 Live from San Jose, California, in the heart of Silicon Valley, it's theCUBE. Covering Hadoop Summit 2016. Brought to you by Hortonworks. Now, here are your hosts, John Furrier and George Gilbert. Hello everyone, welcome back to Silicon Valley. We are here at the Hadoop Summit 2016. This is SiliconANGLE Media's theCUBE. This is our flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier. My co-host George Gilbert, SiliconANGLE Media's and Wikibon's big data analyst. We are here with Tony Cavanaugh, CMO of Actian. Welcome to theCUBE. Thank you very much guys. Good to see you again. First time on theCUBE, CUBE alumni. Welcome, congratulations. Give us the update on Actian. What's going on? Vis-a-vis the landscape of the exploding big data world. Here in this ecosystem, it's gone beyond Hadoop. Things are changing, but it's growing. I mean, there's a lot of growth going on, but it wasn't growing the way people thought it was 10 years ago. It's completely going in a different direction. Yeah, you know, it's a fascinating marketplace. You just know that things are changing radically right now. And if enemy doesn't see that coming there, they've got some waking up to do. But the cool thing is Actian. Actian is a very interesting company. We've been, you know, I've heard directly from customers that we've been a little bit quiet over the past few years. So I want to just take a couple of minutes to give you guys and the viewers a view into what, who Actian are and what we do, you know? So it's a very interesting company. We're probably one of the best kept secrets in Silicon Valley right now. We're a little bit of a dark horse. We are actually one of the largest privately held software companies out there. We have over 400 customers. I'm sorry, we have over 400 employees worldwide and over 10,000 customers, believe it or not. I'll tell you a reason why that's so, that is the way it is in a second. But we are a product portfolio company. So we have acquired companies along the way to build the current product portfolio set that we have. And what we do, we segmented those into two main categories and the first of which is what we call the data management and integration business. At the core of that is, I'm sure everybody knows, this name is a core of that is the Ingress database. And I'm sure you're familiar with Ingress. I learned it in college, database class. It's Ingress. It's undergraduate. I won't date you, that's the 80s. But it is, and it's 40 years right now. I think it's 40 years old this year. I wasn't 10 and believe me. No, but it's a proven database. It's an industry stand. It's one of those things that is still deployed, right? Yeah, absolutely. Even to the point where it's almost a sleeping giant, I feel like, so we have some of the largest companies in the world. Give an example of like some of the things. Most people think of Ingress like, oh, it's a McMain family, small selection. It's not like that at all. It's a little bit more, it's larger than that. Can you give an example of the kinds of deployments that Ingress is still running? Yeah, so you have, so one of the large account name, the name specifically, one of the largest airline companies in the world use it to schedule their aircraft around the world. I mean, that's a pretty important mission critical application. We have revenue commissioners in a couple of European countries that use us maniacally and they're no intention of moving off because there's such a deep footprint and they've got such confidence in it that they just have no intention of moving from it. So it really is a solid business. But of course it's got that a little bit of baggage because along came Oracle, along came IBM, along came Microsoft and SAP and they swept the world. But we do have this great, solid, loyal, established customer base on the Ingress side. Along with that in the DMI business, what we call the Data Management Integration Business, we have other products. We have the Versant database, which is an object database. So Versant is in our portfolio. We got Psequel, which is an embedded database. And then we have our integration suite, which is Data Connect, Data Cloud and Business Exchange. So we really do have some very interesting offerings there. But we want to talk about more specifically because more of the show, and I'll take a little time on this, is our big data business, which is the Actin Analytica platform. And in that we have Matrix, we have Vector and we have Vector in Hadoop. So Matrix is massively parallel, processing database, which is deep. We have Vector, which is broad and wide. And then we have Vector H, which sits in the Hadoop ecosystem, so that you can get access to the Hadoop data and you can analyze it very, very, very quickly using SQL. So we can talk a little bit about what Transverse is. How does your solutions to those three things fit into this ecosystem? You guys contributing to open source, you guys use open source, you're just working with open source solutions. You guys harden it. What's the role of Actin? So we make a clear distinction between being open and being open source. So we are a proprietary technology. So what we like to focus on is Vector in Hadoop, because we're in with the Hadoop conference here and we also got Strato Plus Hadoop at the. So you have enterprise customers that want certain things and they take Hadoop, use it for what it's worth. Is that the customer profile? Well, yeah, it's a large enterprise customer is trying to figure out how do you get, makes sense of all of that data in Hadoop. There's a couple of, it's very interesting. I've been talking to Gartner and looking, doing a lot of research in Gartner reports and talking to Mike Gutierry recently about what is it, where is this business going? Where's this market going? And he referenced this concept of data lakes becoming data swamps or data pits. So we're pushing lots and lots and lots of data into the Hadoop ecosystem. The challenge is how do you get that out? And how do you get it out at speed? So