>>Winston Edmundson here at Hadoop summit. We've got Steve woolens from Teradata. He's going to talk to me a little bit about a exciting new announcement that you had with Hortonworks today. Tell me a little bit about that. >>Yeah. So Teradata has been in the data management analytics space for over 30 years. And with the announcement today, we announced data portfolio for Hadoop, which is a collection of products, services, and customer support for an entire portfolio for the products. So we've got turnkey appliances, we've got commodity offerings and with Hortonworks, we've got a shared customer support model, so we can give our customers everything they need around >>Ultimate support. Pretty exciting. Now this seems like it must've been a long process to put all this together. >>Well, we've had a partnership with Hortonworks for about a year. We've had Hadoop product offerings in the market for about six months. We've seen a lot of uptake from our customers, and it's really about broadening that to make sure that customers can buy a dupe standalone integrated in with the rest of their data architecture and make it a trusted component within that next generation data architecture. >>Tell me what excites you right now with the customers that you're helping, you're meeting their needs. Where do you see things going? What trends are you following right now? >>The big thing we're seeing is customers. Our customers want to better serve their customers. And there's so many new interaction points that they have with those customers through social networks, email, and being able to take things like the call center voice records, but that's been data that hasn't really been explored in the past to figure out how to better serve those customers. So now with Hadoop and other MapReduce technologies, we can incorporate that analysis into how we better serve our customers, customers at the end of the day. If that makes sense, that's ultimately, it's about getting deeper insights into how to better service the customers. And I think with all the new data that's out there and the hype around big data, that's really what it's about. >>Do you find the customers are coming to you with their own ideas or are they looking to you for suggestions on just how they can bring these different data sets together and how they can maximize and leverage some of this data? >>Well, the problem is there's so much hysteria in this market. I mean, it's an exciting place to be, but there's a lot of technologies, right? So I think the thing with Teradata is we do provide that trusted advisor status. I mean, we've been implementing data analytics solutions for a long, long time and a lot of the problems aren't new, they're just incorporating new analytics techniques. So they have ideas in terms of things they've heard about. They're not really sure how to implement it sometimes. So part of our offering is we have services, so we can look across their entire data architecture and figure out where does the dupe really fit? What are the best use cases for it? How do we integrate that across the enterprise? So the end users and the applications that can benefit from that data can really get the value from it. >>How important do you think it is or how much is an advantage that you are tried and true. You've been here. I mean, some of these solution providers, you can call them fly by night. I mean, they just, they're just here on, you know, they've just formed. They don't have a track record. It's your track record of success? One of the main things that customers are attracted to? >>I think so. I mean, the reality is we have, we're like in the trenches with our customers, it's not just the technology, but when we have business consulting, people that come in with domain expertise from a given industry, so you can call it a track record or whatever it is, but it's really understanding, not just technology, but the business and how these things come together to really get the most value from all the cool technology that's out there. So yeah, a lot of the fly by nighters, I mean, there's a lot of innovative things that are happening. And at duke five years ago, it was one of those very new things. And so we've been looking at it for a while and now we figured out the best way to incorporate it into our solution portfolio and to roll it out to customers >>When you're helping a customer. And you're, you're looking at the here and now, this is what they, they need to be addressing. I would imagine a lot of customers want to know what's around the corner, what's around the bend that we should be aware of, that we should try to be, be prepared for. What do you, what do you tell them? >>Well, I think, you know, everybody will say there's just more and more data coming at you. I think other analytic techniques like graph analysis is something that people particularly with social networks are trying to figure out how are people interrelated to each other. So it's a lot of different use cases and there's different analytic techniques that can be combined in unique ways. So a lot of our R and D investment is going into how do we bring more of those analytic techniques and unify them for people in one system. So that regardless of your data scientists or business analysts, you can ask really interesting, tough questions that you couldn't answer ask before. So it's about giving answers to sometimes the unknown questions and helping them explore that data through unique ways. >>What would you say are some of the industries that are maybe there's probably more urgency for them to adopt some of these strategies or perhaps just, they're more likely to have a big return on investment? What industries would you point to? >>I mean, for us, it's a lot of the traditional industries where you have a lot of consumers, right? Telecommunications, retail, retail, financial services, anybody who's working with. A lot of customers that have a lot of products, just have a lot of complexity, a lot of customer interaction touchpoints. So I think those are the people that typically we see adopting new technology and really thinking about how to better serve their customers >>For folks that are watching tuning in. And they're pretty excited about what you might be able to help them with. What's the best way for them to get in touch with you or, or >>You just go to teradata.com and check us out there. That's probably the best way to reach us. >>Right. Fantastic. Thanks for your time. Winston Edmondson here with studio B signing out.

live at hadoop summit this is SiliconANGLE and wiki bonds exclusive coverage of hadoop summit this is the cube our flagship program would go out the advanced extract the signal from the noise i'm to enjoy my co-host Jeff Kelly Jeff welcome to the cube Scott welcome to the cube great to have you here so you kicked off help kick off the show this morning with your keynote talking about a number of things among them the new teradata plans for Hadoop brought it on stage which I thought was great i love i love some i was joined by a dancing appliance okay great it was fantastic a good-looking appliance it was but why don't you tell us a little bit about yourself kind of your role and then we'll kind of get into what tara date is doing here at the show and some of the some of the strategies you're taking towards the big data market okay great well I'm Scott now I'm from tarde de labs and turny two labs is actually organization within teradata that is responsible for research development engineering product management product marketing all the products all of the technology that we roll out kind of the innovation engine of teradata is what we're responsible for and we've been obviously affiliated with hadoop summit we were here last year it's really great to be back having been in the in the data warehouse big data kind of data analytics business for a long time the one thing I have to say about this whole movement in the Hadoop space is that it's unlike anything else I've seen in that it's every geography it's every industry and there's so much energy and emotion around it's unlike any other transition that I've seen and even the difference between our visit here last year and this year where we've seen the the promise turned into reality