>>From the cube studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a cute conversation. Welcome to this cube conversation. I'm Lisa Martin pleased to be joined once again by the co CEO of mem sequel, Raj Verma, Raj, welcome back to the program. >>Thank you very much, Lisa. Great to see you as always. >>It's great to see you as well. I always enjoy our conversations. So why don't you start off because something that's been in the news the last couple of months besides COVID is one of your competitors, snowflake confidentially filed IPO documents with the sec a couple months ago. Just wanted to get your perspective on from a market standpoint. What does that signify? >>Yeah. Firstly, congratulations to the snowflake team. Uh, you know, I've, I have a bunch of friends there, you know, John McMahon, my explosives on the board. And I remember having a conversation with him about seven years ago and it was just starting off and I'm just so glad for him and Bob Mobileye. And, and as I said, a bunch of my friends who are there, um, they're executed brilliantly and, uh, I'm thrilled for that. So, um, we are hearing as to what the outcomes are likely to be. And, uh, it just seems like, uh, you know, it's going to be a great help. Um, and I think what it signifies is firstly, if you have a bit technology and if you execute well, good things happen and there's enough room for innovation here. So that is one, the second aspect is I think, and I think more importantly, what it signifies is a change of thought in the database market. >>If you really see, um, and know if my memory serves me right in the last two decades or probably two and a half buckets, we just had one company go public in the database space and that was Mongo. And, um, and that was in, I think October, 2017 and then, uh, two and a half years. So three years we've seen on other ones and uh, from the industry that we know, um, you know, there are going to be a couple that are going to go out in the next 18 months, 24 months as well. So the fact is that we had a, the iron grip on the database market for almost, you know, more than two decades. It was Oracle, IBM that a bit of Sybase and SAP HANA. And now there are a bunch of companies which are helping solve the problems of tomorrow with the technology of the month. >>And, uh, and that is, um, that is snowflake is a primary example of that. Um, so that's a, that's good change. God is good. I do think the incumbents are gonna find it harder and harder going forward. And also if you really see the evolution of the database market, the first sort of workloads that moved to the cloud with the developer workloads and the big benefactor that that was the no secret movement and one company that executed in my opinion, the best was Mongol. And they were the big benefactor of that, that sort of movement to the cloud. The second was the very large, but Moisey database data warehouse market, and a big benefactor of that has been snowflake big queries, the other one as well. However, the biggest set of tsunami of data that's we are seeing move to the cloud is the operational data, which is the marriage of historical data with real time data to give you real time insights as, or what we call the now are now. >>And that's going to be much, much bigger than, uh, than both the, you know, sequel or the developer data movement and the data warehouse. And we hope to be a benefactor of that. And then the shake up that happens in the database market and the change that's happening there, isn't a vendor take on market anymore, and that's good because you don't then have the stranglehold that Oracle had and you know, some of the ways that are treated as customers and help them to run some, et cetera, um, yeah. And giving customers choice so that they can choose what's best for the business is going to be, it's going to be great. And me are going to see seven to 10 really good database companies in large, in the next decade. And we surely hope them secret as one of them of, we definitely have the, have the potential to be one of them. >>You have the market, we have the product, we have the customers. So, you know, as I tell my team, it's up to us as to what we make of it. And, um, you know, we don't worry that much about competition. You did mention snowflake being advantage station. We, yeah, sure. You know, we do compete on certain opportunities. However, their value proposition is a little more single-threaded than ours. So they are more than the Datavail house space are. Our vision of the board is that, uh, you know, you should have a single store for data, whether it's database house, whether it's developer data or whether it's operational data or DP data. And, uh, you know, watch this space from orders. We make somebody exciting announcements. >>So dig into that a little bit more because some of the news and the commentary Raj in the last, maybe six weeks since the snowflake, um, IPO confidential information was released was, is the enterprise data warehouse dead. And you just had a couple of interesting things we're talking about now, we're seeing this momentum, huge second database to go public in two and a half bigots. That's huge, but that's also signifying to a point you made earlier. There's, there's a shift. So memes SQL isn't, we're not talking about an EDW. We're talking about operational real time. How do you see that if you're not looking in the rear view mirror, those competitors, how do you see that market and the opportunities? >>Yeah, I, I don't think the data warehouse market is dead at thought. I think the very fact that, you know, smoke makers going out at whatever valuation they go out, which is, you know, tens of billions of dollars is, um, is a testimony to the fact that, you know, it's a fancy ad master. This is what it is. I mean, data warehouses have existed for decades and, uh, there is a better way of doing it. So it's a fancy of mousetrap and, and that's great. I mean, that's way to money and it's clearly been demonstrated. Now what we are saying is that I think that is a better way to manage the organization's data rather than having them categorized in buckets of, you know, data warehouse, data developer, data DP, or transactional data, you know, uh, analytical data. Is there a way to imagine the future where there is one single database that you can quit eat, or data warehouse workloads for operational workloads, for OLTB work acknowledge and gain insights. And that's not a fancier mousetrap that is a data strategy reimagine. And, uh, and that's our mission. That's our purpose in life right now and are very excited about it's going to be hard. It's not, it's not a given it's a hard problem to solve. Otherwise, if you can solve it before we have the, uh, we have the goods to deliver and the talent, the deliberate, and, um, we are, we are trying it out with some very, very marquee customers. So we've been very excited about, >>Well, changing of the guard, as you mentioned, is hard. The opposite is easy, the opposite, you know, ignoring and not wanting to get out of that comfort zone. That's taken the easy route in my opinion. So it seems like we've got in the market, this, this significant changing of the guard, not just in, you know, what some of your competition is doing, but also from a customer's perspective, how do you help customers, especially institutions that have been around for decades and decades and decades pivot quickly so that the changing of the guard doesn't wipe them out. >>Yeah. Um, I actually think slightly differently. I think changing of the guard, um, wiping out a customer is if they stick or are resistant to the fact that there is a change of God, you know, and if they, if they hold on to, as we said in our previous conversation, if you stick onto the decisions of yesterday, you will not see the Sundays of tomorrow. So I do think that, uh, you know, change, you have a, God is a, is a symbolism, not even a symbolism as a statement to our customers to say, there is a better way of doing, uh, what you are doing to solve tomorrow's problem. And then doesn't have to be the Oracles and the BB tools and the psychosis of the world. So that's, that's one aspect of it. The second thing is, as I've always said, you're not really that obsessed about, uh, competition. >>The competition will do what they do. Uh, we are really very focused on having an impact in the shortest period of time on our customers and, uh, hopefully a positive impact. And if you can't do it, then, you know, I've had conversations with a few of them saying, maybe be not the company for you. Uh, it's not as if I have to sort of, software's a good one. I supply to the successful customers in the bag to do the unsuccessful with customers. The fact is that, you know, in certain, certain places there isn't an organizational alignment and you don't succeed. However, we do have young, we have in the last 14 months or so made tremendous investments into really ease of use of flexibility of architecture, which is hybrid and tactile, and that shrinking the total time to value for our customers. Because if I, if I believe you, if you do these three things, you will have an impact, a positive impact on the customer, in the sharpest, uh, amount of time and your Lindy or yourself. And I think that is more important than worrying needlessly about competition. And then the competition will do what they do. But if you keep your customers happy by having a positive impact, um, successes, only amount of time, >>Customers and employees are essential to that. But I like that you talked about customer obsession because you see it all over the place. Many people use it as descriptors of themselves and their LinkedIn profiles, for example, but for it actually to be meaningful, you talked about the whole objective is to make an impact for your customers. How do you define that? So that it's not just, I don't want to say marketing term, but something that everyone says they're customer obsessed showing it right within the pudding. >>It's easy to say we are customer obsessed. I mean, this organization is going to say we don't care about our customer. So, you know, of course we all want our customers to be successful. How do you, that's easy, you know, having a cultural value that we put our customers first is, was easy, but we didn't choose to do that. What we said is how do you have an impact on your customer in the shortest amount of time, right? That is, that is what you have. I'm sequel and Lee have now designed every process in mem sequel to align with that word. If, if that is a decision that we have to make a B essentially lenses through the fact of what is in the best interest of our customer and what will get us to have an impact, a positive impact on the customer in the shortest amount of time, that is a decision, which is a buy decision for us to make. >>A lot of times it's more expensive. It's a, a lot duffel. It stresses the, um, the, the, the organization, um, and the people in it. But that's, uh, that's what you have to do if you are. Um, if you are, you know, as, as they say, customer obsessed, um, it is, it's just a term which is easy to use, but very difficult to put here too. And we want to be a tactic. It right to be, we are going to continue to learn. It's a, it's not a destination, it's a journey. And we continue to take decisions and refine our processes do, as I said, huh, impact on our customers in the shortest amount of time. Now, obsessiveness, a lot of times is seen as a negative in the current society that we live in. And there's a reason for that because the, they view view obsession, but I view obsession and aggression is that is a punishing expression, which is really akin to just being cruel, you know, leading by fear and all the rest of it, which is as no place in any organization. >>And I actually think that in society at large, nothing, I believe that doesn't have any place in society. And then there's something which I dumb as instrumentalists, which is, this is where we were. This is where we are. This is where we are going and how do we track our progress on a daily, weekly, monthly basis? And if we, aren't sort of getting to that level that we believe we should get to, if our customers, aren't seeing the value of dramas in the shortest amount of time, what is it that we need to do better? Um, is that obsession, our instrumental aggression is, is, is what we are all about. And that brings with it a level of intensity, which is not what everyone, but then when you are, you know, challenging the institutions which have, uh, you know, the also has to speak for naked, it's gonna take a Herculean effort to ask them. And, uh, you know, the, the basically believed that instrumental aggression in terms of the, uh, you know, having an impact on customer in the shop to smile at time is gonna get us there. And a, and B are glad to have people who actually believe in that. And, uh, and that's why we've made tremendous progress over the course of last, uh, two years. >>So instrumental aggression. Interesting. How you talked about that, it's a provocative statement, but the way that you talk about it almost seems it's a prescriptive, very strategic, well thought out type of moving the business forward, busting through the old guard. Cause let's face it, you know, the big guys, the Oracles they're there, they're not easy for customers to rip and replace, but instrumental aggression seems to kind of go hand in hand with the changing of the guard. You've got to embrace one to be able to deliver the other, right. >>Yeah. So ducks, I think even a fever inventing something new. Um, I mean, yeah, it just requires instrumental aggression, I believe is a, uh, uh, anchor core to most successful organizations, whether in IP or anywhere else. That is a, that is a site to that obsession. And not, I'm not talking about instrumental aggression here, but I'm really talking about the obsession to succeed, uh, which, uh, you know, gave rise to what I think someone called us brilliant jerks and all the rest of it, because that is the sort of negative side of off obsession. And I think the challenge of leadership in our times is how do you foster the positivity of obsession, which needs to change a garden? And that's the instrumental aggression as a, as a tool to, to go there. And how do you prevent the negative side of it, which says that the end justifies the means and, and that's just not true. >>Uh, there is, there is something that's right, and there's something that's wrong. And, uh, and if that is made very clear that the end does not justify the meanings, it creates a lot of trust between, um, Austin, our customers, also not employees. And when their inherent trust, um, happens, then you foster, as I said, the positive side of obsession and, um, get away from the negative side of obsession that you've seen in certain very, very large companies. Now, the one thing that instrumental aggression and obsession brings to a company is that, uh, it makes a lot of people uncomfortable, and this is what I continue to tell. Um, our, our employees and my audience is, um, you know, be comfortable being uncomfortable because what you're trying to do is odd. And it's going to take a, as I say, a Herculean effort. So let's, uh, let's be comfortable being uncomfortable, uh, and have fun doing it. If there's, uh, how many people get a chance to change, uh, industry, which was dominated by a few bears and have such a positive impact, not only on our estimates, but society at large. And, uh, I think it's a privilege. Pressure is a privilege. And, uh, I'm grateful for the opportunity that's been afforded to me and to my colleagues. And, uh, >>It's a great way. Sorry. That's a great way of looking at it. Pressure is a privilege. If you think about, I love what you said, I always say, get, you know, get comfortably uncomfortable. It is a heart in any aspect, whether it's your workouts or your discipline, you know, working from home, it's a hard thing to do to your point. There's a lot of positivity that can come from it. If we think of what's happening this week alone and the U S political climate changing of the old guard, we've got Kamala Harris as our first female VP nominee and how many years, but also from a diversity angle, from a women leadership perspective, blowing the door wide open. >>It's great to see that, um, you know, we have someone that my daughter's going to look up to and say that, uh, you know, yes, there is, there is a place for us in society and we can have a meaningful contribution to society. So I actually think that San Antonio versus nomination is, um, you know, it's a simple ism of change of God, for sure. Um, I have no political agendas, um, at all. Then you can see how it pans out in November, but the one thing is for sure, but it's going to make a lot of people uncomfortable, a change of God, or this makes a lot of people. And, and, uh, and you know, I was reflecting back on something else and in everything that I've actually achieved, which is, is something I'm proud of. I had to go through a zone, but I was extremely uncomfortable. >>Uh, Gould only happens when you have uncomfortable, um, girl to happens in your conference room. And, um, whether it's, um, you know, running them sequel, uh, or are having a society change, uh, if you stick to your comfort zone, you stick to your prejudices and viruses because it's just comfortable there, there's a, uh, wanting to be awkward. And, uh, and, and I think that that's that essential change of God. As I said, at the cost of repeating myself will make a lot of people uncomfortable, but I honestly believe will move the society forward. And, uh, yeah, I, um, I couldn't be more proud of, uh, having a California San Diego would be nominated and it's a, she brings diversity multicultural. And what I loved about it was, you know, we talk about culture and all the rest of it. And she, she was talking about how our parents who were both, uh, uh, at the Berkeley when she was growing up, we were picking up from and she be, you know, in our, in our prime going to protests and Valley. >>And so it was just, uh, it was ingrained in her to be able to challenge the status school and move the society forward. And, uh, you know, she was comfortable being uncomfortable when she was in that, you know, added that. And that's good. Maybe not. I think we sort of, uh, yeah, I, yeah, let's see, let's see what November brings to us, but, um, I think just a nomination has, uh, exchanged a lot of things and, uh, if it's not this time, it can be the next time, but at the time off the bat, but you're going to have a woman by woman president in my lifetime. Um, that's um, I minced about them, uh, and that's just great. >>Well, I should hope so too. And there's so many, I know we've got to wrap here, but so many different data points that show that that technology company actually, companies, excuse me, with women in leadership position are significantly 10, 20% more profitable. So the changing of the guard is hard as you said, but it's time to get uncomfortable. And this is a great example of that as well as the culture that you have at mem sequel Raja. It's always a pleasure and a philosophical time talking with you. I thank you for joining me on the cube today. >>Thank you me since I'm just stay safe, though. >>You as well for my guest, Raj Burma, I'm Lisa Martin. Thank you for watching this cube conversation.

