 Okay, welcome back everyone. This is theCUBE's SiliconANGLE's flagship program. We go out to the events, extract a signal from the noise. I'm John Furrier, the founder of SiliconANGLE. I'm joined with Jeff Kelly, big data analyst, chief analyst at Wikibon's Big Data Practice. And we're here at Lawrence Schwartz, the vice president of marketing and tunity. Welcome back to theCUBE, Cube alumni. Appreciate it. It's always good to be back here. You know, this show, Prokona Live, is really not on the radar for a lot of the mainstream shows. And we've been talking about it all morning. There's so much going on and big data under the covers and cloud, convergent infrastructure. A lot of action at the data layer, databases, MySQL, NoSQL, they're not usually exclusive, but a lot of action's happening. So I want to get your perspective. Obviously, you know, we always commentate with you about big data. Sure. Now we're under the hood. So let's get into that. And what's the news here? You guys have some news and some trends that are happening here. Let's go into the news first and then give us your take on the trends. Absolutely, yeah. So we've actually, it's been an exciting week for us. We've had a couple of announcements. The first one, very relevant to the show. We support at Attunity all sorts of data movement and replication from any type of database, whether it's Oracle, SQL Server, into the data warehouses, when you go into Teradata or Vertica, the whole lot. And we've had a lot of customers using it to move their data around. And what we've seen is, you know, MySQL is yet another source and target that people have in their data center and they've wanted to use with our product, kind of have the one replication solution to manage it all. So this week we announced support for MySQL, which is in part why we're here. And it's been great when you talk about, you know, big data and how do you collect the data, right? A lot of the data that you see with MySQL comes out of, you know, web applications. People are using it to run their online operations. They want to maybe pull that into a larger data warehouse and do a number of different types of analytics and we can help with that. So it's a bigger piece of the overall story. So Gartner's put in some new studies that, you know, IT spendings have Oracle stock sitting at an all-time high, software's back. Data's at the center of all this. So talk about this data movement trend. We were commenting on our intro about, you know, Mobile First, now Microsoft's jumping on the bandwagon with their CEO, Satya Natal, saying Cloud First. Well, we're calling it Data First because now data's at the center of the value proposition when you talk about the asset and the web scale SQL stuff that was announced with Google, Facebook, Twitter, and LinkedIn really shows that companies are using data as really a primary part of their value and competitive advantage, unlike the old model of parking it away and then retrieving for it when you need it, whether it's, you know, way all out in the data warehouse or it's just on disk somewhere. So speed, relevance, asset is the new normal. Describe folks out there, why is that the case and what's the key bottleneck from this hitting a mainstream message? Sure, sure, no, I think it's a, you've got a lot of interesting points there and you talk about data as a source. You know, one of the things that you hear a lot of people talk about are things like data lakes, right? How do I manage all this massive amounts of data, work with it, do analysis on it, run it through Hadoop or whatnot. But one of the things that also people have to work with is, you know, where do they get the, pull the data from? Is it from, you know, sensor data? Is it from remote places? Is it from somewhere else in the data center or another across town data center? So all those questions become important in figuring out, you know, where to source all this. And so if you think of the tradition, you know, the data lake model that people like to use, what are the, how do you feed that? Where are all the tributaries? Where are all the streams that go into it? And that's something we see our customers struggle with, right, how do you manage all that coming together? And that's of course about it's, you know, if you're going to have a data lake, how do you fill that, right? You know, how do you source the data? And that's where we see bottlenecks and that's where we kind of simplify for customers. Well, yeah, that's interesting because the whole idea, you know, kind of, the old way of data manager was a lot of, created a lot of silos. We talked a little bit in our last segment about a lot of my SQL deployments that were kind of siloed, Oracle databases were siloed and now with the data lake concept or data hub, whatever you want to call it, your whole idea is to integrate these different sources and targets. But as you say, it gets complicated. You've got to get data from point A to point B at the right time, use the right method. How are you helping companies do that? I mean, that seems to me while the idea of, well, let's integrate all these data sources and let's break down the siloed walls. Sounds great, but actually doing it sounds like, well, that's a real complex shot. Absolutely, and it's interesting because people look into their toolkit and they often say, what do I have to move data around? What's the traditional tools? And a lot of companies who have a multitude of databases or data warehouses, they kind of reach into their toolkit and they pull up an ETL tool, you know, and ETL tools have been around for 20 plus years now. But those are very complex to use. There's a lot of scripting involved in it. The technology for those are kind of dated and