 Welcome back everybody, my name is Jeff Kelly with wikibon.org, you're watching The Cube, a Silicon Angles flagship product where we go out to the events and as John likes to say extract the signal from the noise, John Furrier is here with me of course and we're joined by Lauren Schwartz, VP of Marketing at Atunity, an old time Cube alum, welcome back to The Cube. Thanks, great to be back here. Well, we were just talking a little bit before we went on air that you've been quite busy over there in your booth. I haven't had a chance to see a lot of the show, but tell us a little bit about what the action you're seeing over your booth today. Sure, sure, we've enjoyed a lot of people coming by talking a lot of different things and one of the things that we hear a lot about with big data is how do you move it around, right? And that's what we help people with. I mean the interesting question now that comes up, you've had so many different solutions out there, you've got these big in memory databases, you've got other solutions out there from other vendors and people are trying to figure out their best to breed solution. So people come to us for how do we do that, how do we work with everybody, whether it's local, remote, and hearing all sorts of good conversations on that topic. Right, so let's set the table a little bit for our guests who may not be familiar with Atunity. Tell us a little bit about the company, as you mentioned, it's about moving data around, it's about data integration, real-time data integration in this really big data world, if you will. So tell us a little bit about the approach that Atunity takes to big data integration. Sure, so our motto is to move any type of data anytime, anywhere, and that's our real focus. So a lot of customers have built up databases over the years, whether it's an Oracle database, and they need to move it to a SQL server, or they need to move it to Exadata, or they need to move it to another data warehouse, Creamflum, Vertica, et cetera. So we help them with those types of solutions. That's often what people want to do, when they want to do reporting or near real-time reporting on a lot of different data stores, so we can help with that. And more recently it's been the question of, well, my data is expanding not just in the data center to all these different types of uses, but it's gone way out, and I'm pulling in data from all different sources, potentially all over the world, and how do I do that effectively? So those are some of the conversations that we deal with and what the company focuses on. We've been doing this for a while, and we just announced our newest offering, which again focuses on going further and supporting more and more types of data stores. So yeah, let's talk about the global implications of big data. So we've covered the industrial internet here on theCUBE. We were at the GE event back in the spring, talking a lot about moving data between whether it's an industrial wind farm and multiple wind farms all over the world, so you've got devices on-site, you want to also integrate that data in maybe a centralized cloud environment. So is that something you help your clients do? Is that really where our community comes in, to actually help make those connections possible? Because really the internet of things or whatever you want to call it is all about interconnections of datasets. Yeah, no, it's a great question. I think you've hit a real important area. I know a lot of companies that focus on the industrial internet, and we see a lot of activity there. So I'll give you an example of one of our customers, a big customer out in Scandinavia called Kongsberg, and they have this classical industrial internet problem, right? The question is, they've got, they're a maritime company, they've got to deal with data coming in from different ships all around the world, different drilling platforms. It's a lot of data. If you look at platforms that do drilling, for example, across the world, you could be pulling up millions of bits of data per minute, they can carry as much as a couple of terabytes per day. Now you multiply that by all the different rigs they have, and it's spread out all over, right? So it's a wealth of information, but how do you collect and gather it? And oftentimes that has to come over, maybe satellite links or indirect ways, so that could be a real problem. So that's one of the things that we've been helping them with, I think they're a classic case with that. And if you think of, you know, even on a drill platform, if something goes wrong, right? If you're looking at one platform, you get on a one piece of data, if you have that global view of all your platforms and what's happening, something that might be a yellow light here, if it's a yellow light in several of them, now you know you have a major problem. So having that comprehensive dashboard becomes important. So it's another angle of how do you make big data go over big distances with a lot of different sources and targets, and that's what we really help with. Talk about the role of the cloud and Oracle, obviously a big database player, you have a lot of experience in that area. What has gone right with the cloud, and what hasn't gone right with the cloud around the big data evolution? You've seen some things work and not work, obviously in memory's hot right now, but what's your take on the evolution? What's gone right, what's gone wrong? Sure, sure, I think a lot of things have gone right. You give a lot of credit to places