>> Announcer: From the CUBEs Studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a CUBE Conversation. >> Welcome to this CUBE Conversation, I'm Lisa Martin. Today talking with the co CEO of MemSQL, Raj Verma. Raj, eelcome back to the CUBE. >> Thank you, Lisa. Good to see you again as always. >> You as well. So we're living in a really strange time, right? There is disruption coming at us from every angle we're used to talking about disruptors and technology as technology innovations like Cloud, for example, but now we've got this other disruption, this catalyst for more disruption with COVID-19. I wanted to ask you though, as we see so much changing in the business world for long storied businesses filing for chapter 11. What, why do companies get disrupted and how can they actually become... How can a company to become a disruptor? >> I think disruption is a tale of innovation, really, innovation from the incumbent or lack there off. And the fact that, you know, incumbents become a lot more inward focused. They become more about doing more of what got them to be successful, more process focused and outcome focused. And the disruptors are essentially again, all about innovation and all about solving the customer's problems for today and for tomorrow. So I do think disruption is at its very core, two tales of innovation, one cautionary and the other somehow legendary. And we see that in the Valley all the time. You see the favorite innovators of a decade ago, just limping along now and just being completely leapfrogged by the innovators of today. And that's really what the Valley is known for. I do think that a big part of being a disruptor or being disrupted, as I said, you know, two sides of the same sort of coin or a double edged sword really, I think for a disruptor, it's all about challenging the status quo and to be effectively able to challenge the status quo, you need a team which is United in purpose and in passion about waking up every morning and trying to, you know, as I said, challenge the status quo and not accept just because things were being done the way they were being done. And that's what tomorrow should be. I think that's really important. And I think there is a total elements to being disrupted or, you know, aiding the disruptors, which is a catalyst event of any sort that might be. You know, it was the internet for some, I mean, some really called itself, the network is a computer, one of my favorite companies and, you know, Scott G. McNealy, someone that I greatly admire and I've got to know over the years and they were preaching this gospel for 15 years and then the internet hit and they just went, they became a rocket ship and you know, Cisco, the same thing happened. A lot of companies and you know, one in particular that we even worked for together, at least I got completely disrupted and blindsided by the Cloud. I do believe that one such a disruptor right now, or one such catalyst, which will disrupt business. And you alluded to that a little while ago, is COVID-19 and the data deluge or the tsunami of data that our accompanies it you know, I was just talking to a friend and he said, you know, we are now living really in 2023, COVID-19, four months of living in COVID-19 as kind of ended up propelling us three years forward in terms of the problems that we had three years to solve, we need to solve it now. And I think, yeah, the innovation, a team that challenges the status quo and a catalyst is what disrupts companies and what aids disruptors. >> You brought up a really good point though, that there's such a huge component of the team to be able to not just react quickly, but be creative enough and confident enough to challenge that status quo. There's a lot of folks who are very comfortable in their swim lanes. memSQL has been a disruptor in the database space, but I think that team that you hit on is really essential. Without that, and without the right folks really focused together, the disruptors are going to be disrupted. >> I agree with you wholeheartedly. I think, I often say it town halls or in private meetings that we are in the talent business. We are only as good as our teams. No, if ands and buts about it. If not, you know, united in 4% in mission have immense diversity of thought and be okay to change our minds when presented with empirical evidence of something different, we will never succeed we will never disrupt. But I think a majority of majority of the population wakes up and it looks for evidence that further makes them comfortable in the prejudices and the biases that they have. And now whether that's in your professional life or in your personal life, that's majority of the population. That's why, you know, majority of the population does not innovate. If you have the courage to say that I was wrong, but the status quo is just not enough, there is a better way out there it's hard, but there is a better way out there. And that is going to add phenomenal value to our customer base, to the world at large. Now that's the kind of people that we are looking for. And we are very lucky to have. And if you are one of them, and if you really do want to make a dent in the database, universe, I know of a company. So give me a call (laughs) >> Well, challenging the status quo is hard, like you said. 'Cause getting up every day and just assuming things are going to be the same and align with your thought process, that's easy, but being willing to, as you said, be courageous is a whole other ball game. And as right now, data from yesterday is too late. You know, not only are we living in an on-demand culture, but now with the disruption, the microbial disruption data from yesterday, isn't good enough to help solve tomorrow's problems. Neither is yesterday's technology. How is memSQL helping your customers even, break the status quo? >> Lisa that's really most of the conversations I tend to have with CIO's and CEO's and given the digital work environment that we live in, there is a lot more availability because of lack of travel and other social obligations. So, you know, I have a number of these conversations with CEOs and CIOs on a weekly basis. And one of the things that most CEO's and CIO's ask for is large, how can I get the now, now? As I was saying that, you know, the COVID-19 crisis, so as to speak or event as really spurred and catalyzed, a lot of these digital innovations and something that could be for, you know, another year and another two years, maybe, or even three years needs to be done now. And the need for the now, has never been greater. Whether it be the responsiveness of your AI ML tools, or how close can we actually put a transaction? Do we, have AI ML Layer for near real time or other real, real time insights as to what's going on in the business? Because the one data point that you have, which can help you make informed decisions in this digital world is data. So how do you do it at speed? How do you do it at scale? How do you do it in a flexible environment? Is the need for the hour. Now, another aspect that they talk about is don't give me a fancier mousetrap as my CPO, the gentleman that we just hired from Google BigQuery is one of the founding members and head their engineering and product management even. And he actually put it really well. He said, you know, I, haven't come here to build a fancier mousetrap. I've come here to build in novel, new way of solving a customer's data problems and delivering the now when the customer needs us. As I said in the fastest, most economical, flexible, secure manner. That is in my opinion, the biggest need for the hour and someone who can deliver that, is going to be extremely successful in my humble opinion, because let me ask a question of any CIO or CEO or whoever is watching here. That if we could say that we would juice up your AI ML dashboard reports, you know, real time dashboards 4X in four weeks. How many of you are going to say no? How many of you are going to say that from a response time of 15 minutes, if he could give you subsecond response times like we've done for many of our vendors in the last three to four weeks, how many of the world would say, no, I stick to my slow dashboards. And that's what we are enabling Lisa, and that's why I am superbly excited about where we are and where we are headed. >> So companies that can work with innovative technology like memSQL, whether it be a retailer or a telco, for example, or healthcare organization, the companies that are going to be able to get the data, to get the now, now are those the next disruptors? >> Beyond doubt, beyond doubt. And we are already seeing like you and I were talking about defaulter show and we have you ever seen a lot of bankruptcies, amazing amount of bankruptcies for companies who did not have the infrastructure for delivering the now, now. And they essentially were feeding their own prejudices and biases by saying, oh no, I made the decision on our goal 15 years ago and I'm just going to stick by it because they're the biggest baddest database yet. But, they can solve the now problem. And guess what happened to your company? And those who were courageous enough to say, yeah, it's some of the problems of yesterday. If you had an unprecedented times and it would take a very hard and deep look and something which will shake up the status quo to be able to deliver the tomorrow for our company. For our company, to see the sunrise of tomorrow, we have to be courageous enough to question our prejudices and bias. And those are the companies which will not only survive, but they will thrive. We were talking to, you know, naturally I have a lot of conversations with investors here. You know, the SAS technology areas, is the new gold now, I mean, that's one segment of the market that's held up because that is what is enabling the courageous enterprises to deliver the tomorrow and help the employees and the customers see the sunrise of tomorrow. And those who don't, they just don't see the sunrise tomorrow. >> I know working and talking with customers is near and dear to your heart. How do you help businesses, like you mentioned a whole bunch of really big brands have filed for chapter 11 recently, brands that we've all known for decades and decades, maybe it's, you know, team, that's just not innovative enough. Like you said, Oracle, we're going to use it. How does memSQL come in? How do you, when you're talking with those customers who might be on the brink of not surviving, how do you help them from a, like a thought diversity perspective to understand what they need to do to not just survive but thrive? >> Yeah, you know, I would like to take too much of the credit here that we can be saviors of companies. The company, and the executive team needs to know their why, and we can deliver the how and we can deliver it faster, cheaper in a more secure fashion. But the courage of saying that if we don't change, we rather die and we will not see the sunrise of tomorrow has to come from the organizations. And I think that's the starting point. And we give them enough empirical evidence that there is a better way out there. And we were working with a very, very large electronic retailer. And for the retail telemetry as you pointed to, they could only get telemetry of their stores all over the world on a every day basis. I think I ran the report every 16 hours and that was just not enough of them. And they've got a very involved CEO. And they wanted sub-second response times. And the team actually taught it was not possible. And continue to say that to the executive team. Till they came across us and he showed that the 16 hour time difference was now 0.8 seconds and they jumped on it. And now their dashboards are powered by memSQL. And instead of running reports, every 16 hours, they run it every second. So you can query your retail telemetry every second. And those kinds of courageous asks and a team saying just because I made a decision two years ago now is the time actually for those teams to say, it was a different world. I made the right decision two years ago, but in the new world, there is a better way of doing things and better way of securing a future and delivering the now. And that's where we come in and we've helped a number of customers. And I actually urge a lot of the organizations who are looking for the now to have that introspective conversations internally. >> So how do you advise companies, whether it's your prospects or customers, or even memSQL to build a team that's poised for disruption? Is it generational? Is it more than that? >> I don't think it's generational at all. I don't think it's an age issue of, you know, seeing the future or having the ability to seek honors. I think it's ultimately, and I know I'm using this term a lot, it is... I've always found that very bright, intelligent self aware individuals have the ability to question their own prejudices and biases, and it requires courage and intelligence and all the rest of it. But I think that is the key that isn't that much more. And what greater impetus or reward would a company want than survival? Sometimes survival is a great impetus for innovation and we are seeing that happen a lot. And those that aren't, then don't do that. However, that said, teams which have focused from early on, on diversity of thought on, you know, different perspectives, just their DNA is more open to challenging the status quo. And that's where the organizations who've had the right cultural values of it's okay to question the status quo, it's okay to have diverse opinions, even though they drive a knife through your prejudices and biases at an organizational level and at an individual level, that DNA helps companies is coming in and paying off, you know, in spades because that cultural thought, you know, Think Tank is driving the new age of innovation and in doing so survival. So I do think that the companies that invested in the right cultural values, the right war shoes, that's being off in spades. And I think that those teams we are seeing, and those organizations with that kind of culture are jumping on the bandwagon of questioning the status quo, of using the technology of tomorrow to solve tomorrow's problems and not be steeped in heritage and even see those companies. And you can see who they will be actually I mentioned them, but they won't survive. And up here you're seeing a whole host of other companies who are so still sort of steeped in justifying that their original thought was the right thought, and I bet my bottom dollar, they don't survive. >> Next question for you, how have you been able to build your executive team at MemSQL? You've been able to build that diverse culture and how has it shaped your leadership style? >> Yeah, you know, I don't think we've... It's not as if we've gotten there, it's a constant journey and it's just something that starts off by saying, you know, we are not going to have a know-it-all culture, but we are going to have a learn-it-all culture. You know, we are going to listen and we are going to think, consider and respond. For me, diversity was a given, you know, I sort of grew up around diversity. Some of the influences of my life that have made me the person I am today came from a viewpoint of, you know, of women, you know, I had some very, very strong female influence in my life. And as I've said repeatedly, I wouldn't have been who I am or half the person I am today without that influence. So for me, it's a very natural sort of progression to have that diversity of thought and opinion as a, you know, weaved into the very fiber of any organization that I've been apart of. And we do that in a manner where we, it's not just good enough to say, we will hire the best team. I don't think that is the way that you are going to sort of address the historical imbalance, which has resulted in very single threaded thought cultures in organizations. We make it a point that at the top end of the funnel, of course, we, in our best candidate, right? However, at the top end of the funnel, we almost know legislate that there has to be X percentage of candidates who are, you know, diverse candidates. So candidates from minorities and then let the best, you know, candidates sort of get qualified. And also if there are two candidates who are equally qualified, then, you know, we encourage someone with a lot more diversity and, you know, to come onto the team. And ultimately that drives a lot of I've thought leadership in the organizations and helps us manage our blind spots a lot better. And I have so many examples of that. The amount of innovation that happens because of these working groups, which are very diverse working groups, is just, you know, unmeasurable. And we've been extremely clear about the fact of what candidates would survive, thrive, and enjoy being at memSQL. And those are the candidates who are here to build something build something for the ages, do right by each other and by the customer. You know, we don't accept the unacceptable challenge, the status quo, if you feel strongly about something stand up and your voice will be heard. You know, just because things were being done a certain way doesn't mean it has to be done the same way. And I'm very proud, very, very proud of the team that we have built and the one that we are building and, you know, it's a team that is united in purpose and very diverse in thought. And I have become a better person and a better professional with all the diversity of thought and the learnings that we have had as a consequence of that over the last a year and a half or so. And that is the cornerstone of what we are building here at memSQL and Lisa, you and I worked with one such individual, who's just made an unbelievable difference in our organization. And lastly, I think, you know, just on a personal note, the diversity angle becomes that much closer to my heart. I'm a father of two lovely girls and two lovely boys. And I just, you know, it's personal to me that if I can't leave the tech industry a better place for my daughters, then I found it, for that matter, even for my sons. But I think, you know, the daughters had their historical, you know, debts to pay. Then I don't think I would have really achieved the success that we all, as a team are hoping for. So yeah, this is extremely personal. >> And thank you for sharing all your insights. You tell a really interesting story. You know, we started talking about disruption, disruptors, how not to be disrupted, how to become a disruptor. And really some of the things that you talk about, it all really kind of comes down to the team, the DNA of the organization, and that thought diversity being courageous to break the status quo. Raj, I wish we had more time 'cause we could keep going on this, but thank you for sharing your insights. It's been really interesting conversation. >> Thank you, Lisa, it's been great to see you and stay safe and well. >> Likewise. For my guests, Raj Verma. I'm Lisa Martin, you're watching this CUBE Conversation. (soft music)

