 From Midtown Manhattan, it's theCUBE. Covering Big Data, New York City, 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. Hey, welcome back everyone. Live here in New York City, this is theCUBE's coverage of our fifth annual event that we put on ourselves in conjunction with Strata Hadoop now called Strata Data. It's theCUBE. We've been covering the scene here at Hadoop World going back to 2010, eight years of coverage. I'm John Furrier, the co-host of theCUBE. Usually Dave Vellante's here, but he's down covering the Splunk Conference. And who was there yesterday was no other than Josh Rogers, my next guest, the CEO of SyncSort. You were with Dave Vellante yesterday and live on theCUBE in Washington, D.C., for the Splunk.Conference. Kind of a big data conference in itself, but it's a proprietary branded event for themselves. This more industry event here in Big Data NYC, the event we put on. Welcome back. I'm glad you flew up on the Concord Jet, private jet. Coach. Early morning, but that was fine. No problems. Great to see you. CEO of SyncSort, you guys have been busy. Yes. For the folks watching in the CUBE community, you know that you've been on many times. For the folks that are learning more about theCUBE every day, you guys had an interesting transformation as a company. Take a minute to talk about where you've come from and where you are today. Certainly a ton of corporate development activity in your end. As you guys are seeing the opportunities, you're moving on them. Yep. Take a minute to explain. So it's been a great journey so far and there's a lot more work to do, but SyncSort is one of the first software companies, right? Founded in the late 60s. Today has a unparalleled kind of franchise in the mainframe space. But over the last 10 years or so, we've branched out into open systems and delivered high performance data integration solutions. And about four years ago, really started to invest in the big data space. We had a DNA around performance and scale and we felt like that would be relevant in the big data space. We delivered a Hadoop focus product and today we focus around that product around helping customers ingest mainframe data assets into their Hadoop clusters, along with other types of data, but a specific focus there. That has led us into understanding a bigger market space that we call big iron to big data. And what we see in the marketplace is that customers are adapted. Just before you get in there, I love that term big iron means big data. You know I love big iron. Used to be a term for the mainframe for the younger generation out there. But you're really talking about, you guys have leveraged experience with the install-based activities at scale. Call it batch, single thread or whatever you want to call it. But as you got into the game of big data, you then saw other opportunities. They get that right. So you got into the game with some Hadoop. Then you realize, whoa, I can do some large scale. What was that opportunity? What was the batch? Well the opportunity is that large enterprise is absolutely investing heavily in the next generation of analytic technologies. And a new stack, Hadoop is a part of that spark and they're rapidly adopting these new infrastructures to drive deeper analytics to answer bigger questions and improve their business in multiple dimensions. The opportunity we saw was that the ability for those enterprises to be able to integrate this new kind of architecture with the legacy architectures, the old architectures that were powering key applications and key producers of data was a challenge. There was multiple kind of technology challenges. There's cultural challenges. And we had this kind of expertise on both sides of the house and we found that to be unique in the marketplace. And so we've put a lot of effort into understanding, defining what are the challenges in that big iron and big data space that help customers maximize their value out of these investments in next generation architectures. And we define the problem in two ways. One is our two components. One is that people are generating more and more data and more and more touch points and driving more and more transactions with their customers. And that's generating increased load on their compute environments. And they want to figure out how do I run that? You know, if I have a mainframe, how do I run that as efficiently as possible, contain my costs, maximize availability and uptime. At the same time, I've got all this new data that I can start to analyze, but I got to get it from the area that's produced into this next generation system and there's a lot of challenges there. So we've started to isolate, you know, what are the specific use cases that present customers challenge and deliver very differentiated solutions? Overarching kind of messages around positioning is around solving the big iron and big data challenge. You guys have done some acquisitions that have been successful. I'm going to talk a little bit about the ones that you like right now, that have happened in the past year or two years. I think you've done five in the past two years. A couple of key notable ones that set you up kind of give you a pole position for some of these big markets. And then after we've done what I want to talk about, your ecosystem opportunity. But let's talk about the acquisitions. What's working for you? What's been the big deals? So the larger, the larger we did in 2016 was a company called Trillium, leader in the data quality space, long time leader in the data quality space. And the opportunity we saw with Trillium was to complement our data movement integration capabilities. You know, a natural compliment, but to focus very specifically on how to drive value in this next generation architecture. You know, particularly in things like Hadoop. You know, what I'd like to be able to do is apply best in class data quality routines directly in that environment. And so from our experience in delivering these big data solutions in the past, we knew that we could take a lot of their technology and create really powerful solutions that leverage the native kind of capabilities