>> Live from New York, it's The Cube, covering The Cube New York City 2018 brought to you by SiliconAngle Media and its Ecosystem partners. >> Okay, welcome back everyone, here live in New York City for Cube NYC, formally Big Data NYC, now called CubeNYC. The topic has moved beyond big data. It's about cloud, it's about data, it's also about potentially blockchain in the future. I'm John Furrier, Dave Vellante. We're happy to have a special guest here, Arun Murthy. He's the cofounder and chief product officer of Hortonworks, been in the Ecosystem from the beginning, at Yahoo, already been on the Cube many times, but great to see you, thanks for coming in, >> My pleasure, >> appreciate it. >> thanks for having me. >> Super smart to have you on here, because a lot of people have been squinting through the noise of the market place. You guys have been now for a few years on this data plan idea, so you guys have actually launched Hadoop with Cloudera, they were first. You came after, Yahoo became second, two big players. Evolved it quickly, you guys saw early on that this is bigger than Hadoop. And now, all the conversations on what you guys have been talking about three years ago. Give us the update, what's the product update? How is the hybrids a big part of that, what's the story? >> We started off being the Hadoop company, and Rob, our CEO who was here on Cube, a couple of hours ago, he calls it sort of the phase one of the company, where it were Hadoop company. Very quickly realized we had to help enterprises manage the entire life cycle data, all the way from the edge to the data center, to the cloud, and between, right. So which is why we did acquisition of YARN, we've been talking about it, which kind of became the basis of our Hot marks Data flow product. And then as we went through the phase of that journey it was quickly obvious to us that enterprises had to manage data and applications in a hybrid manner right which is both on prem And public load and increasingly Edge, which is really very we spend a lot of time these days With IOT and everything from autonomous cars to video monitoring to all these aspects coming in. Which is why we wanted to get to the data plan architecture it allows to get you to a consistent security governance model. There's a lot of, I'll call it a lot of, a lot of fight about Cloud being insecure and so on, I don't think there's anything inherently insecure about the Cloud. The issue that we see is lack of skills and our enterprises know how to manage the data on-prem they know how to do LDAP, groups, and curb rows, and AAD, and what have you, they just don't have the skill sets yet to be able to do it on the public load, which leads to mistakes occasionally. >> Um-hm. >> And Data breaches and so on. So we recognize really early that part of data plan was to get that consistent security in governance models, so you don't have to worry about how you set up IMRL's on Amazon versus LDAP on-prem versus something else on Google. >> It's operating consistency. >> It's operating, exactly. I've talked about this in the past. So getting that Data plan was that journey, and this week at Charlotte work week we announced was we wanted to take that step further we've been able to kind of allow enterprise to manage this hybrid architecture on prem, multiple public loads. >> And the Edge. >> In a connected manner, the issue we saw early on and it's something we've been working on for a long while. Is that we've been able to connect the architectures Hadoop when it started it was more of an on premise architecture right, and I was there in 2005, 2006 when it started, Hadoop's started was bought on the world wide web we had a gigabyte of ethernet and I was up to the rack. From the rack on we had only eight gigs up to the rack so if you have a 2000 or cluster your dealing with eight gigs of connection. >> Bottleneck >> Huge bottleneck, fast forward today, you have at least ten if not one hundred gigabits. Moving to one hundred to a terabyte architecture, for that standpoint, and then what's happening is everything in that world, if you had the opportunity to read things on the assumptions we have in Hadoop. And then the good news is that when Cloud came along Cloud already had decoupled storage and architecture, storage and compute architectures. As we've sort of helped customers navigate the two worlds, with data plan, it's been a journey that's been reasonably successful and I think we have an opportunity to kind of provide identical consistent architectures both on prem and on Cloud. So it's almost like we took Hadoop and adapted it to Cloud. I think we can adapt the Cloud architecture back on prem, too to have consistent architectures. >> So talk about the Cloud native architecture. So you have a post that just got published. Cloud native architecture for big data and the data center. No, Cloud native architecture to big data in the data center. That's hyrid, explain the hybrid model, how do you define that? >> Like I said, for us it's really important to be able to have consistent architectures, consistent security, consistent governance, consistent way to manage data, and consistent way to actually to double up and port applications. So portability for data is important, which is why having security and governance consistently is a key. And then portability for the applications themselves are important, which is why we are so excited to kind of be, kind of first to embrace the whole containerize the ecosystem initiative. We've announced the open hybrid architecture initiative which is about decoupling storage and compute and then leveraging containers for all the big data apps, for the entire ecosystem. And this is where we are really excited to be working with both IBM and Redhat especially Redhat given their sort of investments in Kubernetes and open ship. We see that much like you'll have S3 and EC2, S3 for storage, EC2 for compute, and same thing with ADLS and azure compute. You'll actually have the next gen HDFS and Kubernetives. So is this a massive architectural rewrite, or is it more sort of management around the core. >> Great question. So part of it is evolution of the architecture. We have to get, whether it's Spark or Kafka or any of these open source projects, we need to do some evolution in the architecture, to make them work in the ecosystem, in the containerized world. So we are containerizing every one of the 28 animals 30 animals, in the zoo, right. That's a lot of work, we are kind of you know, sort of do it, we've done it in the past. Along with your point it's not enough to just have the architecture, you need to have a consistent fabric to be able to manage and operate it, which is really where the data plan comes in again. That was really the point of data plane all the time, this is a multi-roadmap, you know when we sit down we are