>> Narrator: From theCUBE's studios in Palo Alto, in Boston, connecting with thought leaders all around the world, this is theCUBE conversation. >> Welcome to this CUBE conversation. I'm Lisa Martin. And today joining me is CUBE alumni, the co-CEO of Mem-SQL, Raj Verma. Raj, welcome back to theCUBE. >> Thank you Lisa. It's great to be back, and it's so good to see you. >> Likewise. So since we last saw each other, a lot of changes going on everywhere. You're now the co-CEO of Mem-SQL. The CEO's role is changing dramatically in this year, and the last few months. Talk to us about some of those changes. >> Yeah. Where do I even start? I was just listening to something or watching something, and it said, in leadership one thing that they never tell you is, you don't find the event, the event finds you. And you know, it was four and a half, almost five months ago, we were at our SQL and if someone had said to me then that we'll be quarantined for five months following that, and most, more likely seven months, I probably wouldn't have believed them. And if I did, I would have gone and start crying. It's been sort of a lot of change for us. The one thing is for sure, as the CEO, I probably made more compelling decisions in the last four months than I probably made in the year prior to that. So there is a lot of decisions, important decisions that are being made now. I think the thing that's impressed me the most about just the human race per se in the last four and a half, five months is the resilience. The adaptability of just the community, and the race at large. There is a lot of goodness that we've seen happen. I think that is a greater appreciation for the life that we sort of had. And I think when everything does one day come back to normal, we would be a lot more appreciative and nicer just as individuals. Now as CEO, I think the first order of duty for me was to embrace our employees and my colleagues. It's a drawing set of circumstances for them, worrying about their health, the health of their aged parents, of their families well being, and whether they have a job or not, and how the economic environment would pan out. So I think it was just a ... My number one priority at the start and continues to be till today were our colleagues and the employees of Mem-SQL. And the first few decisions that we made were 100% employee centric. None of the big ones that was taking the pledge of no retrenchments or no workforce reduction for 90 days to begin with. And we've continued that. We haven't really reduced any employee headcount at all. The second was to go in turn embrace our customers and deliver to the promise that we had in normal times, and help them get back to as much of a normalcy as they could. And the third was to do whatever we could, to use our technology, our efforts, our resources, to help society at large. Whether it was to track and tracing projects that we did for a large telco or a telco in the Middle East, a telco in Asia. And we've put our resources there. Our aura is to just using our platform to heighten public awareness around Juneteenth, and other sort of social issues. Because I think in times of almost societal isolation, using your platform and being a voice for what you stand for is more important than ever before. And those were really the three things that stand out apart from just normal decisions, normal decisions that you make to make sure that you are well-capitalized, that you have enough cash to run your business, that all the fundamentals of the business are sound. So yeah. >> So lots of decisions on a massively accelerated scale, more than the last 10 years. But big strategic decisions made in a quick time period for employees, for customers, for how do we use our platform, what is the key that you need in order to make those decisions, as strategically as you can like that? >> Yeah, you got to lens it through, what is the why of your organization, Our advice is very simple, we want to be the platform of decision making, or what we call the platform of now. Where we can marry historical information with the real time operational data being streamed in to your organization, and be able to deliver up reports and insights that you need for quick decision making in other organizations. So delivering up the now. Internally, when sort of presented with options to make decisions, the lens that I've used is, what's in the best interest of our employees, what's in the best interest of our customers and what is in the best interest of our investors and stakeholders. And if you apply that lens, the decisions aren't actually that difficult. You will never have a 100% of the data that you need to make a decision. So, lensing it through your priorities becomes extremely, extremely important. The other aspect that having data though, having said that, having data now to make decisions is more important than ever before. Because you do not have the sort of physical cues to depend on or clues to depend on. I'm still finding it hard to read the digital clues on Zoom or Google Hangouts or Teams, or what have you. So you just have to have a very steeped-in data decision making, marrying it with, what is it that you stand for as an organization? And the third vector that we've put to this is very simple. We as an organization stand fort authenticity. We like to simplify rather than complicate. And we need to demonstrate courage over comfort. And those are the other vectors that we use to make the majority of our strategic decisions. >> So if data... For years, you've heard this all over the tech circuit, Raj, data's the new gold, data's the new oil. Now you're saying it's even more important than ever in this unprecedented time. How does Mem-SQL help customers get access to as much data as they can to make really fast strategic decisions. To not just survive in this mode, but thrive? >> Yeah, I think two questions, what is the data and the value of data? And you're absolutely right. The value of data now is more than ever before. And also the amount of data that is now being produced is more than ever before. So it's actually a pretty, pretty nontrivial issue to solve. And I think the first thought is that you can't solve the problems of tomorrow with the technology of yesterday. You cannot solve the problems of tomorrow, using a technology that was built for a different era, which was built 45 years ago, 25 years ago. And you know, some of the tenants of the technology are still steeped in. Let's just call it heritage. So first and foremost, the realization that the problems of tomorrow need the tools of now and the talent of now, and the management of now, and the leadership of now to solve it, is paramount. What we do as a technology company, and a lot of companies in our genre called hard tech is exactly that. It's hard tech. It takes a lot of talent, it takes a lot of time, resources, money, clarity of thought to build something which will solve the problems of today and of tomorrow. And today the challenges we actually have is, the real time nature of decision making of interactions, of experience, of security, of compliance, are more exaggerated than ever before. And how do you marry real time information with historical information in the cheapest, easiest to deploy flexible architecture is of paramount importance. And that's exactly what we do, Lisa. We give you a database that is arguably the fastest in the world from a query speed standpoint, the scale's more than any other database in our genre, it has data governance by virtue of us being sequel, it's hybrid multi-cloud so it doesn't lock you in, and it's a among the easiest to use. So, I don't know what the future would bring, Lisa, but one thing I can assure you is, there are five things which wouldn't change which is developers would prefer faster over slow, cheaper over fast, flexible over rigid, ease of use over complexity of use, and a secure, safe platform versus the alternative. And if you have those five tenants, I think you'd be pretty well-versed with solving the problems of today and tomorrow. >> You mentioned real time a minute ago, and that's, I think right now during the COVID-19 crisis, there's nothing that highlights the urgency of which we need information real time. It's not going to help us if it's 24 or 48 hours old. How does Mem-SQL deliver real time insights to customers, whether it's a telecommunications company looking to do contact tracing or a bank? >> Yeah. So let me start with a couple of examples, a very large telephone provider, telecommunication providers in the States, uses us for metric telemetry. So how many calls did Lisa make, how many texts did she send, what time? Without purpose, the privacy attached to it. When did she experienced a call drop, what's the coverage at her home, is the sort of a mobile tower close to her place going to go down, and what would be the inconvenience? All of that. So copious amounts of data required to really deliver a customer experience. And it's a hard enough problem because the amount of data as you can imagine is extremely, extremely, extremely large. But when COVID-19 struck, the data became that much more important, because now it was a tool that you could use as a company to be able to describe or follow cohorts of subscribers in hotbeds like New York at that time. And see which States they were actually, let's call it "fleeing" to or moving to. And to be able to do that in near real time was not good enough, because you had to actually do it in real time. To be able to track where the PPEs work in near real time was not good enough, it had to be real time. And to track where the ventilators were in near real time wasn't good enough. You just needed to do that. And I think that probably is one of the biggest examples of real time that we have in the recent past, and something that we are most proud of. How did we do that? We built this hard tech based on first principles. We didn't try and put a lipstick on a pig, we didn't try and re-architect a 45-year-old technology or a 15-year-old technology. We just said that if we actually had a plain sheet of paper, what would we do? And we said, the need of the future is going to be fast over slow, as I said, you know, cheap or expensive, flexible over rigid, safe over the other alternatives and ease of use. And that's what we've built. And the world will see the amount of difference that we make to organizations and more importantly to society, which is very near and dear to my heart. And yeah, that's what I'm extremely proud, and optimistic about. >> Talk to me about some of the customer conversations that you're having now. I've known you for many years. You're a very charismatic speaker. As you were saying a few minutes ago, it's hard to read body language on Zoom and video conferences. How are those customer conversations going, and how have they changed? >> A lot has changed. I think there are a couple of aspects that you touch upon. One is just getting used to your digital work day. Initially we thought it was two weeks and it's great. You don't have to commute and all the rest of it. And then you started to realize, and the other thing was, everyone was available. There's no one who was traveling. There were no birthday parties. There's no picking up a kid from baseball or school or swimming or whatever. So everyone was available. And we were like, "Wow, this is great, no commute, everyone's available. Let's start meeting and interacting." And then you realize after a while that this digital workday is extremely, extremely exhausting. And if you weren't deliberate about it, it can fill your entire day, and you don't get much done. So one of the things that I've started to do is, I don't get on a digital call unless of course it's a customer or something extremely, extremely important till 11:00 AM. That's my thinking time, it's just, you know, eight to 11 is untouched and people I want to call rather than my calendar describing what my priorities should be. And it's the same thing for our customers as well, in a slightly different way. They are trying to decide and come to terms with not only what today means to them, but what the realities of today means for tomorrow. I'll give you an example of a very, very large bank in the United States, a rich consumer bank, which is essentially believed in the fact that customer relations were the most and customer relationship managers were the most important role for them. They are thinking about moving to bots. So the fact that you would be interacting with bots when you reach your bank is going to be a reality. There is no if and and buts about it. A very, very large company providing financial services, is now trying to see, how do you make the digital platforms more responsive? How do you make analytics foster more responsive and collaborative? Those are really the focus of C-suite attention, rather than which building do we call after our company and add towers to it. Or what coffee machine should we buy for the organization, or should we have a whiskey bar or a wine bar in our office? Now the ... Just the mundaneness of those decisions are coming up. And now the focus is how do we not only survive, to your point, Lisa, but thrive in the digital collaboration economy. And it's going to be about responsiveness. It's going to be about speed. And it's going to be about security and compliance. >> At the end of the day, kind of wrapping things up here, COVID or not the customer experience is critical, right, it's the lifeblood of what your organization delivers. The success of your customers, and their ability to make major business impact is what speaks to Mem-SQL's capabilities. A customer experience I know is always near and dear to your heart. And it sounds like that's something that you have modified for the situation, that really Mem-SQL focused on, not just the customer experience, but your employee experience as well. >> That's exactly it. And I think if you do right by the employees, they'll do right by the customers. And I would any day, any day put the employee first lens to any decision that we make. And that's paid off for us in spades. We've got a family environment, I genuinely, genuinely care about every single employee of Mem-SQL and their families. And we've communicated that often, we have listened, we have learned, these are unprecedented times. There isn't a manual to go through COVID-19 work environment. And I think the realization that we just don't know what tomorrow would bring, it's actually very liberating because it just frees you from rinsing and repeating, and further feeding your prejudice and biases, to getting up every day and say, "Let me learn as much as I can about the current environment, current realities, lens it through our priorities, and make the best decision that we can." And if you're wrong, accept and correct it. Nothing too intellectual, but it's in the simplicity that sometimes you find a lot of solace. >> Yeah. Simplicity in these times would be great. I think you're ... I like how you talked about the opportunities. There's a lot of positive COVID catalysts that are coming from this. And we want to thank you for sharing some time with us today, talking about the changing role of the C-suite, and the opportunities that it brings. Raj it's been great to have you on theCUBE. >> As always Lisa. It's a pleasure. Thank you. >> For the co-CEO of Mem-SQL, Raj Verma, I'm Lisa Martin. You're watching theCUBE conversation.

