 Okay, we're back. This is Dave Vellante. We're live from Las Vegas. This is IBM's information on demand show. We're thinking big. This is the theme of the event. IBM's Thomas Watson think was his mantra. And that's probably the most famous tagline in the computer industry, the IT industry. IBM's evolved that for this event into think big. And we've had a sea of visionary keynote presentations and we've been covering that end to end here at theCUBE, really talking to practitioners and IBM experts and industry opinion makers about IBM's strategy here. I mean a very impressive set in portfolio of data analytics and big data activities going on. Of course blended, it's IBM with a lot of traditional legacy of DB2, IMS, even SPSS, a base of customers. And we see those worlds coming together in real time. Just before us, a lot of business being done here. A lot of suits. This is theCUBE, the Silicon Angle, TV's continuous coverage of events, tech events. We go to these events, we extract the signal from the noise. I'm Dave Vellante, Wikibon.org and I'm here with my colleague. Jeff Kelly, also from Wikibon.org. Covering the big data space. We've got an interesting guest for you. We're here at the IOD, which is really a big data event, but we've got an interesting guest for you now in the networking space and how that can be applied to big data, or I should say how big data is applied to networking. Daniel Blastengame, VP, GM of Embedded Solutions at Nominum, welcome to theCUBE. Thanks, thanks Jeff, I appreciate that. Nominum, interesting company. Tell us about the company and people aren't going to get it right away, but then we'll connect the dots as to why you're here. Sure, we'll start and then at the end, I think people will be able to see where we're coming from. It's kind of one of those movies that you start at the end and you work back and it all makes sense now. Yeah, so Nominum, we're a software company, Silicon Valley based, Redwood City there. We're a venture funded private company that's a little bit atypical when you think startup. The company's almost 13 years old and we've been making software in the naming space. So if you think about DNS and DHCP, that's our heritage. And so our Chairman and Chief Scientist is a guy, a fellow named Dr. Paul Machopetris. Paul is very active at the company and Paul actually invented the DNS back in the 80s. And so Paul was actually inducted into the Internet Hall of Fame this year. And so we kind of built, we came from a heritage of protocol engines. And so at the very base, you know, we've built very fast, very scalable, very secure engines, but what's happened over the last few years is we've evolved into really building intelligence into this layer. And so recently we've announced the into platform. And so what that is, it's a platform that sits on top of these DNS core engines and you're able to easily get information from our engines and analyze it. So with the evolution of Hadoop and big data strategies, and actually real-time analytics is interesting too, because our engines are very fast, very scalable. And without taxing these processes, you can pull interesting information out. And what you're able to do is then run it through streams, for example. Streams is a great real-time processing engine and you can look at things inside the data set of DNS. Example, botnet and malware. That's a great one. Botnet and malware uses DNS as an attack vector. We're able to see that, not only alert and alarm on it, we're also able to actually go make a change through our into platform and change the way that you make a response to this DNS query. So Daniel, talk about, well you mentioned streams. Talk about how you're using that in some detail and how your customer is getting value on that. Our customers are large network operators. Generally, they've been, traditionally, we've had service provider customers in the fixed space. We have some wireless customers, household names around the world, the Comcasts of the world, the Cable Visions. Latin America, we've got a lot of customers. In Europe, we've got a big install base. And what's happened is, they traditionally use it just to have really fast response, but now what's happening is they're building applications on top of DNS. And so you're able to say, for example, we had a customer down in Latin America who wrote an application that sits on top and we look at actually the analytics of what's going on in their user base. Are you seeing a lot of over the top video usage? DNS is a really lightweight way to see you're a Netflix user, you're a Hulu user. You should be looking over the top analytics and maybe you should roll a marketing program out to these users that says, ah, did you know we have our own video and demand service? Or you may need a different package because you're a heavy on-demand user and therefore you can actually preemptively keep them from churning because maybe they're not getting the right service. So do you sell the platform, obviously? Do you sell the data as well? Well, what happens is like, for example, that network operator has their own data, they own that data, that's their data. So we sell a platform and have tools on top of it for them to extract that. And either they write an application or we're writing applications that live on top of that. And so, you know, a churn application that could be nominal written. We have also partners that are what we call our ideal ecosystem and that's the ability to write applications that live on top of the N2 platform. Yeah, so, you know, Jeff, we talk a lot about, you know, machine data, you know, we can Splunk take it off really, really hitting it. You guys sort of fit in that category, don't you? It's similar, you know, if you think about, you know, what big data and people ask me, why is a DNS company at a big data show? It's exactly that. Splunk's done a great job of building a company that says, you know, their tagline is listen to your