they're based on more of a batch-oriented process. Look, let me pull the data out here, get an intermediate server for a touchdown, do transformations and move it over. But when you have all these new sources and targets, just look at the number of data warehouses that have grown in the last few years. How do you make that really simple? And that's kind of our value prop that we come in there instead of having a command line-driven interface. It's all GUI-driven, so it's very easy to kind of pick your target and source, pick your tables and just get started. And if you're managing kind of a best-in-breed enterprise environment, you have all these sources and targets, that becomes essential. You don't have necessarily the expertise on each platform. So that's one thing. How do you monitor it simply, right? How do you make sure the performance is good? And one of the challenges for some of these ETL tools is they're part of a bigger player, some one of the major data companies that are in the marketplace. Because we're an independent company, we're kind of this neutral Switzerland, if you will, we get very good relationships with each database vendor and data warehouse vendor. So we can work with them to kind of tune the performance, tune the loading commands to their native commands. And that's how we differentiate and that's how we really help people kind of move into the real-time environment instead of these traditional batch ETL processes. Well, another recent announcement was a product called Maestro. Tell us a little bit about that because it kind of goes into what we're just talking about, about essentially orchestrating a little of the name, kind of orchestrating data flows. Talk about how that works and again kind of how that relates to kind of the value proposition you were just mentioning. Sure, sure. So as a company, overall, opportunity, we really focus on moving any type of data anytime, anywhere, it's kind of our tagline. So we do a lot of work, not just with databases and data warehouse and structured data, but also with file data, whether it's managed file transfer, or kind of replicating web servers or things like that. And what we found is that, when you go and think back to that stream model, right, where do I get the data? How do I make sure it's going down the stream and working this way? If I have a cascaded rollout of a file system or some web development, how do I make sure that whole process is managed? And there are a lot of tools that kind of handle point-to-point, like I wanna go from here to here and kind of view it. But if you're looking at a larger environment, if you're cascading out from a major central office to many remote offices, that becomes a complex set of streams and rivers and all sorts of things that you have to manage, monitor. So what Maestro does is give you that single point of control, single view on all the data moving through there. You can kind of see the progress in kind of geographical locations and virtual environments. And you can see the progress of things are moving forward. You can set up all different types of flows and environments and kind of get that one simplified view of managing a large amount of data. I mean, it works two ways too. So it's that distribution, but you could also be pulling in a lot of remote sensor data. And how do you manage that whole process and make it a periodic activity and pull it and bring it back to some other source that you wanna manage. So that whole process can become complex in a large enterprise. And that's what we're aiming to simplify. If you will, as you said, orchestrate the movement of all this data and make it coherent and easy to manage. No small feat. Yes. So we're here at Percona Live. Let's talk a little bit about MySQL. I know, I mean, in your former life you had kind of a view on the MySQL world and now in here with Attunity. You know, we saw the announcement, I believe, last week around the Facebook, Google, LinkedIn, Twitter, sporting, I think they're calling it a web-scale SQL essentially. Yes, yes. A joint effort to scale MySQL. Talk a little bit about how MySQL has kind of ridden this wave or ridden the tide as big data has kind of been all the rage, Hadoop and NoSQL get a lot of the coverage. But here we are, MySQL's still a critical element of the infrastructure of these huge web-scale companies. What's your view? How has MySQL kind of held up through this big data paradigm? Yeah, no, it's a great question because there's all sorts of approaches to managing this. I remember there was an article a few years ago where I think it was Stonebreaker, you know, it was a father of a lot of these database companies. He looked at what Facebook was doing with MySQL and said, I think the quote was, boy, if I had to manage MySQL at that scale, that would be a fate worse than death, right? He was very skeptical of it. But I think as Facebook has clearly shown in working cooperatively with the community, other places that contribute a lot to MySQL like Twitter, they've really grown it and grown all the tools and support for it. Everybody has always loved MySQL for the ease of use, the time of getting it going. It's very easy to understand and run. And people have always worked very cooperatively in the community. So this is on a much larger scale, right? Both in the scale of the performance but also in the scale of the vendors involved. But it doesn't surprise me because at the end of the day, when you start scaling and looking at performance, there's a lot of no SQL options, whether it's Hadoop or Mongo. But at the end of the day, you really, if you're gonna repeatedly go after the data, you might probably want an index, right? So you can go ahead and bolt that on to Hadoop or something