(digital music) >> And we're back live in New York. It's theCUBE. It's not SNL, it's better than SNL. Lisa Martin and John Furrier here with about 10,000 to 12,000 folks. (John chuckles) There is a ton of energy here. There's a ton of interest in what's going on. But one of the things that we know that AWS is really well-known for is its massive ecosystem. And one of its ecosystem partners is joining us. Please welcome Domenic Ravita, the VP of Product Marketing from SingleStore. Dominic, great to have you on the program. >> Well, thank you. Glad to be here. >> It's a nice opening, wasn't it? (Lisa and John laughing) >> I love SNL. Who doesn't? >> Right? I know. So some big news came out today. >> Yes. >> Funding. Good number. Talk to us a little bit about that before we dig in to SingleStore and what you guys are doing with AWS. >> Right, yeah. Thank you. We announced this morning our latest round, 116 million. We're really grateful to our customers and our investors and the partners and employees and making SingleStore a success to go on this journey of, really, to fulfill our mission to unify and simplify modern, real time data. >> So talk to us about SingleStore. Give us the value prop, the key differentiators, 'cause obviously customers have choice. Help us understand where you're nailing it. >> SingleStore is all about, what we like to say, the moments that matter. When you have an analytical question about what's happening in the moment, SingleStore is your best way to solve that cost-effectively. So that is for, in the case of Thorn, where they're helping to protect and save children from online trafficking or in the case of True Digital, which early in the pandemic, was a company in Southeast Asia that used anonymized phone pings to identify real time population density changes and movements across Thailand to have a proactive response. So really real time data in the moment can help to save lives quite literally. But also it does things that are just good commercially that gives you an advantage like what we do with Uber to help real time pricing and things like this. >> It's interesting this data intensity happening right now. We were talking earlier on theCUBE with another guest and we said, "Why is it happening now?" The big data has been around since the dupe days. That was hard to work with, then data lakes kicked in. But we seem to be, in the past year, everyone's now aware like, "Wow, I got a lot of data." Is it the pandemic? Now we're seeing customers understand the consequences. So how do you look at that? Because is it just timing, evolution? Are they now getting it or is the technology better? Is machine learning better? What's the forces driving the massive data growth acceleration in terms of implementing and getting stuff out, done? (chuckles) >> We think it's the confluence of a lot of those things you mentioned there. First of all, we just celebrate the 15-year anniversary of the iPhone, so that is like wallpaper now. It's just faded into our daily lives. We don't even think of that as a separate thing. So there's an expectation that we all have instant information and not just for the consumer interactions, for the business interactions. That permeates everything. I think COVID with the pandemic forced everyone, every business to try to move to digital first and so that put pressure on the digital service economy to mature even faster and to be digital first. That is what drives what we call data intensity. And more generally, the economic phenomenon is the data intensive era. It's a continuous competition and game for customers. In every moment in every location, in every dimension, the more data hat you have, the better value prop you can give. And so SingleStore is uniquely positioned to and focused on solving this problem of data intensity by bringing and unifying data together. >> What's the big customer success story? Can you share any examples that highlight that? What are some cool things that are happening that can illustrate this new, I won't say bit that's been flipped, that's been happening for a while, but can you share some cutting edge customer successes? >> It's happening across a lot of industries. So I would say first in financial services, FinTech. FinTech is always at the leading edge of these kind of technology adaptions for speeds and things like that. So we have a customer named IEX Cloud and they're focused on providing real time financial data as an API. So it's a data product, API-first. They're providing a lot of historical information on instruments and that sort of thing, as well as real time trending information. So they have customers like Seeking Alpha, for instance, who are providing real time updates on massive, massive data sets. They looked at lots of different ways to do this and there's the traditional, transactionals, LTP database and then maybe if you want to scale an API like theirs, you might have a separate end-memory cache and then yet another database for analytics. And so we bring all that together and simplify that and the benefit of simplification, but it's also this unification and lower latency. Another example is GE who basically uses us to bring together lots of financial information to provide quicker close to the end-of-month process across many different systems. >> So we think about special purpose databases, you mentioned one of the customers having those. We were in the keynote this morning where AWS is like, "We have the broadest set of special purpose databases," but you're saying the industry can't afford them anymore. Why and would it make SingleStore unique in terms of what you deliver? >> It goes back to this data intensity, in that the new business models that are coming out now are all about giving you this instant context and that's all data-driven and it's digital and it's also analytical. And so the reason that's you can't afford to do this, otherwise, is data's getting so big. Moving that data gets expensive, 'cause in the cloud you pay for every byte you store, every byte you process, every byte you move. So data movement is a cost in dollars and cents. It's a cost in time. It's also a cost in skill sets. So when you have many different specialized data sets or data-based technologies, you need skilled people to manage those. So that's why we think the industry needs to be simplified and then that's why you're seeing this unification trend across the database industry and other parts of the stack happening. With AWS, I mean, they've been a great partner of ours for years since we launched our first cloud database product and their perspective is a little bit different. They're offering choice of the specialty, 'cause many people build this way. But if you're going after real time data, you need to bring it. They also offer a SingleStore as a service on AWS. We offer it that way. It's in the AWS Marketplace. So it's easily consumable that way. >> Access to real time data is no longer a nice-to-have for any company, it's table stakes. We saw that especially in the last 20 months or so with companies that needed to pivot so quickly. What is it about SingleStore that delivers, that you talked about moments that matter? Talk about the access to real time data. How that's a differentiator as well? >> I think businesses need to be where their customers are and in the moments their customers are interacting. So that is the real time business-driver. As far as technology wise, it's not easy to do this. And you think about what makes a database fast? A major way of what makes it fast is how you store the data. And so since 2014, when we first released this, what Gartner called at the time, hybrid transaction/analytical processing or HTAP, where we brought transactional data and analytical data together. Fast forward five years to 2019, we released this innovation called Universal Storage, which does that in a single unified table type. Why that matters is because, I would say, basically cost efficiency and better speed. Again, because you pay for the storage and you pay for the movement. If you're not duplicating that data, moving it across different stores, you're going to have a better experience. >> One of the things you guys pioneered is unifying workloads. You mentioned some of the things you've done. Others are now doing it. Snowflake, Google and others. What does that mean for you guys? I mean, 'cause are they copying you? Are they trying to meet the functionality? >> I think. >> I mean, unification. I mean, people want to just store things and make it, get all the table stakes, check boxes, compliance, security and just keep coding and keep building. >> We think it's actually great 'cause they're validating what we've been seeing in the market for years. And obviously, they see that it's needed by customers. And so we welcome them to the party in terms of bringing these unified workloads together. >> Is it easy or hard? >> It's a difficult thing. We started this in 2014. And we've now have lots of production workloads on this. So we know where all the production edge cases are and that capability is also a building block towards a broader, expansive set of capabilities that we've moved onto that next phase and tomorrow actually we have an event called, The Real Time Data Revolution, excuse me, where we're announcing what's in that new product of ours. >> Is that a physical event or virtual? >> It's a virtual event. >> So we'll get the URL on the show notes, or if you know, just go to the new site. >> Absolutely. SingleStore Real Time Data Revolution, you'll find it. >> Can you tease us with the top three takeaways from Revolution tomorrow? >> So like I said, what makes a database fast? It's the storage and we completed that functionality three years ago with Universal Storage. What we're now doing for this next phase of the evolution is making enterprise features available and Workspaces is one of the foundational capabilities there. What SingleStore Workspaces does is it allows you to have this isolation of compute between your different workloads. So that's often a concern to new users to SingleStore. How can I combine transactions and analytics together? That seems like something that might be not a good thing. Well, there are multiple ways we've been doing that with resource governance, workload management. Workspaces offers another management capability and it's also flexible in that you can scale those workloads independently, or if you have a multi-tenant application, you can segment your application, your customer tenant workloads by each workspace. Another capability we're releasing is called Wasm, which is W-A-S-M, Web Assembly. This is something that's really growing in the open source community and SingleStore's contributing to that open source scene, CF project with WASI and Wasm. Where it's been mentioned mostly in the last few years has been in the browser as a more efficient way to run code in the browser. We're adapting that technology to allow you to run any language of your choice in the database and why that's important, again, it's for data movement. As data gets large in petabyte sizes, you can't move it in and out of Pandas in Python. >> Great innovation. That's real valuable. >> So we call this Code Engine with Wasm and- >> What do you call it? >> Code Engine Powered by Wasm. >> Wow. Wow. And that's open source? >> We contribute to the Wasm open source community. >> But you guys have a service that you- >> Yes. It's our implementation and our database. But Wasm allows you to have code that's portable, so any sort of runtime, which is... At release- >> You move the code, not the data. >> Exactly. >> With the compute. (chuckles) >> That's right, bring the compute to the data is what we say. >> You mentioned a whole bunch of great customer examples, GE, Uber, Thorn, you talked about IEX Cloud. When you're in customer conversations, are you dealing mostly with customers that are looking to you to help replace an existing database that was struggling from a performance perspective? Or are you working with startups who are looking to build a product on SingleStore? Is it both? >> It is a mix of both. I would say among SaaS scale up companies, their API, for instance, is their product or their SaaS application is their product. So quite literally, we're the data engine and the database powering their scale to be able to sign that next big customer or to at least sleep at night to know that it's not going to crash if they sign that next big costumer. So in those cases, we're mainly replacing a lot of databases like MySQL, Postgre, where they're typically starting, but more and more we're finding, it's free to start with SingleStore. You can run it in production for free. And in our developer community, we see a lot of customers running in that way. We have a really interesting community member who has a Minecraft server analytics that he's building based on that SingleStore free tier. In the enterprise, it's different, because there are many incumbent databases there. So it typically is a case where there is a, maybe a new product offering, they're maybe delivering a FinTech API or a new SaaS digital offering, again, to better participate in this digital service economy and they're looking for a better price performance for that real time experience in the app. That's typically the starting point, but there are replacements of traditional incumbent databases as well. >> How has the customer conversation evolved the last couple of years? As we talked about, one of the things we learned in the pandemic was access to real time data and those moments that matter isn't a nice-to-have anymore for businesses. There was that force march to digital. We saw the survivors, we're seeing the thrivers, but want to get your perspective on that. From the customers, how has the conversation evolved or elevated, escalated within an organization as every company has to be a data company? >> It really depends on their business strategy, how they are adapting or how they have adapted to this new digital first orientation and what does that mean for them in the direct interaction with their customers and partners. Often, what it means is they realize that they need to take advantage of using more data in the customer and partner interaction and when they come to those new ideas for new product introductions, they find that it's complicated and expensive to build in the old way. And if you're going to have these real time interactions, interactive applications, APIs, with all this context, you're going to have to find a better, more cost-effective approach to get that to market faster, but also not to have a big sprawling data-based technology infrastructure. We find that in those situations, we're replacing four or five different database technologies. A specialized database for key value, a specialized database for search- >> Because there's no unification before? Is that one of the reasons? >> I think it's an awareness thing. I think technology awareness takes a little bit of time, that there's a new way to do things. I think the old saying about, "Don't pave cow paths when the car..." You could build a straight road and pave it. You don't have to pave along the cow path. I think that's the natural course of technology adaption and so as more- >> And the- pandemic, too, highlighted a lot of the things, like, "Do we really need that?" (chuckles) "Who's going to service that?" >> That's right. >> So it's an awakening moment there where it's like, "Hey, let's look at what's working." >> That's right. >> Double down on it. >> Absolutely. >> What are you excited about new round of funding? We talked about, obviously, probably investments in key growth areas, but what excites you about being part of SingleStore and being a partner of AWS? >> SingleStore is super exciting. I've been in this industry a long time as an engineer and an engineering leader. At the time, we were MemSQL, came into SingleStore. And just that unification and simplification, the systems that I had built as a system engineer and helped architect did the job. They could get the speed and scale you needed to do track and trace kinds of use cases in real time, but it was a big trade off you had to make in terms of the complexity, the skill sets you needed and the cost and just hard to maintain. What excites me most about SingleStore is that it really feels like the iPhone moment for databases because it's not something you asked for, but once your friend has it and shows it to you, why would you have three different devices in your pocket with a flip phone, a calculator? (Lisa and Domenic chuckles) Remember these days? >> Yes. >> And a Blackberry pager. (all chuckling) You just suddenly- >> Or a computer. That's in there. >> That's right. So you just suddenly started using iPhone and that is sort of the moment. It feels like we're at it in the database market where there's a growing awareness and those announcements you mentioned show that others are seeing the same. >> And your point earlier about the iPhone throwing off a lot of data. So now you have data explosions at levels that unprecedented, we've never seen before and the fact that you want to have that iPhone moment, too, as a database. >> Absolutely. >> Great stuff. >> The other part of your question, what excites us about AWS. AWS has been a great partner since the beginning. I mean, when we first released our database, it was the cloud database. It was on AWS by customer demand. That's where our customers were. That's where they were building other applications. And now we have integrations with other native services like AWS Glue and we're in the Marketplace. We've expanded, that said we are a multi-cloud system. We are available in any cloud of your choice and on premise and in hybrid. So we're multi-cloud, hybrid and SaaS distribution. >> Got it. All right. >> Got it. So the event is tomorrow, Revolution. Where can folks go to register? What time does it start? >> 1:00 PM Eastern and- >> 1:00 PM. Eastern. >> Just Google SingleStore Real Time Data Revolution and you'll find it. Love for everyone to join us. >> All right. We look forward to it. Domenic, thank you so much for joining us, talking about SingleStore, the value prop, the differentiators, the validation that's happening in the market and what you guys are doing with AWS. We appreciate it. >> Thanks so much for having me. >> Our pleasure. For Domenic Ravita and John Furrier, I'm Lisa Martin. You're watching theCUBE, live from New York at AWS Summit 22. John and I are going to be back after a short break, so come back. (digital pulsing music)

