 The Cube, at Big Data SV 2014, is brought to you by headline sponsors WAN Disco. We make Hadoop Invincible, and Actian, accelerating Big Data 2.0. Hi everybody, this is Dave Vellante, and I'm here with Jeff Kelly, and this is the Cube. These are covering it live of Big Data SV, Silicon Valley, we're here at the Santa Clara Hilton, right across the street from the Santa Clara Convention Center, we're strata-confused going on all week, and the Cube is, as you know, a live mobile studio. We go out to the events, we extract the signal from the noise, and we love to bring innovators on, startups, big companies, mid-sized companies, customers, and we have a Cube alum here today. Lawrence Schwartz is with Attunity, he's the Vice President of Marketing, and has been on a number of times. Lawrence, welcome to the Cube, good to see you again. Thanks for having me back. So, Attunity is smoking hot, you guys, you know, the public company, stocks doing great, and has really been a meteoric rise, people are sort of getting the opportunity that you guys are chasing, and you're executing. You got some announcements this week that we're going to talk about, but let's start with, you know, what's going on across the street at strata. Sure. I hear it's, you know, pretty packed, as usual, a lot of good is Dev going on, so what's your take? Yeah, no, it's been pretty interesting, you know, I've been here for a couple years now, and it's amazing to see the evolution. I'm always intrigued by how much more and more we hear about Hadoop, and I know I've heard you talking about the trend here, where there's just a lot of changes to that platform. I sat through the Hadoop 2.0, you know, tutorial yesterday for a couple hours, and to see the developments there with, you know, yarn that they're putting in, and all the stuff with storm, and making this more real time, that's offering kind of a good glimpse into, you know, the future of where the adoption is going to go. So it's interesting to hear that, interesting to hear the use cases for it, and I think now you hear, you know, you still hear about the interesting cool technology, but a lot of people are really talking about how it's driving, you know, value for their businesses, how they're using it in conjunction with data warehouses, its role in the ecosystem, so it's, you know, people are putting the pieces together. And you guys, you know, play a vital role, I mean, everybody talks about data, having data strategies, we've had a lot of discussions about chief data officers, so it all starts with the data, and being able to integrate all the different data sources is a key starting point, really. I mean, if you can't do that, you really can't get value out of the data, so why don't you talk about that a little bit, and where you guys fit. Sure, sure. So I keep hearing, you know, the term used a lot here around a data lake, right, and the things that you can do with the data lake. You know, I'm from New England, I like the state of Maine a lot, you know, there's a couple of thousand lakes in there, right? But one of the problems that you have is you have all these, you know, waterways in Maine, and as I like to say in Maine, you can't get here from there. Actually, they say you can't get here from there. Exactly, that's a good accent. So I think that's the problem that we see in the digital lakes side of things, right, people have all these repositories, they might be, you know, one thing on SQL server somewhere, somewhere on Oracle, Vertica, you know, you name and terror data, and how do you move data around as you need to in a very efficient fashion, a quick, efficient way to do that with speed, with performance, ease of use, and that's kind of the problem that we go after and we help out with. Some people have called that a data landfill, right, it's just there and you can't get to it, maybe the tributaries aren't connected, or maybe they are, you can't really navigate them, right, and that's really what you guys do. And it's, yeah, and you think about the time to value, right, it's, you know, of course everyone cares about performance and we help with that, but there's also the fact that, hey, if I want to set up a new data stream, pull it in from somewhere else and I've got a new project that you're going, if it's from an existing data store, which in most of the time it is, you know, that could take somebody weeks or months to do, you know, dedicated DBA, dedicated development effort, and all of a sudden this great idea you had for a project to put to test is something that you're now looking at three months down the line and how valuable is it then. So addressing those types of problems, getting the data to where it needs to go is a big part of what we do. You know, I wonder if you could unpack that a little bit because I think for a lot of people, it sounds like black magic, right, taking all these diverse data sets and all of a sudden you're making sense out of it and does that really work? How does that really work? What's the sort of secret sauce behind all that and why all of a sudden is this industry able to do it? I mean, I presume it's a