like Amazon who have kind of built up trust in the cloud, built up a name for themselves and built up credibility. So when we look at it from that angle, we've tried to be a good partner to them and focus on, well, if you're going to use a cloud, they focus on how do you make it a well-known and secure system, and we focus on how do we get in there faster. When you look at what's gone wrong, I think you just have to look at the headlines from the past week or so with nirvanics, right? It's one example of a company that was doing well and they've come across them hard times, and I think they get, some people are trying to figure out the business model, how to compete with some of the bigger vendors, right? So I think places like Amazon have figured it out, Oracle's figuring it out as well, but it's a challenge. Some of the more specialized ones, I think are going to face the trouble as some of this becomes a bit more larger. Oracle more present tense, figuring it out. Right, right, yeah, sure. What are they doing right and wrong in your opinion? Sure, I think that they can do things that other players can't. They've got the experience from working on-premise with large data stores and how that carries over to the cloud. We learned from that experiences too. We were doing this for over 10 years working on-premise, so a lot of the problems that come up over the cloud are similar to what we've seen there and we can lend that experience. So I think that's one advantage for a place like Oracle, right? You're not coming in from it with a clean sheet, you can actually think about that. So when you look at the cloud, a lot of the problems of how do I put a data warehouse in the cloud or how do I put Redshift and manage that, they already know how to do a lot of that. They speak all those different languages and so that helps some of the bigger players. It's not as easy as it looks. I mean, you've seen SAP stumble a little bit, it had success facts, it's on-prem stuff, and they're obviously shifting. What's been the hardest thing that people don't realize about the cloud and moving the data in there? Sure, sure. I think one of the hard problems that at least we see people struggling with and having an issue with is it's a great concept, people want to try it, they do some test and development and then the scale-up can become a real problem, right? So that's one big issue that people need to focus on is how do you manage and deal with that? The other issue is once you get it up and going, it might be great, but kind of getting all of your sources, getting all of that information set up to go in there. So we worked with one of our customers, Domain Holdings, and they manage all these different properties online and they looked at the case of, they wanted to go into the cloud, they looked at doing it all themselves from different traditional data stores and they estimated it would take about three months of effort, have to hire a full-time DBA, spend about 50 or 60,000 a year, but they look to us and what we help with and hopefully other people are trying to do this too is simplifying that process, right? Make it more automated, make it much more easy to kind of click and go and get it moving. So the promise is there, but how do you deal with all this legacy and how do you make that transition much easier and lower that barrier? So we've got to talk about Oracle and their kind of data integration play, of course. And so obviously data integration is a pretty competitive market. You've got players like Oracle, you've got Informatica, you've got IBM. Help us understand a little bit where you differentiate some of those players. So Oracle, we know it's got the Golden Gate acquisition back in 2009. Sure. A similar approach, I think, but correct me if I'm wrong, and tell us a little bit of how you differentiate and kind of the benefit of an independent provider like yourselves versus Golden Gate, which is part of the big red stack, if you will, and that comes with all the implications that we've talked about today. Sure. Well, I think there's a couple of key things there. One is, again, how do you make it easy to move over? Because that becomes a big question of data integration, pulling in all these legacy sources and whatnot. And one of the things that we've done is that's tough for others to do and haven't invested in, is how do you simplify that? So when a lot of the other players talk about, I've got automation, that automation is often, well, what happens after they spend all this time scripting to make that happen? All that scripting work can take a lot of resources, it can take months of effort. So what we really help differentiate on is, we hide that under the coverage, we do all that work, and then it's kind of a nice, easy to use GUI to kind of get going. And that's a big factor, right? If they don't need a specialized DBA, they don't need a training, they don't have to invest as much, and then that's a much lower barrier to kind of get started. That's one thing. The other aspect is just pure performance, right? A lot of the CDC change data capture work that's been done over the years has been very, very focused on what you'd call more moving from database to database, more of a transaction model, right? But when you're moving into data warehouses now and you're having all these different targets in there, whether it's Exadata for Oracle, or GreenFlum, or Teradata, or Vertica, how do you deal with a CDC model that's much more built for data warehouse so you