of Hadoop, but added on a layer of proven technology for best in class data quality. Probably the biggest news over the last few weeks has been that we were acquired by a new private equity partner called Centerbridge Partners. In that acquisition, they actually acquired SyncSort and they acquired a company called Vision Solutions. And we've combined those organizations. What did that happen? The deal was announced early July and it closed in the middle of August. And Vision Solutions is a really interesting company. They're the leader in high availability for the IBMI market. IBMI, it was originally called AS400, it's had a couple of different names. And a dominant kind of market position. What we liked about that business was, A, that market position, 4,000 customers, generally large enterprise. And also, you know, market leading capability around data replication in real time. And we saw IBMI- So it was a migration data, it just has a recovery kind of thing? It's DR, it's high availability, it's migrations, it's also a change to capture, actually. And leveraging all kind of common kind of technology elements there. But it also represents a market leading franchise in IBMI, which is, you know, in many ways, very similar to the mainframe. Run, optimize for transactional systems, hard to kind of get at and understand how to move down. So it sounds like you're reconstructing the mainframe in the cloud. So it's not so much that as a recognition that those compute systems still run the world. They still run all the transactions in the cloud world. Well some say the cloud doesn't solve for a mainframe as a distributed mainframe. I think over time you'll see that. We don't see that in our business today. There is a cloud aspect to our business. It's not to move those transactional applications running on those platforms into the cloud yet. Although I suspect that happens at some point. But our point was, our interest was more, these are the systems that are producing the world's data. And it's hard to get the- I mean they're big, they're big power sources of data. I mean they're not going anywhere. And so we've got the expertise to source that data into these next generation systems. And that's a tricky problem for a lot of customers. And not something that everybody's- And it's a problem they have. And you guys are in this threat corner of the market on that. So think about big iron and big data as these two components, you know, be able to source data and make it productive in these next generation analytics systems. And also be able to run those existing systems as efficiently as possible. All right, so how do you talk to customers, and I've asked you this question before, so I'll just ask it again. Oh, SyncSword, now you've got vision. You guys are such old mainframe guys. What do you know about cloud native? So a lot of the hipsters of the young guns out there might not know about some of the things you're doing on the cutting edge. Because even though you have secured the power based on these old big systems, which are throwing off massive amounts of data that aren't going anywhere, you still are integrated into some cutting edge systems. Talk about that narrative and how you're going to develop it. Yeah, so I mean the folks that we target. I use cloud native as an example. Yeah, so shiny new cool tool toys. The organizations we target in our customers and prospects, and generally we serve large enterprise, you know, large complex global enterprises, they are making significant investments in Hadoop and Splunk in these next generation environments. And we approach them and say, we believe to get full value out of your investments in these next generation technologies, it would be helpful if you had your most critical data assets available. And that's hard, and we can help you do that. And we can help you do that in a number of ways that you won't be able to find anywhere else. That includes features in our products, it includes experts on the ground. And what we're seeing is there's a huge demand because, you know, Hadoop is really kind of, you can see it in the Cloud Air and Hortonworks results and the scale of revenue. I mean, this is a real foundational component of data management at this point. The enterprises are embracing it. And if they can't solve that integration challenge between the systems that produce all the data and, you know, where they want to analyze the data, there's a big value gap. And we think we're uniquely positioned to be able to do that. One, because we've got kind of the technical expertise. Two, they're all our customers at this point. We have 6,000 customers. You guys have executed very well on that. It's got to say, you guys are just slowly taking territory down, and you get a great stretch, you get into a business, you don't overplay your hand or get over your skis, whatever you want to call it. And you kind of figure it out and see if it's a fit. If it is, grab it. If not, you move on. So also you guys have relationships. So we'll talk about your ecosystem. What is your ecosystem, and what is your partner strategy? I'll talk a little bit about the overall strategy. I'll talk about how partners fit into that. You know, our strategy is to identify specific use cases that are common and challenging in our customer set that fall within this big item, the big data kind of umbrella. It's then to deliver a solution that is highly differentiated. Now, the third piece of that is to partner very closely with the emerging platform vendors in the big data space. And the reason for that is we are solving an integration challenge for them. Like Cloudera, like Hortonworks, like Splunk. We launched a relationship with Calibra in the middle of the year. We just announced a relationship. Yeah, for them the benefit to them is they don't have to do the heavy lifting. You've got that covered. We can solve a lot of pain points they have getting their platforms set up. That's hard to replicate on there. And so it's not like they're going to go build it. Cloudera and Hortonworks, they don't have mainframe skills. They don't understand how to go access the data sets. Classic