confluence of another factors, storage, processing power and algorithms and the like, but I wonder if you could sort of help us squint through that confusion a little bit. Sure, sure. Well, I think if you look at the history of this year, right, people have had tools, you know, for 20, 30 years now around ETL, right, for moving data, which is all about extracting, doing the transformation, doing the loading. So most big companies have that in their toolkit and it's something they, the first thing they think of when they want to move data. But a lot of those technologies were built, again, for the databases, data warehouses, if you will, of 20 years ago. Now things are much more fluid, dynamic, there's so many more different ones. And that process doesn't work. If you think now just about the new, you know, powerful data warehouses out there, you know, whether it's, you know, Vertica or what's going on, you know, Teradata with their Aster or their Unified Data Architecture or anything with Pivotal, these are very, very powerful platforms. And so you have the capability now to get the data over there and then do the work, you know, use the processing horsepower to actually do any, you know, real transformations or other things you might want to do on it. So the paradigm has changed. People really care about get it over there as quickly as possible. And then the technologies evolve that you can actually figure out what you want to do with it once it's over there. So that's been kind of one shift that's enabled us to come along and look at it a little bit differently. You don't have to do this in a batch process. You don't have to do, you know, all this crazy work on it before you move it over necessarily for a lot of cases. And we've been able to come in there and use newer technologies like in memory processing, looking at how you do change data capture and doing that, not just for transactions, but optimizing that for data warehouses. We have a lot of data moving in one direction most of the time. We've been able there and really update the interfaces. I mean, we have a very nice, easy to use, you know, GUI interface. As you might expect, most platforms will have, but a lot of the people who are doing ETL products, they either look they're either a command line interface, believe it or not, or they are, you know, they look at Windows 3.1 interface, you know, very basic and simple. So the technology has changed and needs have changed and that's allowed us to come in there and play it a little bit differently. Excellent. So let's talk a little bit about some news you guys announced back in December. Some important news, acquisition of Hayes technology and I understand it's focused around SAP and some of the, of course, HANA is the center of their efforts these days. Really, they're building out their whole portfolio on top of HANA at this point. Tell us a little bit about Hayes and what kind of capabilities that brings to ATINITY. Sure. Sure. This is a great, you know, complementary, you know, acquisition for us for what we do. And they solve the problem of when you look at an SAP, you know, dataset, it is very interconnected, right? If you have one transaction record, it might touch, you know, a piece of the dataset that might be over an HR, it might be a piece of the data might be over in sales transactions. So it touches all these different places at the application level. And we've seen our customers ask about this and we're very focused on the, you know, database and data warehouse level, but you have to kind of think the next level up with SAP. And they have been working with SAP for many, many years on solving the problem of how do I get the data out if I need to do something efficiently with it, whether that's my test and development set, how do I carve a piece out, or if I need to do some sort of synchronization between two sites. And how do I do that efficiently? Because one way to do it is just take a whole copy of everything, move it over, and then do your work. And that would take you, in some cases, days or, you know, and be very expensive to store it. And then the problems only amplified, as you said, with HANA. You know, great platform, you know, really solves, you know, a lot of high performance issues. But you have to think about the cost for performance trade-off. And trying to move a whole, you know, HANA set over would be, you know, an expensive proposition. So it's a way to solve, again, that data movement problem that we address. And we've been doing that for files and databases and data warehouses and taking that to the next logical step. But what are the challenges people have at that SAP level, or more of that application level, and help them with their data movement? So just digging that to a little bit more, if you could. So is that, so it's a challenge because not only is it the database layer, but they've also got all these different applications where the data is essentially a surface to multiple applications. And that would, that's what makes it more of a complex effort to get that data out. Is that correct? Exactly. Because the SAP, you know, if you want