(upbeat trumpet music) >> From our studios in the heart of Silicon Valley, Palo Alto, California. This is a CUBE Conversation. >> Welcome, everybody, I'm Dave Vellante and we're here in our Palo Alto studios and we're going to talk about big data. For the last ten years, we've seen organizations come to the realization that data can be used to drive competitive advantage and so they dramatically lowered the cost of collecting data. We certainly saw this with Hadoop, but you know what data is plentiful, insights aren't. Infrastructure around big data is very challenging. I'm here with Kumar Sreekanti, co-founder and CEO of BlueData, and a long time friend of mine. Kumar, it's great to see you again. Thanks so much for coming to theCUBE. >> Thank you, Dave, thank you. Good to see you as well. >> We've had a number of conversations over the years, the Hadoop days, on theCUBE, you and I go way back, but I said up front, big data sounded so alluring, but it's very, very complex to get started and we're going to get into that. I want to talk about BlueData. Recently sold to company to HPE, congratulations. >> Thank you, thank you. >> It's fantastic. Go back, why did you start BlueData? >> When I started BlueData, prior to that I was at VMware and I had a great opportunity to be in the driving seat, working with many talented individuals, as well as with many customers and CIOs. I saw while VMware solved the problem of single instance of virtual machines and transform the data center, I see the new wave of distributed systems, vis-a-vis first example of that is Hadoop, were quite rigid. They were running on bare metal and they were not flexible. They were having, customers, a lot of issues, the ones that you just talked about. There's a new stack coming up everyday. They're running on bare metal. I can't run the production and the DevOps on the same systems. Whereas the cloud was making progress so we felt that there is an opportunity to build a Vmware-like platform that focuses on big data applications. This was back in 2013, right. That was the early genesis. We saw that data is here and data is the new oil as many people have said and the organizations have to figure out a way to harness the power of that and they need an invisible infrastructure. They need very innovative platforms. >> You know, it's funny. We see data as even more valuable than oil because you can only once. (Kumar laughs) You can use data many, many times. >> That's a very good one. >> Companies are beginning to realize that and so talk about the journey of big data. You're a product guy. You've built a lot of products, highly technical. You know a lot of people in the valley. You've built great teams. What was the journey like with BlueData? >> You know, a lot of people would like it to be a straight line from the starting to that point. (Dave laughs) It is not, it's fascinating. At the same time, a stressful, up and downs journey, but very fulfilling. A, this is probably one of the best products that I've built in my career. B, it actually solves a real problem to the customers and in the process you actually find a lot of satisfaction not only building a great product. It actually building the value for the customers. Journey has been very good. We were very blessed with extremely good advisors from the right beginning. We were really fortunate to have good investors and I was very, as you said, my knowledge and my familiarity in the valley, I was able to build a good team. Overall, an extremely good journey. It's putting a bow on the top, as you pointed out, the exit, but it's a good journey. There's a lot of nuance I learned in the process. I'm happy to share as we go through. >> Let's double-click on the problem. We talked a little bit about it. You referenced it. Everyday there's a new open source project coming out. There's The Scoop and The Hive and a new open open source database coming out. Practitioners are challenged. They don't have the skillsets. The Ubers and the Facebooks, they could probably figure it out and have the engineers to do it, but the average enterprise may not. Clearly complexity is the problem, but double-click on that and talk a little bit about, from your perspective, what that challenge is. >> That's a very good point. I think when we started the company, we exactly noticed that. There are companies that have the muscle to hire the set of engineers and solve the problem, vertically specific to their application or their use case, but the average, which is Fortune 500 companies, do not have that kind of engineering man power. Then I also call this day two operations. When you actually go back to Vmware or Windows, as soon as you buy the piece of software, next day it's operational and you know how to use it, but with these new stacks, by the time stack is installed, you already have a newer version. It's actually solutions-led meaning that you want to have a solution understanding, but you want to make the infrastructure invisible meaning, I want to create a cluster or I want to funnel the data. I don't want to think about those things. I just wanted to directly worry about what is my solution and I want BlueData to worry about creating me a cluster, automating it. It's