 Live from the San Jose Convention Center, extracting the signal from the noise, it's theCUBE, covering Hadoop Summit 2015, brought to you by headline sponsor Hortonworks, and by EMC, Pivotal, IBM, Pentaho, Teradata, Syncsort, and by Atunituandisco, now your host, John Furrier. Okay, welcome back, everyone. We are live here in Silicon Valley, by Hadoop Summit 2015. I'm John Furrier, this is theCUBE, our flagship program. We go out to the events and extract the signal noise. We just had Rob Bearden on, CEO of Hortonworks. A lot of great stuff happening. We've got two great guests here, Josh Rogers, President of Syncsort, and Mike Fontaine, National Sales Director, disruptive Susan at Cloud and Big Data at Dell. Guys, welcome to theCUBE. Thanks, John. Thanks, John. Thanks for seeing you again. Good to see you. Big Data is great for you guys, they've been doing amazing lately. Been following you guys on Twitter. The business performance is great. Get some big news to share with Dell. Let's get right to it. What's going on? Yeah, so we're announcing a joint solution. It's the first and only opportunity for customers to get their hands on a complete solution for data offload for data warehouses in ETL. And it's a reference architecture, Dell's technology, Claudeira's technology, Syncsort's technology, an end-to-end solution from bottom to top for customers to tackle this great use case, which both frees up budget, funds their Hadoop cluster, and populates it with the data that they need. It's a great solution. Mike, what's the Dell impact? So we're really excited because we're really taking a use case-based approach to solving customer problems. So we've been in this business for the last seven, eight years, started with a big web tech firms in Hadoop and solving their problems. And now the mainstream enterprises are getting involved. It's important for us to focus on specific customer use cases. And then to Josh's point, putting together a whole solution to make it as consumable as possible for those folks. The timing is really interesting for this announcement because it kind of supports our indicators that we were pointing to earlier. And then Rob Bearden came on from Horton worth pointing out his data, even Gardner might be a little bit watered down, but clearly it's crossed the chasm. So a lot of enterprise adoption's there. You guys have a lot of product and services Dell and the data centers, huge install base. What are they saying? Like, hey, I need to have the sync sort integration because like that becomes, I mean, there's a lot of big name decals that have the mainframes. And this is like the perfect storm. We were talking to some of the IBM folks just recently about their mainframe business is booming. These large, many computers are still around. They're not going away. So what's the impact on your business from a customer standpoint? So I think it's huge. I think the opportunity to actually focus on the customer's business problem. I mean, Dell's been in the infrastructure business for a long time. We've made some big investments in terms of software IP services. The partnership with sync sort is critical because they bring a trusted, experienced solution to marketplace that solves frankly the customer problem we see most, right, as we've transitioned from sort of the early web tech days where we were heavily involved, big social media type. Now that you're a private company you can tell us to sell through data. Yeah, exactly. I'm not going there. I wish it didn't take long to get to the limits. All right, come on, Josh. What's the numbers? I mean, it must get your attention. This is a significant deal in terms of revenue, right? Oh, absolutely. Yeah, it's, I mean, if you think about the number of customers. The number of customers and across the breadth of segments from the smallest startup companies all the way to the largest globals, are the opportunities there. Yeah, I mean, I'll comment. You know, we came out with our DMXH Hadoop-first DTL solution a couple of years ago and, you know, as we engaged with customers and saw that gain traction, you know, the number one use case was offload. And it's a perfect starting point for these organizations because, you know, it accomplishes so many things. It gives them a very kind of understandable way to get started with Hadoop. It drives cost savings or cost affirmant immediately. Their teams learn how to deploy the infrastructure and manage the infrastructure and it saves money. And it also populates that cluster with all the data that they need to start to get those transformational insights. So, you know, as we have seen customers adopt offload as their first use case, we've, you know, built purpose, built features to make that easy. Now, when you combine that with Dell's expertise and their reach, you know, we just think we have an unmatched solution to be able to kind of get people started on the journey to big data. Well, and you get also distribution in all the corners of the world now with the distribution. And you've got platform use cases. This is not a newbie. You've got Linux and other like