to move over a certain record, it says, well, you know, you better take over, you know, this part of the SAP, you know, application. And you might have to take over this one and that one because that could change with it. Even if it hasn't, right, it's going to basically insist that you're moving large parts of it over because they want to bring a very large consistent set of the SAP information. And so being able to know those endpoints, being able to carve those pieces out and bring over that consistent is a hard challenge. And the founder of Haze, a guy named Matt Haze, you know, has been working on that for 10 plus years and really focused on that and they become a very popular solution for the SAP community. Yeah, it's interesting, having, you know, been in this market for a while, SAP, you know, great applications and a great company, very successful. But there are always there has always been some challenges getting data in and out of the system and getting, in a lot of cases, non SAP data to kind of integrate with SAP focused data. But so talk about how that kind of complements your overall portfolio. So I mean, sure, you've ticked the boxes, right? You work, you can work with Oracle, SAP, right, some of these new no SQL databases. We'll talk a little bit more about Hadoop and where that's going. Sure. It sounds like you kind of got the pretty much you got the database ecosystem, all the boxes checked, it sounds like. It does. It does. It's funny, you know, in the fall, we did a little blog, I think we called it, you know, the 31 flavors of databases because we cover so many, right, and data warehouses. So this this adds to that and very complimentary. So it's, you know, it fits with our model of trying to help our customers and, you know, it makes sense from business side. We already had customers out there who were using attunity products for doing more typical like SQL work location and whatnot. And they were looking at Hayes and after the acquisition, they said, oh, well, you know, we're already using attunity. It's easy for us to sign this deal. You know, we know attunity, they're a true vendor and bring it in. So there's a complimentary, not just on the technology side, of course, but on the business side, a lot of the customers that we face are the larger enterprises that have, you know, lots of different flavors of databases and data warehouses and 10 to one, you know, they're probably going to have an SAP somewhere in their business. So it lets us, you know, call on each other's customers and understand how we can help them with kind of some of those broader questions. Right. It's a good fit from a customer perspective. So let's talk about Hadoop. You mentioned, you know, we're seeing a lot of action around or people working to make Hadoop real time. Sure. That's through yarn, integration with Storm, as you mentioned, it was kind of the streaming framework born on Twitter. So talk a little bit about how that, how you approach that market. You know, we're at that point now, we're seeing a lot of talk about that. And that's clearly where the platform is going. Sure. And so what role does that play in or what role will data integration play once, you know, once you've got the promise of a real time platform, you've got to get the data into the platform and you've got to do it in a timely way. And that's right where attunity comes in. Do you have plans to kind of work closely more closely with the Hadoop community? How do you see, see yourselves attacking that problem? Sure. Well, I'd say it is an interesting area. And, and I, you know, I heard Jeffrey Moore's talking of the crossing the chasm. And when you think about Hadoop, you know, I think that's an interesting one that's going to kind of move up and, you know, grow an adoption there. I also think it's, you know, disruptive, right? When you think about disruptive technologies, it kind of starts out for one uses data like processing lots of things. And then as it moves up market, right, if you think of adding on storm and other things, now it becomes more real time. So that changes the landscape of everything around it, right? It's not just how fast can I get the data, but what other things can come in there support it. And that's where data integration is going to play a role. You know, we see people today thinking about the problem of maybe I just want to get things and do my data like, you know, do the processing in there and then move it into, you know, maybe a data warehouse on the back end. So we see those cases. Today, we're, you know, we're kind of at the beginning steps of that. We work a lot with Amazon and the cloud and whatnot. And besides, you know, Redshift and RDS, we also support EMR. So customers will take files and bring them into S3 quickly and efficiently. And we help them with that. And then they'll get them into EMR. So we're seeing, at least in our community, that kind of sandbox, you know, trial proof of concepts, easy to get spun up in the cloud. And as the demand grows for doing this more, you know, on site and other things, we're definitely going to follow that closely because I think