partnering example. But the other piece is we do real engineering work with these partnerships. So we build, we write code to integrate and add value to those platforms. It's not a bar any deals, it's not an optical deal. Absolutely. Well, any jazz is very critical at the end world of some of the deals he's been talking to the industry and referring to his deal. That seems to be back in vogue, thank God that people are going to say they're going to do a deal and they back it up with actual following through. What about other partnerships? How else, how are you looking at partnering? So pretty much where it fits your business are people coming to you, are you going to them? We certainly have people coming to us. The key thing, the number one driver is customers. And as we understand use cases and as customers introduce us to new challenges that they are facing, we will not just look at how do we solve it, but what are the other platforms that we're integrating with? And if we believe we can add unique value to that partner, we'll approach that partner. Let's talk customers. Give me some customer use cases that you're working on right now that you think are notable worth highlighting. Sure, so we do a lot in the financial services space. We have a number of customers, where there's a lot of main friends, but it's not just in financial services, but here's an interesting one, it was an insurance company. And they were looking at how to transition their mainframe archive strategy. So they have regulations around how they have to keep data. They had been using traditional mainframe archive technology, very expensive on an annual basis, and also un-flexible, they didn't have access to the data. They need performance too, and they don't forget performance. They want performance. This was more of an archive use case and what they really wanted was an ability to both access the data and also lower the cost of storing that data for the required time from a regulation perspective. And so they made the decision that they wanted to store it in the cloud. They wanted to store it in S3. There's a complicated data movement there. There's a complicated data translation process there. And you need to understand the mainframe and you need to understand AWS and S3 and all those components. And we had all those pieces and all that expertise and we were able to solve that. And so we're doing that with a few different customers now. But that's just an example of, there's a great ROI, there's a lot more business flexibility, and there's a modernization aspect that's just very attractive. Well, great to hear from you today. I'm glad you made it up here. Again, you were in DC yesterday. Thanks for coming in and checking out two shows. You're certainly pounding the pavement, as they say in New York, to quote a New Yorker phrase. What's new for you guys? What's coming to happen? More acquisitions happening. What are you guys going to, what's the outlook for Syncsor? So we're always active on the M&A front. We certainly have a pipeline of activities and there's a lot of different, interesting spaces, adjacencies that we're exploring right now. There's nothing that I can really talk about there, but there's certainly things to have. Can you talk about the categories you're looking at? Sure, things around metadata management, things around kind of real-time data movement, cloud opportunities. There's some interesting opportunities in the artificial intelligence machine learning space. So, you know, those are all- Deep learning. And deep learning. Deep learning, those are all interesting spaces for us to think about. Security is another space that's interesting. So we're pretty active in a lot of adjacent- Classic adjacent markets that you're looking at, so you take one step at a time, slow- But then we try to innovate after the catch, right? So, you know, we did three announcements this week, you know, transaction tracing for Ironstream and a kind of a refresh of a data quality and for Hadoop approach. And so we'll continue to innovate on the organic side as well. Final question on the whole private equity thing, so that's done. So they put a big bag of money in there and brought the two companies together. Is there structural changes, management changes? You're the SyncSort CEO, is there a new co-name? Is there, what's it called? The combined companies will operate under the SyncSort name. I'll serve as the CEO. The SyncSort is the remaining name. And you guys now have the company under it. Yes, right, that's right. And cash they put in, probably a boatload of cash. So that's the appetite for corporate development and acquisitions. The announced deal value was $1.2 billion, a little over $1.2 billion. So, exciting opportunity. And so you get a checkbook, looking to buy companies. We are going to continue. As I said yesterday to Dave, you know, I like to believe that we've proved the hypothesis for about the second inning. You know, can't wait to keep playing the game. You know, it's interesting. Real quick, while I got you, I know we got a break coming up for the guys, but private equity moves is a good movement in these transitional markets. You and I have talked about this in the past, off camera, is that it's a great thing to do is take, if you're public and you're not really knocking out of the park, kill the 90-day shot clock, go private. This seems to me a lot of movement there. Retool and then re-emerge stronger. Yeah, yeah, so we've never been public, but I will say the center bridge team has been terrific. A lot of resources there. And certainly, we do talk of, we're still very quarterly focused, but I think we've got a great partner and look forward to continuing. The ways are coming, get ready, the big ways are coming, so get your big surfboard out, as we say in California. Josh, thanks for spending the time. Josh Rogers, CEO of Syncsor here on theCUBE, more live coverage in New York. At this break, stay with us for our day two of three days of coverage of Big Data NYC, the R event that we hold every year here in conjunction with Hadoop World, right around the corner. I'm John Furrier, we right back.