 Live from the MGM Grand Convention Center in Las Vegas, Nevada, it's theCube at Splunk.com 2014. Brought to you by headline sponsor Splunk. Here are your hosts, John Furrier and Jeff Kelly. Okay, great. Okay, welcome back everyone. We are here live in Las Vegas for the Splunk Conference 2014. It's theCube, our flagship program. We go out to the events and extract the soup of the noise. I'm John Furrier, the co-founder of SiliconANGLE Media. Jeff Kelly, the number one big data answer, wikibon.org. Our next guest is Harvey Tesler, the co-founder of SyncSort. Welcome to theCube. We've had you guys on many times. Great to see you. Thanks, John. Thanks, Jeff. So give us the update. So SyncSort, ironically, I was just having a crowd chat this morning with Katalogic, which I said, I've never heard of you guys before. You got a startup? That turns out that's your technology. Yes. What ironic, ironic today. So you guys are everywhere. And you've got, of course, been around for you guys been around for a long time, very successful. Give us the update. What's going on with SyncSort? Why are you here? We're here because there are many mainframe customers that are trying to get data into Splunk and they're trying to get the mainframe data in. And what's happened is they have this great view of their data operational data, their security data in Splunk, but it doesn't cover the mainframe systems. And so somebody's saying, well, we don't have the whole picture here. Why do we want to have a separate monitor or separate way of collecting that? Why can't we put it all on one screen? So we started going to our mainframe customers who know us for many, many years. We've got more than half of the mainframe market on ZOS. So those mainframe customers trust us. And are you going to put software on our ZOS system? Yes, we are. And you know that we're good at it and we have the relationships. And now we're able to pull down real-time machine data from ZOS into Splunk so that a transaction that may be an ATM swipe or a package delivery that's starting out on the distributed system but makes its round trip through DB2 on ZOS. If someone's looking at the screen and say, why did that transaction take 20 seconds? It's because there was some problem on the DB2 side and right now they call the mainframe guy and he says, I'll get to that by tonight and let you know. Yeah, maybe, yeah, maybe. If he gets to it that fast. Exactly. Okay, so you guys are bringing the Splunk to basically the mainframe market. That's mainly the big deal. And that's the big deal. And this is new for you in terms of bringing mainframe data, unlocking mainframe data. So you do this with Hadoop. Yes. And now you're doing, so we think of Hadoop more as that large-scale historical analysis where Splunk is more of the real-time type of game. Exactly, right, exactly. So are those the two kind of use cases you're seeing for those two different markets? Yes, although ultimately we were talking to a large New York financial institution last week and they want the real data real-time. I mean, that's really a big difference. But they're saying, you know what? If we can keep lots of historical data in Splunk, we can then, when something's taking three seconds, they can say, well, what was it a week ago? What was it last month? What was it six months ago? What are the patterns here? And Splunk is delivering more and more analytics so that those patterns can be easily recognized. And you know, there are already monitors systems on ZOS. But Splunk gives them a new dimension of historical data and real-time that matches with the other systems that there, other transaction systems that I mentioned earlier about package delivery and ATM and credit card swipes and retail transactions. So let's take a step back, add a little context. Some of our viewers might be watching saying, mainframes are, who's using mainframes anymore? But there's quite a few, isn't there? I mean, the demise of the mainframe was predicted quite a few times and it just hasn't happened. It's still a steady business for IBM, isn't it? Yes, and the MIPS that IBM has in ZOS grows every year. It's not growing at 50% a year. It's not growing at 30% a year, but it is growing at 10% a year. You might say, well, who's buying these MIPS? Well, it's mostly the existing footprints that they have and even though there's pressure to hold down those costs, a lot of those MIPS are on WebSphere applications, Z-Linux applications, but there's still a ton of data that's the data of record for almost all the large banks around the world, insurance companies, financial institutions, all the credit card companies, all the package delivery companies, all the big retail companies, all the data, important data and transactional data is on the mainframe. Well, this gets back to a conversation we were having with Steve Summer earlier about the importance of, when we think about big data, it's not just the new sources of data, which are important, but it's about bringing in legacy data sources for lack of a better term and integrating those in a way that you can correlate patterns based on all of the data at your disposal. And it sounds like that's something where things work can come in and actually help you get data to where it needs to be so you can do this analysis. You know, if you think about the mainframe and the ZOS operating system, I think it just had its 50th anniversary and I guess I could say that I was near the start of it. But in any case, so if you think about an application that was collecting machine data back in 1964, so it was probably a small amount, we want to know when a job starts, when a job ends, how much resource did it use as far as