(upbeat music) >> From theCUBE studios in Palo Alto, in Boston bringing you data-driven insights from theCUBE and ETR. This is braking analysis with Dave Vellante. >> Database is the heart of enterprise computing. The market is both exploding and it's evolving. The major force is transforming the space include Cloud and data, of course, but also new workloads, advanced memory and IO capabilities, new processor types, a massive push towards simplicity, new data sharing and governance models, and a spate of venture investment. Snowflake stands out as the gold standard for operational excellence and go to market execution. The company has attracted the attention of customers, investors, and competitors and everyone from entrenched players to upstarts once in the act. Hello everyone and welcome to this week's Wikibon CUBE Insights powered by ETR. In this breaking analysis, we'll share our most current thinking on the database marketplace and dig into Snowflake's execution. Some of its challenges and we'll take a look at how others are making moves to solve customer problems and try to get a piece of the growing database pie. Let's look at some of the factors that are driving market momentum. First, customers want lower license costs. They want simplicity. They want to avoid database sprawl. They want to run anywhere and manage new data types. These needs often are divergent and they pull vendors and technologies in different direction. It's really hard for any one platform to accommodate every customer need. The market is large and it's growing. Gardner has it at around 60 to 65 billion with a CAGR of somewhere around 20% over the next five years. But the market, as we know it is being redefined. Traditionally, databases have served two broad use cases, OLTP or transactions and reporting like data warehouses. But a diversity of workloads and new architectures and innovations have given rise to a number of new types of databases to accommodate all these diverse customer needs. Many billions have been spent over the last several years in venture money and it continues to pour in. Let me just give you some examples. Snowflake prior to its IPO, raised around 1.4 billion. Redis Labs has raised more than 1/2 billion dollars so far, Cockroach Labs, more than 350 million, Couchbase, 250 million, SingleStore formerly MemSQL, 238 million, Yellowbrick Data, 173 million. And if you stretch the definition of database a little bit to including low-code or no-code, Airtable has raised more than 600 million. And that's by no means a complete list. Now, why is all this investment happening? Well, in a large part, it's due to the TAM. The TAM is huge and it's growing and it's being redefined. Just how big is this market? Let's take a look at a chart that we've shown previously. We use this chart to Snowflakes TAM, and it focuses mainly on the analytics piece, but we'll use it here to really underscore the market potential. So the actual database TAM is larger than this, we think. Cloud and Cloud-native technologies have changed the way we think about databases. Virtually 100% of the database players that they're are in the market have pivoted to a Cloud first strategy. And many like Snowflake, they're pretty dogmatic and have a Cloud only strategy. Databases has historically been very difficult to manage, they're really sensitive to latency. So that means they require a lot of tuning. Cloud allows you to throw virtually infinite resources on demand and attack performance problems and scale very quickly, minimizing the complexity and tuning nuances. This idea, this layer of data as a service we think of it as a staple of digital transformation. Is this layer that's forming to support things like data sharing across ecosystems and the ability to build data products or data services. It's a fundamental value proposition of Snowflake and one of the most important aspects of its offering. Snowflake tracks a metric called edges, which are external connections in its data Cloud. And it claims that 15% of its total shared connections are edges and that's growing at 33% quarter on quarter. This notion of data sharing is changing the way people think about data. We use terms like data as an asset. This is the language of the 2010s. We don't share our assets with others, do we? No, we protect them, we secure or them, we even hide them. But we absolutely don't want to share those assets but we do want to share our data. I had a conversation recently with Forrester analyst, Michelle Goetz. And we both agreed we're going to scrub data as an asset from our phrasiology. Increasingly, people are looking at sharing as a way to create, as I said, data products or data services, which can be monetized. This is an underpinning of Zhamak Dehghani's concept of a data mesh, make data discoverable, shareable and securely governed so that we can build data products and data services that can be monetized. This is where the TAM just explodes and the market is redefining. And we think is in the hundreds of billions of dollars. Let's talk a little bit about the diversity of offerings in the marketplace. Again, databases used to be either transactional or analytic. The bottom lines and top lines. And this chart here describe those two but the types of databases, you can see the middle of mushrooms, just looking at this list, blockchain is of course a specialized type of database and it's also finding its way into other database platforms. Oracle is notable here. Document databases that support JSON and graph data stores that assist in visualizing data, inference from multiple different sources. That's is one of the ways in which adtech has taken off and been so effective. Key Value stores, log databases that are purpose-built, machine learning to enhance insights, spatial databases to help build the next generation of products, the next automobile, streaming databases to manage real time data flows and time series databases. We might've missed a few, let us know if you think we have, but this is a kind of pretty comprehensive list that is somewhat mind boggling when you think about it. And these unique requirements, they've spawned tons of innovation and companies. Here's a small subset on this logo slide. And this is by no means an exhaustive list, but you have these companies here which have been around forever like Oracle and IBM and Teradata and Microsoft, these are the kind of the tier one relational databases that have matured over the years. And they've got properties like atomicity, consistency, isolation, durability, what's known as ACID properties, ACID compliance. Some others that you may or may not be familiar with, Yellowbrick Data, we talked about them earlier. It's going after the best price, performance and analytics and optimizing to take advantage of both hybrid installations and the latest hardware innovations. SingleStore, as I said, formerly known as MemSQL is a very high end analytics and transaction database, supports mixed workloads, extremely high speeds. We're talking about trillions of rows per second that could be ingested in query. Couchbase with hybrid transactions and analytics, Redis Labs, open source, no SQL doing very well, as is Cockroach with distributed SQL, MariaDB with its managed MySQL, Mongo and document database has a lot of momentum, EDB, which supports open source Postgres. And if you stretch the definition a bit, Splunk, for log database, why not? ChaosSearch, really interesting startup that leaves data in S-3 and is going after simplifying the ELK stack, New Relic, they have a purpose-built database for application performance management and we probably could have even put Workday in the mix as it developed a specialized database for its apps. Of course, we can't forget about SAP with how not trying to pry customers off of Oracle. And then the big three Cloud players, AWS, Microsoft and Google with extremely large portfolios of database offerings. The spectrum of products in this space is very wide, with you've got AWS, which I think we're up to like 16 database offerings, all the way to Oracle, which has like one database to do everything not withstanding MySQL because it owns MySQL got that through the Sun Acquisition. And it recently, it made some innovations there around the heat wave announcement. But essentially Oracle is investing to make its database, Oracle database run any workload. While AWS takes the approach of the right tool for the right job and really focuses on the primitives for each database. A lot of ways to skin a cat in this enormous and strategic market. So let's take a look at the spending data for the names that make it into the ETR survey. Not everybody we just mentioned will be represented because they may not have quite the market presence of the ends in the survey, but ETR that capture a pretty nice mix of players. So this chart here, it's one of the favorite views that we like to share quite often. It shows the database players across the 1500 respondents in the ETR survey this past quarter and it measures their net score. That's spending momentum and is shown on the vertical axis and market share, which is the pervasiveness in the data set is on the horizontal axis. The Snowflake is notable because it's been hovering around 80% net score since the survey started picking them up. Anything above 40%, that red line there, is considered by us to be elevated. Microsoft and AWS, they also stand out because they have both market presence and they have spending velocity with their platforms. Oracle is very large but it doesn't have the spending momentum in the survey because nearly 30% of Oracle installations are spending less, whereas only 22% are spending more. Now as a caution, this survey doesn't measure dollar spent and Oracle will be skewed toward the big customers with big budgets. So you got to consider that caveat when evaluating this data. IBM is in a similar position although its market share is not keeping up with Oracle's. Google, they've got great tech especially with BigQuery and it has elevated momentum. So not a bad spot to be in although I'm sure it would like to be closer to AWS and Microsoft on the horizontal axis, so it's got some work to do there. And some of the others we mentioned earlier, like MemSQL, Couchbase. As shown MemSQL here, they're now SingleStore. Couchbase, Reddis, Mongo, MariaDB, all very solid scores on the vertical axis. Cloudera just announced that it was selling to private equity and that will hopefully give it some time to invest in this platform and get off the quarterly shot clock. MapR was acquired by HPE and it's part of HPE's Ezmeral platform, their data platform which doesn't yet have the market presence in the survey. Now, something that is interesting in looking at in Snowflakes earnings last quarter, is this laser focused on large customers. This is a hallmark of Frank Slootman and Mike Scarpelli who I know they don't have a playbook but they certainly know how to go whale hunting. So this chart isolates the data that we just showed you to the global 1000. Note that both AWS and Snowflake go up higher on the X-axis meaning large customers are spending at a faster rate for these two companies. The previous chart had an end of 161 for Snowflake, and a 77% net score. This chart shows the global 1000, in the end there for Snowflake is 48 accounts and the net score jumps to 85%. We're not going to show it here but when you isolate the ETR data, nice you can just cut it, when you isolate it on the fortune 1000, the end for Snowflake goes to 59 accounts in the data set and Snowflake jumps another 100 basis points in net score. When you cut the data by the fortune 500, the Snowflake N goes to 40 accounts and the net score jumps another 200 basis points to 88%. And when you isolate on the fortune 100 accounts is only 18 there but it's still 18, their net score jumps to 89%, almost 90%. So it's very strong confirmation that there's a proportional relationship between larger accounts and spending momentum in the ETR data set. So Snowflakes large account strategy appears to be working. And because we think Snowflake is sticky, this probably is a good sign for the future. Now we've been talking about net score, it's a key measure in the ETR data set, so we'd like to just quickly remind you what that is and use Snowflake as an example. This wheel chart shows the components of net score, that lime green is new adoptions. 29% of the customers in the ETR dataset that are new to Snowflake. That's pretty impressive. 50% of the customers are spending more, that's the forest green, 20% are flat, that's the gray, and only 1%, the pink, are spending less. And 0% zero or replacing Snowflake, no defections. What you do here to get net scores, you subtract the red from the green and you get a net score of 78%. Which is pretty sick and has been sick as in good sick and has been steady for many, many quarters. So that's how the net score methodology works. And remember, it typically takes Snowflake customers many months like six to nine months to start consuming it's services at the contracted rate. So those 29% new adoptions, they're not going to kick into high gear until next year, so that bodes well for future revenue. Now, it's worth taking a quick snapshot at Snowflakes most recent quarter, there's plenty of stuff out there that you can you can google and get a summary but let's just do a quick rundown. The company's product revenue run rate is now at 856 million they'll surpass $1 billion on a run rate basis this year. The growth is off the charts very high net revenue retention. We've explained that before with Snowflakes consumption pricing model, they have to account for retention differently than what a SaaS company. Snowflake added 27 net new $1 million accounts in the quarter and claims to have more than a hundred now. It also is just getting its act together overseas. Slootman says he's personally going to spend more time in Europe, given his belief, that the market is huge and they can disrupt it and of course he's from the continent. He was born there and lived there and gross margins expanded, do in a large part to renegotiation of its Cloud costs. Welcome back to that in a moment. Snowflake it's also moving from a product led growth company to one that's more focused on core industries. Interestingly media and entertainment is one of the largest along with financial services and it's several others. To me, this is really interesting because Disney's example that Snowflake often puts in front of its customers as a reference. And it seems to me to be a perfect example of using data and analytics to both target customers and also build so-called data products through data sharing. Snowflake has to grow its ecosystem to live up to its lofty expectations and indications are that large SIS are leaning in big time. Deloitte cross the $100 million in deal flow in the quarter. And the balance sheet's looking good. Thank you very much with $5 billion in cash. The snarks are going to focus on the losses, but this is all about growth. This is a growth story. It's about customer acquisition, it's about adoption, it's about loyalty and it's about lifetime value. Now, as I said at the IPO, and I always say this to young people, don't buy a stock at the IPO. There's probably almost always going to be better buying opportunities ahead. I'm not always right about that, but I often am. Here's a chart of Snowflake's performance since IPO. And I have to say, it's held up pretty well. It's trading above its first day close and as predicted there were better opportunities than day one but if you have to make a call from here. I mean, don't take my stock advice, do your research. Snowflake they're priced to perfection. So any disappointment is going to be met with selling. You saw that the day after they beat their earnings last quarter because their guidance in revenue growth,. Wasn't in the triple digits, it sort of moderated down to the 80% range. And they pointed, they pointed to a new storage compression feature that will lower customer costs and consequently, it's going to lower their revenue. I swear, I think that that before earnings calls, Scarpelli sits back he's okay, what kind of creative way can I introduce the dampen enthusiasm for the guidance. Now I'm not saying lower storage costs will translate into lower revenue for a period of time. But look at dropping storage prices, customers are always going to buy more, that's the way the storage market works. And stuff like did allude to that in all fairness. Let me introduce something that people in Silicon Valley are talking about, and that is the Cloud paradox for SaaS companies. And what is that? I was a clubhouse room with Martin Casado of Andreessen when I first heard about this. He wrote an article with Sarah Wang, calling it to question the merits of SaaS companies sticking with Cloud at scale. Now the basic premise is that for startups in early stages of growth, the Cloud is a no brainer for SaaS companies, but at scale, the cost of Cloud, the Cloud bill approaches 50% of the cost of revenue, it becomes an albatross that stifles operating leverage. Their conclusion ended up saying that as much as perhaps as much as the back of the napkin, they admitted that, but perhaps as much as 1/2 a trillion dollars in market cap is being vacuumed away by the hyperscalers that could go to the SaaS providers as cost savings from repatriation. And that Cloud repatriation is an inevitable path for large SaaS companies at scale. I was particularly interested in this as I had recently put on a post on the Cloud repatriation myth. I think in this instance, there's some merit to their conclusions. But I don't think it necessarily bleeds into traditional enterprise settings. But for SaaS companies, maybe service now has it right running their own data centers or maybe a hybrid approach to hedge bets and save money down the road is prudent. What caught my attention in reading through some of the Snowflake docs, like the S-1 in its most recent 10-K were comments regarding long-term purchase commitments and non-cancelable contracts with Cloud companies. And the companies S-1, for example, there was disclosure of $247 million in purchase commitments over a five plus year period. And the company's latest 10-K report, that same line item jumped to 1.8 billion. Now Snowflake is clearly managing these costs as it alluded to when its earnings call. But one has to wonder, at some point, will Snowflake follow the example of say Dropbox which Andreessen used in his blog and start managing its own IT? Or will it stick with the Cloud and negotiate hard? Snowflake certainly has the leverage. It has to be one of Amazon's best partners and customers even though it competes aggressively with Redshift but on the earnings call, CFO Scarpelli said, that Snowflake was working on a new chip technology to dramatically increase performance. What the heck does that mean? Is this Snowflake is not becoming a hardware company? So I going to have to dig into that a little bit and find out what that it means. I'm guessing, it means that it's taking advantage of ARM-based processes like graviton, which many ISVs ar allowing their software to run on that lower cost platform. Or maybe there's some deep dark in the weeds secret going on inside Snowflake, but I doubt it. We're going to leave all that for there for now and keep following this trend. So it's clear just in summary that Snowflake they're the pace setter in this new exciting world of data but there's plenty of room for others. And they still have a lot to prove. For instance, one customer in ETR, CTO round table express skepticism that Snowflake will live up to its hype because its success is going to lead to more competition from well-established established players. This is a common theme you hear it all the time. It's pretty easy to reach that conclusion. But my guess is this the exact type of narrative that fuels Slootman and sucked him back into this game of Thrones. That's it for now, everybody. Remember, these episodes they're all available as podcasts, wherever you listen. All you got to do is search braking analysis podcast and please subscribe to series. Check out ETR his website at etr.plus. We also publish a full report every week on wikinbon.com and siliconangle.com. You can get in touch with me, Email is David.vellante@siliconangle.com. You can DM me at DVelante on Twitter or comment on our LinkedIn posts. This is Dave Vellante for theCUBE Insights powered by ETR. Have a great week everybody, be well and we'll see you next time. (upbeat music)