automation, automation, automation, orchestration, orchestration, orchestration. >> Okay, so that's the general way in which you solve this problem. Automate, you got to take the humans out of the equation. Talk specifically about the BlueData architecture. What's the secret sauce behind it? >> We were very fortunate to see containers as the new lightweight virtual machines. We have taken an approach. There are certain applications, particularly stateful, need a different handling than cloud-native non-stateful applications so what we said was, in fact our architecture predates Kubernetes, so we built a bottoms-up, pure white-paper architecture that is geared towards big data, AIML applications. Now, actually, even HPC is starting to move into that direction. >> Well, tell me actually, talk a little bit about that in terms of the evolution of the types of workloads that we've seen. You know, it started all out, Hadoop was batch, and then very quickly that changed. Talk about that spectrum. >> It's actually when we started, the highest ask from the customers were Hadoop and batch processing, but everybody knew that was the beginning and with the streaming and the new streaming technologies, it's near realtime analytics and moving to now AIML applications like H2O and Cafe and now I'm seeing the customer's asking and say, I would like to have a single platform that actually runs all these applications to me. The way we built it, going back to your previous question, the architecture is, our goal is for you to be able to create these clusters and not worry about the copying the data, single copy of the data. We built a technology called DataTap which we talked about in the past and that allows you to have a single copy of the data and multiple applications to be able to access that. >> Now, HPC, you mentioned HPC. It used to be, maybe still is, this sort of crazy crowd. (laughter) You know, they do things differently and everybody bandwidth, bandwidth, bandwidth and very high-end performance. How do you see that fitting in? Do you see that going mainstream? >> I'm glad you pointed out because I'm not saying everything is moving over, but I am starting to see, in fact, I was in a conversation this morning with an HPC team and an HPC customer. They are seeing the value of the scale of distributed systems. HPC tend to be scale up and single high bandwidth. They are seeing the value of how can I actually bring these two pieces together? I would say it's in infancy. Don't take me to say, look how long Hadoop take, 10 years so it's probably going to take a longer time, but I can see enterprises thinking of a single unified platform that's probably driven by Kubernetes and have these applications instantiated, orchestrated, and automated on that type. >> Now, how about the cloud? Where does that fit? We often say in theCUBE that it's not Moore's Law anymore. The innovation cocktail is data, all this data that we've collected, applying machine intelligence, and then scaling with the cloud. Obviously cloud is hugely important. It gobbled up the whole Hadoop business, but where do you see it fitting? >> Cloud is a big elephant in the room. We all have to acknowledge. I think it provides significant advantages. I always used to say this, and I may have said this in my previous CUBE interviews, cloud is all about the innovation. The reason cloud got so much traction, is because if you compare the amount of innovation to on-prem, they were at least five years ahead of that. Even the BlueData technology that we brought to the barer, EMR on Amazon was in front of the data, but it was only available Amazon. It's what we call an opinionated stack. That means you are forced to use what they give you as opposed to, I want to bring my own piece of software. We see cloud, as well as on-prem pretty much homogenous. In fact, BlueData software runs both on-prem, on the cloud, in a hybrid fashion. Same software and you can bring your stack on the top of the BlueData. >> Okay, so hybrid was the next piece of it. >> What we see is cloud has, at least from the angle from my exposure, cloud is very useful for certain applications, especially what I'm seeing is, if you are collecting the large amounts of data on the cloud, I would rather run a batch processing and curate the data and bring the very important amount of data back into the on-prem and run some realtime. It's just one example. I see a balance between the two. I also see a lot of organizations still collecting terabits of data on-prem and they're not going to take terabits of data overnight to the cloud. We are seeing all the customers asking, we would like to see a hybrid solution. >> The reason I like the acquisition by HPE because not only is it a company started by a friend and someone that I respect and knows how to build solid technology that can last, but it's software. HPE, as a company, my view needs more software content. (Kumar laughs) Software's eating the world as Marc Andressen says. It would be great to see that software live as an independent entity. I'm sure decisions are still being made, but how do you see that playing out? What are the initial discussions like? What can you share with us? >> That's a very, very, well put there. Currently, the goal from my boss and the teams there is, we want to