the mainframe cover. So you're extending your tentacles of string sort into wherever environment you need to build software connectors to, right? Yeah, you know, our goal, we really took an approach of, you know, Hadoop is going to win. Hadoop is going to be the big data operating system. And our job is to make it as easy as possible for customers to suck those expensive workloads that are running in other places into Hadoop along with the data. And we believe that's going to be a great catalyst for, you know, getting people started on that Hadoop journey. Obviously with this relationship, we're tackling data warehouse optimization, ETL offload. We have another relationship we launched in Q4 where we've gotten our initial wins with Cognizant tackling mainframe offload, which is another use case that is populating our pipeline more so than we thought. And there the savings are a bit more measurable and immediate because as soon as you offload those MIPS into a Hadoop environment, you start saving money that day. So we are continuing to look for those use cases that will help customers justify and give direction to their big data ambitions. And I'll question them. Well, they've got to enable some analytics, right? So the key is with scale out, right? Dell has made a great run with us on the scale out commodity hardware business or industry standard, whatever works best for the optics. But, you know, that is not proprietary. That's going to be scale out. So now you guys are in a good business software. What, I mean, this thing sort of ultimately becoming non-mainframe software company. At some point, I mean. More and more of our use cases are, you know, extending beyond the mainframe for sure. You know, we have a number of customers that don't have mainframes and still use us. But you know, when people want to leverage the compute that they put on the floor with Hadoop for, you know, high scale mission critical processing, you know, we are the logical choice because of our expertise and because of all of the, you know, engineering that we've done over the last decade in our core engine that we've now run, you know, directly on Hadoop. So take us through the concept with the Dell customer that would sync sort, how that would play out. And comment specifically on the challenge that we hear in the marketplace, which is, I want to unify my data. I got to have some unification on the ingest. You know, you got a lot of stuff everywhere. And you know, could be, you know, Cassandra over here, cluster, Hadoop and the big mainframe in the glasshouse doing its business. You know, grandpa mainframe doing its thing. Okay, I got to unify it together. Now, so how does that work with the Dell? So just take me through a use case. Yeah, so, you know, we engage with a number of customers and we understand their environment. We figure out, okay, if you have a mainframe, tell us about what you're trying to accomplish their reduced cost. You have a data warehouse, is that at capacity? Yes. Would you like to avoid upgrades? Yes. Would you like to have a more flexible infrastructure for leveraging your data assets? Yes. What do you think that's going to be? Hadoop. You know, does it make sense to think about starting to suck the expensive workloads running on the mainframe in the warehouse into Hadoop to populate the infrastructure and also save some money? That would be great. Can you help us on the hardware piece of that? What decisions should we make? That's where I think the Dell relationship is so important is that it gives the customer a complete end-in recipe for how do I build the right infrastructure, you know, starting at the server and going all the way up to the software layer to deliver and tackle this use case in a way that is proven. I think the benefit to the thing sort is, Mike, you guys got feet on the street saying, hey, I got budget to do a Hadoop rollout. We went from POC, we kicked the tires, but now I got a factor in this new element called the mainframe, which I didn't factor into my original, you know, maybe scope, and then I got more budget, I need end-to-end, so that's what you're getting at, right? So you're getting it both ways, you're pushing leads down to Dell and Dell bringing business to Sync Store. Absolutely, absolutely. I mean, IT-centric use case, every customer that's got a data warehouse has an issue, they're going to have to expand it at some point, or they've got performance issues or capacity issues today, and they're a prime candidate to say, hey, let's offload some of that activity, free up that precious resource to do the really high-value analytics and BI type use cases. Mike, talk about Dell. What's going on with Dell? So we were talking before we came on, we did Dell World last year at theCUBE, really familiar with Michael, big fan of what he's done, certainly over the years, and then taking it private, which I was a huge fan of, innovation-focused, what's going on inside the camp? I know that people are happy because everyone I talked to is like, oh man, it's great right now, it's so awesome. What's the real deal? So it is a great time