more of those data integration challenges will start popping up. Yeah. And I mean, just what do you make generally of the, I guess, the Hadoop ecosystem and kind of the landscape, you know, obviously we cover here that we cover the horse race between the different players. Sure. Sure. What do you, what do you, what is your take on kind of where the, is all that competition benefiting the platform generally, seeing more innovation because of the competition? How do you kind of view that Hadoop landscape? Sure. I think it's, I think it's very, you know, it's been good for the landscape. It's not just the new players that are doing it. As you know, there's some established companies with their Hadoop offerings and that is forced, you know, the big players to really rethink about, you know, their current databases, their data warehouses, how this fits into the whole thing. So can I predict, you know, how that's going to look in five years? I look, I have no idea. But I think it's forced enough of visibility into the market that people now have a lot of selection, a lot of choices and that's a big thing, I think, for the end users. Yeah. Well, it's interesting to see how the kind of the megabenders, the IBMs, the oracles of the world are kind of contorting themselves to fit into this Hadoop world and, you know, where they've got these legacy products and databases that don't really fit, you know, especially with the appliance model, with the scale out, you know, open source commodity hardware paradigm. Sure. But it's interesting to watch and I'm curious to see, of course, we've talked about today whether we'll see more acquisitions in this space, but always very interesting. So, but let's talk a little bit about what's next for you guys. What do you expect this year in terms of, what's on your roadmap, I should say, is it focusing on some more technology innovation or is this more kind of a year for you guys to scale even a little further in terms of sales? What's kind of on your roadmap this year? No, we've had a, you know, great run last year in terms of both of our products and whatnot. Our big data offering products grew by about 140 percent. So it was a nice year. So we've really replicated. That's a replicate. Yeah, it's those and products around those. And so we've had very good growth there. So we've focused on, you know, looking forward on how do we capitalize on that? So we've hired a lot on the sales side, you know, to grow that in the marketing side. So we're trying to, you know, scale up the business. We'll be integrating more and more of all the things we do with with the haze technology and the crossover with SAP. We'll also are looking at, you know, more of the, if you want to think of the systems management side of replication, because a lot of our users will use us in, you know, certain departments in certain areas. And then they start thinking about, well, how do I manage, you know, everything around that and put all the pieces together and have that kind of control panel view, if you will, of things. So we're working on some innovative things around there. And as I mentioned, you know, we've got some work with Hadoop now through the EMR side. And we're following that market. And I think, you know, we'll keep an eye on that. And then, of course, it's been very successful with the cloud and Amazon. So we're we're working closely with them, looking at ways to, you know, grow that that model as well. So a lot of different fronts will keep us busy. Well, kind of related to just one more question about the cloud. How do you see the cloud playing, playing out that the whole cloud meets big data? Sure. You know, we've been covering this, we did our market study. And it's still relatively small. Kind of the big data workloads that are in the cloud. We're seeing a lot of tests and dev and nobody else. What's it going to take, in your opinion, for, you know, the big data and cloud really consummate their courtship, if you will, to really make it, make it where a place where, you know, enterprises are going to actually run, you know, big production workloads, mission critical applications. Sure, sure. I think like a lot of things it's it's showing the value of it. And we've helped, you know, customers do that. So a lot of people see the promise, you know, the ease of scalability, lower cost points of like Redshift as an example. I know you've talked to some of our customers who use that before as well. And I think what shows up on the value side is they can see that the tangible results, you know, when they start using Intunity right away. So oftentimes, I mentioned, you know, you see the promise of cloud, but then wait, it's going to take me three months to get in there. I'm going to have to dedicate a DBA to the project and do all this work. Well, this isn't sounding as good as I thought it would, right? So, you know, if we come in there and others come in there and really ease that onboarding process, right, then you start delivering more of the value and people can really capitalize on it. So I think it's seeing that ROI, seeing the quick ROI, that's what's going to help drive