else. Or you can look at, what are the existing tools I have and just scale that out. And people have done great things with that kind of MySQL backend. You've got companies like, I was talking to folks from the affinity be here, right? They kind of use that as a backend to kind of do more of a calendar approach, right? So people have found ways to be very flexible and kind of breathe life into it. And some of these, the biggest companies really see the value support it. As you mentioned, Google, Facebook, Twitter. So I think it's a great idea. I think they're up to the challenge and everybody would love to see MySQL used in wider use cases. So MySQL is a huge developer community. You're talking about a quarter of the DBMS developer, multi-database developers are out there using MySQL, hundreds of thousands of developers. So what about this new world here that in Percona Live makes developers get the scale they need? Because we're hearing two major themes here. One, we hear Gary Ornstein from Fusion and I talking about scale with web scale, SQL. And some of the stuff that do non-volta compression. The other one is flexibility, right? So you're kind of, you're hitting that part about the data movement. How does a MySQL developer, which tends to be much more lampstack developer, traditional software developer, get into that kind of scale? What do you guys see there and what are you guys offering? Sure, sure. So we handle and help is when you've got particularly a large MySQL instance and you want to get it into a data warehouse quickly, right? So it could be a very large instance for MySQL. That could be a couple of terabytes. And how do you pull it in and do additional analysis of it? Maybe you're pulling it into Vertica or some other platform out there like Pivotal. So we can really help with managing that massive amount of data and making sure it works and sings harmoniously with the rest of your data center. So that's the value that we bring and we approach that. So we help with that scalability. We help with moving it in. And the other piece that we also help with is when you look at RDS and what's going on in the cloud. So a lot of people see the value of Amazon for whether it's Redshift or RDS. And the question is, well, how do I keep it in sync with the ground? How do I make sure it's not just easy to load which we do, but how do I make sure all the changes are captured moving through the system? So we also come in and help of, hey, if I want to offload some of this big data into the cloud, take advantage of RDS or maybe even do analytics on the cloud with Redshift, we can help with that as well. So it's all those kind of connection points as you scale that become important. What are some of the customer use cases you're hearing? Ones that want to be the next Facebook, want to be the next Google, they see all that greatness and go, hey, why don't we have that? Right, right. And they realize, wait a minute, they can't, it's hard to hire. Hard to get the skill sets. But so what technology and software is coming down the pike? That's really going to help the enterprise move from, I'm buying general purpose stuff to, I don't want to say specialism or specialized software, but getting that hyper scale, web scale, enterprise footprint, what are they, what are you hearing, what are you seeing them go to? Sure, sure. We're seeing a number of activities going back to the cloud, right? People are looking to deploy that to handle the scale. And there's a real value performance trade off there, which is nice that they can take advantage of, but a challenge often becomes of how do I get it there? So if you look at, if they look at doing say analytics in a redshift environment, a big question becomes, well, how easy is it to move? And we've talked to many customers that say, well, we see the value prop there, we want to go to it, but say they're going from Oracle or MySQL or what Matt, it could take a couple of months of developer time to kind of script it up, to code it, to build all the interfaces. So the promise is really pushed out, that time to value is not there. So we see adoption of tools like that, and we try to facilitate that because that's really going to help on some of the scalability, right? And ability to scale up kind of on demand, but the tools have to be there to support it. Talk about the marketplace. Actually, Jeff and I were commenting on the Cloudera financing earlier, and yeah, so, I mean, did your evaluation go up because of it? I mean, everything's going great. I mean, that's a fantastic finance. You're talking about billion dollars, 1.2 billion dollar raise for Cloudera. Yes. Who would have saw that coming? It's a huge success for Cloudera. Does that kind of put a wrinkle in the equation for the industry? Is that just cap table magic mojo or it's that they're doing with Intel's getting a position? Does that change the game? I mean, Intel is traditionally an enabling platform. Cloudera certainly is open to it, but there's other competition going on. Clients on the enterprise side have told us in the Cube that they like Cloudera, it's involved in POCs, but there's position as a data warehouse, business intelligence might not be their sweet spot. Although the vision's right on, so meanwhile Hortonworks is kind of doing their thing. So did Cloudera not have the funding you think? Do you think that this is enough gas in the tank for them? Do you think they can compete with the big boys? Sure. No, obviously that amount of money puts them in very good position to compete. And when you come in there and more and more they're gonna compete with the traditional database and data warehouses, right? Some of the work they do now is side by side, but over time there's definitely