data. Agree, and they're focused on, you know, the syslog data, they're focused on making sense of all this machine data. Well, just think of us as a little bit higher up the stack. DNS data looks at browsing habits, it looks at botnet and command and control. You know, we just did an operation last month with Microsoft to where we went to court with Microsoft as a declarant and were able to help solve a real problem. There was a bad operator out there that had about three million good domains, but 70,000 bad domains or subdomains to 3322.org. You can go out and do a search on the operation. There's a lot of information out there. But what we did is in DNS, we're able to actually answer the good queries based on some special sauce that we and Microsoft put in this. Properly, the bad queries we sink hold or we dis-allowing this command and control conversation to happen, rendering this not all botnet basically useless. So you mentioned infosphere streams earlier. So talk a little bit about how you incorporate that into what you do. And put more generally around streaming analytics and the ability to actually take action in real time and how that's evolved over recent years. I mean, what we're talking about what you're doing really wasn't possible even probably just a few years ago in terms of the technology available. That's right. If you look across our install base today, we have about 500 million households that use us throughout all of our different customer bases. That's about 1.1 trillion queries a day. So if you think about that, I mean, that's a massive, we talk about exabytes and petabytes and zettabytes, but really if you think about just a number of queries, those queries are not very big, but there's a lot of them and they're very fast. So if you look at a single network operator, whether you're a large enterprise, they're not quite as fast, but there are a lot of queries out there. If you're a big cable operator, there are a lot of queries. There were not tools that could handle that. That data is being bit bucketed. However, people often call it dirty data, but with the tools and techniques that are out there today, you're able to extract value and you can either do it at rest like with Hadoop or Big Insights or with Streams, you're able to actually see this data coming through. They do 12 million tuples. That's what they quote, 12 million tuples a second in a single Streams instance. Well, we're able to, we dump millions and millions of queries per second out of a big network. So what Streams is able to do is rather than looking at data, examining it and saying, oh my gosh, two or three weeks ago, this is what happened, you're able to say right now, this is what's going on. How should we respond to this threat? How should we respond to this marketing opportunity? Using DNS as a great source of data and we're trying to expose it to the world. And the applications that you're writing or your customers, so you persist the data? Well, it depends. Some of it, you know, you may want to look at it and it may not be interesting. I'll give you an example. Out of all of these queries, we're doing an exercise right now with a big operator down in Latin America. If you look at the Alexa, let's say the Alexa 1000, you know those are all good sites. So why would you even keep all the Google queries, all the Facebook queries? That's not bad. The value is as you go down, why are you responding to this .ru that has a really bad reputation? And you score that and DNS helps you get a better picture of what's going on. It's really powerful. So you mentioned the ability to take action in real time rather than waiting two or three weeks when something's already passed, an attack has happened, the damage is done. So which sounds, I think in our role, that sounds like, okay, that's an intuitive understanding, but really give some more examples about the kind of things you can do with real-time analytics that really impact, really deliver business value, either by stopping an attack or finding new revenue opportunities. Yeah, so, I mean, security's the first one, the first stop on that train. We talked about that, malware and botnets. And what's happening is you're going to see that continue to propagate across more devices. So as mobile devices continue to roll out in massive quantities, you're going to see that propagate. That's important that you're able to make real-time decisions. There are other things that DNS could help in. Customer sentiment is one. Let's say that people have asked me, could you build a DNS heat map around the, we're in the middle of the election. And it's, people are trying to figure out, is granular as possible, can we tell what's going on in a segment of the country? You could look at DNS data and based on the analytics that are out there, we've built a couple nascent, kind of early analytics engines are, our security one is more advanced. But if you look at some of the analytics that are being built out here with other partners, you could take this DNS data and they could mine really valuable marketing information out of it. Churn is another one. Churn's a great example. You look at call detail records. I mean, a big operator may have six billion call detail records a day. Well, that's a certain piece of it. You should also look at the fixed broadband traffic. If I'm a subscriber of someone that's got fixed and mobile, you should look at me as a holistic customer. You should look at my broadband, traffic and say, you know what, Daniel, would you like to opt into something that would give you better service? Yes, I would. Then I would let you use that data and couple that with this unstructured data. And I think you have a better picture of me as a consumer. Right, I think, you know, when it comes to, when people hear the term machine data, I think they think, okay, well that's good for solving kind of technical problems. It's going to tell me my machine is not working properly sooner. But