adoption overall. So I wonder if we can talk about your growth. I said at the top of the spot here that you guys have been smoking and the street, segments of the street have been catching on. I mean, you're still, you know, sort of viewed as a niche to a lot of people, but your growth has been quite astounding. You had a great quarter, last quarter, you know, showing good run rate, see if you're executing it also investing a lot in sales and marketing. So you got all these new salespeople. I wonder if you could talk about how you as the head of marketing are helping make them more productive. That's all, you know, right, right. The company you're under a lot of pressure, obviously, to execute. And a lot of that falls on you to make the salespeople more productive. So what are you doing there? And then I got a follow-up question on just partner productivity. Yeah, yeah. No, it's and those are absolutely related. So, you know, it's a big part in training that we do. We also are in a very fortunate position right now where, you know, we've gained enough momentum that we're able to hire, you know, the best and brightest from, you know, what have been our competitors in the past. I think they're starting to say, you know, who is this attunity here? You know, why are they coming in here and taking our business? And maybe I want to join them, right, you know, when a recruiter might reach out. So we're, you know, making sure that we hire the people who know the business well and can kind of get in there and up and running. So that helps make my job easier. You know, I've been focused on really getting the word out in, you know, different platforms on what we do. And that's, you know, all the traditional things like events and whatnot. And when we look at events and how you think about that, because we work with so many partners, we focus a lot of our time on those events and making, you know, those successful and making our partners successful. And then it's, you know, other things that we do on, you know, making sure that, you know, we're in the conversations that happen around it. You know, we did a great infographic that we're going to release soon that talks about data movement in the industry. That has a lot, and it pulls together a lot of research as well and work with some agencies on that. So it's trying to be, you know, trying to get the word out a lot more. I mean, I joined about eight months ago and we were relying, not completely on word of mouth, but we were, you know, very lucky our customers were bringing us in. We had a little bit of visibility, but I've tried to amp it up on the press, the analyst work that we do, you know, the partner work. And just from all those angles, and we're starting to see that critical mass, and you know, in terms of website performance, leads coming in, and that's been very helpful. Okay, and then I wonder if you could talk about the competition more specifically. So you, presumably you compete with the likes of, I guess, Oracle, and Informatica, maybe some others in that space. What sets you apart? Where are you winning? Sure, well I think for us, if you look at, you know, the competitors and other people in the market, you know, there was a company, still a part of Oracle called Golden Gate that was acquired by Oracle. And you know, I think now that they're, you know, they have to work with, you know, the bigger Oracle portfolio and bigger company, and they're working on technology that's been around for a while. Our products are fairly new, fairly innovative, so we've got that kind of technology advantage when you look at that. And then we also have, you know, the unique side of being independent, right? So that if other players, other major data warehouse providers want to work with someone, we're kind of that neutral Switzerland in the mix, if you will, that's big enough and have enough known customers that they're comfortable working with. And that can be attractive from a business side to work with versus that. When you look at Informatica, you know, they're a great company, but a lot of their solutions are very focused on, you know, the ETL side of things. Again, we're more focused on adopting the technology, our replicate technology for the modern use case, where it's all focused on getting it over there as quickly as possible, making the process easy, making it efficient. And because we're so focused on that, we bring immediate value there in a bit of a different play. So you can, I guess historically, you compete with Golden Gate, but you're also a partner with Oracle, right? Do you not? I, yeah, I can't say that much about Oracle as a company and what our relationship is, but you know, we find ways to work with a lot of people. Yeah, okay, all right, great. So I guess my follow-up question there is, I'm trying to get to an opportunity in IP and how critical it is to your partners, you know? Yeah, yeah. And it's, again, sometimes it's hard to squint through all these relationships, so I guess, oh, you can't talk about it too much, but. But I'll give you an example, you know, we have a great relationship with, you know, Microsoft, right? You