where we've got customers who are implementing where we've got businesses who are driving value from the solutions that they're really that they're integrating with the solutions that they've already got and and being able to demonstrate that value really emphasizes the importance and I think will help to continue the momentum that we feel in this market Scott one of the things I want to ask you was obviously the theme at had dude was off loading data warehouses what they do is a benefit there but you have a relationship with Hortonworks and we've had we were talking early with Murph was an analyst at Gartner was talking about the the early adopters and the mainstream getting it now and but there's always a question of value right where's the value because his legacy involved right so the most of the web based companies are going to be cloud they'll be SAS they might have a Greenfield clean sheet of paper to work with on big data but an existing enterprise large financial institutions insurance company or what have you they have legacy technology and they have to but they want Hadoop they want to bring it in when you talk to folks out there what are some of the challenges and opportunities they have with that environment and the technology specifically sure that was like a long question there's a lot of a lot of threads in there I want to really try to hit on a couple of important themes because you know you hear it here I get asked a lot about it you know one of the things that people often say is you know this why are you here this whole Hadoop thing is offloading data warehouses isn't that bad doesn't that bother you and the answer is absolutely not certainly there's some hype around that and you know those some marketing around that but when you really look at the technology and the value of what it brings to the table it's a new technology that really allows us to harness new kinds of data and store those new kinds of data in the native format and you know storing detailed data in the native format really enables the best world-class analytics we've seen this happen for you know as long as my career is in the traditional data space so that's a really good thing the way I view it though is sure will some work load move around the infrastructure from the data warehouse to a Hadoop cluster potentially right and by the way if Hadoop is a great solution for it it should go there all right but at the same time there is more demand than there is supply of technology and what I mean by that is the demand for analytics is so extreme that actually adding this tool to the toolkit gives customers more choice and gives them the opportunity to really catch up with the backlog of things that they've wanted to invest in overtime and then the final point really I view what's happening here as perhaps one of the single largest opportunities for expansion of the role and size and scope of the data warehouse in an enterprise because one of the big things that Hadoop brings to the table is a whole lot of raw material a whole lot more data data that used to be thrown away data that never existed a year ago is now going to be able to capture be captured be stored be refined be analyzed and as companies start to find relationships as companies start to find actionable tidbits from the analytics in this huge source of raw material I think it's actually an opportunity for upside for them to integrate more data into their data warehouse where they can actually do the real-time interaction and streaming that's going to get them to the demonstrable business benefit so it's the modernization of the enterprise it's its modernization the way I look at it is also it's sometimes the word incremental can be it can sound like it we're trying to downplay it but I see it as incremental in that it's different data and it's incremental data it's incremental subject areas its new stuff that's going to come into the environment and based on what we've seen in the history of analytics right that there's no end to the value that companies find and there's no end to competition in their businesses so this is a huge opportunity for the entire community to deliver more analytics and i think that there's actually more upside for traditional legacy data warehouse vendors and there is anything I think that's a really important point because as you said a lot of people think about that offloading workloads but it's also about offloading we're close but bringing in new data doing more analytics and then moving some of that into back into the data warehouse you can actually create more value from it yeah I mean one of the things that I've seen is you know over time and Moore's law is something that's been going on for some time right and and cost erosion in Hardware has been going on for a long time and you think about the thing that you buy today for your bi implementation the hardware costs what twenty percent of what it costs three four years ago and you know what revenues continue to increase because they're such pent-up demand that as it gets less expensive it becomes more consumable and I think the same thing it's really going to continue to happen as we add in these new technologies and these new data types so one of the things I want to commend teradata for doing is focusing on kind of that reference protector and helping customers understand how this new technology of Hadoop and big data fits in with everything else that they're doing talk a little bit a bit about how from a reference architecture and then maybe even from a product perspective how teradata goes about turning this into a reality for enterprise customers who you know really you know they're not looking to just kick the tires of the Duke they want they want to use this for its really support you know applications and workflows they're really you know critical to their business yeah I think you know one of the biggest things that we can do to help the industry and to help our customers really is to define a realistic roadmap that's consumable for them in their enterprise and so while it's certainly easy to have marketing release or press release it says uh this new technology does everything in slices bread it washes your car does all these things in reality there are very few things like that in the world right but the new technologies and the new innovations really do fit into some very interesting new use cases and so by providing this integrated roadmap of how customers can deploy and fit these technologies together is a really great education process and it's been extremely well received by our customers and prospects I have to tell you that even in advance of the announcement of the things that we had here today we've already got customers who have gone down this path with us because it's such a compelling value proposition the other thing is that we don't actually put specific technology in those boxes it's a reference architecture we hope that there's some teradata product in there but at the same time we you know our customers understand that there is choice in the marketplace and the best solution is going to win and by providing this reference architecture I think we helped elevate ourselves to more of a trusted advisor status with with the the industry and in how we see these things fitting together and providing very effective very low-risk kinds of solutions well I think you hit on something that trusted advisor I think companies and enterprises are just crying out for some leadership and to help to help them really understand how they're going to make this a reality in their organizations and you know you mentioned kind of the openness and being you know allowing enterprises shoots a technology that fits that fits the the work case of course you know you hope that stared at in a lot of cases but it could be something else so talk a little bit about your relationship with hortonworks so I know you announced today kind of a reseller agreement you're going to be actually reselling the the subscription service to Hortonworks service offering talk about that a little bit and also I want to dive into the tech as well the Hadoop appliance I mentioned earlier like you announced and maybe just kind of walk us through some of the news to them sure