to be at Dell. So I've been around Dell for the last 15 years, and with the privatization, with our transformation into a solutions company, we're taking a little different approach where the solution has to start with a customer's business problem. It's no longer about build it and they will come, or build it and this will solve every problem you've got. So I think we have a unique opportunity, given our partnerships with folks like Sync Sort, given our open systems, open source-based approach, it's in our DNA, taking the approach of solving customer business problems, getting closer to their business problems, it's happening. I mean, we're not a hardware company anymore. I asked Michael Dell, a little tidbit, I said, hey Michael, you know, going private. You know, you don't have the stock options, maybe you can give some people some stock odds, but people, you know, want to get, how do you attract such good talent? He goes, John, we have so much freaking cash flow, I just pay the talent, top dollar and more. And I'm like, that works, right? So, you know, things are good over there. I mean, Dave and I were talking about on theCUBE that, you know, the business wasn't really hurting, and it was, I mean, it had thrown off a lot of cash. So, the new transformations there for Dell, what is the cloud story with Hadoop? I mean, is it services-based? I mean, I'm still trying to get my arms around the cloud piece for Dell, the cloud big data piece, if you could share the vision there. Well, across, actually, yeah, there's a couple different angles on that, but I think that we've seen both in the HBC market as well as in the big data market, the cloud provides some flexibility for transient use cases. You can get a use case into a cluster, get it out. So, I think a cloud environment provides flexibility for customers who may not be able to afford a dedicated cluster for HBC or for Hadoop, right? They can have them move inside and out of the cloud. I mean, that's the biggest thing I see in terms of where the two are crossing paths. I also think cloud is becoming a bigger piece of our business, and we're seeing it lower the threshold for people to take advantage of some of these big data capabilities. There was an article published a couple weeks ago about Dickies Barbecue. So Dickies Barbecue is the largest barbecue chain in the United States, 500 locations. And if you look at what they're doing, they're leveraging big data, POS data directly from stores to both manage inventories on a daily basis, drive specials on an intraday basis, and then also kind of manage the menu selection across all the regions. Their ability to do that is truly given the economics cloud. They can now build that infrastructure. They're leveraging us to collect distributed data. They would have to build a schema, understand the use case, no experimentation, or anything like that. Exactly, by all the hardware, figure, build it to peak, et cetera. And that is such a great article because it connects the business flexibility you can get if you can truly harness the power of big data. So we work together with IOLAP and Yellowfinn on that, and it's a great solution, it's a great story. And it's becoming, we're seeing that pattern emerging. Were you guys involved in that deal? Yeah, yeah. I saw that in the press, I see you guys, all right. We actually highlighted that in one of our crowd pages, came out of the crowd. Yeah, yeah, we're the ETLA in that solution. All right, so how does that translate to corporate America? Because I think that's a real life example of, this is the impact at any level of, whether you're Dickies Barbecue or Joe Department Head in any company. There's a little bit of an underreported story that goes at, if you dramatically lower the cost structure for analyzing data, you can just ask a whole lot more questions. And I think Dickies actually does a good job of highlighting that. And that's true for large enterprises as well. I don't think people have a good sense of the cues that they have internally to go ask questions of their data. And what Hadoop allows customers to do is to dramatically lower that cost structure. We see it in our customer comm scores, a great example. This is a company that measures internet activity globally. 20 terabytes a day ingested into a 10 petabyte Hadoop cluster. That cost structure was not possible 10, 15 years ago. And Hadoop is a key component of driving the lower cost. I got to ask you this question. You bring up a good point that's, we've been circling this around all morning. John Chambers was kind of talking about yesterday in his last keynote speech at Cisco Live, which is there, he's handing the CEO job over to the new guy. And he's talking about being disrupted or being the disruptor. But what you brought up is the key thing, at what point does ROI become not a factor? And right now we still talk, it's like it's almost kind of funny in a way, like that we still talk about ROI. Like, oh no, we should really get it. I want to see some ROI on that big data project. At what point, Josh, in your opinion with seeing customers, when do we