can combine a lot of data, kind of package it up and put it together and streamline it before it moves over so you're making a much more efficient use of the bandwidth? So that's another unique aspect that we offer. The other aspect too is how do you optimize to really get the best connection to each player, right? So you can imagine because we're an independent player, we're kind of a Switzerland, if you will, in the whole space. It's very easy for us to come in and work very closely for this. I know we talked about Vertica, I think last time we spoke, but just the process of going into their lab, being invited into HP's lab, spending a few weeks with them, working on the interface, optimizing it for the SQL copy commands that they have, that type of unfettered access that we get because of our position in the marketplace has also been really helpful to optimize performance. So it's that simplified ease of use to get going and get started, it's the higher performance, it's that independence that we have and then we do a bunch of other nice things too, like some of the other guys, you'll have to install software at the target and source and we keep that as lightweight as possible so most of the time you don't have to do that. So it's very easy to get up and running as well. So it's about a smaller footprint, it's about better performance, just making it simpler with the GUI model and then of course the being independent, as you said, you get invited to HP's lab which I don't think, I highly doubt Golden Gate is going to get invited to HP's Vertica lab to do any of that kind of work anytime soon. You said that, not me, but I can see that. I'm going to go out and live on that one. So tell us about how do you as a marketer, you're going up against some of these behemoths, how are you getting this message out and do you come up against, I imagine if you go up into an Oracle environment for instance, I'm sure Oracle brings their mites to the table, tries to get their install base to use Golden Gate, do some of their other integration capabilities. How are you, what's your strategy against some of these giants in the industry? Sure, sure, part of it is getting the word out for the company, I mean the nice thing is I've been here a little under half a year now, so not that long, but the company has proved itself out technology-wise. So when we get in to actually do a trial and approve a concept, we do quite well and that's where we show ourselves off. So for us it's getting that visibility, getting on the radar and focusing on our messages in the right area. And I run marketing there and a big focus of mine has been how do we get into more events like this so people are more aware of this, how do we get found online when people are looking for us, how do we make our messaging really focus around the data movement rather than doing the jack of all trades if you will. And it's tough, you are a small and nimble player but you have to keep the message targeting, get the word out here and do things like theCUBE here. Fantastic, so we talked a little bit about the industrial internet, let's go back to that if we could. So what are some of the other areas you're seeing as potential use cases, potential applications for attunity, I mean as we've documented, there's certainly applications in healthcare, the electricity, the utilities industry, trucking, transportation, that kind of thing. So there are a lot of industries that you might not traditionally think of as big data industries that are being, equipment's being, sensors are being aided, added to that equipment. You're just seeing incredible amounts of data being created. David Foyer, our CTO did a study on this and determined that the amount of data is growing twice as fast in that industrial internet world as the consumer of big data world if you will. So what are some of the other use cases you see as potential applications for your technology? Sure, well one classic one that is typical example is a company that we work with that deals in the manufacturing space, right? So they're manufacturing memory and other kind of parts like that and they have worldwide distribution. They're trying to pull data in from lots of different Oracle sources into like a SQL server to monitor it. So how do you actually manage that and how do you to do that and we can help them. And again, manufacturing is maybe one of the less sexual ones than what you might hear, but that's a typical big user that uses the data. For us, some new areas that we're excited to get into as well that we've gotten more requests from and were actually announced at this show too is disaster recovery and business continuity. So we've made everything bidirectional now so you have more fault tolerance and whatnot. So even though we've been used so far like in the financial industry for reporting like companies like Equifax for pulling in a lot of information to like a green plum, now we have the door open with some of our new solutions to really focus on, well, how do I help the bank or how do I help any of these other scenarios go with a two-way replication which gives you that whole fault tolerance capability. So I think the door will open more. We're using a lot of the areas you mentioned, it spills out to manufacturing, finance and others and in the web and I think that's going to grow even more. So another of course important area that people are talking about a lot these days around big data and the cloud in particular is security. So we've got the NSA