so I mean obviously we have a strategic relationship with Hortonworks and it's our second year here at Summit and it really started with I think a very common view of what's happening in the marketplace and how these technologies should really play well together at the same time we also really believe that it's important that the community embrace the open source Apache version of the software so that it doesn't become fragmented and become obsolete right so Horton is spot-on in terms of business model and putting everything back into the Apache open source version so that means that I think this is the version that will win and this will be the version that companies can count on to be sustainable so i think that there's an advantage there implied so that's said i think it fits into the right place we've got a great engineering relationship and a great common vision on how the enterprise architecture and how the pieces can fit together and be optimized for different workloads for different service levels and for different applications so having that common vision and kind of I think bringing to Best of Breed providers together with Wharton works on the on the Hadoop side and teradata for what we're very well known for I think it's really the best of all worlds and we work together to lay out this reference architecture and so it's not just you know tur data came down from the mountain said this should be your reference architecture we've got some validation we got some validation of use cases and then we went to work from an engineering perspective on how we go build these things out and make them work and optimize them and support them end to end because obviously not only in you know with the all of the new solutions is their kind of a scarcity of talent and some confusion support becomes really really important so one of the things we added to our portfolio we announced today is an expanded relationship on the support side where customers can come to teradata for integrated support of all of their data analytics environments whether it be teradata whether it be asked her whether it be Hadoop with hdb and you know that's a really nice thing where there's one phone number to call we've got fully integrated processes we can help with a global footprint in the 80 countries where we do business and obviously Hortonworks with the with the extreme depth and ability to manage the content of the kernel can get it done unlike anyone else Scott we've been talking enterprise-grade all morning as you did those the theme of the keynote mer from our garden about security compliance I mean these are meat and potatoes enterprise issues right so I got to ask you what's what are you guys looking at what's what's coming next obviously the platform to do has a stabilized developers going to want to program on it in different environments but the reality in the enterprise is a certain requirement so what are you looking at in the labs that's coming around the corner that's it going to be really really important for customers to realize the value of scaling and harnessing the big data of Hadoop with the existing infrastructure yeah I mean I think there are two things that will continue to do one is will look to build out kind of that framework of ecosystem and in all of the keynotes this morning you know everyone talked about the value of the ecosystem and it's amazing the ecosystem how they're just more and more logos this year than there were last year and I think that that will continue but really building out that ecosystem so that those things that are important can be realized and they can be realized in a very repeatable fashion I think in addition to that kind of ease of use right because despite the fact that we have burgeoning numbers of newly minted data scientists and people getting into the marketplace that's really good there still aren't enough and so de-risking things by making them easier to deploy and easier to support i think is a key focus area and then you know finally I said two things but now third you know finally it will say to me I'd all right we'll continue to look at performance and just making sure that we have the best density the best performance the cost performance value proposition that our customers will want because I also continue to believe that the supply of data will outstrip any customers ability to invest in infrastructure I'd love to get your take on want to go back to mention to what you mentioned about the you know the Hadoop distribution focusing on a patchy and moving a patchy compatible so I take that number one to me and Tara day is not going to be coming out with their own Hadoop distribution absolutely not but how do you think about that yeah I think we can say that pretty definitively so but what about how do you see this whole Hadoop market playing out them you've got a Hortonworks Cloudera map are some others how do you see this playing out in the next year or so I mean is this you mentioned you think again that's kind of the open source of patchy versions going to kind of win when do you think that's going to happen you've got some competitors in the market and different business models hot yeah you know there are different business models and different innovators and you know my crystal ball is probably only about as clear as anyone elses but you know kind of for the long term I think it's best for the industry if if it mimics a model similar to the way Linux is deployed where this kind of a duopoly maybe three vendors it's very largely open source there's a lot of portability between I think that really strengthens the position of Hadoop as a tech as a core technology and foundation for some of the things that we're doing and so I would hope that in you know the most successful outcome would be that we'd end up with a duopoly or or you know maybe three kind of providers around a similar colonel because that would that would remove fragmentation from the market by the way I think it you know where we are software company so I think it's fair for companies to have value add proprietary software that's not a bad thing but at the file system level at a core two level I think the open source community cannot be out innovated right and and so I think that that's a really important thing so I think you know hopefully we'll get to that duopoly or maybe three companies that kind of have that I don't know if we will but I sure hope we do and I think the if I were to bet on it I would say it's odds on that that will be the case now will that be 18 months three years five years I don't know Scott thanks for coming inside the cube obviously you guys have a great position in the market place and the enterprise message is straw here that's what the demand is we're seeing a lot of trends out there that want the enterprise grade big data which is not just once there's but Hadoop's a big part of it Thanks coming inside the cube and sharing your perspective and what you got working on certainly having the new products come out to be great so thanks for coming onto the cube this is SiliconANGLE and wiki bonds coverage of hadoop summit we'll be right back with our next guest after this short break you

