to actually spin up a version of our device to front end VPC's and AWS so you can then terminate. Essentially, we treat the cloud as a node in the fabric right. So it helps all the policies, it helps all the securities. Security aspects of it day one. So it's really super simple to set up. We don't treat the cloud separatetly, we just say,"well here's another branch "or a head end". Let's just, can I connect it in. And let the customer define the policies that they see fit. >> That's great so AWS and Office 365 leaders in their categories, got the Google Show going on this week. What do you hear from your customers when it comes to G Suite and Google Cloud? >> Yeah I mean there's a lot of customers who use the G Suite. Mainly Googe Docs particularity. In the context of sort of some of the small medium business that we work with. So again, our job is to really bring users to the applications with the lowest leniency of having the best experience possible. So lot of the could providers essentially don't necessarily worry about how customers get there. They just assume the customer shows up the the door but is a SasS platform or infrastructure is a service platform. So our partnerships with a lot of these providers are about insuring that you know we can collectively guarantee that their users get the best path forward. And that creates more stickiness for them. In terms of their service. >> Okay Praveen, let's talk about Viptela for a second, What's on your plate this year? Those industry watchers? What should we be expecting to see from you coming forward? >> Yeah what's interesting about Viptela is I mean we talk about obviously software define WAN as a category. And clearly as I mentioned, there's a huge leitant requirement to evolve the WAN connectiveness. And I would think that what Viptela does is sort of the next generation overlay. And we talked about sort of the different forms of connectivity which we give the control back to the enterprise. To say, "All you need to worry about Mr. Customer is "to say how can I define the segment or policy per user, "per application". So that's been sort of the focus of our initial use case for our fabric. And we've been tremendously successful, you know most of what we focus primarily on the global fortune 1000 type customers. So we have pretty much every verticals represented in our customer base. Large financials, industrial companies, car companies, retailers, health care and such like. But we think about this fabric as essentially solving the problem of connectivity so you now the next phase of our solution is really about how do we make cloud connectivity really simple and secure? So we're going to launch something in that space, where we make connectivity to infrastructure, service, SaaS platforms really seamless as part of our platform. So if you're a user in a branch or at the edge, you should be able to connect to your data center at the same level of experience and security as you would go to your cloud. So we want to make that super seamless. So that's I think, we call that Cloud En ramps. That's something that we're going to be announcing pretty soon. When I think about the longer term plan, evolution of this because of the platform is fundamentally grounded in routing, in understanding how scale happens, we have taken the traditional routing stake and disaggregated it. There's a data plane that's onsite, there's a control plane which is essentially your routing, and a management organization plane that sits in the cloud. So this allows us to solve many problems. So you can extrapolate forward and say well there's a whole problem internet of things. What is the internet of things problem? It is a whole bunch of devices at the edge which need to be connected to end points whether it's a data center or a you know a collection point. Dynamically, dependent on the phase of their. So those are the kind of problems we think we can solve. So Viptela is interesting because it's not just about SDN it's really about the next generation overlay between the users and the cloud and being able to address multiple use cases. >> Okay, and there are a number of companies. Plenty of startups, some of the big guys there. In the market, what really differentiates you guys? What are your customers coming to you for that the other guys can't do? >> Yeah I think it's, I would say really, so we're all routing geeks. I pretty much spent 19 years at Cisco. Built every platform that Cisco ships today. And so are most of member of the teams. We have I think one of the strongest collection of networking talent in the industry. And what we're able to do with that is as I mentioned re-imagine what the network connectivity needs to look like. In the era of cloud, in the era of internet of things. Our architecture is fundamentally modular as I mentioned right. There's a data plane, there's a control plane, management organization plane. We are cloud managed and cloud delivered. So we solve for scale very elegantly. Because we inherently use the properties of routing that has allowed the internet to scale to what it is as part of the core of our solution. That's one thing that's unique. The second aspect of this is, for us security is a day zero thing. You know, when we bring up a box, zero touch provisioning, it comes up with an Ipsec tunnel encrypted. And we do it without having to exchange keys. So it's inherently secure right. So that is a very significant issue because if you're using the internet as your pipe for your mission critical traffic how do you assure yourself that you're not going to be hacked? And your traffic is not going to be intercepted. So that's you know, some of the largest financial institutions have been on our architecture. Because they trust that. So that's a second piece. The third piece is from an application and a policy perspective we have the ability with our controllers to push policies and create segmentations for different use cases on a dynamic basis. So I'll give you an example so if you have a user in a branch, and you have basically another user comes in they have a different set of requirements. You can dynamically switch up a tunnel from your cloud controller to enable that to happen without every having to touch or configure any of the end boxes. So our cloud platform gives us tremendous amount of scale and flexibility. So