keep the BlueData software independent. It runs on all x86 hardware platforms and we want to drive the roadmap driven by the customer needs on the software like we want to run more HPC applications. Our roadmap will be driven by the customer needs and the change in the stack on the top, not by necessarily the hardware. >> Well, that fits with HPE's culture of always trying to give optionality and we've had this conversation many, many times with senior-level people like Antonio. It's very important that there's no lock-in, open mindset, and certainly HPE lives up to that. Thanks so much for coming-- >> You're welcome. Back into theCUBE. >> I appreciate you having me here as well. >> Your career has been amazing as we go back a long time. Wow. From hardware, software, all these-- >> Great technologies. (laughter) >> Yeah, solving hard problems and we look forward to tracking your career going forward. >> Thank you, thank you. Thanks so much. >> And thank you for watching, everybody. This is Dave Vellante from our Palo Alto Studios. We'll see ya next time. (upbeat trumpet music)

>> Announcer: Live from Midtown Manhattan, it's theCUBE, covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsor. >> Okay, welcome back, everyone, to our live special CUBE coverage in New York City in Manhattan, we're here in Hell's Kitchen for theCUBE's exclusive coverage of our Big Data NYC event and Strata Data, which used to be called Strata Hadoop, used to be Hadoop World, but our event, Big Data NYC, is our fifth year where we gather every year to see what's going on in big data world and also produce all of our great research. I'm John Furrier, the co-host of theCUBE, with Peter Burris, head of research. Our next guest, Itamar Ankorion, who's the Chief Marketing Officer at Attunity. Welcome back to theCUBE, good to see you. >> Thank you very much. It's good to be back. >> We've been covering Attunity for many, many years. We've had many conversations, you guys have had great success in big data, so congratulations on that. But the world is changing, and we're seeing data integration, we've been calling this for multiple years, that's not going away, people need to integrate more. But with cloud, there's been a real focus on accelerating the scale component with an emphasis on ease of use, data sovereignty, data governance, so all these things are coming together, the cloud has amplified. What's going on in the big data world, and it's like, listen, get movin' or you're out of business has pretty much been the mandate we've been seeing. A lot of people have been reacting. What's your response at Attunity these days because you have successful piece parts with your product offering? What's the big update for you guys with respect to this big growth area? >> Thank you. First of all, the cloud data lakes have been a major force, changing the data landscape and data management landscape for enterprises. For the past few years, I've been working closely with some of the world's leading organizations across different industries as they deploy the first and then the second and third iteration of the data lake and big data architectures. And one of the things, of course, we're all seeing is the move to cloud, whether we're seeing enterprises move completely to the cloud, kind of move the data lakes, that's where they build them, or actually have a hybrid environment where part of the data lake and data works analytics environment is on prem and part of it is in the cloud. The other thing we're seeing is that the enterprises are starting to mix more of the traditional data lake, the cloud is the platform, and streaming technologies is the way to enable all the modern data analytics that they need, and that's what we have been focusing on on enabling them to use data across all these different technologies where and when they need it. >> So, the sum of the parts is worth more if it's integrated together seems to be the positioning, which is great, it's what customers want, make it easier. What is the hard news that you guys have, 'cause you have some big news? Let's get to the news real quick. >> Thank you very much. We did, today, we have announced, we're very excited about it, we have announced a new big release of our data integration platform. Our modern platform brings together Attunity Replicate, Attunity Compose for Hive, and Attunity Enterprise Manager, or AEM. These are products that we've evolved significantly, invested a lot over the last few years to enable organizations to use data, make data available, and available in the real time across all these different platforms, and then, turn this data to be ready for analytics, especially in Hive and Hadoop environments on prem and now also in the cloud. Today, we've announced a major release with a lot of enhancements across the entire product line. >> Some people might know you guys for the Replicate piece. I know that this announcement was 6.0, but as you guys have the other piece part to this, really it's about modernization of kind of old-school techniques. That's really been the driver of your success. What specifically in this announcement makes it, you know, really work well for people who move in real time, they want to have good data access. What's the big aha for