 From Midtown Manhattan, it's theCUBE. Covering Big Data, New York City, 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. Okay, welcome back everyone. We're here live in New York City for the week, three days of wall-to-wall coverage of Big Data NYC. It's Big Data Week here in conjunction with Strata, Hadoop, Strata Data, which is an event running right around the corner, it's theCUBE. I'm John Furrier with my co-host, Peter Burris. Our next guest is Jacques Estacuz, the head of Data at Pivotal. Welcome to theCUBE, good to see you again, likewise. So you guys had big news, we covered at VMworld, obviously the Kubernetes craze is fantastic. You're starting to see cloud-native platforms front and center, even in some of the operational worlds like in cloud. Data, you guys have been here for a while with Green Plum and now Pivotal's been adding more to the Data Suite. So you guys are a player in this ecosystem, correct? As it grows, we much more developer-centric and enterprise-centric and AI-centric. What's the update? So I'd like to talk about a couple things, just three quick things here. One focused primarily on simplicity. And so first and foremost, as you said, there's a lot of things going on on the cloud-boundary side, a lot of things that we're doing with Kubernetes, et cetera, super exciting. I will say Tony Baird just wrote a nice piece about Green Plum in ZDNet, essentially calling Green Plum the best-kept secret in the analytic database world. And why I think that's important is what isn't really well-known is that over the period of Pivotal's history, now the last four and a half years, we focused really heavily on the cloud-boundary side, on DevOps, on getting users to actually be able to publish code. What we haven't talked about as much is what we're doing on the data side. And I find it very interesting to repeatedly tell analysts and customers that the Green Plum business has been and continues to be a profitable business unit within Pivotal. And so as we're growing on the cloud-boundary side, we're continuing to grow a business that many of the organizations that I see here at Strata are still looking to get to, that ever-forgotten profitability zone. So then- How about there's a legacy around Green Plum? I'm not going to say they pivoted and unintended Pivotal. You've just been adding stuff around Green Plum. So Green Plum might've get lost in the messaging because it's been now one of many ingredients. It's true. When we formed Pivotal, I think there were 34 some different SKUs that we have now focused in on over the last two years or so. And what's super exciting is, again, kind of over that time period, one of the things that we took to heart within the Green Plum side is this idea of extreme agile. And so, as you guys know, Pivotal Labs being a core part of the Pivotal mission helps our customers figure out how to actually build software. We finally are drinking our own champagne and over the last year and a half of Green Plum R&D, we're shipping code, like a complete data platform or shipping that on a cadence of about four to five weeks, which, again, kind of is a little bit unheard of in the industry, being able to move at that pace. We worked through the backlog and what is also super exciting, and I'm glad that you guys are able to help me tell the world, we released version five last week. Version five is actually the only parallel open source data platform that actually has native ANSI compliance SQL. And I feel a little bit like I've rewound the clock 15 years where I have to actually throw in the ANSI compliance, but I think that in a lot of ways there are SQL alternatives out there in the world. They are very much not ANSI compliant, and that hurts. I mean, it's a nuance, but it's table stakes in the enterprise. ANSI compliance is just- Well, but there's a reason why you want to be ANSI compliance is because there's a whole swath of analytic applications, mainly in the data warehouse world that were built using ANSI compliant SQL. Yeah, so why do this with version five? I presume it's got to have something to do with you want to start capturing some of those applications and helping customers modernize them. That is correct. And so I think the SQL piece is one part of the data platform, of really a modern data platform. The other parts are again, becoming table stakes, so being able to do text analytics. So we've baked Apache solar within Green Plum. Being able to do graph analytics or spatial analytics, anything from classifications or regressions, all of that actually becomes table stakes. And we feel that enterprises have suffered a little bit over the last five or six years. They've had this promise of having a new platform that they can leverage for doing interesting new things, machine learning, AI, et cetera. But the existing stuff that they were trying to do has been super, super hard. And so what we're trying to do is bridge those together and provide both in the same platform out of the gate so that customers can actually use it immediately. And I think one of the things that we've seen is there's about a thousand to one SQL experienced individuals within the enterprise versus like say for example, Hadoop experienced individuals. The other thing that I think is actually super important and almost bigger than everything else I talked about is we're the, so a lot of the old school Postgres deriviance of MPP databases forked their databases at some point in Postgres' history for a variety of reasons from licensing