what am I gonna spend my dollars? They do, I would think they do need the money, the capital, to kind of compete with a lot of the major players who've been around for a while. So I could see them doing that. Obviously it's a lot of money going in, it's some validation of it. Do I know in five years who's gonna win and who's gonna be left over? I think that I couldn't predict that. Well, I always say it's hard to go out of business when you have money in the bank. That's right. So that's classic. But no, so they have the long play. So this is one of the things that Cloudera always needed, they needed that runway. Sure. And so now they've got the runway to kind of expand out. Do you think it alienates the market at all? Do you think it rises the tide? Do you think it floats all the boats? Some boats sink, some boats float? What's your take on that? No, I think in the short term it rises the tide. I think it brings everybody's awareness up of what's going on in the market with Hadoop. And it also follows what we've seen even as a company, you know, we're not a Hadoop distributor at all, right? But we've seen more and more people just in the past quarter asking about Hadoop, looking at the implementation. And so I think it's a combination of the validation of money going into it, people finding the right use cases, all that's coming together and making it seem an attractive story, this is here to say. So I think, is it the right amount? I'm not a VC, but I think it does validate what's going on in the market. It's insane numbers in terms of valuation or anything else, and it's good for the industry. So Hadoop aside, now let's move to the analytics market, okay? So you have the analytics markets exploding, Clare Story just announced financing for $30 million from Miller's company. Platform just got a big round of funding. Bubble Behavior aside, there's real movement in the enterprise, Gardner has a study out IT spendings up. What's going on in the analytics space in your mind? What do you see there? Sure, it's an area that people are looking for, the simplicity, the ease, right? I think places like Tableau and places like Splunk have kind of set the standard of how easy it can be to kind of mine through data and look at data so the expectations are raised there. And they've shown real value with it. Is data scientist market really happening or is this going to be the data analyst market? Boy. Because that's always been the question, do people really become data scientists or do analysts become a new title called data scientist? Yeah, that's a good question. I'm sure there's blending of both there, but yeah, it's either way, there's a lot of opportunity on the tool side, there's a lot of growth in those areas. So you think the jury's still out on that? Yeah, I mean, where it'll end up, I'm not sure, but I can see when we work with Amazon, for example, go back to the cloud, we get pulled into webinars with them with us talking about the infrastructure, people talking about the Redshift and then working with Jaspersoft on top of that, right? So people want to know the whole story, they want to know the whole stack. So it is an important area, there's a lot of growth there, there's been some good open source work there too, so I think that's a positive market. Yeah, I mean, Jeff and I were talking before we started, and I always talk to Dave about this from our old IT days, rip and replace always is a hard sale, but with open source, you can now incrementally get some beach head and kind of build on that. Okay, final question for you before we break is, information governance was a topic that came up in our crowd chat earlier today that we had around IBM Impact, big event coming up, but that still seems to be the big thing that everyone's trying to get their arms around, and everyone kind of knows it's important, policies is a top down, bottoms up, what's your take on data governance? Because data obviously will be at the center of the value proposition, and there'll be movement, different virtual machines, all this stuff's happening. What's going on with data governance? Boy, yeah, I see people that we work with at the application level, kind of wondering about that, looking for the support of it, whether it's where they store it or the security on it, but the overall market and what's happening there, I'm going to have to look at what you're working on. It's something we haven't seen as the infrastructure company as much, but I know it's coming up more and more at the app level. So overall application you're seeing a lot of data, you see New Relic made a big strategy change, they're putting some big data out there, seeing data in the applications, are you seeing that too? Yeah, and New Relic's an interesting one because they're at the point now where I was listening to streaming music service up in my room, and I'm hearing advertisements from New Relic, right? So they're showing up quite a bit. They're carpet bombing Facebook too, and Twitter. Yeah, yeah, it's amazing. Spotify or Pandora? It was, no, it was Slackered out. But the interesting thing was for these New Relic guys, I remember it was actually a Precona show in New York a few years ago where I was at my last company and they had this little table next to ours, and it's amazing and a kudos to them for their grill. Lawrence, thanks for coming inside theCUBE. Great to have you, great to get your perspective. You see in the landscape out there, the big data is key part of it. You got to store it in a database, and scale is the number one priority. This is theCUBE, we are exploring that conversation and more here live in Santa Clara, convinced in the heart of Silicon Valley. We'll be right back with our next guest after this short break.