the customers out there with Attunity on this announcement? >> That's a great question, thank you. First of all is that we're bringing it all together. As you mentioned, over the past few years, Attunity Replicate has emerged as the choice of many Fortune 100 and other companies who are building modern architectures and moving data across different platforms, to the cloud, to their lakes, and they're doing it in a very efficient way. One of the things we've seen is that they needed the flexibility to adapt as they go through their journey, to adapt different platforms, and what we give them with Replicate was the flexibility to do so. We give them the flexibility, we give them the performance to get the data and efficiency to move only the change of the data as they happen and to do that in a real-time fashion. Now, that's all great, but once the data gets to the data lake, how do you then turn it into valuable information? That's when we introduced Compose for Hive, which we talked about in our last session a few month ago, which basically takes the next stage in the pipeline picking up incremental, continuous data that is fed into the data lake and turning those into operational data store, historical data stores, data store that's basically ready for analytics. What we've done with this release that we're really excited about is putting all of these together in a more integrated fashion, putting Attunity Enterprise Manager on top of it to help manage larger scale environments so customers can move faster in deploying these solutions. >> As you think about the role that Attunity's going to play over time, though, it's going to end up being part of a broader solution for how you handle your data. Imagine for a second the patterns that your customers are deploying. What is Attunity typically being deployed with? >> That's a great question. First of all, we're definitely part of a large ecosystem for building the new data architecture, new data management with data integration being more than ever a key part of that bigger ecosystem because as all they actually have today is more islands with more places where the data needs to go, and to your point, more patterns in which the data moves. One of those patterns that we've seen significantly increase in demand and deployment is streaming. Where data used to be batch, now we're all talking about streaming. Kafka has emerged as a very common platform, but not only Kafka. If you're on Amazon Web Services, you're using Kinesis. If you're in Azure, you're using Azure Event Hubs. You have different streaming technologies. That's part of how this has evolved. >> How is that challenge? 'Cause you just bring up a good point. I mean, with the big trend that customers want is they want either the same code basis on prem and that they have the hybrid, which means the gateway, if you will, to the public cloud. They want to have the same code base, or move workloads between different clouds, multi-cloud, it seems to be the Holy Grail, we've identified it. We are taking the position that we think multi-cloud will be the preferred architecture going forward. Not necessarily this year, but it's going to get there. But as a customer, I don't want to have to rebuild employees and get skill development and retraining on Amazon, Azure, Google. I mean, each one has its own different path, you mentioned it. How do you talk to customers about that because they might be like, whoa, I want it, but how do I work in that environment? You guys have a solution for that? >> We do, and in fact, one of the things we've seen, to your point, we've seen the adoption of multiple clouds, and even if that adoption is staged, what we're seeing is more and more customers that are actually referring to the term lock-in in respect to the cloud. Do we put all the eggs in one cloud, or do we allow ourselves the flexibility to move around and use different clouds, and also mitigate our risk in that respect? What we've done from that perspective is first of all, when you use the Attunity platform, we take away all the development complexity. In the Attunity platform, it is very easy to set up. Your data flow is your data pipelines, and it's all common and consistent. Whether you're working on prem, whether you work on Amazon Web Services, on Azure, or on Google or other platforms, it all looks and feels the same. First of all, and you solve the issue of the diversity, but also the complexity, because what we've done is, this is one of the big things that Attunity is focused on was reducing the complexity, allowing to configure these data pipelines without development efforts and resources. >> One of the challenges, or one of the things you typically do to take complexity out is you do a better job of design up front. And I know that Attunity's got a tool set that starts to address some of of these things. Take us a little bit through how your customers are starting to think in terms of designing flows as opposed to just cobbling together things in a bespoke way. How is that starting to change as customers gain experience with large data sets, the ability, the need to aggregate them, the ability to present them to developers in different ways? >> That's a great point, and again, one of the things we've focused