to when they started. Green Plum's no different. So we forked right around 8.2. With this last release of version five, we've actually up-leveled the Postgres base within Green Plum to 8.3. Now in and of itself, it doesn't sound. What does that mean? So we are now taking a 100% commitment both to open source and both to the Postgres community. I think if you look at Postgres today in its latest versions, it is a full-fledged mission-critical database that can be used anywhere. And what we feel is that if we can bring our core engineering developments around parallelism, around analytics, and combine that with Postgres itself, then we don't have to implement all of the low-level database things that a lot of our competitors have to do. And what's unique about it is one, Green Plum continues to be open source, which again, most of our competitors are not. Two, if you look at primarily what they're doing, nobody's got that level of commitment to the Postgres community, which means all of their resources are gonna be stuck building core database technology, even building that ANSI SQL compliance in, which will get quote unquote for free, which will let us focus on things like machine learning. Just give a quick second to just talk about the relevance of Postgres because of the success. First of all, it's massive, it's everywhere, but it's not going anywhere. I mean, just give a quick, for the audience watching, what's the relevance of it? Sure, sure, sure. Like you said, I mean, it's everywhere. It is the most full-featured actual database in the open source community. Arguably, MySQL has more market share, but MySQL projects that generally leverage them are not used for mission-critical enterprise-ish applications. So being able to have parity allows us not only to have that database technology baked in the green foam, but it also gives us all of the community stuff with it. So everything from being able to leverage the most recent ODBC and JDBC libraries, but also integrations into everything from the PostGIS driver for geospatial to being able to connect to other types of data sources, et cetera. So this big community shows us that it's successful, but then again. And it doesn't come in a red box. It does not come in a red box, if that is correct. Which is not a bad thing. But look, PostGIS, as a technology, was developed a long time ago, largely in response to the need to think about how analytics and transaction or analytics and operating applications might eventually come together. And we're now moving in a world where we can actually see the hardware and a lot of practices, et cetera, are beginning to find ways where this may start to happen. So I know green foam and PostGIS, both MPP-based. So by going to this, you're able to stay more modern, more up to date on all the new technology that's coming together to support these new, richer, more complex classes of applications. So you're spot on. I suppose I would argue that PostGIS, I feel, kind of came up with as a response to Oracle in the past of, you know, we need an open source alternative to Oracle. But other than that, 100% correct. I think- But there's always a difference between PostGIS and MySQL. Always. MySQL always was, okay, so that's that. Well, let's do that open source and PostGIS, coming out of Berkeley and coming out of some other places, always had a slightly different notion of the types of problems it was gonna take on. 100% correct, 100%. So, but to your question before, what does this all mean to customers? I think the one thing that version five really gives us the confidence to say is, and a lot of times I hate lobbying on the walls out like this, but we welcome and embrace with open arms any teradata customers out there that are looking to save millions of, not tens of millions of dollars on a modern platform that can actually run not only on-premise, not only on bare metal, but virtually, and off-premise. So we're truly the only MPP platform, the only open source MPP data platform that can allow you to build analytics and move those analytics from Amazon to Azure to back on-prem. Talk about this, the teradata thing for a second. They want to get down to double click on that. Customers don't want to change code. They don't. So what specifically are you guys offering teradata customers specifically? So with the release of version five, with a lot of the development that we've done and some of the partnering that we've done, we are now able to take without changing a line of code of your teradata applications. You load the data within the Green Plum platform, you can point those applications directly to Green Plum and run them unchanged. So I think in the past, the reticence to move to any other platform was really the amount of time it would take to actually redevelop all of the stuff that you had. And so we offer an ability to go from an immediate ROI to a platform that, again, kind of bridges that gap, allows you to really be moderate. Peter, I want to talk to you about that importance that we just said, because we've been, you've been studying the private cloud report, true private cloud, which is on-premises, moving to a cloud operating model, automating away undifferentiated labor and shipping that to differentiated labor. But this brings up what customers want in hybrid cloud and ultimately having public cloud and private cloud. So hybrid sits there. They don't want to change their code base. This is a huge deal. So I would say a couple of things to build upon what Jock