>>Ash it's, you know, what will that mean to my investment? And the announcement fusion IO is that, you know, we're 25 times faster on read intensive HBase applications. The combination. So as organizations are deploying Hadoop, and they're looking at technology changes coming down the pike, they can rest assured that they'll be able to take advantage of those in a much more aggressive fashion with map R than, than other distribution. >>Jack, how I got to ask you, we were talking last night at the Hadoop summit, kind of the kickoff party and, you know, everyone was there. All the top execs were there and all the developers, you know, we were in the queue. I think, I think that either Dave or myself coined the term, the big three of big data, you guys ROMs cloud Cloudera map R and Hortonworks, really at the, at the beginning of the key players early on and Charles from Cloudera was just recently on. And, and he's like, oh no, this, this enterprise grade stuff has been kicked around. It's been there from the beginning. You guys have been there from the beginning and Matt BARR has never, ever waffled on your, on your messaging. You've always been very clear. Hey, we're going to take a dupe open source a dupe and turn it into an enterprise grade product. Right. So that's clear, right? That's, that's, that's a great, that's a great, so what's your take on this because now enterprise grade is kind of there, I guess, the buzz around getting the, like the folks that have crossed the chasm implemented. So what can you comment on that about one enterprise grade, the reality of it, certainly from your perspective, you haven't been any but others. And then those folks that are now rolling it out for the first time, what can you share with them around? What does it mean to be enterprise grade? >>So enterprise grade is more about the customer experience than, than a marketing claim. And, you know, by enterprise grade, what we're talking about are some of the capabilities and features that they've grown to expect in their, their other enterprise applications. So, you know, the ability to meet full S SLA is full ha recovery from multiple failures, rolling upgrades, data protection was consistent snapshots business continuity with mirroring the ability to share a cluster across multiple groups and have, you know, volumes. I mean, there's a, there's a host of features that fall under the umbrella enterprise grade. And when you move from no support for any of those features to support to a few of them, I don't think that's going to, to ha it's more like moving to low availability. And, and there's just a lot of differences in terms of when we say enterprise grade with those features mean versus w what we view as kind of an incomplete story. So >>What do you, what do you mean by low availability? Well, I mean, it's tongue in cheek. It's nice. It's a good term. It's really saying, you know, just available when you sometimes is that what you mean? Is this not true availability? I mean, availability is 99.9%. Right? >>Right. So if you've got a, an ha solution that can't recover from multiple failures, that's downtime. If you've got an HBase application that's running online and you have data that goes down and it takes 10 to 30 minutes to have the region servers recover it from another place in the distribution, that's downtime. If you have snapshots that aren't consistent across the cluster, that doesn't provide data protection, there's no point in time recovery for, for a cluster. So, you know, there's a lot of details underneath that, but what it, what it amounts to is, do you have interruptions? Do you have downtime? Do you have the potential for losing data? And our answer is you need a series of features that are hardened and proven to deliver that. >>What about recoverability? You mentioned that you guys have done a lot of work in that area with snapshotting, that's kind of being kicked around, are our folks addressing, what are the comp what's your competition doing in those areas of recoverability just mentioned availability. Okay, got that. Recoverability security, compliance, and usability. Those are the areas that seem to be the hot focus areas what's going on in the energy. How would you give them the grade, the letter grade, if you will, candidly, compared to what you guys offer? Well, the, >>The first of all, it's take recoverability. You know, one of the tenants is you have a point in time recovery, the ability to restore to a previous point that's consistent across the cluster. And right now there's, there's no point in time recovery for, for HDFS, for the files. And there's no point in time recovery for HBase tables. So there's snapshot support. It's being talked about in the open source community with respect to snapshots, but it's being referred to in the JIRAs as fuzzy snapshots and really compared to copy table. >>So, Jack, I want to turn the conversation to the, kind of the topic we've talked about before kind of the open versus a proprietary that, that whole debate we've, we've, we've heard about that. We talked about that before here on the cube. So just kind of reiterate for us your take. I mean, we, we hear perhaps because of the show we're at, there's a lot of talk about the open source nature of Hadoop and some of the purists, as you might call them are saying, it's gotta be open a hundred percent Patrick compatible, et cetera. And then there's others that are taking a different approach, explain your approach and why you think that's the key way to make, to really spur adoption of a dupe and make it >>W w we're we're a part of the community we're, we've got, you know, commitment going on. We've, you know, pioneered and pushed a patchy drill, but we have done innovations as well. And I think that those innovations are really required to support and extend the, the whole ecosystem. So canonical distributes RN, three D distribution. We've got, you know, all our, our packages are, are available on get hub and, and open source. So it's not, it's not a binary debate. And I think the, the point being that there's companies that have jumped ahead and now that Peloton is, is, you know, pedaling faster and, and we'll, we'll catch up. We'll streamline. I think the difference is we rearchitected. So we're basically in a race car and, you know, are, are racing ahead with, with enterprise grade features that are required. And there's a lot of work that still needs to be done, needs to be accomplished before that full rearchitecture is, is in place. >>Well, I mean, I think for me, the proof is really in the pudding when you, when it comes to talk about customers that are doing real things and real production, grade mission, critical applications that they're running. And to me that shows the successor or relative success of a given approach. So I know you guys are working with companies like ancestry.com, live nation and Quicken loans. Maybe you could, could you walk us through a couple of those scenarios? Let's take ancestry.com. Obviously they've got a huge amount of data based on the kind of geological information, where do you guys do >>With them? Yeah, so they've got, I mean, they've got the world's largest family genealogy services available on the web. So there's a massive amount of data that they make accessible and, and, you know, ability for, for analysis. And then they've rolled out new features and new applications. One of which is to ship a kit out, have people spit in a tube, returned back and they do DNA matching and reveal additional details. So really some really fabulous leading edge things that are being done with, with the use of, of Hadoop. >>Interesting. So talk about when you went to, to work with them, what were some of their key requirements? Was it around, it was more around the enterprise enterprise, grade security and uptime kind of equation, or was it more around some of the analytics? What, what, what's the kind of the killer use case for them? >>It's kind of, you know, it's, it's hard with a specific company or even, you know, to generalize across companies. Cause they're really three main areas in terms of ease of use and administration dependability, which includes the full ha and then, and then performance. And in some cases, it's, it's just one of those that kind of drives it. And it's used to justify, in other cases, it's kind of a collection. The ease of use is being able to use a cluster, not only as Hadoop, but to access it and treat it like enterprise storage. So it's a complete POSIX compliance file system underneath that allows the, the mounting and access and updates and using it in dynamic read-write. So what that means from an application level, it's, it's faster, it's much easier to administer and it's much easier and reliable for developers to, to utilize. >>I got to ask you about the marketing question cause I see, you know, map our, you guys have done a good job of marketing. Certainly we want to be thankful to you guys is supporting the cube in the past and you guys have been great supporters of our mission, but now the ecosystem's evolving a lot more competition. Claudia mentioned those eight companies they're tracking in quote Hadoop, and certainly Jeff and I, and, and SiliconANGLE by look at there's a lot more because Hadoop washing has been going on now for the term Hadoop watching me and jumping in