that's the way I think about it. Scalability, security, an application policy and the different use cases that we're able to bring to bear. >> So final question I have of you Praveen, the networking world is changing faster than it used to. But I think back to... >> Praveen: Finally. >> for many years I would do slides on networking, and we'd talk about decade scale. So it's like you know, here's how the standard comes, here's how it roles out, here's how it adoption. The enterprise is risk adverse. Slow to change. Not doing anything. Why are things so exciting now in the networking space? What's different? What's driving that move and our customers moving faster? >> Yeah it's a great question and you know I think to put it differently I think networking enjoyed architectural consistency and stability for almost two decades. Which is not the case when you think about the data center or some of the other environment where there's constant change. Now having said that, when we think about what's driving this change it's really that these two revolutions that are going on, one in the edge where users are evolving really rapidly whether it's connectivity or sort of devices and such like and one of the data center of the cloud where applications are fundamentally changing their ephemeral. They're able to migrate between locations. So that's putting a lot of pressure back onto the network. To say, "Hey we need the network to be a lot more dynamic". We need the network to be a lot more flexible. A lot more cost effective. And that is the fundamental driver which we see as driving the customers' willingness to say, "I need to re-look at the network". And the other aspect of this is, as I said we re-imagined networking ground up. Clean sheet of paper. Learned the lessons from the past. And say, "How do you make this painless for the customer"? The reason why the network particularly the WAN has been stagnant is because it is painful right. It involved multiple connectivities, multiple carriers, multiple policies, it's not something that most enterprises want to deal with. By abstracting all that complexity away. We allow customers to focus on what they care about. Is how do I connect? Enable user connectivity with applications. And we take care of the underlay right. So I think those are the key things. I mean it's essentially the last leg of the stool if you will. In terms of moving truly to the cloud era. >> Alright well Praveen Akkiraju thank you so much for joining us again. You're watching the worldwide leader in live enterprise tech coverage the Cube. (upbeat music)

(upbeat music) >> Hi everybody, this is Dave Vellante. And welcome to this CUBE conversation where we welcome an ESG senior analyst, Bob Laliberte Bob, good to see you. >> Great to see you too. Thanks for having me >> Love it, I love to have the analyst sessions. Set it up. What's your scope, what's your area of expertise? >> So my coverage area right now is networking in its entirety. So that spans everything from enterprise networking, wired, wireless, campus, data center, et cetera. All the way up through telco and, in cloud networking. >> So how do you look at the landscape? One of the big things I think about a lot is how does the shift to cloud migration? How does that affect the existing, network layers? I mean, you got Cisco as the big whale and it's just, it's amazing to me. They still have whatever percent market share they have 60, 65% of the market. Are things, what's happening in the competitive landscape. How is cloud affecting that? >> That's a great question. I think the interesting piece is so many times organizations think about the network as plumbing. But the reality is the it's really important plumbing because as you talk about cloud and things get more distributed, well, guess what connects those distributed locations? It's the network. And so organizations as they've moved to the cloud you've seen a big shift with things like SD-WAN and so forth. How do I get more efficient connectivity up to that cloud? How do I not only enable able better connectivity between my data centers in the cloud, but now all my remote workers in the cloud. And so there's been a lot of big shifts going on that have driven the importance of having not only network, but secure networks. So like I said, cloud is one thing, and you're moving your applications there. But with the pandemic you saw the remote work. Think about the network administrators who we're managing, hey, I've got to control network connections between my data centers, a couple clouds and maybe dozens maybe a hundred remote branches. And now I'm connecting to 10,000 micro branches that I need to ensure that they can connect up to these applications and so forth. Hell of a lot more complex environment today than it used to be for these network teams. When we look at the, what we're seeing, how the networking providers are responding it's by driving comprehensive end-to-end solutions. So unifying, wired, wireless, and WAN. Driving efficiencies there. You're seeing even ThousandEyes for Cisco and things like that. Because they know the Internet's becoming more integral part of the corporate network. So being able to drive those types of things being able to, I think look at how to drive those operational efficiencies through AI and ML. So one of the big shifts we've seen in networking is the transition to cloud-based network management. And obviously that couple of things that helps with, first of all, the operations teams who are working remotely can more easily access it. But once all that data is up in the cloud, it creates a platform to be able to invest in AI/ML, and be able to drive intelligent alerting and even automation. And that's really what's needed because as the environments get more distributed and complex, you need to have that those operational efficiencies that automation, that intelligence to help them. >> How has remote work and hybrid work affected sort of network, spending priorities. Obviously when the pandemic hit you had to accommodate end points. And I always have this theory okay, when people come back to the office and I know it's going to be a different world but, the HQ probably needs some love as well. So has that been a tailwind for the industry? >> Absolutely, that's what we're seeing now. I think when the pandemic first hit, everyone