(upbeat music) >> On February 19th of this year, Barron's dropped an article declaring Oracle, a cloud giant and the article explained why the stock was a buy. Investors took notice and the stock ran up 18% over the next nine trading days and it peaked on March 9th, the day before Oracle announced its latest earnings. The company beat consensus earnings on both top-line and EPS last quarter, but investors, they did not like Oracle's tepid guidance and the stock pulled back. But it's still, as you can see, well above its pre-Barron's article price. What does all this mean? Is Oracle a cloud giant? What are its growth prospects? Now many parts of Oracle's business are growing including Fusion ERP, Fusion HCM, NetSuite, we're talking deep into the double digits, 20 plus percent growth. It's OnPrem legacy licensed business however, continues to decline and that moderates, the overall company growth because that OnPrem business is so large. So the overall Oracle's growing in the low single digits. Now what stands out about Oracle is it's recurring revenue model. That figure, the company says now it represents 73% of its revenue and that's going to continue to grow. Now two other things stood out on the earnings call to us. First, Oracle plans on increasing its CapEX by 50% in the coming quarter, that's a lot. Now it's still far less than AWS Google or Microsoft Spend on capital but it's a meaningful data point. Second Oracle's consumption revenue for Autonomous Database and Cloud Infrastructure, OCI or Oracle Cloud Infrastructure grew at 64% and 139% respectively and these two factors combined with the CapEX Spend suggest that the company has real momentum. I mean look, it's possible that the CapEx announcements maybe just optics in they're front loading, some spend to show the street that it's a player in cloud but I don't think so. Oracle's Safra Catz's usually pretty disciplined when it comes to it's spending. Now today on March 17th, Oracle announced updates towards Autonomous Data Warehouse and with me is David Floyer who has extensively researched Oracle over the years and today we're going to unpack the Oracle Autonomous Data Warehouse, ADW announcement. What it means to customers but we also want to dig into Oracle's strategy. We want to compare it to some other prominent database vendors specifically, AWS and Snowflake. David Floyer, Welcome back to The Cube, thanks for making some time for me. >> Thank you Vellante, great pleasure to be here. >> All right, I want to get into the news but I want to start with this idea of the autonomous database which Oracle's announcement today is building on. Oracle uses the analogy of a self-driving car. It's obviously powerful metaphor as they call it the self-driving database and my takeaway is that, this means that the system automatically provisions, it upgrades, it does all the patching for you, it tunes itself. Oracle claims that all reduces labor costs or admin costs by 90%. So I ask you, is this the right interpretation of what Oracle means by autonomous database? And is it real? >> Is that the right interpretation? It's a nice analogy. It's a test to that analogy, isn't it? I would put it as the first stage of the Autonomous Data Warehouse was to do the things that you talked about, which was the tuning, the provisioning, all of that sort of thing. The second stage is actually, I think more interesting in that what they're focusing on is making it easy to use for the end user. Eliminating the requirement for IT, staff to be there to help in the actual using of it and that is a very big step for them but an absolutely vital step because all of the competition focusing on ease of use, ease of use, ease of use and cheapness of being able to manage and deploy. But, so I think that is the really important area that Oracle has focused on and it seemed to have done so very well. >> So in your view, is this, I mean you don't really hear a lot of other companies talking about this analogy of the self-driving database, is this unique? Is it differentiable for Oracle? If so, why, or maybe you could help us understand that a little bit better. >> Well, the whole strategy is unique in its breadth. It has really brought together a whole number of things together and made it of its type the best. So it has a single, whole number of data sources and database types. So it's got a very broad range of different ways that you can look at the data and the second thing that is also excellent is it's a platform. It is fully self provisioned and its functionality is very, very broad indeed. The quality of the original SQL and the query languages, etc, is very, very good indeed and it's a better agent to do joints for example, is excellent. So all of the building blocks are there and together with it's sharing of the same data with OLTP and inference and in memory data paces as well. All together the breadth of what they have is unique and very, very powerful. >> I want to come back to this but let's get into the news a little bit and the announcement. I mean, it seems like what's new in the autonomous data warehouse piece for Oracle's new tooling around four areas that so Andy Mendelsohn, the head of this group instead of the guy who releases his baby, he talked about four things. My takeaway, faster simpler loads, simplified transforms, autonomous machine learning models which are facilitating, What do you call it? Citizen data science and then faster time to insights. So tooling to make those four things happen. What's your take and takeaways on the news? >> I think those are all correct. I would add the ease of use in terms of being able to drag and drop, the user interface has been dramatically improved. Again, I think those, strategically are actually more important that the others are all useful and good components of it but strategically, I think is more important. There's ease of use, the use of apex for example, are more important. And, >> Why are they more important strategically? >> Because they focus on the end users capability. For example, one of other things that they've started to introduce is Python together with their spatial databases, for example. That is really important that you reach out to the developer as they are and what tools they want to use. So those type of ease of use things, those types of things are respecting what the end users use. For example, they haven't come out with anything like click or Tableau. They've left that there for that marketplace for the end user to use what they like best. >> Do you mean, they're not trying to compete with those two tools. They indeed had a laundry list of stuff that they supported, Talend, Tableau, Looker, click, Informatica, IBM, I had IBM there. So their claim was, hey, we're open. But so that's smart. That's just, hey, they realized that people use these tools. >> I'm trying to exclude other people, be a platform and be an ecosystem for the end users. >> Okay, so Mendelsohn who made the announcement said that Oracle's the smartphone of databases and I think, I actually think Alison kind of used that or maybe that was us planing to have, I thought he did like the iPhone of when he announced the exit data way back when the integrated hardware and software but is that how you see it, is Oracle, the smartphone of databases? >> It is, I mean, they are trying to own the complete stack, the hardware with the exit data all the way up to the databases at the data warehouses and the OLTP databases, the inference databases. They're trying to own the complete stack from top to bottom and that's what makes autonomy process possible. You can make it autonomous when you control all of that. Take away all of the requirements for IT in the business itself. So it's democratizing the use of data warehouses. It is pushing it out to the lines of business and it's simplifying it and making it possible to push out so that they can own their own data. They can manage their own data and they do not need an IT person from headquarters to help them. >> Let's stay in this a little bit more and then I want to go into some of the competitive stuff because Mendelsohn mentioned AWS several times. One of the things that struck me, he said, hey, we're basically one API 'cause we're doing analytics in the cloud, we're doing data in the cloud, we're doing integration in the cloud and that's sort of a big part of the value proposition. He made some comparisons to Redshift. Of course, I would say, if you can't find a workload where you beat your big competitor then you shouldn't be in this business. So I take those things with a grain of salt but one of the other things that caught me is that migrating from OnPrem to Oracle, Oracle Cloud was very simple and I think he might've made some comparisons to other platforms. And this to me is important because he also brought in that Gartner data. We looked at that Gardner data when they came out with it in the operational database class, Oracle smoked everybody. They were like way ahead and the reason why I think that's important is because let's face it, the Mission Critical Workloads, when you look at what's moving into AWS, the Mission Critical Workloads, the high performance, high criticality OLTP stuff. That's not moving in droves and you've made the point often that companies with their own cloud particularly, Oracle you've mentioned this about IBM for certain, DB2 for instance, customers are going to, there should be a lower risk environment moving from OnPrem to their cloud, because you could do, I don't think you could get Oracle RAC on AWS. For example, I don't think EXIF data is running in AWS data centers and so that like component is going to facilitate migration. What's your take on all that spiel? >> I think that's absolutely right. You all crown Jewels, the most expensive and the most valuable applications, the mission-critical applications. The ones that have got to take a beating, keep on taking. So those types of applications are where Oracle really shines. They own a very large high percentage of those Mission Critical Workloads and you have the choice if you're going to AWS, for example of either migrating to Oracle on AWS and that is frankly not a good fit at all. There're a lot of constraints to running large systems on AWS, large mission critical systems. So that's not an option and then the option, of course, that AWS will push is move to a Roller, change your way of writing applications, make them tiny little pieces and stitch them all together with microservices and that's okay if you're a small organization but that has got a lot of problems in its own, right? Because then you, the user have to stitch all those pieces together and you're responsible for testing it and you're responsible for looking after it. And that as you grow becomes a bigger and bigger overhead. So AWS, in my opinion needs to have a move towards a tier-one database of it's own and it's not in that position at the moment. >> Interesting, okay. So, let's talk about the competitive landscape and the choices that customers have. As I said, Mendelssohn mentioned AWS many times, Larry on the calls often take shy, it's a compliment to me. When Larry Ellison calls you out, that means you've made it, you're doing well. We've seen it over the years, whether it's IBM or Workday or Salesforce, even though Salesforce's big Oracle customer 'cause AWS, as we know are Oracle customer as well, even though AWS tells us they've off called when you peel the onion >> Five years should be great, some of the workers >> Well, as I said, I believe they're still using Oracle in certain workloads. Way, way, we digress. So AWS though, they take a different approach and I want to push on this a little bit with database. It's got more than a dozen, I think purpose-built databases. They take this kind of right tool for the right job approach was Oracle there converging all this function into a single database. SQL JSON graph databases, machine learning, blockchain. I'd love to talk about more about blockchain if we have time but seems to me that the right tool for the right job purpose-built, very granular down to the primitives and APIs. That seems to me to be a pretty viable approach versus kind of a Swiss Army approach. How do you compare the two? >> Yes, and it is to many initial programmers who are very interested for example, in graph databases or in time series databases. They are looking for a cheap database that will do the job for a particular project and that makes, for the program or for that individual piece of work is making a very sensible way of doing it and they pay for ads on it's clear cloud dynamics. The challenge as you have more and more data and as you're building up your data warehouse in your data lakes is that you do not want to have to move data from one place to another place. So for example, if you've got a Roller,, you have to move the database and it's a pretty complicated thing to do it, to move it to Redshift. It's a five or six steps to do that and each of those costs money and each of those take time. More importantly, they take time. The Oracle approach is a single database in terms of all the pieces that obviously you have multiple databases you have different OLTP databases and data warehouse databases but as a single architecture and a single design which means that all of the work in terms of moving stuff from one place to another place is within Oracle itself. It's Oracle that's doing that work for you and as you grow, that becomes very, very important. To me, very, very important, cost saving. The overhead of all those different ones and the databases themselves originate with all as open source and they've done very well with it and then there's a large revenue stream behind the, >> The AWS, you mean? >> Yes, the original database is in AWS and they've done a lot of work in terms of making it set with the panels, etc. But if a larger organization, especially very large ones and certainly if they want to combine, for example data warehouse with the OLTP and the inference which is in my opinion, a very good thing that they should be trying to do then that is incredibly difficult to do with AWS and in my opinion, AWS has to invest enormously in to make the whole ecosystem much better. >> Okay, so innovation required there maybe is part of the TAM expansion strategy but just to sort of digress for a second. So it seems like, and by the way, there are others that are doing, they're taking this converged approach. It seems like that is a trend. I mean, you certainly see it with single store. I mean, the name sort of implies that formerly MemSQL I think Monte Zweben of splice machine is probably headed in a similar direction, embedding AI in Microsoft's, kind of interesting. It seems like Microsoft is willing to build this abstraction layer that hides that complexity of the different tooling. AWS thus far has not taken that approach and then sort of looking at Snowflake, Snowflake's got a completely different, I think Snowflake's trying to do something completely different. I don't think they're necessarily trying to take Oracle head-on. I mean, they're certainly trying to just, I guess, let's talk about this. Snowflake simplified EDW, that's clear. Zero to snowflake in 90 minutes. It's got this data cloud vision. So you sign on to this Snowflake, speaking of layers they're abstracting the complexity of the underlying cloud. That's what the data cloud vision is all about. They, talk about this Global Mesh but they've not done a good job of explaining what the heck it is. We've been pushing them on that, but we got, >> Aspiration of moment >> Well, I guess, yeah, it seems that way. And so, but conceptually, it's I think very powerful but in reality, what snowflake is doing with data sharing, a lot of reading it's probably mostly read-only and I say, mostly read-only, oh, there you go. You'll get better but it's mostly read and so you're able to share the data, it's governed. I mean, it's exactly, quite genius how they've implemented this with its simplicity. It is a caching architecture. We've talked about that, we can geek out about that. There's good, there's bad, there's ugly but generally speaking, I guess my premise here I would love your thoughts. Is snowflakes trying to do something different? It's trying to be not just another data warehouse. It's not just trying to compete with data lakes. It's trying to create this data cloud to facilitate data sharing, put data in the hands of business owners in terms of a product build, data product builders. That's a different vision than anything I've seen thus far, your thoughts. >> I agree and even more going further, being a place where people can sell data. Put it up and make it available to whoever needs it and making it so simple that it can be shared across the country and across the world. I think it's a very powerful vision indeed. The challenge they have is that the pieces at the moment are very, very easy to use but the quality in terms of the, for example, joints, I mentioned, the joints were very powerful in Oracle. They don't try and do joints. They, they say >> They being Snowflake, snowflake. Yeah, they don't even write it. They would say use another Postgres >> Yeah. >> Database to do that. >> Yeah, so then they have a long way to go. >> Complex joints anyway, maybe simple joints, yeah. >> Complex joints, so they have a long way to go in terms of the functionality of their product and also in my opinion, they sure be going to have more types of databases inside it, including OLTP and they can do that. They have obviously got a great market gap and they can do that by acquisition as well as they can >> They've started. I think, I think they support JSON, right. >> Do they support JSON? And graph, I think there's a graph database that's either coming or it's there, I can't keep all that stuff in my head but there's no reason they can't go in that direction. I mean, in speaking to the founders in Snowflake they were like, look, we're kind of new. We would focus on simple. A lot of them came from Oracle so they know all database and they know how hard it is to do things like facilitate complex joints and do complex workload management and so they said, let's just simplify, we'll put it in the cloud and it will spin up a separate data warehouse. It's a virtual data warehouse every time you want one to. So that's how they handle those things. So different philosophy but again, coming back to some of the mission critical work and some of the larger Oracle customers, they said they have a thousand autonomous database customers. I think it was autonomous database, not ADW but anyway, a few stood out AON, lift, I think Deloitte stood out and as obviously, hundreds more. So we have people who misunderstand Oracle, I think. They got a big install base. They invest in R and D and they talk about lock-in sure but the CIO that I talked to and you talked to David, they're looking for business value. I would say that 75 to 80% of them will gravitate toward business value over the fear of lock-in and I think at the end of the day, they feel like, you know what? If our business is performing, it's a better business decision, it's a better business case. >> I fully agree, they've been very difficult to do business with in the past. Everybody's in dread of the >> The audit. >> The knock on the door from the auditor. >> Right. >> And that from a purchasing point of view has been really bad experience for many, many customers. The users of the database itself are very happy indeed. I mean, you talk to them and they understand why, what they're paying for. They understand the value and in terms of availability and all of the tools for complex multi-dimensional types of applications. It's pretty well, the only game in town. It's only DB2 and SQL that had any hope of doing >> Doing Microsoft, Microsoft SQL, right. >> Okay, SQL >> Which, okay, yeah, definitely competitive for sure. DB2, no IBM look, IBM lost its dominant position in database. They kind of seeded that. Oracle had to fight hard to win it. It wasn't obvious in the 80s who was going to be the database King and all had to fight. And to me, I always tell people the difference is that the chairman of Oracle is also the CTO. They spend money on R and D and they throw off a ton of cash. I want to say something about, >> I was just going to make one extra point. The simplicity and the capability of their cloud versions of all of this is incredibly good. They are better in terms of spending what you need or what you use much better than AWS, for example or anybody else. So they have really come full circle in terms of attractiveness in a cloud environment. >> You mean charging you for what you consume. Yeah, Mendelsohn talked about that. He made a big point about the granularity, you pay for only what you need. If you need 33 CPUs or the other databases you've got to shape, if you need 33, you've got to go to 64. I know that's true for everyone. I'm not sure if that's true too for snowflake. It may be, I got to dig into that a little bit, but maybe >> Yes, Snowflake has got a front end to hiding behind. >> Right, but I didn't want to push it that a little bit because I want to go look at their pricing strategies because I still think they make you buy, I may be wrong. I thought they make you still do a one-year or two-year or three-year term. I don't know if you can just turn it off at any time. They might allow, I should hold off. I'll do some more research on that but I wanted to make a point about the audits, you mentioned audits before. A big mistake that a lot of Oracle customers have made many times and we've written about this, negotiating with Oracle, you've got to bring your best and your brightest when you negotiate with Oracle. Some of the things that people didn't pay attention to and I think they've sort of caught onto this is that Oracle's SOW is adjudicate over the MSA, a lot of legal departments and procurement department. Oh, do we have an MSA? With all, Yes, you do, okay, great and because they think the MSA, they then can run. If they have an MSA, they can rubber stamp it but the SOW really dictateS and Oracle's gotcha there and they're really smart about that. So you got to bring your best and the brightest and you've got to really negotiate hard with Oracle, you get trouble. >> Sure. >> So it is what it is but coming back to Oracle, let's sort of wrap on this. Dominant position in mission critical, we saw that from the Gartner research, especially for operational, giant customer base, there's cloud-first notion, there's investing in R and D, open, we'll put a question Mark around that but hey, they're doing some cool stuff with Michael stuff. >> Ecosystem, I put that, ecosystem they're promoting their ecosystem. >> Yeah, and look, I mean, for a lot of their customers, we've talked to many, they say, look, there's actually, a tail at the tail way, this saves us money and we don't have to migrate. >> Yeah. So interesting, so I'll give you the last word. We started sort of focusing on the announcement. So what do you want to leave us with? >> My last word is that there are platforms with a certain key application or key parts of the infrastructure, which I think can differentiate themselves from the Azures or the AWS. and Oracle owns one of those, SAP might be another one but there are certain platforms which are big enough and important enough that they will, in my opinion will succeed in that cloud strategy for this. >> Great, David, thanks so much, appreciate your insights. >> Good to be here. Thank you for watching everybody, this is Dave Vellante for The Cube. We'll see you next time. (upbeat music)