and doing Hadoop, slapping that onto an existing solution. It's not been happening full, full, full bore for a year. At least what's the next for you guys to break above the noise? Obviously the communities are very active projects are coming online. You guys have your mission in the enterprise. What's the strategy for you guys going forward is more of the same and anything new even share. >>Yeah, I, I, I think as far as breaking above the noise, it will be our customers, their success and their use cases that really put the spotlight on what the differences are in terms of, of, you know, using a big data platform. And I think what, what companies will start to realize is I'd rather analogy between supply chain and the big, the big revolution in supply chain was focusing on inventory at each stage in the supply chain. And how do you reduce that inventory level and how do you speed the, the flow of goods and the agility of a company for competitive advantage. And I think we're going to view data the same way. So companies instead of raw data that they're copying and moving across different silos, if they're able to process data in place and send small results sets, they're going to be faster, more agile and more competitive. >>And that puts the spotlight on what data platform is out there that can support a broad set of applications and it can have the broadest set of functionality. So, you know, what we're delivering is a mission grade, you know, enterprise grade mission, critical support platform that supports MapReduce and does that high performance provides NFS POSIX access. So you can use it like a file system integrates, you know, enterprise grade, no SQL applications. So now you can do, you know, high-speed consistent performance, real time operations in addition to batch streaming, integrated search, et cetera. So it's, it's really exciting to provide that platform and have organizations transform what they're doing. >>How's the feedback on with Ted Dunning? I haven't seen a lot of buzz on the Twittersphere is getting positive feedback here. He's a, a tech athlete. He's a guru, he's an expert. He's got his hands in all the pies. He's a scientist type. What's he up to? What's his, what's his role within Mapa and he's obviously playing in the open-source community. What's he up to these days, >>Chief application architect, he's on the leading edge of my house. So machine learning, so, you know, sharing insights there, he was speaking at the storm meetup two nights ago and sharing how you can integrate long running batch, predictive analytics with real-time streaming and how the use of snapshots really that, that easy and possible. He travels the world and is helping organizations understand how they can take some very complex, long running processes and really simplify and shorten those >>Chance to meet him in New York city had last had duke world at a, at a, a party and great guy, fantastic geek, and certainly is doing a great work and shout out to Ted. Congratulations, continue up that support. How's everyone else doing? How's John and Treevis doing how's the team at map are we're pedaling as best as you can growing >>Really quickly. No, we're just shifting gears. Would it be on pedaling >>Engine? >>Yeah. Give us an update on the company in terms of how the growth and kind of where you guys are moving that. >>Yeah. We're, we're expanding worldwide, you know, just this, you know, last few months we've opened up offices and in London and Munich and Paris, we're expanding in Asia, Japan and Korea. So w our, our sales and services and engineering, and basically across the whole company continues to expand rapidly. Some really great, interesting partnerships and, and a lot of growth Natalie's we add customers, but it's, it's nice to see customers that continue to really grow their use of map are within their organization, both in terms of amount of data that they're analyzing and the number of applications that they're bringing to bear on the platform. >>Well, that a little bit, because I think, you know, one of the, one of the trends we do see is when a company brings in big data, big data platform, and they might start experiment experimenting with it, build an application. And then maybe in the, maybe in the marketing department, then the sales guys see it and they say, well, maybe we can do something with that. How is that typically the kind of the experience you're seeing and how do you support companies that want to start expanding beyond those initial use cases to support other departments, potentially even other physical locations around the world? How do you, how do you kind of, >>That's been the beauty of that is if you have a platform that can support those new applications. So if you know, mission critical workloads are not an issue, if you support volumes so that you can logically separate makes it much easier, which we have. So one of our customers Zions bank, they brought in Matt BARR to do fraud detection. And pretty soon the fact that they were able to collect all of that data, they had other departments coming to them and saying, Hey, we'd like to use that to do analysis on because we're not getting that data from our existing system. >>Yeah. They come in and you're sitting on a goldmine, there are use cases. And you also mentioned kind of, as you're expanding internationally, what's your take on the international market for big data to do specifically is, is the U S kind of a leaps and bounds ahead of the rest of the world in terms of adoption of the technology. What are you seeing out there in terms of where, where the rest of the, >>I wouldn't say leaps and bounds, and I think internationally, they're able to maybe skip some of the experimental steps. So we're seeing, we're seeing deployment of class financial services and telecom, and it's, it's fairly broad recruit technologies there. The largest provider of recruiting services, indeed.com is one of their subsidiaries they're doing a lot with, with Hadoop and map are specifically, so it's, it's, it's been, it's been expanding rapidly. Fantastic. >>I also, you know, when you think about Europe, what's going on with Google and some of the, the privacy concerns even here, or I should say, is there, are there different regulatory environments you've got to navigate when you're talking about data and how you use data when you're starting to expand to other, other locales? >>Yeah. There's typically by vertical, there's different, different requirements, HIPAA and healthcare, and basal to, and financial services. And so all of those, and it, it, it basically, it's the same theme of when you're bringing Hadoop into an organization and into a data center, the same sorts of concerns and requirements and privacy that you're applying in other areas will be applied on Hindu. >>I'm now kind of turning back to the technology. You mentioned Apache drill. I'd love to get an update on kind of where, where that stands. You know, it's put, then put that into context for people. We hear a lot about the SQL and Hadoop question here, where does drill fit into that, into that equation? >>Well, the, the, you know, there's a lot of different approaches to provide SQL access. A lot of that is driven by how do you, how do you leverage some of the talent and organization that, you know, speak SQL? So there's developments with respect to hive, you know, there's other projects out there. Apache drill is an open source project, getting a lot of community involvement. And the design center there is pretty interesting. It started from the beginning as an open source project. And two main differences. One was in looking at supporting SQL it's, let's do full ANSI SQL. So it's full 2003 ANSI, sequel, not a SQL like, and that'll support the greatest number of applications and, you know, avoid a lot of support and, and issues. And the second design center is let's support a broad set of data sources. So nested sources like Jason scheme on discovery, and basically fitting it into an enterprise environment, which sometimes is kinda messy and can get messy as acquisitions happen, et cetera. So it's complimentary, it's about, you know, enabling interactive, low latency queries. >>Jack, I want to give you the final word. We are out of time. Thanks for coming on the cube. Really preached. Great to see you again, keep alumni, but final word. And we'll end the segment here on the cube is your quick thoughts on what's happening here at Hadoop world. What is this show about? Share with the audience? What's the vibe, the summary quick soundbite on Hadoop. >>I think I'll go back to how we started. It's not, if you used to do putz, how you use to do and, you know, look at not only the first application, but what it's going to look like in multiple applications and pay attention to what enterprise grade means. >>Okay. They were secure. We got a more coverage coming, Jack Norris with map R I'll say one of the big three original, big three, still on the, on the list in our mind, and the market's mind with a unique approach to Hadoop and the mid-June great. This is the cube I'm Jennifer with Jeff Kelly. We'll be right back after this short break, >>Let's settle the PR program out there and fighting gap tech news right there. Plenty of the attack was that providing a new gadget. Let's talk about the latest game name, but just the.