said I've got to ramp up my VPNs. I've got to scale out my concentrators. I've got to add more firewalls in my data center. And then after a while, when they realized this was here to stay, they said, okay we just created that hub-and-spoke network that we just got rid of with SD-WAN. So what are the better solutions we can implement? So now you're seeing them not only implement better networking solutions for the remote workers. But reimagining what the campus looks like. Because it's not going to be ever 100% full or maybe it will, but how, for how many times a year will it be 100% full? So you've got to go from 80% cubes and 20% conference and collaboration areas, to 80% collaboration areas and 20% cubes. So we're seeing a lot of transition taking place in the campus environment as organizations are deploying newer technologies like Wi-Fi 6E. That have greater bandwidth to allow for those collaboration apps to run in those collaboration areas. Instead of just having the single wired conference room for video. Everyone's got to be able to run their video, voice and video collaboration apps. >> So how do you look at the landscape now? Again, you can't talk about networking without talking about Cisco. I think they, up there, I saw you and Zeus as talking about out, Cisco's quarter and other networking topics. Their long term guidance is for 60% growth for a company that size that's really outstanding. I mean, Cisco's, really has always been an execution machine of course. And it's a new era now under Chuck. There are more than ankle biters. If you look at Arista's doing pretty well there's guys like Extreme, there's others that are out there but nobody seemed to be able to unseat Cisco. What's happening in the landscape? >> I mean, that's a great question. Cisco's just been around for so long and been so big for so long. And you have to also keep in mind that with Cisco it's not just about the technology, but the fact from a if you think about it from a cultural standpoint these are workers who have been trained on Cisco since, some of them since high school. The educational component that Cisco has done has groomed generations of network technologists. So when they come into the market, they're fully familiar and used to Cisco. Plus they make a really good product and they've got products that cover everything. They cover the whole gambit. So they're still able to maintain their share. They're able to grow. They're able to move. They've made a shift last year. They announced in last spring that they were going to focus more on end-to-end. So instead of just having, hey, here's a point product, here's a point product. Here's a point product. Let's think about it in its entirety. Let's deliver a complete end-to-end solution solve bigger problems for customers, which obviously makes it much harder to remove when you're just trying to remove a piece of that single problem. But the other competitors are also having good years. And I think also the rising tide floats all boats. And so because of this distributed nature, the importance of the network, everyone is doing that. Plus obviously this has to be said, the supply chain issues where people are ordering ahead as well. But organizations, you look at Arista, they've gone from just being a data center company to expanding all the way down to the campus edge, wireless, right there creating an end-to-end environment Extreme did the same thing. They went out and made a lot of acquisitions. They pulled them all together, integrated. They're all moving to this cloud based end-to-end network management. Arista has been on a tear, bringing in a lot of, not only innovative technology, but innovative technologists. So if you look at some of the organizations they bought. I keep calling it Route 128, it's 128 Technologies. So sorry folks I live in Massachusetts. It's always been Route 128. >> You Remember when don't we. 128 Technology's Mist was their big. Mist was their, Mist was kind of like their VMware. VMware to EMC was Mist was to Juniper. And so we call it the Mistification of Juniper where every organization, every company they bring in they're rolling under that and this the AI engine. So they're bringing in 128 Technologies into that. They've got their own, their own stuff under that, their wired switches. So they've got this unified wired and wireless and WAN assurance now that they have. They've been gaining a lot of traction with that. And again, for the things we were talking about because it's far more distributed and complex. You need to have, It's not like people are getting replaced. It's not like, hey, we're leveraging this automation so that we can get rid of network teams. It's because it's getting so much more complex just to have the same number of people manage that more complex environment. We need those intelligence solutions. >> So I want to ask you about network and multi-cloud. And so it's kind of tongue in cheek because we coined this term super cloud. And so what we meant by that, so here's the premise. And I wonder you could give us your perspective. Multi-cloud, I've said many times is I think largely a symptom of multi-vendor I run in this, I run in AWS or, Azure, I've done the work to understand their primitives and or Google, whatever it is. But it's not like an abstraction layer that's floating above all those but now you're starting to see that. In fact, it re:Invent in November. The ecosystem it seemed like was everybody was focused on developing what we call these super clouds. And again, it's tongue in cheek, this abstraction layer it hides the underlying complexity of the primitives and the APIs adds incremental value on top of that. So there's a company Prosimo, which Steve Herrod, is invested in and others Praveen Akkiraju, whom I'm sure you know from Viptela. Aviatrix is another company that's sort of, Steve Malaney has come on theCUBE and talked about what they're doing. Like yeah, that's super cloud. It seems like it's something new and different than just multi-cloud which is kind of connecting in to different clouds. It's that value on top. What do you think about that? And what does that mean for networking? >> That's a really good point because we are starting to see the inception of organizations going beyond having multiple cloud providers and looking at starting to deploy applications across