>> From The Cube Studios in Palo Alto and Boston, bringing you data driven insights from The Cube and ETR, this is Breaking Analysis with Dave Vellante. >> Despite it's faster growth and infrastructure as a service, relative to AWS and Azure, Google Cloud platform remains a third wheel in the race for cloud dominance. Google begins its Cloud Next online event starting July fourteenth in a series of nine rolling sessions that go through early September. Ahead of that, we want to update you on our most current data on Google's cloud business. Hello everyone, this is Dave Vellante, and welcome to this week's Wikibon Cube insights, powered by ETR. In this session, we'll review the current state of cloud, and Google's position in the market. We'll drill into the ETR data and share fresh insights from our partner and the Cube community. So let's get right into it. You know, Google, if you think about it, was actually very early into the cloud game. Google's 2004 IPO was a milestone event for the tech industry, and in you know many ways, it really marked the end of the post-dotcom malaise. It signaled the beginning of a new era of innovation. During this time, Google was busy building out its massive, global cloud infrastructure, probably the largest in the world, with undersea cables, global data centers, and tools like the Google file system, and of course Bigtable. But it took many years for Google to pull its head out of its ad serving butt and realize the opportunity to sell its cloud services to global enterprises. Bigtable, Google's no-sequel database, for example, was released in 2005, but it wasn't until 2015 that Google made this service available to its customers. That was the same year Google brought in VMware founder, Diane Greene to begin its enterprise journey in earnest. Now Google, they have a dizzying array of services in compute, storage, database, networking, IT ops, dev tools, machine learning, AI, analytics, big data, security, on and on and on. Name a category and it's likely that Google has something in it as a cloud service. But Google, to this day, still hasn't figured out how to sell to the enterprise. It really struggles to find the right formula. So, as you know, Google brought in Thomas Kurian from Oracle, to figure this out. Of course Kurian is, he's going to go with Google's strengths like analytics and database, but it has to have differentiation, so it comes up with unique pricing models like sustained discounts, which automatically apply discount for heavy usage, as opposed to forcing users to buy reserved instances such as what AWS does. You know Google is more aggressive partnering around multi-cloud, for instance, with Anthos, and it's smartly open-sourced Kubernetes really to minimize the importance of, physically, where workloads run. The bottom-line, however, is that these moves are necessary for Google to compete because it lags behind the leaders. And it has a long way to go before it's going to be satisfied with its cloud business. Let's look at the IaaS market in context. Now, I don't want to say it's all gloom and doom for Google. Far from it. Earnings for Q2, they're going to start rolling out later this month, but this chart shows our latest estimates of IaaS and PaaS for the big three cloud players. Now, I got to caution you, as I did before, other than AWS, which reports very clean numbers each quarter on IaaS and PaaS, we have to estimate Azure and GCP revenue because they bundle in other things. I'll give an example. Google reports its overall cloud numbers which include G Suite. Microsoft reports a category they call intelligent cloud. Now that includes public, private clouds, hybrid, sequel server, Windows server, system center, GitHub, enterprise support and consulting services. And Azure, the IaaS and PaaS numbers are also in there too. So what we have to do is to squint through the earnings reports and the 10 Ks and try to get a clean IaaS and PaaS figure for these players, and that's what we show here. Now there's really two points that we want to stress with this data. First, on a trailing 12 month basis, the big three cloud players now account for nearly 60 billion dollars in IaaS and PaaS revenue. And this 60 billion dollars, on a weighted average basis, is growing in the mid 40% range. So well on its way to being a 100 billion dollar business. Just for these three firms. And as we've reported, that's eating directly into the on-premises infrastructure install base, which is a flat to declining market. And that trend is going to play out in a big way this decade. We've predicted that public cloud is going to out pace on-prem infrastructure by more that 1800 basis points over the next 10 years, from a spending standpoint. Now the second point that I want to make relates to Google IaaS and PaaS growth. We peg it at greater than 70%, based on public statements, reading the 10 Ks and ETR data, which we'll discuss in a moment. So, very healthy growth, but from a much smaller install base than, or base than AWS and Azure. But in our view it's not enough, because AWS and Azure are so large and strong still, growth wise, that we feel Google is going to remain a distant third, really indefinitely. Nonetheless, a lot of companies would be thrilled to have a four billion dollar cloud business and there's certainly good news in the data for Google. So let's look at some of that survey data. Now, as we've reported in the past, Google pushes G Suite very hard, as part of its cloud story, and it leads often times with G Suite in its messaging. You know, but to us that's never really been that compelling. So let me start with some anecdotal data from ETR. ETR runs a regular program, they call it VENN, and in the VENN they invite clients into a private session to listen to named CIOs talk about their experience with vendors and overall spending intentions. It's a facilitated session. And we've had ETR's Eric Bradley on as a guest who directs the VENN program, and does much of the facilitation, and here's a statement from a recent VENN session quoting a CIO at a midsize Telco, that I think sums it up nicely. He says Google's G Suite is fine and dandy, but I don't see that truly as an enterprise solution. And frankly, it's still not of the quality of an Office application, talking about Microsoft. All in all I really like the infrastructure-as-a-service and the platform-as-a-service components that GCP had. And I thought they were coming along very very well in that space. Now, the reason that I share this is because the IT buyers that we speak with, you know they're very serious about exploring Google. They want options other than Azure and AWS and they see Google as having great tech and as a viable alternative. So let's talk about GCP and the enterprise. We looking, when we look into the ETR data for the most recent survey, which ran in June and early July, GCP is showing strength in one really important bellwether category, the giant public and private companies. These are the largest firms in the ETR dataset and often point to secular trends. Now, before we get into that, let's look at the picture for GCP using ETR's net score up methodology. This is fundamental to the ETR approach, and remember, each quarter ETR goes out and asks its respondents, are you planning to spend more or less? In its July survey, ETR focuses on second half spending. The next chart captures results across Google's entire portfolio. So here's the breakdown for, for Google across all sectors. 14% of the respondents are adopting new, that's the lime green. 39% plan to increase spending in the second half versus the first half, that's the forest green. Then there's a big fat middle, that's flat, and you see that in the gray area. And the 7% are spending less, with 2% replacing, that's the pinkish and dark red, respectively. So, I would say this result is mixed, in my opinion. Yeah, it's not bad, don't get me wrong, and we've, we'll see once ETR comes out of its quite period, how this compares to Azure and AWR, so remember, I can only share limited data until ETR clients get the data and have time to act on it. But this calculates out to a net score of 44%, which is respectable, but frankly not overly inspiring. So let's look across the GCP portfolio using the ETR taxonomy and see what it looks like. This chart shows the net score comparisons across three different surveys, October 19, April 20, and July 20. So reading the bars left to right, you can see Google's strong suit really is machine learning and AI. Container platforms are also very strong, as are functions, or server-less, and databases, very solid, we'll talk more about that in a minute. You know, video conferencing was just added by ETR and sure it pops up with the work from home. Cloud is actually holding firm when compared to October of last year. But surprisingly, analytics is looking a bit softer. And ETR for the first time added G Suite with, it shows a 26% net score, first time out, which is pretty tepid. I mean not very impressive at all. But overall, the picture looks pretty good for Google. So let's dig further into the giant public and private sector, that bellwether I talked about. And let's peal the onion a bit and look closer at the results from the largest companies in the dataset. So this chart shows the giant public, plus private organizations. So it would include like monster public companies but also large companies like a Cargill or a Coke Industries, if in fact they responded in this survey. And you can see, in that all important sector, it's a story of a lot of green with hardly any red, so quite a positive sign for Google within those bellwethers. Here's what I think is happening here. Is these large, and often far flung organizations, have realized that they have multiple cloud vendors, and they're asking their senior IT leadership to bring some consistency and sanity to their cloud strategies. So they look at the big three and say, okay, what's the best strategic fit for each workload? So they might say for instance let's use AWS for core IaaS, let's use Azure for productivity workloads, and we'll sprinkle some Google in for machine learning and related projects. So we do see some real strength in some of the larger strongholds for Google, although interestingly ETR sort of tells me that there's softness in the midsize and smaller companies that have powered AWS for so many years. And of course this, with Google's base, but compare that to AWS and AWS is much stronger in those smaller companies, start-ups and the like, and of course COVID's the wild car in all this. You know, we have to take that into account, and we will with Sagar Kadakia, who's ETR's director of research in the coming weeks. But I want to look at Google in the all important database category. So before we wrap, let's look at database. You remember, Google's playing catch up in the cloud and its marketing takes a more open posture around partners and things like multi-cloud and you know you can contrast that with AWS for example, but look, make no mistake, Google wants you data in their cloud, and that's why database is so strategic and so important. Look, it's the mother of all lock specs. All you got to do is look at Oracle and their success. Now, as we've reported many times, there's a new workload emerging in the cloud around this idea of the modern data warehouse. I mean I don't even like that term anymore, data warehouse, because it sounds just so static. But anyway, any rate, I'm talking about workloads that bring database, machine learning, AI, data science, compute and storage along with visualization tools to deliver real-time insights and operational analytics. Database is at the heart of everything here. Win the database and everything else falls into place. Now, Google has six or seven database products and one of the most impressive, in my opinion, is BigQuery. I mean, for those who have followed me over the years you know I love the technology behind Google's banner, but BigQuery is where much of the action is around this new workload that I'm talking about. So, let's look at, deeper at Google's position in database. This chart shows one of my favorite views. On the Y axis is the net score, or spending momentum, and on the X axis is market share or pervasiveness in the ETR dataset. The chart plots various database companies and their position within the all important giant public plus private sector. So these are the companies in the ETR survey that are the largest, and oftentimes, again, are a bellwether. And you can see Microsoft and Oracle and AWS have very strong presence on the horizontal axis. Mongo, MongoDB looms large, MemSQL, they just raised 50 million dollars this past May, MariaDB just raised another 25 million this month. You can see Couchbase and Redis, they show up, and they're on my radar. I'm learning more about those companies. Folks, database is hot. VC's are pouring money in and it's something that's very important to the Cube community to look at. And of course you see Google in the chart, with a strong net score, you know, but not the type of market presence that you see from the other big cloud players. In fact, they've pulled back a little somewhat in this last ETR survey. So despite some bright spots in the enterprise in terms of spending momentum, just not quite enough presence yet. Oh, by the way, look who's right there with Google. I know I sound like a broken record, but Snowflake is everywhere. You'll find them in AWS, you'll find them in Azure and on GCP. Now remember, Snowflake is only about one tenth the size of Google's IaaS and PaaS business. But it has stronger spending momentum than all the big guys, and it continues to creep its way to the right in terms of market share or presence. You know, but Google has great database tech and BigQuery is at the heart of its strategy to support analytics at scale, and automate the data pipeline. BigQuery's very well designed, it started as a cloud native database, it's based on server-less, it's highly scalable, and it's very cost-effective. In fact, ESG, enterprise strategy group, wrote a report comparing the TCO of the cloud databases. Let me pull that up and show you. Now the report was commissioned by Google, so I got to caution you there. But it was very well done in my opinion by a guy named Aviv Kaufmann, and you can see here it compares BigQuery with the other cloud databases, and of course, you know, BigQuery wins, got the lowest TCO, but again I thought the report was really detailed and well researched. I have no doubt that Snowflake has an answer for the big brown bar, which is on-demand cloud cost. I think ESG was making certain assumptions, maybe worst case assumptions, about the need to over-provision resources for Snowflake, which I'm sure ESG can defend, but I'll bet dollars to donuts that Snowflake, you know, has an answer to that or a comeback. I'm going to ask them. But the point I want to make here is that BigQuery was designed from day one, again, as a cloud-native database. We've been talking about that a lot. It's very efficient and is going to be competitive. So you can see, there are some bright spots in the enterprise, for Google. Okay, let's wrap up. Now, having called out some of the positives, and there are many, Google is still not getting it done in the enterprise, in my opinion. I certainly would not say too little too late, but I would say they spotted the competition a huge lead, and the only reason is Google just didn't act on the opportunity staring them in the face, within the enterprise, fast enough, and they finally woke up. But enterprise sales are, they're really hard. Thomas Kurian, for all his experience, is coming from way, way behind with regard to the enterprise go to market, systems and processes, pricing, partnerships, special deals for the enterprise. Google's still learning how to sell the business outcomes and is relying far too much on its technology chops, which, while impressive, are not going to win the day without better enterprise sales, marketing, and ecosystem integration. Now I feel like for years, Google has said to the enterprise market, give me heat and I'll add the wood. Meaning we have the best tech, go ahead and use it. That strategy just doesn't work in the enterprise. Kurian knows it and I suspect that's why Google's showing some strength within these large, giant public and private companies. They're probably applying focused sales resources to nail customer success with some of its top accounts where they have a presence, and then once they nail that they'll broaden to the market. But they got to move fast. We'll learn more about Google's intentions and its progress over the next few, next few months as they try their online event experiment, and of course we'll be there providing our wall to wall coverage. Remember, these Breaking Analysis episodes, they're all available as podcasts. ETR is shortly exiting its quiet period, this week, and will be rolling out the data, so check out etr.plus. I publish weekly on wikibon.com and siloconeangle.com and as always please comment on my LinkedIn posts, I really appreciate the feedback. This is Dave Vellante for the Cube Insights, powered by ETR. Thanks for watching everyone. We'll see you next time.