CPU time. But now you have a whole department of developers that are responsible for that, so next year maybe we'll add another piece of information about that job and another piece. So it's got 50 years of adding more and more granularity and richness to that mainframe data. And that data, to a large extent, is being utilized today with some of the larger mainframe companies that sell products. But it's too much data to kind of keep for a long history and it goes into the big data that Splunk gives you and you can get more historical information from it. And I think that as people start putting more and more mainframe data into Splunk, they're going to say, wow, we could do that and we can add to our security, we can enhance our insecurity, we can enhance our operational health management and our problem resolution. Well, that's going to be my next question. So what are the real business problems, the business challenges that people are solving now or they can solve now that they're being able to bring data out from the mainframe into their Splunk environment? Well, there's one source of data on the mainframe, it's the Operator Console. In ZOS language it's called SysLog, although SysLog has another meaning on the distributed side. So one of our customers came to us and said, we have multiple applications that can be using the same DB2 database. If that DB2 table is deadlocked because two applications are trying to access it at the same time, then we have that application then stops. So we want a real-time alert that's on the same screen as the application performance monitor for that application. So when the application is stopping it's because of the mainframe, they'll get that. Another customer is looking at, they know that they've designed their, let's say their web application for customers to be able to handle 50,000 transactions or 50,000 log-ons a second or web hits. And they want a monitor that's going to be able to tell them how close they are to getting to that log-on threshold as well as the latency for each of those. So it's performance and performance management on a real-time basis. And that's just not something they could get with the traditional tools that allow them to monitor their clients. Not really. I mean, there's a lot of the traditional tools that tell you, well, your CPU is 98% utilized or this DB2 region is being, is overtaxed. But the individual applications, those are the areas that they're trying to look at so that the business users can now know exactly what's happening with their, with their. Harvey, I want to, I want to get your take. Real appreciate you coming on theCUBE. You guys own the mainframe market. We're very familiar with you guys. We're getting hooked on time here. So I want to give you the final word. Share with the folks out there how dominant you guys are in the mainframe. You guys are basically the splunk of the mainframe. You have great customers. They trust you, you operationalize and modernize a lot of the things. What's the big deal, the big trend in your world right now? Is it mobile infrastructure connecting to the mainframe? Is it app latency? Obviously, Splunk brings up a value proposition that's obvious, right? They have one real-time data going through the mainframe. It's your market. So share with the folks out there. SyncSort, mainframe, Splunk, the value proposition. Final word. Eric, we have over 50% of the ZOS market. Our sort product first sold in 1971 to a bank in North Carolina. It was called First Computer Services. They sent us a check for $5,000 in a signed contract. That First Computer Services was the first national bank in North Carolina, which is now Wells Fargo. As it goes up the chain. How much cobalt you guys still have? So we've got customers for a long, long time. And they trust us to help them save money. So we have products where we push processing onto IBM zip engines. So we have several thousand licenses for mainframe licenses. And so they're looking for us to come out with more and more products that have to do with how can you save me money? The Splunk opportunity is not only, now you're giving me an opportunity to leverage my mainframe data. And I know that you're a, meaning us, Syncsort, are trusted, reliable, great customer service. And because in this sales cycle, you have to convince the mainframe guy, it's okay to entrust what's going on here because I have a CICS DB2 application. It's got to meet its SLAs. Yeah, and it kicks us. That's been around for a while. But I love their story. I love talking to the Syncsort guys. Great team, fun to talk to. But gotta ask you, what's $5,000 worth today by 1974 standard? That's a pretty big check. And there was no bill pay back then. Well, the world's probably got great bill play. Well, I mean, that's a good, that's a great deal. So what does that equate to today? Bulk market for me. But I would say, I would say that that license today now, the MIPS they were using then is a lot less than the MIPS they're using today. But that would be maybe $75,000, $100,000 today. Nice. Great story. Love that. I love how you weave that in there. Love to tell in the story. Thanks for coming on theCUBE. Really appreciate it. Co-founder of Syncsort. Great company. If you don't know them, they own the mainframe. Trusted partners. Doing great work. Obviously, they're involved in big data. Really modernizing and bringing that equipment up a notch and staying relevant and staying with great staying power. The mainframe has proven to withstand anything and it's great staying power. Thanks to you guys. So we are live here in Las Vegas. This is theCUBE. I'm John Furrier with Jeff Kelly. We'll be right back after this short break.