multiple clouds. It's still really early. The vast majority of organizations are still, I use this application for this cloud and this application for that cloud. But that's the next frontier. That's what they're trying to solve is how do I create this basically cloud fabric and make it as simple as possible. And again, all the things we've been talking about how do I, instead of you having to learn Amazon, Google, Azure networking technology, learn mine, I'll take care of it, but I'll abstract all that complexity from you and make it so much simpler to be able to connect to these interconnect, and connect to them in a seamless fashion. And so that's what they're really trying to do is they're. And the hard part is it takes really sophisticated solutions to remove that high level of complexity and make it simple for an organization to do that. So yeah, absolutely. >> If I had more time I'd make it shorter as somebody who writes a lot. And I think you're right. I think it is future. It's not definitely not here today, but the other thing is it ties into digital transformation. We used this again, throw that buzzword around but, companies not just tech company, I mean everybody's becoming like a tech company, but organizations, financial services companies, healthcare they're building their own clouds on top of the hyperscalers who spend $100 billion a year on CapEx. And that seems to be a trend that I think is going to take legs over this next decade. Just like in the previous decade everybody was thinking, okay, we're going to SaaSify our business softwares (indistinct) the world. And now it's software and cloud services are the way in which I'm going to create customer experiences. >> Correct, yeah. It's why should I go out and make an investment in technology when the technology's already there? And I can rent it for when I need it scale it as I need it and, and do all of that. I agree with that. I think that's something that we're seeing. The interesting part though is that when we look at our data points, probably let than 40% of the applications and workloads are in the cloud today. So there's still a role that the corporate data center plays. We are seeing over time. They expect that to progress and transition but I think there's still always going to be maybe a quarter of the workloads and applications may never leave. Depending on how they're built, et cetera. So there's always going to be that distributed environment where you've got workloads in the private data centers, workloads in multiple public clouds. And also, the big thing too is don't forget about the edge. We're seeing a lot more edge activity take place as organizations recognize, as they deploy more IOT devices, and want to get realtime business insights they've got to deploy the compute there. >> Well, and that's something that I wanted to ask you about, but going back to what you just said, which is, I agree with you. So that suggests to me, Bob that we're just kind of, with cloud just entering the steep part of the S curve. Amazon's headed toward $100 billion, run rate business. Maybe they probably won't get there this year but they will next year. We're entering that steep growth phase, really could be. It's incredible. But I wanted to ask you about the edge. Because you're right is we got to move compute to the edge, ARM is going to dominate. I would think, the edge. They already are with our smartphones. How do you see the cloud guys participating in the edge? Whether it was Andy Jassy, or now Adam Selipsky or anybody at Amazon. They have the dogma of in the fullness of time all workloads are going to be in the cloud. So they either have to change their definition of cloud. Or they're wrong. So what's your thought on that? >> I think it really starts coming down to what's your definition of edge. And so, much like when the cloud technologies first came about and you had all the shadow IT. Everyone running off, and everyone thought oh this is all great, until you realized you had to operationalize it and you had to pull the brakes. Stop doing that. We're going to make sure IT operations. >> Call the CIO up. Exactly, finding out where stuff was by going through accounting and seeing credit card charges. For the edge what we've seen I think is maybe organizations really saying I've got to deploy my servers in my own site. Right at that edge in order to get the lowest possible latency. And so what I think we're starting to see is organizations looking at that and saying, okay well I'm in a metro and I've got 25 locations in a metro. And I've deployed technology to every single one of those sites. Do I need it there? Or can I put it in an Equinix facility that's less than five milliseconds from all 25 sites? So I think there's starting to be this pragmatic approach of looking at let's look at the edge, let's take a look at what type of latencies. What is our definition of real time. When do we actually need the data and so forth? What kind of connectivity do we have? And then from there figure out how we go about connecting it. And so for companies like AWS and Google and Azure a lot of them there's local zones and things like that. They're deploying them in those colos because they don't have data centers in every metro but they can leverage an Equinix. They can leverage someone else's hardware that's there to deploy their software stack within that location. So I think that's something that we're starting to see more and more of as the edge. And obviously the association with the telcos as well. They've got a great footprint. If you want to get close to the edge with their colos Their home offices and things like that and whatnot. Their ability to move the compute closer to the edge, the base stations of the antennas and things like that, are certainly significant. And that's why you're seeing the wavelengths and things like that, programs like that. >> So I was going to close, but there some really interesting topics you just brought up. Call it whatever you going to call it near edge, far edge or deep edge. And you mentioned real time. Yeah. So for those Equinix data centers, I don't need, true real time. But for Tesla, I need real time. I need real time inference at the edge probably using a bunch of ARM cores and I can't go back to any cloud. How do you look at that? Both, I would think big markets. Do you