know, they, you know, they OEM a lot of our stuff, so they find it as a critical technology. Obviously they have a lot of work they do with SQL Server, they have stuff they do with PDW and whatnot. So, so yeah, I think the big players are seeing, you know, high value in what we do. Yeah, so, okay, so you guys will partner with them and you're a key component of their sale, trying to get to, you know, how key. I mean, I know you're gonna say, you know, very key, but is it a function? I mean, would they lose the sale if it weren't for you? Or could they replace you with some other? Yeah, it's, you know, like any partnership, you know, the value of it is, you know, goes back to, are they getting some real value out of what we do? I mean, that's a big yes for our partners. For them, it's a question of I have a new implementation, you know, going that I wanna get running and I need to get the data in there and I need to get it quickly, easily. I wanna make this as efficient process as possible and we help them with the sale that way, right? You know, we've had sales that we've done with partners where, you know, they sign up for both of us and then the kind of paperwork follows for us because they're already pretty big guys and then we're kind of the ride along. Yeah, you'll get paid. Yeah, you'll get the money. Just delivery. Exactly. But yeah, so they bring us in. We're very fortunate of that and because again, they get high value on it. So what makes a good partner for you guys? I wonder if you could describe that generically. Sure, sure. I think one of the things we've benefited very well from in the partnership ecosystem is, you know, working, you know, getting that close open door to like their test labs and what they do. So I'll give the example of, again, we have a lot of partners but I'll give the example of Vertica. I know the guys are just in here. But it was fantastic. We had our Vertica offering, you know, middle of last year or so, announced it at the Vertica show. And, you know, as part of that, we spent weeks, our technical guys in their labs working side by side, basically getting pretty unfettered access to the questions that arise, the specific ways that they do things, how they do their copy commands on the technical level. And when the partners trust us enough to open the doors for that type of relationship, it's beneficial for both sides. We have a better solution. We get a better working relationship. And then they want to pull us in, right? Because they know us well. We know them well. And if there's an issue props up, we know exactly how to kind of resolve it. So pretty much any database vendor would be a great partner for you, right? Is that fair? Yeah, yeah. And when we've covered the, you know, we've covered the waterfront pretty well. I mean, you know, we added, you know, as I mentioned Vertica, we added, we've added a teaser. We've added- Are you working with Green Plum at all? We work with the Pivotal guys and all that, yeah. You used to work at EMC, right? I used to work at EMC, but that predated my join. Yeah, yeah, right. So they've had a good relationship with EMC. So it's, yeah, it's hard for us to mention, you know, somebody that we don't work with. The list is pretty well set now. Well, I think the important point about being the Switzerland is it's hard to imagine HP letting, you know, Golden Gate Oracle to come into their lab and work that closely with them. And that's what I think being independent allows you guys to do. Yeah. So, you know, while, you know, Golden Gate has the benefit of, you know, the Oracle machine behind it, they don't necessarily get the access and the kind of integration with some of the database players that an independent player would get. Yeah, well, you said it, not me, but yeah. I think that's a good thought, yeah. That's my take. That's my analysis, Dave. What do you think? Well, I think again, I just, I think that you've got a differentiating technology. It fits perfectly with the momentum of the big data market, as I say. I think your partnerships are making you guys very, very productive. Absolutely, yeah. And that, to me, is a key to you guys continuing to execute and live up to the expectations, more recent expectations. Again, I think nobody really knew about attunity. You came sort of on the map. Wall Street sort of picked up on it. You had some sharp analysts that focused on you and the stock's done very well, and now people are starting to pay attention. And I think there's a lot of momentum right now for you all. Yeah, yeah, no, I'm very, very happy where we've come, especially in the last year, so. Good, all right, well, good. Keep it up, you know, the pressure's on. That's right. You can't let up in this marketplace, but Lawrence, thanks very much for coming back to theCUBE. It's always a pleasure. Good to see you again. Oh, great to be here. Thanks for having me. All right, keep it right there, everybody. We'll be back. John Ferrier, Jeff Kelly, and myself and the entire CUBE team. We're live from Silicon Valley. This is Big Data SV hashtag. Big Data SV Silicon Valley. This is theCUBE, right back.