>> Announcer: Live from midtown Manhattan, it's theCUBE, covering BigData New York City 2017, brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Okay, welcome back everyone, we're live in New York City, this is theCUBE's coverage of BigData NYC, this is our own event for five years now we've been running it, been at Hadoop World since 2010, it's our eighth year covering the Hadoop World which has evolved into Strata Conference, Strata Hadoop, now called Strata Data, and of course it's bigger than just Strata, it's about big data in NYC, a lot of big players here inside theCUBE, thought leaders, entrepreneurs, and great guests. I'm John Furrier, the cohost this week with Jim Kobielus, who's the lead analyst on our BigData and our Wikibon team. Our next guest is Yaron Haviv, who's with iguazio, he's the founder and CTO, hot startup here at the show, making a lot of waves on their new platform. Welcome to theCUBE, good to see you again, congratulations. >> Yes, thanks, thanks very much. We're happy to be here again. >> You're known in the theCUBE community as the guy on Twitter who's always pinging me and Dave and team, saying, "Hey, you know, you guys got to "get that right." You really are one of the smartest guys on the network in our community, you're super-smart, your team has got great tech chops, and in the middle of all that is the hottest market which is cloud native, cloud native as it relates to the integration of how apps are being built, and essentially new ways of engineering around these solutions, not just repackaging old stuff, it's really about putting things in a true cloud environment, with an application development, with data at the center of it, you got a whole complex platform you've introduced. So really, really want to dig into this. So before we get into some of my pointed questions I know Jim's got a ton of questions, is give us an update on what's going on so you guys got some news here at the show, let's get to that first. >> So since the last time we spoke, we had tons of news. We're making revenues, we have customers, we've just recently GA'ed, we recently got significant investment from major investors, we raised about $33 million recently from companies like Verizon Ventures, Bosch, you know for IoT, Chicago Mercantile Exchange, which is Dow Jones and other properties, Dell EMC. So pretty broad. >> John: So customers, pretty much. >> Yeah, so that's the interesting thing. Usually you know investors are sort of strategic investors or partners or potential buyers, but here it's essentially our customers that it's so strategic to the business, we want to... >> Let's go with GA of the projects, just get into what's shipping, what's available, what's the general availability, what are you now offering? >> So iguazio is trying to, you know, you alluded to cloud native and all that. Usually when you go to events like Strata and BigData it's nothing to do with cloud native, a lot of hard labor, not really continuous development and integration, it's like continuous hard work, it's continuous hard work. And essentially what we did, we created a data platform which is extremely fast and integrated, you know has all the different forms of states, streaming and events and documents and tables and all that, into a very unique architecture, won't dive into that today. And on top of it we've integrated cloud services like Kubernetes and serverless functionality and others, so we can essentially create a hybrid cloud. So some of our customers they even deploy portions as an Opix-based settings in the cloud, and some portions in the edge or in the enterprise deployed the software, or even a prepackaged appliance. So we're the only ones that provide a full hybrid experience. >> John: Is this a SAS product? >> So it's a software stack, and it could be delivered in three different options. One, if you don't want to mess with the hardware, you can just rent it, and it's deployed in Equanix facility, we have very strong partnerships with them globally. If you want to have something on-prem, you can get a software reference architecture, you go and deploy it. If you're a telco or an IoT player that wants a manufacturing facility, we have a very small 2U box, four servers, four GPUs, all the analytics tech you could think of. You just put it in the factory instead of like two racks of Hadoop. >> So you're not general purpose, you're just whatever the customer wants to deploy the stack, their flexibility is on them. >> Yeah. Now it is an appliance >> You have a hosting solution? >> It is an appliance even when you deploy it on-prem, it's a bunch of Docker containers inside that you don't even touch them, you don't SSH to the machine. You have APIs and you have UIs, and just like the cloud experience when you go to Amazon, you don't open the Kimono, you know, you just use it. So our experience that's what we're telling customers. No root access problems, no security problems. It's a hardened system. Give us servers, we'll deploy it, and you go through consoles and UIs, >> You don't host anything for anyone? >> We host for some customers, including >> So you do whatever the customer was interested in doing? >> Yes. (laughs) >> So you're flexible, okay. >> We just want to make money. >> You're pretty good, sticking to the product. So on the GA, so here essentially the big data world you mentioned that there's data layers, like data piece. So I got to ask you the question, so pretend I'm an idiot for a second, right. >> Yaron: Okay. >> Okay, yeah. >> No, you're a smart guy. >> What problem are you solving. So we'll just go to the simple. I love what you're doing, I assume you guys are super-smart, which I can say you are, but what's the problem you're solving, what's in it for me? >> Okay, so there are two problems. One is the challenge everyone wants to transform. You know there is this digital transformation mantra. And it means essentially two things. One is, I want to automate my operation environment so I can cut costs and be more competitive. The other one is I want to improve my customer engagement. You know, I want to do mobile apps which are smarter, you know get more direct content to the user, get more targeted functionality, et cetera. These are the two key challenges for every business, any industry, okay? So they go and they deploy Hadoop and Hive and all that stuff, and it takes them two years to productize it. And then they get to the data science bit. And by the time they finished they understand that this Hadoop thing can only do one thing. It's queries, and reporting and BI, and data warehousing. How do you do actionable insights from that stuff, okay? 'Cause actionable insights means I get information from the mobile app, and then I translate it into some action. I have to enrich the vectors, the machine learning, all that details. And then I need to respond. Hadoop doesn't know how to do it. So the first generation is people that pulled a lot of stuff into data lake, and started querying it and generating reports. And the boss said >> Low cost data link basically, was what you say. >> Yes, and the boss said, "Okay, what are we going to do with this report? "Is it generating any revenue to the business?" No. The only revenue generation if you take this data >> You're fired, exactly. >> No, not all fired, but now >> John: Look at the budget >> Now they're starting to buy our stuff. So now the point is okay, how can I put all this data, and in the same time generate actions, and also deal with the production aspects of, I want to develop in a beta phase, I want to promote it into production. That's cloud native architectures, okay? Hadoop is not cloud, How do I take a Spark, Zeppelin, you know, a notebook and I turn it into production? There's no way to do that. >> By the way, depending on which cloud you go to, they have a different mechanism and elements for each cloud. >> Yeah, so the cloud providers do address that because they are selling the package, >> Expands all the clouds, yeah. >> Yeah, so cloud providers are starting to have their own offerings which are all proprietary around this is how you would, you know, forget about HDFS, we'll have S3, and we'll have Redshift for you, and we'll have Athena, and again you're starting to consume that into a service. Still doesn't address the continuous analytics challenge that people have. And if you're looking at what we've done with Grab, which is amazing, they started with using Amazon services, S3, Redshift, you know, Kinesis, all that stuff, and it took them about two hours to generate the insights. Now the problem is they want to do driver incentives in real time. So they want to incent the driver to go and make more rides or other things, so they have to analyze the event of the location of the driver, the event of the location of the customers, and just throwing messages back based on analytics. So that's real time analytics, and that's not something that you can do >> They got to build that from scratch right away. I mean they can't do that with the existing. >> No, and Uber invested tons of energy around that and they don't get the same functionality. Another unique feature that we talk about in our PR >> This is for the use case you're talking about, this is the Grab, which is the car >> Grab is the number one ride-sharing in Asia, which is bigger than Uber in Asia, and they're using our platform. By the way, even Uber doesn't really use Hadoop, they use MemSQL for that stuff, so it's not really using open source and all that. But the point is for example, with Uber, when you have a, when they monetize the rides, they do it just based on demand, okay. And with Grab, now what they do, because of the capability that we can intersect tons of data in real time, they can also look at the weather, was there a terror attack or something like that. They don't want to raise the price >> A lot of other data points, could be traffic >> They don't want to raise the price if there was a problem, you know, and all the customers get aggravated. This is actually intersecting data in real time, and no one today can do that in real time beyond what we can do. >> A lot of people have semantic problems with real time, they don't even know what they mean by real time. >> Yaron: Yes. >> The data could be a week old, but they can get it to them in real time. >> But every decision, if you think if you generalize round the problem, okay, and we have slides on that that I explain to customers. Every time I run analytics, I need to look at four types of data. The context, the event, okay, what happened, okay. The second type of data is the previous state. Like I have a car, was it up or down or what's the previous state of that element? The third element is the time aggregation, like, what happened in the last hour, the average temperature, the average, you know, ticker price for the stock, et cetera, okay? And the fourth thing is enriched data, like I have a car ID, but what's the make, what's the model, who's driving it right now. That's secondary data. So every time I run a machine learning task or any decision I have to collect all those four types of data into one vector, it's called feature vector, and take a decision on that. You take Kafka, it's only the event part, okay, you take MemSQL, it's only the state part, you take Hadoop it's only like historical stuff. How do you assemble and stitch a feature vector. >> Well you talked about complex machine learning pipeline, so clearly, you're talking about a hybrid >> It's a prediction. And actions based on just dumb things, like the car broke and I need to send a garage, I don't need machine learning for that. >> So within your environment then, do you enable the machine learning models to execute across the different data platforms, of which this hybrid environment is composed, and then do you aggregate the results of those models, runs into some larger model that drives the real time decision? >> In our solution, everything is a document, so even a picture is a document, a lot of things. So you can essentially throw in a picture, run tensor flow, embed more features into the document, and then query those features on another platform. So that's really what makes this continuous analytics extremely flexible, so that's what we give customers. The first thing is simplicity. They can now build applications, you know we have tier one now, automotive customer, CIO coming, meeting us. So you know when I have a project, one year, I need to have hired dozens of people, it's hugely complex, you know. Tell us what's the use case, and we'll build a prototype. >> John: All right, well I'm going to >> One week, we gave them a prototype, and he was amazed how in one week we created an application that analyzed all the streams from the data from the cars, did enrichment, did machine learning, and provided predictions. >> Well we're going to have to come in and test you on this, because I'm skeptical, but here's why. >> Everyone is. >> We'll get to that, I mean I'm probably not skeptical but I kind of am because the history is pretty clear. If you look at some of the big ideas out there, like OpenStack. I mean that thing just morphed into a beast. Hadoop was a cost of ownership nightmare as you mentioned early on. So people have been conceptually correct on what they were trying to do, but trying to get it done was always hard, and then it took a long time to kind of figure out the operational model. So how are you different, if I'm going to play the skeptic here? You know, I've heard this before. How are you different than say OpenStack or Hadoop Clusters, 'cause that was a nightmare, cost of ownership, I couldn't get the type of value I needed, lost my budget. Why aren't you the same? >> Okay, that's interesting. I don't know if you know but I ran a lot of development for OpenStack when I was in Matinox and Hadoop, so I patched a lot of those >> So do you agree with what I said? That that was a problem? >> They are extremely complex, yes. And I think one of the things that first OpenStack tried to bite on too much, and it's sort of a huge tent, everyone tries to push his agenda. OpenStack is still an infrastructure layer, okay. And also Hadoop is sort of a something in between an infrastructure and an application layer, but it was designed 10 years ago, where the problem that Hadoop tried to solve is how do you do web ranking, okay, on tons of batch data. And then the ecosystem evolved into real time, and streaming and machine learning. >> A data warehousing alternative or whatever. >> So it doesn't fit the original model of batch processing, 'cause if an event comes from the car or an IoT device, and you have to do something with it, you need a table with an index. You can't just go and build a huge Parquet file. >> You know, you're talking about complexity >> John: That's why he's different. >> Go ahead. >> So what we've done with our team, after knowing OpenStack and all those >> John: All the scar tissue. >> And all the scar tissues, and my role was also working with all the cloud service providers, so I know their internal architecture, and I worked on SAP HANA and Exodata and all those things, so we learned from the bad experiences, said let's forget about the lower layers, which is what OpenStack is trying to provide, provide you infrastructure as a service. Let's focus on the application, and build from the application all the way to the flash, and the CPU instruction set, and the adapters and the networking, okay. That's what's different. So what we provide is an application and service experience. We don't provide infrastructure. If you go buy VMware and Nutanix, all those offerings, you get infrastructure. Now you go and build with the dozen of dev ops guys all the stack above. You go to Amazon, you get services. Just they're not the most optimized in terms of the implementation because they also have dozens of independent projects that each one takes a VM and starts writing some >> But they're still a good service, but you got to put it together. >> Yeah right. But also the way they implement, because in order for them to scale is that they have a common layer, they found VMs, and then they're starting to build up applications so it's inefficient. And also a lot of it is built on 10-year-old baseline architecture. We've designed it for a very modern architecture, it's all parallel CPUs with 30 cores, you know, flash and NVMe. And so we've avoided a lot of the hardware challenges, and serialization, and just provide and abstraction layer pretty much like a cloud on top. >> Now in terms of abstraction layers in the cloud, they're efficient, and provide a simplification experience for developers. Serverless computing is up and coming, it's an important approach, of course we have the public clouds from AWS and Google and IBM and Microsoft. There are a growing range of serverless computing frameworks for prem-based deployment. I believe you are behind one. Can you talk about what you're doing at iguazio on serverless frameworks for on-prem or public? >> Yes, it's the first time I'm very active in CNC after Cloud Native Foundation. I'm one of the authors of the serverless white paper, which tries to normalize the definitions of all the vendors and come with a proposal for interoperable standard. So I spent a lot of energy on that, 'cause we don't want to lock customers to an API. What's unique, by the way, about our solution, we don't have a single proprietary API. We just emulate all the other guys' stuff. We have all the Amazon APIs for data services, like Kinesis, Dynamo, S3, et cetera. We have the open source APIs, like Kafka. So also on the serverless, my agenda is trying to promote that if I'm writing to Azure or AWS or iguazio, I don't need to change my app. I can use any developer tools. So that's my effort there. And we recently, a few weeks ago, we launched our open source project, which is a sort of second generation of something we had before called Nuclio. It's designed for real time >> John: How do you spell that? >> N-U-C-L-I-O. I even have the logo >> He's got a nice slick here. >> It's really fast because it's >> John: Nuclio, so that's open source that you guys just sponsor and it's all code out in the open? >> All the code is in the open, pretty cool, has a lot of innovative ideas on how to do stream processing and best, 'cause the original serverless functionality was designed around web hooks and HTTP, and even many of the open source projects are really designed around HTTP serving. >> I have a question. I'm doing research for Wikibon on the area of serverless, in fact we've recently published a report on serverless, and in terms of hybrid cloud environments, I'm not seeing yet any hybrid serverless clouds that involve public, you know, serverless like AWS Lambda, and private on-prem deployment of serverless. Do you have any customers who are doing that or interested in hybridizing serverless across public and private? >> Of course, and we have some patents I don't want to go into, but the general idea is, what we've done in Nuclio is also the decoupling of the data from the computation, which means that things can sort of be disjoined. You can run a function in Raspberry Pi, and the data will be in a different place, and those things can sort of move, okay. >> So the persistence has to happen outside the serverless environment, like in the application itself? >> Outside of the function, the function acts as the persistent layer through APIs, okay. And how this data persistence is materialized, that server separate thing. So you can actually write the same function that will run against Kafka or Kinesis or Private MQ, or HTTP without modifying the function, and ad hoc, through what we call function bindings, you define what's going to be the thing driving the data, or storing the data. So that can actually write the same function that does ETL drop from table one to table two. You don't need to put the table information in the function, which is not the thing that Lambda does. And it's about a hundred times faster than Lambda, we do 400,000 events per second in Nuclio. So if you write your serverless code in Nuclio, it's faster than writing it yourself, because of all those low-level optimizations. >> Yaron, thanks for coming on theCUBE. We want to do a deeper dive, love to have you out in Palo Alto next time you're in town. Let us know when you're in Silicon Valley for sure, we'll make sure we get you on camera for multiple sessions. >> And more information re:Invent. >> Go to re:Invent. We're looking forward to seeing you there. Love the continuous analytics message, I think continuous integration is going through a massive renaissance right now, you're starting to see new approaches, and I think things that you're doing is exactly along the lines of what the world wants, which is alternatives, innovation, and thanks for sharing on theCUBE. >> Great. >> That's very great. >> This is theCUBE coverage of the hot startups here at BigData NYC, live coverage from New York, after this short break. I'm John Furrier, Jim Kobielus, after this short break.