thinking about what we'll do in 22, and 23. But we really have to execute on a multi-roadmap. >> And Data plane was a lynch pin. >> Well it was just like the sharp edge of the sword. Right, it was the tip of the sphere, but really the idea was always that we have to get data plan in to kind of get that hybrid product out there. And then we can sort of get to a inter generational data plan which would work with the next generation of the big data ecosystem itself. >> Do you see Kubernetes and things like Kubernetes, you've got STO a few service meshes up the stack, >> Absolutely are going to play a pretty instrumental role around orchestrating work loads and providing new stateless and stateful application with data, so now data you've got more data being generated there. So this is a new dynamic, it sounds like that's a fit for what you guys are doing. >> Which is something we've seen for awhile now. Like containers are something we've tracked for a long time and really excited to see Docker and RedHat. All the work that they are doing with Redhat containers. Get the security and so on. It's the maturing of that ecosystem. And now, the ability to port, build and port applications. And the really cool part for me is that, we will definitely see Kubenetes and open shift, and prem but even if you look at the Cloud the really nice part is that each of the Cloud providers themselves, provide a Kubenesos. Whether it's GKE on Google or Fargate on Amazon or AKS on Microsoft, we will be able to take identical architectures and leverage them. When we containerize high mark aft or spark we will be able to do this with kubernetes on spark with open shift and there will be open shift on leg which is available in the public cloud but also GKE and Fargate and AKS. >> What's interesting about the Redhat relationship is that I think you guys are smart to do this, is by partnering with Redhat you can, customers can run their workloads, analytical workloads, in the same production environment that Redhat is in. But with kind of differentiation if you will. >> Exactly with data plane. >> Data plane is just a wonderful thing there. So again good move there. Now around the ecosystem. Who else are you partnering with? what else do you see out there? who is in your world that is important? >> You know again our friends at IBM, that we've had a long relationship with them. We are doing a lot of work with IBM to integrate, data plane and also ICPD, which is the IBM Cloud plane for data, which brings along all of the IBM ecosystem. Whether it's DBT or IGC information governance catalogs, all that kind of were back in this world. What we also believe this will give a flip to is the whole continued standardization of security and governance. So you guys remember the old dpi, it caused a bit of a flutter, a few years ago. (anxious laughing) >> We know how that turned out. >> What we did was we kind of said, old DPI was based on the old distributions, now it's DPI's turn to be more about merit and governance. So we are collaborating with IBM on DPI more on merit and governance, because again we see that as being very critical in this sort of multi-Cloud, on prem edge world. >> Well the narrative, was always why do you need it, but it's clear that these three companies have succeeded dramatically, when you look at the financials, there has been statements made about IBM's contribution to seven figure deals to you guys. We had Redhat on and you guys are birds of a feather. [Murhty] Exactly. >> It certainly worked for you three, which presumably means it confers value to your customers. >> Which is really important, right from a customer standpoint, what is something we really focus on is that the benefit of the bargain is that now they understand that some of their key vendor partners that's us and Ibm and Redhat, we have a shared roadmap so now they can be much more sure about the fact that they can go to containers and kubernetes and so on and so on. Because all of the tools that they depend on are and all the partners they depend on are working together. >> So they can place bets. >> So they can place bets, and the important thing is that they can place longer term bets. Not a quarter bet, we hear about customers talking about building the next gen data centers, with kubernetes in mind. >> They have too. >> They have too, right and it's more than just building machines up, because what happens is with this world we talked about things like networking the way you do networking in this world with kubernetes, is different than you do before. So now they have to place longer term bets and they can do this now with the guarantee that the three of us will work together to deliver on the architecture. >> Well Arun, great to have you on the Cube, great to see you, final question for you, as you guys have a good long plan which is very cool. Short term customers are realizing, the set-up phase is over, okay now they're in usage mode. So the data has got to deliver value, so there is a real pressure for ROI, we would give people a little bit of a pass earlier on because set-up everything, set-up the data legs, do all this stuff, get it all operationalized, but now, with the AI and the machine learning front and center that's a signal that people want to start putting this to work. What have you seen customers gravitate to from the product side? Where are they going, is it the streaming is it the Kafka, is it the, what products are they gravitating to? >> Yeah definitely, I look at these in my role, in terms of use cases, right, we are certainly seeing a continued push towards the real-time analytics space. Which is why we place a longer-term bet on HDF and Kafka and so on. What's been really heartening kind of back to your sentiment, is we are seeing a lot of push right now on security garments. That's why we introduced for GDPR, we introduced a bunch of cable readies and data plane, with DSS and James Cornelius wrote about this earlier in the year, we are seeing customers really push us for key aspects like GDPR. This is a reflection for me of the fact of the maturing of the ecosystem, it means that it's no longer something on the side that you play with, it's something that's more, the whole ecosystem is now more a system of record instead of a system of augmentation, so that is really heartening but also brings a sharper focus and more sort of responsibility on our shoulders. >> Awesome, well congratulations, you guys have stock prices at a 52-week high. Congratulations. >> Those things take care of themselves. >> Good products, and stock prices take care of themselves. >> Okay the Cube coverage here in New York City, I'm John Vellante, stay with us for more live coverage all things data happening here in New York City. We will be right back after this short break. 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