on is to make the process of developing or configuring these different data flows easy and modular. First, while in Attunity you can set up different flows in different patterns, and you can then make them available to others for consumption. Some create the data ingestion, or some create the data ingestion and then create a data transformation with Compose for Hive, and with Attunity Enterprise Manager, we've now also introduced APIs that allow you to create your own microservices, consuming and using the services enabled by the platform, so we provide more flexibility to put all these different solutions together. >> What's the biggest thing that you see from a customer standpoint, from a problem that you solve? If you had to kind of lay it out, you know the classic, hey, what problem do you solve? 'Cause there are many, so take us through the key problem, and then, if there's any secondary issues that you guys can address customers, that seems the way conversation starts. What are key problems that you solve? >> I think one of the major problems that we solve is scale. Our customers that are deploying data lakes are trying to deploy and use data that is coming, not from five or 10 or even 50 data sources, we work at hundreds going on thousands of data sources now. That in itself represents a major challenge to our customers, and we're addressing it by dramatically simplifying and making the process of setting those up very repeatable, very easy, and then providing the management facility because when you have hundreds or thousands, management becomes a bigger issue to operationalize it. We invested a lot in a management facility for those, from a monitoring, control, security, how do you secure it? The data lake is used by many different groups, so how do we allow each group to see and work only on what belongs to that group? That's part it, too. So again, the scale is the major thing there. The other one is real timeliness. We talked about the move to streaming, and a lot of it is in order to enable streaming analytics, real-time analytics. That's only as good as your data, so you need to capture data in real time. And that of course has been our claim to fame for a long time, being the leading independent provider of CDC, change data capture technology. What we've done now, and also expanded significantly with the new release, version six, is creating universal database streaming. >> What is that? >> We take databases, we take databases, all the enterprise databases, and we turn them into live streams. When you think, by the way, by the most common way that people have used, customers have used to bring data into the lake from a database, it was Scoop. And Scoop is a great, easy software to use from an open source perspective, but it's scripting and batch. So, you're building your new modern architecture with the two are effectively scripting and batch. What we do with CDC is we enable to take a database, and instead of the database being something you come to periodically to read it, we actually turn it into a live feed, so as the data changes in the database, we stream it, we make it available across all these different platforms. >> Changes the definition of what live streaming is. We're live streaming theCUBE, we're data. We're data streaming, and you get great data. So, here's the question for you. This is a good topic, I love this topic. Pete and I talk about this all the time, and it's been addressed in the big data world, but it's kind of, you can see the pattern going mainstream in society globally, geopolitically and also in society. Batch processing and data in motion are real time. Streaming brings up this use case to the end customer, which is this is the way they've done it before, certainly store things in data lakes, that's not going to go away, you're going to store stuff, but the real gain is in motion. >> Itamar: Correct. >> How do you describe that to a customer when you go out and say, hey, you know, you've been living in a batch world, but wake up to the real world called real time. How do you get to them to align with it? Some people get it right away, I see that, some people don't. How do you talk about that because that seems to be a real cultural thing going on right now, or operational readiness from the customer standpoint? Can you just talk through your feeling on that? >> First of all, this often gets lost in translation, and we see quite a few companies and even IT departments that when you talk, when they refer to real time, or their business tells them we need real time, what they understand from it is when you ask for the data, the response will be immediate. You get real time access to the data, but the data is from last week. So, we get real time access, but for last week's data. And that's what we try to do is to basically say, wait a second, when you mean real time, what does real time mean? And we start to understand what is the meaning of using last week's data versus, or yesterday's data, over the real time data, and that makes a big difference. We actually see that today the access, the availability, the availability to act on the real time data, that's the frontier of competitive differentiation. That's what makes a customer experience better, that's what