what a real differentiation is in our analytic, actually an analytic platform, is we're fast. Now I know it sounds like a speeds and fees literary, but we're so fast. We have independent benchmarks, a TPCH benchmark. We just released a paper today at SIGMOD, which adopted the TPCH. So performance-centric customers love you guys. Absolutely, fast, fast, fast. And I'm talking 10, 100, 1,000 times faster than some of those open source. So you allow people to do data lakes with massive speed. Absolutely. All those query using SQL, standard query language. Okay, so let's take the impact of customers. That's probably financial transaction stuff. Okay, now how do, in this world we're seeing a couple trends I want to get your thoughts on and how you see that, what's your vision there? The Docker container madness is seeing that at the application developer Hadoop and open source in general seems to be stalled, right? I'll see, we have Arun Murthy on here saying, on theCUBE saying it's gone beyond Hadoop, which is basically implying Hadoop is one building block of a few other fundamental building blocks in big data. So you have a developer tsunami coming in, application greenfield and brownfield developer opportunities, plus this DevOps cloud environment has now gone mainstream. So you have a developer dream situation here for the enterprise customers, because they now have the capability. Where do you guys fit into that whole trend? Well, I think, well, is there a factor, is there integration? So there's a very big question there. There's a lot of things that you talk about. Okay, big trend is DevOps, cloud and developers. You could argue that it's a multi-tool world, multi-analytical tool world, integration world, ecosystem is critical. So a lot of you are trying to figure out what the chessboard looks like. Yeah, what customers are. We are one of our top, the way we describe ourselves when we're talking about prospects and the market is that we solve some of the world's toughest data challenges. And with our data management and integration capabilities, we have the capabilities there to do that. And then our analytic platform, we have the capabilities to do that. But what we're seeing is, So you have that today, integration is a big part of that. Integration is a big part of what we do. So it sits alongside that Ingress database. We have those additional offerings that allow us to. So the Ingress guys love you because that's a path to the new promised land. That for integration, yeah. For integration. Yeah, and if you look at the even in the Hadoop ecosystem, one of the big challenges on the big data world is data management, it's data integration, it's data sovereignty. So we can, at one start, part of our business, yes. The other side. I'm kind of probably speaking. Yes, yes. And not a connector as in like an API connector. The other side of the business is, I'm going to quickly pass that over, right? Stuff happens on theCUBE, it's live, so it's what it is. And then the other side is the analytical business. It's our analytical business. So what's interesting though is that, yes, there's a lot of this grounds for the developers who are getting involved and who are, you know, really rolling through new open source technology who are really trying to get, you know, get their arms around what is the next big thing? The problem is that, you know, a lot of these open source technologies are not enterprise grade, per se. They really aren't. When it comes down to how do we make this thing work for the enterprise? The interesting staff from Gartner talks about, there's two of them, if I can quote them. I haven't written them, I wrote them down also. But I'm trying to do them from memory. By 2018, they say that 90% of data lakes are useless, or will be useless by 2018 because of just they have become just this murky amalgamation of data. And folks are going to try and see how they can get things out of them. That's right, I agree with that, but that's okay. No, it's a good data point. Another data point is that 70% through 2018 again, 70% of Hadoop implementations will not have realized the ROI that they said I have to do just because of the just inappropriate or unsuccessful implementation or skills gap. You know, there's a skills gap, along with these new technologies. There's this. This is a good point. You've read some that George and I and Peter Birch talk about the valuation of data question, which is, what is the value of the data? You can say, oh, if I'm running an Ingress database, I'm running flight plans on Ingress, that's pretty damn important. That data is pretty valuable for the company. But the data lake thing is interesting. So that forecast assumes that a data is not worth anything, or is not being used, or is not addressable. So you could argue, we are arguing that in the Wikibon team is that if you've got a data lake and the data is just sitting there and it, quote, looks like a swamp, if it's addressable and can move in real time at the right spot, it then becomes valuable. So it's the potential value of the data. So the question is, if you've got a swamp that's not addressable and can't move with low latency to a transaction, then it's not valuable. It's not valuable, exactly. So the question is, that kind of poo-poo's that thing. So you have to have the addressable data out there. How do you pull it out of the swamp? So exactly. So you've got to, well, first of all you've got to have the right plan. You've got to, I don't think we have actually figured this big data world out. The great thing is there's all these people who have got this massive mind share around trying to figure this thing out. We haven't quite gotten there. The future is bright, as we talked about, but where does it land, and where is the value in that? And we're trying to help companies do that with acting and allowing you to get access to that data in a language that developers understand, which is sequel, when it comes down to it. Question on acting and then being part of a broader product