have a sense as to, is one bigger than the other? Are they both just enormous or we don't even know yet. >> I'm not sure that we know yet. I think certainly, it's riding the tail of the IOTs. So the more sensors, the more things that are deployed the more that, that data businesses realize they can leverage that data to make real time business insights to drive either better experiences. And if you're in retail. So location based services and real time offer management it doesn't do any good to offer a coupon for something that you've, that's 40 yards behind you. That that's past, like you said with the cars there's, I've seen some studies recently. They say, well, based on the latency, if the command is to stop and you're at one millisecond, it stops within four inches. If you are at 50 milliseconds, it stops 10 feet later. That's a big difference. And I don't know if those numbers are right but you get the idea about the impact, what the real time impact is of. >> Margin is not huge. >> Exactly, so that's where organizations, I think first and foremost need to take a pragmatic approach to determine what is real time for us. What's our definition of it. And then that can lead them to where do I need to place this compute technology? And then that goes to how do I then connect to it? So for the Teslas and so forth, obviously you're going to want 5G connections if possible. Ultra low latency and not just any 5G. The good stuff, the millimeter bandwidth stuff that that's the ultra low latency. >> So let's wrap. So, what's going on in your research world obviously the big, big acquisition tech target they seem to be investing in ESG. You guys are really growing and hiring. That's awesome. Any research that you're working on? >> Yeah, there's a couple of couple of projects we have going on right now. We're wrapping up a four part distributed cloud research series. So we did it on distributed cloud infrastructure. Applications, observability. And now this last one is on the edge. Coincidentally. So we're working on that. We've got some new network modernization research that we've published. And we're going to be looking, from a networking perspective looking at end-to-end network modernization which will be coming out soon. >> Awesome, Bob, thanks so much for coming on theCUBE. I really would love to have you back and chat about some of those things. Observability hot space. God, I wish we had more time. >> Absolutely, appreciate it, thanks. >> And thank you for watching this CUBE conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

>> From The Cube Studios in Palo Alto and Boston connecting with thought-leaders all around the world, this is a Cube Conversation. >> Hello, everyone, and welcome to this Cube Conversation, I'm Dave Vellante. Now, you know I love data, and today we're going to introduce you to a new data and analytical platform, and we're going to take it to the world of cloud database and data warehouses. And with me is Sagar Kadakia who's the head of Enterprise IT (indistinct) 7Park Data. Sagar, welcome back to the Cube. Good to see you. >> Thank you so much, David. I appreciate you having me back on. >> Hey, so new gig for you, how's it going? Tell us about 7Park Data. >> Yeah. Look, things are going well. It started at about two months ago, just a, you know, busy. I had a chance last, you know a few months to kind of really dig into the dataset. We have a tremendous amount of research coming out in Q4 Q1 around kind of the public cloud database market public cloud analytics market. So, you know, really looking forward to that. >> Okay, good. Well, let's bring up the first slide. Let's talk about where this data comes from. Tell us a little bit more about the platform. Where's the insight. >> Yeah, absolutely. So I'll talk a little about 7Park and then we'd kind of jump into the data a little bit. So 7Park was founded in 2012 in terms of differentiator, you know with other alternative data firms, you know we use NLP machine learning, you know AI to really kind of, you know, structure like noisy and unstructured data sets really kind of generate insight from that. And so, because a lot of that know how we ended up being acquired by Vista back in 2018. And really like for us, you know the mandate there is to really, you know look across all their different portfolio companies and try to generate insight from all the data assets you know, that these portfolio companies have. So, you know, today we're going to be talking about you know, one of the data sets from those companies it's that cloud infrastructure data set. We get it from one of the portfolio companies that you know, helps organizations kind of manage and optimize their cloud spend. It's real time data. We essentially get this aggregated daily. So this certainly different than, you know your traditional providers maybe giving you quarterly or kind of by annual data. This is incredibly granular, real time all the way down to the invoice level. So within this cloud infrastructure dataset we're tracking several billion dollars worth of spend across AWS, Azure and GCP. Something like 350 services across like 20 plus markets. So, you know, security machine learning analytics database which we're going to talk about today. And again like the granularity of the KPIs I think is kind of really what kind of you know, differentiates this dataset you know, with just within database itself, you know we're tracking over 20 services. So, you know, lots to kind of look forward to kind of into Q4 and Q1. >> So, okay. So the main spring of your data is if I'm a customer and I there's a service out there there are many services like this that can help me optimize my spend and the way they do that is I basically connect their APIs. So they have visibility on what the transactions that I'm making my usage statistics et cetera. And then you take that and then extrapolate that and report on that. Is that right? >> Exactly. Yeah. We're seeing just on this one data set that we're going to talk about today, it's something like six 700 million rows worth of data. And so kind of what we do is, you know we kind of have the insight layer on top of that or the analytics layer on top of all that unstructured data, so that we can get a feel for, you know a whole host of different kind of KPIs spend, adoption rates, market share, you know product