I think you're doing a great job here is tying that to real business results. It's not just tuning an application or tuning a device. It's translating that into making better business decisions, whether it's around the customer, you know, preventing them from churning or offering them a better service. Sure. I wonder if I could ask you, go ahead. I was going to say just one other thing. You know, when you talk about machine data, DNS, we've talked mostly about kind of customer data browsing, things like that. But there's a lot of information. Botnet is machine to machine, of course. But on the enterprise side, I mean, there are applications. So we're partnering with some application delivery controller companies, Radwares, one of them, about looking at making applications work better. And you should also, applications also need access to these resources and they use DNS as a way to do that. Whether it's around load balancing, whether it's around DDoS mitigation or denial of service mitigation. DNS plays a role in all of these pieces and we're trying to, at Nominem, through the N2 platform and the ideal ecosystem, make that easier for people to use. I want to talk about the company a little bit. You mentioned 13-year-old company. Big data wasn't around 13 years old. Maybe it was, but we weren't calling it big data. VCs weren't throwing money at it like crazy. Did you, everybody talks, you're in the valley, but it talks about pivot, you know, okay, fine. I don't necessarily see this as a pivot as more of an incremental layer that you built on top of it, opportunistic. Did you see that and then raise new venture to go after this opportunity? Sure, no, we've not raised any capital since 2005. So if you look back at the history of the company, you're right, it was very much around network services. You know, if you think about DNS, it's kind of a fundamental network service. If you look on our board, we've got a great board. I mean, David Cowan from Bessemer is on our board. You've got Gary Morgan-Thaler from Morgan-Thaler Ventures, Vicky Gonnison from Globes Fan. So those guys were early investors and they kind of stuck with us. And when we built, between 2000 and 2005, the company was trying to find its way. Really, 2005, it found these large network operators who needed scalable, fast DNS network services. And then we did, I would say, from then, we haven't had a round of funding. We've generated cash every year. We've got actually some cash that we're investing right now. We're hiring a lot of people. So if you're online and you're looking for a job, Nominum's a great place to work and we're hiring engineers right now. We didn't do that through funding. We've done it through being a profitable company, which isn't that interesting sometimes in the Valley. Everyone wants to talk about massive growth, but we've been profitable since 2005. And so now we're investing that. And there is a slight pivot. I think a lot of the ecosystem is caught up to some of the things that we built and we find ourselves either fortuitously, either by design or by happenstance in the right place at the right time. So my follow-up question on that is, I want to talk about IBM, why IBM? I mean, Andreessen Horowitz, Mark Andreessen says, none of my portfolio companies use Oracle. They run their business on Oracle, right? And so you don't necessarily, typically associate companies like IBM and Oracle with fueling startups. Now, of course, we see Tableau here, we see Couch Base here, those are more partners, but you guys are actually leveraging products. We had another company on earlier that was leveraging some of IBM's products, Streams in particular. Why IBM, are you using other products from IBM besides your streams? We started out, we started out building our own, a couple years ago, building our own Hadoop environment. And then, and we still run that and we productized some things around that and used it. But now what's happening is we need to, we need to actually innovate quickly. And there are some products out there. IBM has spent, you know, five, eight billion dollars in this space over the last few years. They've got some really good products. And so, even on the engineering side, you know, our team is looking at some of the analytics, some of the things we've built. And then we look at it and we say, do we want to build this? Do we want to buy this from someone or partner with someone like IBM? Or do we want to go into the marketplace? And is there an up-and-coming company that we want to go buy to bring this in? So those three things, you know, we look at every day. And right now, IBM, I'm very pleased with the partnership. But Anjo Bambri has been great. The big data team and the data enablement teams have been really, really good. So, you know, maybe you don't think of IBM as, you know, it's not a Silicon Valley startup. However, they have some great tools, especially in the security space and the big data space. They've done a really nice job. So is it just, are you just using streams or are you using other products? We're using streams, we're also looking at, you know, when you ask, what do you do with the data once you go through streams? Well, we're looking at dumping that into Hadoop. We can either put it in our Hadoop system or actually big insights. It could be a good fit there. We're actually going through the partnership. It should be signed, the documents are signed. We're doing the proof of concept right now with Q1 Labs. So Q-Radar is, I don't know if you're familiar with Q-Radar, it's IBM's security event management system. So we're using Q-Radar, we're using streams and you know, there's other part of the X-Force suite is really interesting to us in pure systems. And so we're validated, we're validated on PureFlex and so you can go get a nominum appliance, it's a virtual appliance that drops right onto PureFlex. So how would a customer use that? Talk about that. So let's say PureFlex is, you've