>>Come back here. This is Silicon Valley coverage of ADU Summit. I'm John Fur, the founder. We're, we're pleased to have a friend inside the cube. It's rare to have such luminaries, Ama Aala, good friend and also co-founder of Cloudera. Really the pioneer in the space that helped build this industry that we're living here at at Hadoop Summit. I'm with Dave Ante from wiba.org. Amour, welcome back to the Cube Cub alumni. Thank you for having me here. Wow, what a journey. Are you co-founded Cloudera? I remember when you in Stealth Mo, I really can't talk about it. And, and then of course the history of Silicon Angle being, you know, founded and kind of built in in your office when you only had like 20 something employees. Yep. We owe a great deal of gratitude to you and, and congratulations to you Michael Olson, the team for building an industry. So I just wanted Thank you. Thank you. And welcome to the Cube. >>Thank you. It was great to be here. >>So what do you think, what's your take on the current Hadoop ecosystem right now? I mean, obviously a lot's happened. I mean it's big now. It's growing up fast. Yeah. The word enterprise grade is out there. You're seeing it move from, you know, trying to change the world. Our first interview, you said, I've seen the future, I want to bring it to the mainstream. It's here. Yeah. It's hitting mainstream right now. Yeah. What's your take of the current situation of the ecosystem and it's, and its value? >>Yeah, so I, I have a quick question first. Should I look to you or look to the camera? Look to >>The camera or both? Whatever you, whatever you'd like. >>So I think it's, the ecosystem is definitely growing, which is very, very healthy. However, there is a side question there, which is what do you think of all the competition coming into the space? So five years ago when Cloudera was started was just Cloudera. There was no other commercial vendor trying to support or enable Hadoop in the, in the industry for enterprises. And today there is at least 10 of them trying to compete with us, right? And that includes big companies, established companies that decided, hey, we gonna start addressing the space, but includes many, many newcomers who like Hortonworks, who were founded over the last couple of years. That's a healthy thing. I mean, that's absolutely a sign of a growing market. If the market wasn't growing, if there wasn't money in the market, if there wasn't, if it was just hype, there wouldn't have been all of these new companies and new ventures showing up. That said, I never look at competition as something that worries me, that I'm afraid now or what's gonna happen to me, or that's normal. That's exactly what happens to successful companies. If you look at Red Hat, when Red Hat was launching with the Linux, they had 25 competitors or even more 30 competitors. That's when Red Hat was forming out. And today, even of these 25, 30 competitors, they still have six or seven still left. So I think it's a very, very healthy sign of the graph of this market and the maturity that's reaching. >>What do you think about some of the, the white spaces that are evolving? You guys have obviously been involved in a lot of deployments at Cloudera. Again, you're doing a lot of, lot of work with the top, top names and the clients that you have aren't usually disclosed cuz you really can't disclose them. What, what are you seeing right now as the white spaces for things to do in the Hado platform? >>It's a very, very good question. So first I can't talk about future, future roadmap. Right now we're becoming a big company at that level where we can't comment on future roadmaps. >>Ah, that's sinus sign of the >>Time. You're well media train, good to see they're doing a good job keeping you >>A, You want more information on that? I can connect you with a pt, >>Please. No, no, no, we're good. We're good. We'll get it outta you. But, >>But our vision, our vision for Cloudera from day one, like you were saying earlier, we saw the future, right? So our vision from from day one was really to build this data system where we can have detail of any type, whether that data is structured or unstructured or images, it doesn't matter. And then on top of that data run any type of workloads. That workload could be the initial genesis of Hado, which is map use, which is batch processing. But now as as we made many announcements through the last few years, we also now have Impala for interactive analytics as a workload. We have a very, very strong partner partnership with SaaS for doing machine learning and statistics as a workload. And a few weeks ago we announced search as another workload. So you have multiple types of workloads that can handle different types of problems that you have within your organization and bring all of these workloads to all of your data regardless of type. And that's the vision that we'll continue to deliver on. That's exactly what we're building going into the >>Future. So how's that fit in with yarn, right? We're hearing a lot at this conference about yarn, the ability to, you know, do more with less in a lot of the things that you typically hear with the enter within the enterprise. And, and so talk about that a little bit. >>Yarn is a very core part to our platform. In fact, yarn has been part of CDH four for more than a year now out in the, in the markets. So we did bring, we were one of the, I think we were the first vendor who brought yarn into a distribution of Hado out there. It's very, very fundamental to us because that is how we're gonna coordinate. We are gonna be using yarn to coordinate launching all of these different type of workloads. You're gonna have the map produce workload, which is very batch oriented. The Impala workload, which is very latency sensitive. The, the search workload, which is also very latency sensitive. The machine learning workload, which is more batch oriented, et cetera, et cetera. And yarn is a very, very central piece to helping us coordinate all of these different types of workloads onto the >>Platform. Cloudera has been a great citizen in the community also. You, you mentioned and, and we witnessed that your team create the industry. You guys were there, you took the chance, you were the first ones commercially funded by the venture capitalists, you know, then others will follow and I'll see huge ecosystem here. Yes. A lot of noise. A lot of people trying to get attention. So I got to ask you, because I want you to address this because I know it's been talked about in some of the other blogs is there's a lot of fud going on around who's doing what? Who's doing what, and in some cases maybe flat out, you know, misinformation and that happens in a growing market, you know, the elbows get sharp. Yes. So I want you share with the audience anything that you want say about the fud around what people say about Cloudera or about others or what you're doing. Just to clarify, cuz there has been, I mean I've gotten back channel information around, you know, not sure the committers this, and it's been, it's been well documented. There's a lot of fu out there. What, what would you say to the folks out there to clarify >>That? Yes, I, I would say that