stop talking about ROI? When it's so obvious that you just have to get going. What I've seen in our dozens of customers have gotten into production deployments, is once you get over the hurdle of saying, I'm going to make the investment to build the infrastructure and the skills. First of all, the marginal cost of delivering the next project goes way down. Second, that we've seen is it just attracts users and it attracts new business use cases and existing processing workloads. And new talent for the company. Absolutely. I mean engineers too, we're like, hey, I'm going to work on a new cool project. Well, I was meeting with a customer last week, one of our first Hadoop customers. They started with the traditional data warehouse optimization ETL offload. They're saying their plan is to go from approximately 300 nodes now to 6,000 nodes over the next three years. And that's based on the demand they're seeing from their business users, the new use cases coming to them. So, I think once you get the infrastructure in place, once you get the skills built internally and you have the right set of tools to execute various use cases, the demand just explodes internally. And that's what we're seeing. That's why we're focusing this solution with Dell on that on-ramp, which is offload. You wrote a good point. I talked to a CIO friend in a big company, I won't say their name, I don't think I can disclose it, but he said they meet every year with their key people and the worker bees in the trenches. Big off-site meeting, they write a big check, they go to a hotel, they have off-site flip chart, you know, the kumbaya, rah rah, were great, cut the server budget, consolidate. He said, he put a straw poll out and said, hey, off-site meeting or use that money to do something cool in the cloud. They all voted do something cool in the cloud. That was actually the team-building exercise in that company. So what he said was, what was interesting to your point is that the new technology attracted, it would became a human resources team-building exercise. At the same time, he was forging a path, so he has total consensus points. So he used the cultural shift to get that point. So is that happening that kind of, not that particular tactic, but that kind of cultural thing happening across the enterprise? Do you see a percentage of them already there with that we have to get going? People are energized? Or what percentage are still kind of living? Like, well, I'm doing my data center and we've got stuff rolling. And so I don't talk to anybody that's not thinking about what to do. I talk to a whole different range of people on how firm the ideas are and how informed perhaps their ideas are. And I think a lot of people are still struggling with the complexity of getting started. I think that there is an ever-growing number of animals in the zoo, if you will, and making sense of that is hard. And I think that's what we're trying to do is to make it easy. We're trying to show up with customers and say, look, you can use your existing skills. You can attack a use case that will have a short payback that you can defend and sell internally, and it will set you up for transformational success in the future. And I think that's, you know, the organizations we see being most successful in getting to that tipping point, starting with that type of use case. Mike, I got to ask you, disruptive solutions is a great description of, and a charter, right? You go out and have disruptive solutions. But if the culture is different from company to company, is it hard to match an operational plan to go out and have to deliver the solutions to customers? And how do you deal with that? I mean, you want to be bringing disruptive solutions, but at the same time, if you're too disruptive, the clients can't handle it. So like, you know what I'm saying? Where's the balance? Totally agree. And I think the beautiful thing about this technology and Josh said earlier is the fact that we've got some use cases that are IT oriented, that are operational around operational efficiency, ROI, paying for themselves. Reference architectures? Reference architectures, they help deliver on that. So it resonates with that traditional and minded shop. It also prepares them without being obviously disruptive. We're solving a problem around the data warehouse in this case. Let's solve that with an ROI based traditional approach and then start building a database, you know, a new set of data that we can do analytics on that are actually going to impact the business down the road. So you give them a straight and narrow roadmap. Yeah, that they're comfortable with. And you just incrementally move the ball down the field if you will through the reference architectures. And I think one of our challenges collecting me as a partnership is getting people to think outside of the current paradigm. You know, you no longer have to figure out what data you're going to collect, how you're going to structure, what you're going to use it for. Let's just start collecting the data. We'll figure out the secondary and tertiary value that down the road. Josh, talk