size, retention rates, spend, you know, net price all that type of stuff. So, yeah, that's exactly what we're doing. >> Love it, there's more transparency the better. Okay. So, so right, because this whole world of market sizing has been very opaque you know, over the years, and it's like you know, backroom conversations, whether it's IDC, Gartner who's got what don't take, you know and the estimations and it's very, very, you know it's not very transparent so I'm excited to see what you guys have. Okay. So, so you have some data on the public cloud and specifically the database market that you want to share with our audience. Let's bring up the next graphic here. What are we looking at here Sagar? What are these blue lines and red lines what's this all about? >> Yeah. So and look, we can kind of start at the kind of the 10,000 foot view kind of level here. And so what we're looking at here is our estimates for the entire kind of cloud database market, including data warehousing. If you look all the way over to the right I'll kind of explain some of these bars in a minute but just high level, you know we're forecasting for this year, $11.8 billion. Now something to kind of remember about that is that's just AWS, Azure and GCP, right? So that's not the entire cloud database market. It's just specific to those three providers. What you're looking at here is the breakout and blue and purple is SQL databases and then no SQL databases. And so, you know, to no one's surprise here and you can see, you know SQL database is obviously much larger from a revenue standpoint. And so you can see just from this time last year, you know the database market has grown 40% among these three cloud providers. And, you know, though, we're not showing it here, you know from like a PI perspective, you know database is playing a larger and larger role for all three of these providers. And so obviously this is a really hot market, which is why, you know we're kind of discussing a lot of the dynamics. You don't need to Q and Q Q4 and Q1 >> So, okay. Let's get into some of the specific firm-level data. You have numbers that you want to share on Amazon Redshift and Google BigQuery, and some comments on Snowflake let's bring up the next graphic. So tell us, it says public cloud data, warehousing growth tempered by Snowflake, what's the data showing. And let's talk about some of the implications there. >> Yeah, no problem. So yeah, this is kind of one of the markets, you know that we kind of did a deep dive in tomorrow and we'll kind of get this, you know, get to this in a few minutes, we're kind of doing a big CIO panel kind of covering data, warehousing, RDBMS documents store key value, graph all these different database markets but I thought it'd be great, you know just cause obviously what's occurring here and with snowflake to kind of talk about, you know the data warehousing market, you know, look if you look here, these are some of the KPIs that we have you know, and I'll kind of start from the left. Here are some of the orange bars, the darker orange bars. Those are our estimates for AWS Redshift. And so you can see here, you know we're projecting about 667 million in revenue for Redshift. But if you look at the lighter arm bars, you can see that the service went from representing about 2% of you know, AWS revenue to about 1.5%. And we think some of that is because of Snowflake. And if we kind of, take a look at some of these KPIs you know, below those bar charts here, you know one of the things that we've been looking at is, you know how are longer-term customer spending and how are let's just say like newer customers spending, so to speak. So kind of just like organic growth or kind of net expansion analysis. And if you look at on the bottom there, you'll see, you know customers in our dataset that we looked at, you know that were there 3Q20 as well as 3Q19 their spend on AWS Redshift is 23%. Right? And then look at the bifurcation, right? When we include essentially all the new customers that onboard it, right after 3Q19, look at how much they're bringing down the spend increase. And it's because, you know a lot of spend that was perhaps meant for Redshift is now going to Snowflake. And look, you would expect longer-term customers to spend more than newer customers. But really what we're doing is here is really highlighting the stark contrast because you have kind of back to back KPIs here, you know between organic spend versus total spend and obviously the deceleration in market share kind of coming down. So, you know, something that's interesting here and we'll kind of continue tracking that. >> Okay. So let's maybe come back to this mass Colombo questions here. So the start with the orange side. So we're talking about Snowflake being 667 million. These are your estimates extrapolated based on what we talked about earlier, 1.5% of the AWS portfolio of course you see things like, they continue to grow. Amazon made a bunch of storage announcements last week at the first week of re-invent (indistinct) I mean just name all kinds of databases. And so it's competing with a lot of other services in the portfolio and then, but it's interesting to see Google BigQuery a much larger percentage of the portfolio, which again to me, makes sense people like BigQuery. They like the data science components that are built in the machine learning components that are built in. But then if you look at Snowflake's last quarter and just on a run rate basis, it's over there over $600 million. Now, if you just multiply their last quarter by four from a revenue standpoint. So they got Redshift in their sites, you know if this is, you know to the extent this is the correct number and I know it's an estimate but I haven't seen any better numbers out there. Interesting Sagar, I mean Snowflake surpassed the value of snowflakes or past service now last Friday, it's probably just in trading today you know, on Monday it's maybe Snowflake is about a billion dollars less than the in value than IBM. So you're saying snowflake in a lot of attention, post IPO the thing is even exploded more. I mean, it's crazy. And I presume that's rippled into the customer interest areas. Now the ironic thing here of course, is that that snowflake most of its revenue comes from AWS running on AWS at the same time, AWS and or Redshift and snowflake compete. So