our focus should be to continue to work as a community, to push the platform forwards. I would say that at Cloudera we do a lot of contributions. Horton works definitely is one of the top contributors out there as well. I'll acknowledge that. So as many, many, many other companies and we wanna continue to see the platform evolve. I will stress though that at Cloudera we do have a number of the original project founders working at the company. So it's not just the, the contribution that we bring, but the fact that we have the founders of these projects working at Cloudera. And some of these projects actually were created at Cloudera from day one as opposed to created in some other company. And then you hire the employee and they work for you. So I gave you what examples from Cloudera dot cutting. >>He is the creator of Hudu dot Cutting is also the creator of Luine, which became solar, which is part of the search project that we launched recently. Dot Cutting wasn't with Cloudera from day one, right? So, so when he created these technologies, he actually was at Tia for example, when he created had he was at ta, wasn't at Cloudera. However, he now works for Cloudera. So we get that because now that cutting works for Cloudera. So that's one example. On the flip side, there is projects like Flume and Scoop that are now part of every single distribution out there. And flu and Scoop were both created at Calera. They were actually created inside of Cloudera. Yeah. So the key point is, and and that's what I would like all of the vendors out there that are trying to leverage had and get benefit about out Hadoop is please don't be just takers. >>There are some vendors out there who are just takers. Just wanna take from the open source, take from the open source and don't give back. Right? I'm not gonna name them, but there is a few of them out there. Please, please, please. I mean that that, that is very, very a selfish behavior. It's not gonna help the ecosystem in the long term. We would like to see you both take and give at the same time. So that would be my core message. And that's for example, like I thank Hortonworks because that's exactly what Hortonworks is doing. They're both giving and taking at the same >>Time. You guys have always been clear on that. Nobody, I mean here contribution to open source has been well documented and there's, there's no question about that. John and I have talked about it a lot that you guys help get it all started. And even Haak when we had 'em on a couple years ago, when Horton Works came to the market said, Hey, the more people work on an open source, the better. >>Yeah, >>Exactly. So yeah, it's always been, been your posture. You're not playing games there. Anyways, having said that, you you, you have a strategy to layer on top of that open source some of your own proprietary code. And so you have choices to make Yes. In terms of how you allocate those resources. So as an engineering manager, how do you allocate those resources in terms of, okay, what do we do for the community and what do we do for our own, you know, future because of the business model that we chose? How do you make those trade offs? >>Yes, that's a very, very good question. So first it's important to stress that our core platform, CDH, is open source. Everything we put in the core platform is open source. So for example, in Palo, which we launched very recently as a ga, now we launched beta last year, but now's ga is a hundred percent Apache license, a hundred percent open source search, which we announced very recently is also open source. So the platform itself, we're committing to everything in there to be open source. Now we believe fundamentally just from having lots of history in studying the open source markets from our ceo Mike Olson himself being one of the very first open source people in the world with, with sleepy cats, the company that he sold to Oracle before founding Cloudera from our investors, helping many other open source companies. To have a successful open co open source company, you need to have a very good engine between the business model that generates revenue and between the product that you are creating. If you don't have a good feedback loop there between these two, you won't be able to sustain the innovation to continue to push the, the boundaries of how good the product is. So we strongly believe in that if you are, if your product is literally a hundred percent open source, meaning both the management and every, there is nothing proprietary whatsoever inside of your products. I can't tell what that is. It's >>Taking a picture. >>Oh, sorry, I thought somebody was waiting >>For me. >>Sorry about that. >>It's a cheap signal. >>It >>Was like a's really good. >>I thought it's like a card of paper with some writing. You, >>You, you have a fan fans out there. They're storming the, the concert here. >>Okay, that's, that's good to hear. That's good to hear. Sorry about that interruption. So if, if, if you have everything a hundred percent open source, that creates two problems. First you have no differentiation whatsoever, meaning another big corporation without naming who the big corporations could be, we just can take everything you do, literally every single bit of source code you have and say, Hey, we can do it too. Come to us, don't work with those guys. Right? We have the latest, greatest things that they have. Why do you wanna continue to work with them? So no, no differentiation is number one, which is very dangerous. And number two, when it becomes, if, if it's a hundred percent open source and there is lots of other vendors able to take the art, the open source artifact and work with it, then it becomes now purely about maintenance and insurance on the products, which is a commodity product, which obviously the prices for that will go down to the ground and you won't be able to have this sustain this positive feedback effect between your business model and between your product code map and won't be able to build a long-lasting company. >>So that's why we do have a combination of open source artifacts and proprietary artifacts. Now our pro proprietary AR artifacts is always around the management of the system, right? So how do we manage the security of the system? How do we manage the, the data flow within the system? How do we manage the services inside the, of the system across all layers, right? Not just the Hado player but the edge based layer, the zookeeper layer, et cetera, et cetera. So that's where we focus our efforts going forward and that's how we differentiate ourself from our, from other vendors out there. Cloudera manager, Cloudera navigator are very unique to us. Nobody else has anything close to those capabilities out there. >>So it sounds like the contributions you make to open source are cultural of, of, in nature, I mean DNA of sorts of Right. And so you're, that's something that you guys do cuz you've always done it. Absolutely. And then the, the artifacts that are proprietary are essentially around rationalizing the revenue opportunity with the expense that you're gonna apply there and making a business case decided >>How to balance. That's that's one. And then two, the differentiation from other competitors. So these two things, Yes. >>Okay. >>I believe that's fundamental to business to open source business models. >>Yeah, I mean there are many open source business models, right? You can go pure service, you can go, like you said, you can totally bogart the code. >>There is no, there is no pure service open source model company that was able to build the longlasting surviving public company, never happened in history. They always get acquired because it becomes a commodity. I >>Mean, right. I mean, I mean and even ibm, right? >>Tom or I want to ask you about the storage thing. We were talking before camera, the, the hor and worst announcement storage you, what's your take on that? >>Which one? The Gluster, the one with Red Hats? Yes. Yes. So Red Hats and yeah, there has been recent news about Red Hat with, with Hor Works having a version of the Haddo platform that uses map use for the computation but uses Red Hat for the storage, right? So Red Hat has a new storage offering that was built based off of a company they acquired was