about some of the success. We've got a couple of minutes left here. What's going on with SyncSort? Customers, product, obviously you guys have a great business model right now. You know, I'm a big fan. I always kind of like scratch my head saying, damn, you've got a great business model. And scratch mainframes and now an emerging software business which is great leverage for you guys. Yeah, so, you know, continuously great growth on the Hanoop side. The degree to which the big data phenomenon is infecting the opportunities we have on the mainframe is quite remarkable. So we just released IronStream in Q4. IronStream is a real time data forwarder for mainframe log data into Splunk. We are seeing terrific success there. Splunk users have used that platform to great success to manage their IT operations, manage security. One challenge they have was they did not have a good and easy way to get mainframe log data of which there is a lot into that platform. So we're kind of closing that gap, but that is an important step for us and then it sets up real time data flow off the mainframe into not just Splunk, but a variety of other environments including obviously DMXH on Hadoop. And so we're very excited about that. We've got a partnership with Cognizant called Big Frame that's focused on mainframe offload. I referenced that earlier. I am shocked at the uptake that we're seeing on that solution. It is terrific that the analysis that Cognizant's able to do on batch workloads on mainframe to identify the offloadable workloads is showing terrific results, 50, 60%. We did a recent POC at a customer. We took one of 200 jobs that we had deemed offloadable. We rewrote it, ran it in DMX, or DMXH on Hadoop. The elapsed time of the job went from 90 minutes to six minutes that MIPS, the CPU seconds on the mainframe went from 100 minutes to less than a minute. That job in and of itself saving over $100,000 moving into Hadoop. So that's a great opportunity for us and we're really excited about that. I think the last thing was cloud which we mentioned earlier. We're doing a lot in the tech to make sure that we have best-in-class connectivity with Redshift, with S3 to make it really easy for customers to leverage that platform. And then finally, we've introduced in release eight, which just came out in Q1, an intelligent execution capability that allows customer design once and then run that exact graph or that exact job, that data flow in on an edge node, on Linux, in the Hadoop cluster, in scale out fashion, in the cloud. And we think that's game-changing capability both because it gives customers flexibility but also future-proofs their environments. We're going to be able to let them choose what type of engine they want to use. In fact, we believe we can make the software choose the best engine as Hadoop continues to evolve and you have new execution engines. We should be able to use the data, the job characteristics to choose whether that should be MR or absolutely. So there's a lot of really interesting both tech and partnerships that we've been able to bring to market here the last couple of years and that'll continue. Awesome, well, guys, we're short of time. Thanks for coming on theCUBE. Quick sound bite to end the segment. I want to get both of your perspectives for the folks that aren't here, that are watching or might watch the reruns. What's going on at this show? I mean, there's a lot of weirdness going on here. There's always slowing down as the tide is our new wave coming in. Is it, it's not slowing in growth, that's for sure. I mean, packed house. So what's your take? Yeah, I'll give you a quick, I was staring at the board they have outside the exhibit hall here that shows the entire calendar for the day. And I was really taken aback at the number of sessions dedicated to managing multiple workloads on a cluster. And what that says to me is people are now not only taking advantage of the storage they've put on the floor, but they're starting to take advantage, real advantage of the compute and running mission critical workloads. And we believe that is going to be a, that is a real point of maturity in the market. And so I think you're going to see this start to really accelerate as people start to learn how to manage these environments and run mission critical workloads. Mike, what's your take on the show? Thing I'm seeing is over the years we used to see a lot more technology companies here and it was all technologists and engineers. Now you're seeing this shift dramatically to the enterprise customer who's trying to solve problems. So we're in the middle of that transition. It's like, you know, when you're, I grew up on the East coast, it's like, you can tell it's going to snow and you just smell in the air. I mean, here, the inflection point is literally, I think either the bubble is going to burst or that it'd be an inflection. But I think the bubble might burst in Silicon Valley on the consumer side, but enterprise side, a lot of great stuff here. So guys, thanks for the insight. Josh, appreciate it, Mike. It's theCUBE right back after this short break.