said. The first thing is that you're right. People want the data to run where the data naturally needs to run, or should run. And that's the big argument about public versus hybrid versus what we call true private cloud. The idea that increasingly the workload needs to be located where the data, where it naturally should be located because of the physical, legal, regulatory, intellectual property attributes of the data. So being able to do that is really, really important. The other thing that Jock said, and Bill's running on this question, John, is that ultimately in too many domains within this analytics world, which is fundamentally predicated in the idea of breaking data out of applications so that you can use it in new and novel and more value-creating ways, is that the data gets locked up in a data warehouse. And what's valuable in a data warehouse is not the hardware, it's the data. And so by providing the facility for being able to point an application at a couple of different data stores, including one that's more modern or takes advantage of more modern technology and can be considerably cheaper, it means that the shop can elevate the story about the asset. And the asset here is the data and the applications that run against it, not the hardware and the system where the data is stored and located. One of the biggest challenges we talked earlier with one of the, just to go on for a second, we talked earlier with a couple of other guests about the fact that the industry still, when your average user still doesn't understand how to value data, how to establish a data asset. And one of the reasons is because it's so constantly commingled with the underlying hardware silos. And actually, I'd even further go on, like I think the advent of some of these new cloud data warehouses forgets that notion of being able to kind of run it in different places and provides one of the things that customers are really looking for, which is simplicity. The ability to spin up a quick MPP SQL system within, say, Amazon, for example, almost without a doubt, a lot of the business users that I speak to are willing to sacrifice capabilities within the platform, which they are for the simplicity of getting it up and going. And so one of the things that we've really focused on in V5 is being able to give that same-term key feel. And so Green Plum exists within the Amazon Marketplace, within the Azure Marketplace, Google later this quarter. And then, in addition to the simplicity, it has all of the functionality that is missing in those platforms. So again, kind of all the analytics, all the ability to reach out and federate queries against different types of data. I think it's exciting as we continue to progress in our releases. Green Plum has, for a number of years, had this ability to seamlessly query HGFS. Again, like a lot of the competitors. But HGFS isn't going away. Neither is a generic object store like S3. But we continue to extend that to things like Spark, for example. And so now the ability to actually house your data within a data platform and seamlessly integrate with Spark back and forth. If you want to use Spark, use Spark. But somewhere that data needs to be materialized so that other applications can actually leverage it as well. But even then, people have been saying, well, if you want to put it on this disk, then put it on this disk. Even the question about Spark versus some other database manager is a higher level conversation than many of the shops who invested millions and millions and millions of dollars in their analytic application portfolio. And all you're trying to do, as I interpret it, is trying to say, look, the value in the portfolio is the applications and the data. It's not the underlying elements. There's a whole bunch of new elements that we can use. You can put it in the cloud. You can put it on-premise if that's what the data belongs. You can use some of these new and evolving technologies, but you're focused on how the data and the applications continue to remain valuable to the business over time and not the traditional hardware assets. Correct. And I'll again kind of leverage a notion that we get from labs, which is this idea of user-centric design. And so everything that we've been putting into the Greenblum database is around, ideally, the four primary users of our system. Not just the analysts and not just the data scientists, but also the operators and the IT folks. And that is where I'd say the last tenant of where we're going really is this idea of co-opetition. And so I would, as the Vividel Greenblum guy that's been around for 10 plus years, I would tell you very straight up that we are, again, an open-source MPP data platform that can rival any other platform out there, whether it's Teradata, whether it's Hadoop. We can be that platform. Why should customers call you up? Why should they call you? All this other stuff out, they've got legacy, they've got Teradata, and I might have other things. People are knocking on my door. Sure. I mean, they're getting pounded with sales messages. Yeah. Buy me, I'm better than the other guy. Why Vividel data? So the first thing I would say is the latest reviews from Gartner, for example. Well, actually, let me rewind. I will easily argue that Teradata has been the data warehouse platform for the last 30 years that everyone has tried to emulate. I'd even argue so much is that when Hadoop came on the scene eight years ago, what they did was they changed the dynamics, and what they're doing