called Guster. And that, that news was very, very surprising to me. And it, the reason why it was surprising, it's correlated also with a shift in messaging from, from Horton works. If you look at Horton Works last year at had Summit last year, one of the key messages that they deliver to us is that within the next five years or by 2015, the tagline back then by 2015, and you're doing research right now to see if I'm saying the right thing. By 2015, half the world data data will be on, will be stored in had would be stored in had. Yes. If you look today at the slides, it >>Doesn't say that it says within five years, >>Right? No, no, no. It says, well >>That was the second iteration was within five years. And now they say something >>Different. Now say they say within 2015 by, sorry, by 2015, half the world's data will be processed by Hado and instead of stored by Hado. And that's a very, very fundamental So >>It's a nuance. >>It's a, it's a very important >>Nuance. Well it's a big deal because yes, when I first saw that I said, Hmm, what does this all mean? And then it sounds 2015 sounds a little early. Yes. And now you're saying processed by, Okay that's different. >>Yes, exactly. And and the reason why now is we believe s GFS is very, very core to the had platform. S GFS is very core to had platform, the storage system of had we want. It's really the layer that Mid had with is more than anything else is how scalable, how reliable and how economical the sdfs storage layer is. So we, we really, I mean ask qu works and ask all the companies working in the, in the had community not to fragment at the storage layer. We need the storage for had to stay inside of had and not to fragment that out. That's very, very critical. >>Okay. So but so >>You're saying that they're in indicating through the gesture that, that they're not come out saying we're going to fragment Hgfs, but the way that this is position might signal >>No, no, no. The announcement, the announcement with Red Hat is >>That is the direct signal. It's >>Literally, we, you'll be able to run map produce directly on top of Red Hat storage instead of sdfs. >>Okay. So >>I >>Interpreted it, I interpret it as they were just hortonwork was hedging on its prediction, which I said Okay, I'll give 'em a break on that. You're saying it's something different, >>It's a shift in strategy potentially. Yeah. Which can be dangerous. It's shift in strategy. >>Is that a compliance issue? Cuz you know, the, the Dishon Hads poss Yeah. Red Hat does have a lot of enterprise customers. Yeah. So is that just maybe if >>Then invest in making had poss compliance, which actually by the way, we are as a community investing in that. Yeah. Yes. You must have. Yeah. So we are investing in adding compulsive poss compliance to had, we're investing in adding snapshots into had, which will be coming very, very soon overnight. >>Well, do you think that that pick a year, I don't care if it's 2015 2000, 22,000 whenever that the majority of the world's data will be running into do >>The majority of worse data that has to do with analytics. Yes. Okay. So so there is, >>So that is that >>Is it's very important, the caveat. Yes, exactly. Because there is lots of types of data that are not very suitable for, had at all. For example, that data storage for Oracle systems, for Oracle database systems. No, you wanna store that in an NetApp emc you don't wanna store that in Hao the, the, the, the, the data storage for streaming video files, right? For just streaming lots and lots of video files. No, you don't wanna store that indu. It's >>A huge >>Proportion of the data. Yeah. Which is a huge, huge >>Proportion of data files, in fact that could overwhelm the data. >>Yeah. So the new nuance, like I would say like I agree that the half thing but the half thing within the world of data for the purpose of analysis. >>Yeah. Okay. So that's, that's >>Narrow down the >>Yeah, okay. But it's a more reasonable, But I've, I >>Never, It's still a huge market by the way. It is. Yeah, >>It is. Yes. Okay. So, so what's next for you? A are you, you, you've gone on this, this journey, you start this company. You've, you've been traveling around like crazy working with customers. What's the next phase of aara do's, you know, career? >>What >>Do you want to have happen next? I mean, what, what do you, what excites you? What do you, what are you working on? >>Yeah, it's just to continue to grow cloud there to be the biggest company it can be. I mean, we want to be literally, we want be one of the very few companies that we're able to take an open source model and turn that into a large publicly traded corporation. >>So you've talked about that you guys brought a new CEO on Right. Look at the background of the ceo and it's, you know, clearly it's got some IPO chops. Yes. So that's, that's an aspiration that you guys have put forth. Okay. >>And you're outward facing now. So you're doing a lot of travel. Yes. So what, what, where have, what have your travels taken now? You've been in China, you obviously you've got a European office Yeah. Open. So what's going on internationally? Give us some sound bites of, of what's happening in the field. Yeah, >>So in, in internationally, I mean, Europe definitely is our next big focus right now. And we now have a big operation in Europe and we have an office presence in, in Europe and a big team down there. And it's growing very quickly. I would say Europe is about two years behind the US kind of like that's how the, how the growth usually matters. What's happening here. And yeah, so we, our, our next big market is Europe. We are looking at China. We don't have a big process in China right now. Japan, we have a big presence in Japan. Japan is growing very quickly. So yeah, I mean we're obviously Canada with the US growing very quickly as well. >>Great to have you on the cube again, for me personally and, and for, for Dave. And I wanna say thanks to Cloudera for some great support over the years. You guys have been fantastic. You know, I say it's built a great company. It's so hard to build a company. You guys have done a great job. I gotta ask you the final question because you did bring that first sound bite, which was, I saw the future, this is back when you guys were just in your B round in, in Palo Alto office, just ramping up, just starting to ramp what's next? What do you see as around the corner? Obviously we're on a trajectory right now. A lot of things gonna get done. Positive compliance, a lot of stuff's gonna fill in. The platform's gonna get stronger. Yeah. We think that open source will win. Yeah. Through all the democratization of open source. What's next? What's the, what's around the corner that you're watching personally that you're, that's interesting to you? A or around where this will take us? >>Yeah. So what, what's next is having this, having this vision become true. Having this future vision that, that you refer to become true. Meaning having a single platform that can store all of your data and that can, regardless of the type of that data, and allow you to extract value for different types of workloads, whether that be batch, interactive machine learning or search or more, right? There will be more things that will come to the platform, but how to bring your applications, all of your data applications, how to bring them to your data and all of your data as opposed to have the data go to them. >>And what are the landmines out there that you need to avoid Yes. In the industry and community needs to avoid to make that a reality. >>The, the key landmine, it's, it's a bit technical. The landmine is a bit technical, which is making sure that they, they are vision continues to evolve and that we have the capability to properly have a multi workload resource management system that allows me to run all of these type of workloads without having them step on each other's steps. That's the key key step going forward. And >>Of course, playing well together in the sandbox. And as always, competitive competition is good. And again, Hadup is doing great. Amma Aala, co-founder of Cloudera inside the Cube. This is Silicon Angle and Wiki Bond's exclusive coverage of ADU Summit here in Silicon Valley. Right back with our next guest after the short break.