got kind of an all and one solution with many different pieces in it. If you're looking at, you look at the N2 platform, and you say, hey, you know what? This analytics out of DNS is interesting to me. I'm a PureFlex customer. I could go package our Vantio instance, which is our core engine with the segment, the parts of the N2 platform that we want. Maybe we want the policy engine. We drop all that into a package that installs right on PureFlex. And so we just finished up some validations with them and we're going to continue to grow that relationship. Can you talk about the, I know you can't give specific figures. I mean, if you can, great, but I doubt you can. But just the relative order of magnitude of this new business versus the traditional business. What's the trajectory look like? Where do you see it going? It's hard to talk about that. We do think this is an investment area. I told you earlier, we're investing in this area. The line of business that I'm in, it's called Embedded Solutions or OEM. And it's really, when you say, you asked, did we pivot? We did pivot on that. And we've actually are being more open. I think there's a period of gloss notes that's going on right now at Nominum. And so I can't give you, put numbers on this TAM, but I do think that this is an area that we're going to see drastic growth on because right now we really have zero business in this market right now. We've added some in the last year that we've built ourselves, but we're looking at broadening it in the market. So it would be a great growth area for us. So if I had a sort of mental model you relative to some public company, I mean, who would I look at? Would I look at Akamai? Would I look at? It's Akamai is really services-based. And so we don't have, we do have some services that can recurring revenue subscription service, but that's not the biggest part. We're more based around, typically it's been perpetual licenses. I think we're trending more toward the security space. You know, we don't make appliances. We're software only. Andreessen wrote software eating the world or I don't know what his quote was, but so we're in that space. I don't have a hardware appliance. So we're not a pure play like unified threat management company. We're not, you know, Fortinet. We're not, we're not someone like, you know, just an appliance company like Infoblox. Infoblox has gone down a different path. They've done a nice job in IPO'd, but they're really focused on like network and element management. We're focused on. So Symantec maybe, even though this is a diverse portfolio, but maybe portions of it. I would probably, you know, if you were to put a scatter, a scatter diagram, we'd probably skew a little more toward the security side. Yeah, so okay, so the security side, but pure software play. So you're talking about a company that might trade it between five and 15 times revenue, depending on your growth rates. I think that would be fair or maybe, you know, if we're, let's say that you were to take that and cross it with a little bit of SDN, that would be really a really nice multiple to look at. You know, look at NYSERA or whatever. But if you think about the evolution of the network, I mean, we're talking big data here, but software defined networking is really changing. It's changing the way people are looking at networking. And if you look at core network services, lack DNS, like the ability to put policy in that layer, we think that there's a real strong play for us there too. So I mean, we're investigating those areas now. So we've looked a lot at the whole software led infrastructures, you know, software defined network is obviously a piece of that. Can you, can you just add some color to what you see going on in the, in the space? You mentioned NYSERA, it was like, you know, where is Instagram? Right, well, you know, if you look at that, it's a, I'm kind of a networking guy. I came kind of from a networking background. And so I look at it as the evolution of disk, you know, you just have a proprietary disk and disk became virtualized and storage became virtualized. And then servers, everyone had the kind of proprietary server then that became a virtualized environment with VMware kind of winning that battle. The network is next and the network, we're at the beginnings of it. If you'd asked me a year ago, I was like, you know, I think it's a long way off. The last year has accelerated. I mean, the adoption of open flow, really the purchases like that you see, like with NYSERA being bought by VMware, you look at investments, you look at what's going on with, even like the 10 gig switch players, you know, you've got Andy Bechelsheim and the guys down at, what's this? A Rista? Yeah, a Rista, I mean, you got a lot of money kind of looking at the network right now. And we're in the middle of the network. We're not a layer one, layer two company, layer three company, but we're above that. These network services are important as you build out a virtualized network. So I think it's evolving faster than we thought a year ago. Well, plus now flash storage comes into the mix and you're pushing the bottleneck from the spinning disk. Now it becomes the network's the bottleneck. There's a lot of innovation actually going on there. I mean, you look at compute power has gotten cheaper and faster, disk has gotten, the network is lagging. The network is lagging. It's, it is the bottleneck right now. So there's a lot of innovation, a lot of money. I mean, this business four or five years ago, database, boring, network, really kind of boring, not really a lot of action going on. It's just a hot areas, it's exploding. So it's just a great industry we live in, isn't it? Sure, sure. All right, Daniel, listen, thanks very much for coming on theCUBE. A really interesting story. Check out Nominem. Keep it right there. We'll be back with our next guest live from Silicon Angles theCUBE at Las Vegas, IBM's IOD. Keep it right there. Thanks.