now is actually trying to emulate the Teradata success through things like SQL on top of Hadoop. What that has basically gotten us to is we're looking for a Teradata replacement at Hadoop-like prices. That's what Greenplum has to offer in space. Now, if you actually extend that just a little bit, I still recognize that not everybody's gonna call us, there are still 200 other vendors out there that are selling a similar product or similar kinds of stories. What I would tell you in response to those folks is that Greenplum has been around in production for the last 10 plus years. We're a proven technology for solving problems. Many of those are not. We work very well on this cooperative spirit of, Greenplum can be the end-all, be-all, but I recognize it's not gonna be the end-all, be-all. So this is why we have to work within the ecosystem. I think any modern enterprise is gonna open up more. It's dominating. I mean, at the Linux event, we catch cover open source summit, 90% of software written will be open source libraries, 10% is where the value's being added. It won't take that. For sure. If you were to start up a new startup right now, would you go with a commercial product? No. It's folks, grass, databases, good. All right, final question was to end the segment. This big data space is now being called data. Certainly, Hadoop is now strata data. It's trying to keep that show going longer. But you've got Microsoft Azure making a lot of waves going on right now with Microsoft Ignite, so cloud is into the play here. Data's changed. The question is, how has this industry changed over the past eight years? I mean, go back to 2010 when my sub-Greenplum come prior to even getting bought out, but they were gonna ask the same product kind of all. Where has the space gone? I mean, what's happened? How would you summarize it to someone who's walking in for the first year like, hey, back in the old days when we used to walk to school and the snow with no shoes on. Both ways. It's like, now it's like, get off my lawn, you young developer. Seriously, what is the evolution of the invention? I would you explain it? So again, I would start with, Teradata started the industry, I mean, by far. And then folks like Nathisa and Greenplum came around to really give a lower cost alternative. Hadoop came on the scene eight some years ago and what I pride myself in being at Greenplum for this long, and Greenplum implemented the MapReduce paradigm as Hadoop was starting to build. And as it continued to build, we focused on building our own distribution and sequel on Hadoop. I think what we're getting down to is a brass tacks of the business is tired of technological science experiments and they just want to get stuff done. And what we- And a cost of ownership that's manageable. That is correct. And sustainable. And sustainable. And not in a spot where they're gonna be locked into a single vendor. Hence the open source. So the ones that are winning today employed what strategy that ended up working out and what strategy didn't end up working about? If you go back and say, yeah, the people who took this path failed, people who took this approach won. What was the answer? So I would say, I mean, clearly anybody who was in appliance, that has long since kind of drifted. I'd also say Greenplum's in this unique position where- In appliance too. Well, so pseudo-appliance, yes. I still have to respond to that. We were always open source. We were always software. You pivoted luckily before you pivoted. But putting that aside, the hardware vendors have gone away. All of the software competitors that we had have actually either been sunset, sold off, and forgotten. And so Greenplum, here we sit as kind of the sole standard or person that's been around for the long haul. We are now seeing a spot where we have no competition other than the forgotten really legacy guys like Teradata. People are longing to get off of legacy and onto something modern. The trick will be whether that modern is some of these new and upcoming players in technologies or whether it really focuses on some of the models. So what was the strategy? What was the winning strategy? Stick to your knitting, stick to what you know? Or was it more- So for us it was twofold. Long it was continuing to service our customers and make them successful. So that was how we built a profitable data platform business. And then the other was to double down on the strategies that seem to be interesting to organizations which were cloud, open source, and analytics. And like you said, I talked to one of the folks over at the Air Force and he was mentioning how to him data is actually more important than fuel. Being able to understand where the airplanes are, where the fuel is, where the people are, where the missiles are, et cetera. And that's actually more important than the fuel itself. And so data is the thing that powers everything. Data is the currency of everything now. Great. Shox, thanks so much for coming on theCUBE. Congratulations. Pivotal data platform, Data Suite, Green Plum now with all these other assets, congratulations. Stay on the path, helping customers you can't lose. Exactly. All right, it's theCUBE here helping you figure out the big data noise. We're obviously in big data in New York City event for our annual SiliconANGLE Cube Wikibon event in conjunction with Strata data across the street. More live coverage here for three days here in New York City. I'm John Furrier, Peter Burris. We'll be back after this short break.