you have this interesting dynamic going on. >> Yeah. You know, we've spoken to so many CIOs about kind of the dynamics here with Redshift and BigQuery and Snowflake, you know as it kind of pertains to, you know, Redshift and Snowflake. I think, you know, what I've heard the most is, look if you're using Redshift, you're going to keep using it. But if you're new to data warehousing kind of, so to speak you're going to move to Snowflake, or you're going to start with Snowflake, you know, that and I think, you know when it comes to data warehousing, you're seeing a lot of decisions kind of coming from, you know, bottom up now. So a lot of developers and so obviously their preference is going to be Snowflake. And then when you kind of look at BigQuery here over to the right again, like look you're seeing revenue growth, but again, as a as a percentage of total, you know, GCP revenue you're seeing it come down and look, we don't show it here. But another dynamic that we're seeing amongst BigQuery is that we are seeing adoption rates fall versus this time last year. So we think, again, that could be because of Snowflake. Now, one thing to kind of highlight here with BigQuery look it's kind of the low cost alternative, you know, so to speak, you know once Redshift gets too expensive, so to speak, you know you kind of move over to, to BigQuery and we kind of put some price KPIs down here all the way at the bottom of the chart, you know kind of for both of them, you know when you kind of think about the net price per kind of TB scan, you know, Redshift does it pro rate right? It's five bucks or whatever you, you know whatever you scan in, whereas, you know GCP and get the first terabyte for free. And then everything is prorated after that. And so you can see the net price, right? So that's the price that people actually pay. You can see it's significantly lower that than Redshift. And again, you know it's a lower cost alternative. And so when you think about, you know organizations or CIO's that want to save some money certainly BigQuery, you know, is an option. But certainly I think just overall, you know, Snowflake is is certainly having, you know, an impact here and you can see it from, you know the percentage of total revenue for both these coming down. You know, if we look at other AWS database services or you mentioned a few other services, you know we're not seeing that trend, we're seeing, you know percentage of total revenue hang in or accelerate. And so that's kind of why we want to point this out as this is something unique, you know for AWS and GCP where even though you're seeing growth, it's decelerating. And then of course you can kind of see the percentage of revenue represents coming down. >> I think it's interesting to look at these two companies and then of course Snowflake. So if you think about Snowflake and BigQuery both of those started in the cloud they were true born in the cloud databases. Whereas Redshift was a deal that Amazon did, you know with parxl back in the day, one time license fee and then they re-engineered it to be kind of cloud based. And so there is some of that historical o6n-prem baggage in there. I know that AWS did a tremendous job in rearchitecting that but nonetheless, so I'll give you a couple of examples. If you go back to last year's reinvent 2019 of course Snowflake was really the first to popularize this idea of separating compute from storage and even compute from compute, which is kind of nuance. So I won't go into that, but the idea being you can dial up or dial down compute as you need it you can even turn off compute in the world of Snowflake and just, you know, you're paying an S3 for storage charges. What Amazon did last reinvent was they announced the separation of compute and storage, but what the way they did it was they did it with a tiering architecture. So you can't ever actually fully turn off the compute, but it's great. I mean, it's customers I've talked to say, yes I'm saving a lot of money, you know, with this approach. But again, there's these little nuances. So what Snowflake announced this year was their data cloud and what the data cloud is as a whole new architecture. It's based on this global mesh. It lives across both AWS and Azure and GCP. And what Snowflake has done is they've taken they've abstracted the complexity of the clouds. So you don't even necessarily have to know what you're running on. You have to worry about it any Snowflake user inside of that data cloud if given access can share data with any other user. So it's a very powerful concept that they're doing. AWS at reinvent this year announced something called AWS glue elastic views which basically allows you to take data across their entire database portfolio. And I'm going to put, share in quotes. And I put it in quotes because it's essentially doing copying from a source pushing to a target AWS database and then doing a change data management capture and pushes that over time. So it, it feels like kind of an attempt to do their own data cloud. The advantages of AWS is that they've got way more data stores than just Snowflake cause it's one data store. So was AWS says Aurora dynamo DB Redshift on and on and on streaming databases, et cetera where Snowflake is just Snowflake. And so it's going to be interesting to see, you know these two juxtaposing philosophies but I want it to sort of lay that out because this is just it's setting up as a really interesting dynamic. Then you can bring in Azure as well with Microsoft and what they're doing. And I think this is going to be really fascinating to see how this plays out over the next decade. >> Yeah. I think some of the points you brought up maybe a little bit earlier were just around like the functional limits of a Redshift. Right. And I think that's where, you know Snowflake obviously does it does very, very well you know, you kind of have these, you know kind of to come, you know, you kind of have these, you know if you kind of think about like the market drivers right? Like, let's think about even like the prior slide that we showed, where we saw overall you know, database growth, like what's driving all of that what's driving Redshift, right. Obviously proximity application, interdependencies, right. Costs. You get all the credits or people are already working with the big three providers. And so there's