scandal, whatever you want to call it is out there. It seems like there's more revelations every day and the amount of data that was breached, I'm sure those reports are to keep leaking out. I'm just curious, one of the bigger things we've been talking about is the potential of that scandal and just the concerns around security in the cloud to maybe dampen enthusiasm for cloud is specifically around big data, moving your data into a cloud environment. What are your thoughts on that? Do you think that this is going to have a long-term effect or what do we as an industry have to start thinking about in terms of cloud security? Yeah, I think you have to look at it from the same viewpoints that companies that have dealt with this for a while have had to deal with. So we learned a lot about it through our acquisition. We acquired a company about two years ago called ReploWeb that works on managed file trans for moving over distances and whatnot and keeping that secure with high levels of encryption as well as with key and the middle protection and whatnot. So we actually, before we went into the cloud and we said, how do we take our technology which has been focused on on-premise databases and how do we partner that with Redshift, for example. We actually pulled in the technology from our managed file transfer company that we acquired to look at how do you do that security and how do you actually make sure that that links up and running and how do you make sure that you've got the right key layers. So that work had already been done. So I think there's a lot to learn from companies outside the cloud, moving files over distances and taking that technology and bringing it to the cloud rather than trying to reinvent the wheel and saying, okay, I'm getting into the cloud, I've got a pipe, now what do I need to do, right? So it's kind of that ground up approach. Lawrence, we're going to get tight on time. We want to find a couple of questions. One, what's going on in the booth? You said you didn't really have a chance to get the show because you're in the booth. Yeah, yeah. Talk about what's going on in the booth and talk about the posts that you guys put out on your blog around the 31 flavors of support because it's complicated out there. I was thinking, you guys have some new issues. Talk about what's going on in the booth, the demos that you're doing and then the support issue that you guys see and are taking advantage of. Absolutely. So yeah, we put that blog out there in a little bit tongue-in-cheek but it's a real issue, right? When you look at all the targets and sources that have developed over the years for databases, going all the way back to mainframe and i-series and non-stop, which are still around, they're not going away anytime soon. So now you look at these proliferation of data warehouses, everything from Green Plum to Vertica to Exadata in the list, keeps going to Teradata's work. So when we started adding those up and I'm like, boy, that's more than 30, right? That we can actually do. And sure enough, it gets into 30 to 40. And six new ones that you're announcing, right? So a lot of different versions. Yeah, exactly. So we've gone into side-bays, we've gone into Vertica recently, we've gone into Microsoft PDW. So we're trying to cover all those because at the end of the day, customers are going to choose what they want, right? Especially the larger shops want the best of breed performance, the best of breed behavior. So we're trying to make sure all those are covered. We will keep introducing more and more by the end of the year. We keep covering that path. And we want to be the go-to solution, right? To handle all the different types that they have. Yeah, back in the old days, Dave and I always talk about the old days, being in the 80s and 90s. Multi-vendor is a big thing. Now that seems to be moving up the stack. You're seeing the lower parts of the stack hardening up, the multi-vendor is moving up into the middleware and the app layer. You see the same thing as well? I think so. You've got people are trying to cover the whole base and the whole waterfront and all that sort of stuff. So there's a lot more activity there. You know, and we do well by being really focused on what we do best and just taking that technology. When you learn how to integrate with one data warehouse, you learn a lot of the kind of tips and trades to deal with others, right? A lot of the nuances. The nuances and all that. So you become better as a whole at doing that. And if you're just doing one or two or that's kind of one piece of your multifaceted business, it's hard to do that, so. So is that about what you guys are announcing here at Oracle? Anything, any, you guys had some announcements with the replication? Exactly, yeah. So we've announced a couple of things. One is supporting these additional targets that I just mentioned. The other is this whole industrial internet and supporting much better, more resilient, higher performance, more secure, long distance links from site to site or site into the cloud. And then the last piece is all about this disaster recovery and business continuity. How do we ensure that there's two ways of communication so that when something goes down, we have the solution that people turn to as well. Lawrence Schwartz, VP of the two things for coming on the queue. Appreciate the time. This is live in San Francisco. This is theCUBE, we'll be right back. Stay tuned, we'll be right back with our next guest after this short break. Thank you.