line, or in this case, not in terms of, some of the cloud vendors are putting together data management fabric, where it's a couple specialized databases that are kind of deeply integrated with each other. Four or five years ago, like when Nintala was just being talked about and introduced, people were like, okay, so now we're going to have a mature, you know, BI-oriented sequel engine. We'll have hype for ETL. But we had a perfusion of these databases. Databases. What's the access of competition now? So I think here's what's really interesting, and you know, I spent a couple years at DataStacks, which were fantastic, a company, great technology, great people. What emerged from that over the years is that databases are moving to this multi-model world. So recently, we've provided DataStacks, they have issued a release to DSE graph, or DataStacks Enterprise graph, so they're focusing in on different type of problem that these databases solve different problems, right? There's different use cases very much for different databases. There's some of my 290 plus databases out there, and they're all built for varying purposes. So you've got to look across, you know, what is the use case, what are the use cases you're trying to address, and what is the right database for that? Well, the database, if they pick, if they don't have open data, if you have open data, it assumes the database is not an issue. Yeah. You pick your database and just, as long as it's open. Yeah. So, but you have to have it, but it depends on what you're trying to solve for. So graph solves for something very, very different from a column restore. And it does things very, very differently. So you've got that LinkedIn model, or that Facebook model, it's a relationship model. It's not a relational model, but the relationships and its vertices and axes and nodes and so on. And then you have your relational database, that's a very specific use case, as does a distributed database like an Apache Cassandra. Okay, so Tony, you have a challenge. You have actually a portfolio of companies that were acquired together, but now it's a patchwork. I mean, look at Google Alphabet. I mean, you're starting to see that, that's now a norm in corporate business structure, and then build the synergies on top of it. Is there plans along that? Could you take a minute to explain kind of what your plans are with Actian? What your thoughts are? Oh, absolutely, and it is a challenge. I mean, particularly when you acquire companies across, you know, over a period, you know, how do you make it all work together? And I think what we have done is we have looked at, you know, we've said, right, data management and integration is one aspect. It's a significant thing to solve for. And that the analytics piece is also something we have looked at as being separate, but there's definitely this across cell opportunity there. There's definitely a cross-pollination. I mean, as we talked about in the big ecosystem, data management, integration, sovereignty is a very, very important thing. Oftentimes something that you've got to think of first, which is something that we have knocked on. But global businesses have to think about that for sure. Absolutely, but we've not done that from the outset. And now it's coming back to being that. So what we're doing is we're actually looking into the market and we've had a, we're having a very, we haven't established business. And we're, as you said, we've got over 400 employees and thousands and thousands of customers. So we've got amazing technology. Now we've just got to figure out where does that apply? And the world we talked about the outset is changing and rapidly changing. Big opportunity. So it's a massive opportunity. So it behooves us. We have to step back and go, okay, what is happening now? You know, in columns like this, they're burgeoning. I mean, it's bigger than it was last year. Straddle plus the deep in New York is going to be, it's going to be incredible. I mean, we're looking forward to being there. Well, it's always the eye of the storm. You don't know whether you're in the eye of the storm or the storm past your eye, but cloud has certainly over the past year, two years. But this past 12 months exploded the big data world. Now you got compute, you got interoperability. Now you got Docker containers for application developers to the whole DevOps thing. It's just propelling the applications, into the data, into the applications. Yeah, so what we've done, so to that point, what we've done is we're stepping back and we're getting out there, putting our feeders out, doing a lot of research. There's a couple of key trends that we saw, we're seeing popping up. One, of course, is the continued growth of Hadoop. The country to whatever the analysts are saying about whether things are going to be successful or not, the growth is there and it's not stopped. Okay, so my final question, I've got to ask the question that's on my mind, everyone's mind, is there a master plan being hatched right now in acting headquarters? Sounds like you're doing the research, big opportunity, a lot of assets that play here. I think you always, in our business, you've always got to be hatching a master plan. You really do. I mean, it's particularly at the rate at which the market is moving, you've got to always be on top of what's coming up. You've got to be ahead of that next train. Because people expect that of you and for us, what's next is really, we being quiet, I'm telling you, I'm not behind the door about this. Acting is not being out in front of the market and we're going to change that. We're going to change it. As CMO, you're going to change that. And you hope to change that, right? Hope to change that. All right. Tony, thanks for coming on theCUBE. CMO of ActiN here on theCUBE at Hadoop Summit. The world is exploding. There's great stuff happening in big data, big data cloud, analytics, all driving value. Big value, this is theCUBE, live from Silicon Valley. We're right back with more after this short break.