so many reasons to continue spending with them, obviously, you know, COVID-19 right. Obviously all these apps being developed right in the cloud versus data centers and things of that nature. So you have all of these market drivers, you know for the cloud database services for Redshift. And so from that perspective, you know you kind of think, well why are people even to go to a third party vendor? And I think, you know, at that point it has to be the functional superiority. And so again, like a lot of times it depends on, you know, where decisions are coming from you know, top down or bottom up obviously at the engineering at the developer level they're going to want better functionality. Maybe, you know, top-down sometimes, you know it's like, look, we have a lot of credits, you know we're trying to save money, you know from a security perspective it could just be easier to spin something up you know, in AWS, so to speak. So, yeah, I think these are all the dynamics that, you know organizations have to figure out every day, but at least within the data warehousing space, you are seeing spend go towards Snowflake and it's going away to an extent as we kind of see, you know growth decelerate for both of these vendors, right. It's not that revenue's not going out there is growth which is that growth is, it's just not the same as it used to be, you know, so to speak. So yeah, this is a interesting area to kind of watch and I think across all the other markets as well, you know when you think about document store, right you have AWS document DB, right. What are the impacts there with with Mongo and some of these other kind of third party data warehousing vendors, right. Having to compete with all the, you know all the different services offered by AWS Azure like the cosmos and all that stuff. So, yeah, it's definitely kind of turning into a battle Royal, you know as we kind of head into, into 2021. And so I think having all these KPIs is really helping us kind of break down and figure out, you know which areas like data warehousing are slowing down. But then what other areas in database where they're seeing a tremendous amount of acceleration, like as we said, database revenue is driving. Like it's becoming a bigger part of their overall revenue. And so they are doing well. It just, you know, there's obviously snowflake they have to compete with here. >> Well, and I think maybe to your point I infer from your point, it's not necessarily a zero sum game. And as I was discussing before, I think Snowflake's really trying to create a new market. It's not just trying to steal share from the Terra datas and the Redshifts and the PCPs of the world, big queries and and Azure SQL server and Oracle and so forth. They're trying to create a whole new concept called the data cloud, which to me is really important because my prediction is what Snowflake is doing. And they don't even really talk a ton about this but they sort of do, if you squint through the lines I think what they're doing is first of all, simplicity is there, what they're doing. And then they're putting data in the hands of business people, business line people who have domain context, that's a whole new way of thinking about a data architecture versus the prevalent way to do a data pipeline is you got data engineers and data scientists, and you ingest data. It's goes to the beginning of the pipeline and that's kind of a traditional way to do it. And kind of how I think most of the AWS customers do it. I think over time, because of the simplicity of Snowflake you're going to see people begin to look at new ways to architect data. Anyway, we're almost out of time here but I want to bring up the next slide which is a graphic, which talks about a database discussion that you guys are having on 12/8 at 2:00 PM Eastern time with Bain and Verizon who what's this all about. >> Yeah. So, you know, one of the things we wanted to do is we kind of kick off a lot of the, you know Q4 Q1 research or putting on the database spark. It is just like kind of, we did, you know we did today, which obviously, you know we're really going to expand on tomorrow at a at 2:00 PM is discuss all the different KPIs. You know, we track something like 20 plus database services. So we're going to be going through a lot more than just kind of Redshift and BigQuery. Look at all the dynamics there, look at, you know how they're very against some of the third party vendors like the Snowflake, like a Mongo DB, as an example we got some really great, you know, thought leaders you know, Michael Delzer and Praveen from verizon they're going to kind of help, or they're going to opine on all the dynamics that we're seeing. And so it's going to be a very kind of, you know structured wise, it's going to be very quantitative but then you're going to have this beautiful qualitative discussion to kind of help support a lot of the data points that we're capturing. And so, yeah, we're really excited about the panel you know, from, you know, why you should join standpoint. Look, it's just, it's great, competitive Intel. If you're a third party, you know, database, data warehousing vendor, this is the type of information that you're going to want to know, you know, adoption rates market sizing, retention rates, you know net price reservers, on demand dynamics. You know, we're going through a lot that tomorrow. So I'm really excited about that. I'm just in general, really excited about a lot of the research that we're kind of putting out. So >> That's interesting. I mean, and we were talking earlier about AWS glue elastic views. I'd love to see your view of all the database services from Amazon. Cause that's where it's really designed to do is leverage those across those. And you know, you listen to Andrew, Jesse talk they've got a completely different philosophy than say Oracle, which says, Hey we've got one database to do all things Amazon saying we need that fine granularity. So it's going to be again. And to the extent that you're providing market context they're very excited to see that data Sagar and see how that evolves over time. Really appreciate you coming back in the cube and look forward to working with you. >> Appreciate Dave. Thank you so much. >> All right. Welcome. Thank you everybody for watching. This is Dave Vellante for the cube. We'll see you next time. (upbeat music)