makes the business more operationally efficient than the competition. >> It's the data, not so much the process of what they used to do. They're version of real time is I responded to you pretty quickly. >> Exactly, the other thing that's interesting is because we see it with, again, change of the capture becoming a critical component of the modern data architecture. Traditionally, we used to talk about different type of tools and technology, now CDC itself is becoming a critical part of it, and the reason is that it serves and it answers a lot of fundamental needs that are now becoming critical. One is the need for real-time data. The other one is efficiency. If you're moving to the cloud, and we talked about this earlier, if you're data lake is going to be in the cloud, there's no way you're going to reload all your data because the bandwidth is going to get in the way. So, you have to move only the delta. You need the ability to capture and move only the delta, so CDC becomes fundamental both in enabling the real time as well the efficient, the low-impact data integration. >> You guys have a lot of partners, technology partners, global SIs, resellers, a bunch of different partnership levels. The question I have for you, love to get your reaction and share your insight into is, okay, as the relationship to the customer who has the problem, what's in it for me? I want to move my business forward, I want to do digital business, I need to get up my real-time data as it's happening. Whether it's near real time or real time, that's evolution, but ultimately, they have to move their developers down a certain path. They'll usually hire a partner. The relationship between partners and you, the supplier to the customer, has changed recently. >> That's correct. >> How is that evolving? >> First of all, it's evolving in several ways. We've invested on our part to make sure that we're building Attunity as a leading vendor in the ecosystem of they system integration consulting companies. We work with pretty much all the major global system integrators as well as regional ones, boutique ones, that focus on the emerging technologies as well as get the modern analytic-type platforms. We work a lot with plenty of them on major corporate data center-level migrations to the cloud. So again, the motivations are different, but we invest-- >> More specialized, are you seeing more specialty, what's the trend? >> We've been a technology partner of choice to both Amazon and Microsoft for enabling, facilitating the data migration to the cloud. They of course, their select or preferred group of partners they work with, so we all come together to create these solutions. >> Itamar, what's the goals for Attunity as we wrap up here? I give you the last word, as you guys have this big announcement, you're bringing it all together. Integrating is key, it's always been your ethos in the company. Where is this next level, what's the next milestone for you guys? What do you guys see going forward? >> First of all, we're going to continue to modernize. We're really excited about the new announcement we did today, Replicate six, AEM six, a new version of Compose for Hive that now also supports small data lakes, Aldermore, Scaldera, EMR, and a key point for us was expanding AEM to also enable analytics on the data we generate as data flows through it. The whole point is modernizing data integration, providing more intelligence in the process, reducing the complexity, and facilitating the automation end-to-end. We're going to continue to solve, >> Automation big, big time. >> Automation is a big thing for us, and the point is, you need to scale. In order to scale, we want to generate things for you so you don't to develop for every piece. We automate the automation, okay. The whole point is to deliver the solution faster, and the way we're going to do it is to continue to enhance each one of the products in its own space, if it's replication across systems, Compose for Hive for transformations in pipeline automation, and AEM for management, but also to create integration between them. Again, for us it's to create a platform that for our customers they get more than the sum of the parts, they get the unique capabilities that we bring together in this platform. >> Itamar, thanks for coming onto theCUBE, appreciate it, congratulations to Attunity. And you guys bringing it all together, congratulations. >> Thank you very much. >> This theCUBE live coverage, bringing it down here to New York City, Manhattan. I'm John Furrier, Peter Burris. Be right back with more after this short break. (upbeat electronic music)

>>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.

Yeah, I'm Aala, They're the co-founder back to back. This is the cube silicon angle.com, Silicon angle dot TV's production of the cube, our flagship telecasts. We go out to the event. That was a great conversation. I was really just, just cool. I could have, we could have probably hit on a few more things, obviously well read. Awesome. Co-founder of Cloudera a. You were, you did a good job teaming up with that co-founder, huh? Not bad on the cube, huh? He's not bad on the cube, isn't he? He, >>He reads the internet. >>That's what I'm saying. >>Anything is going on. >>He's a cube star, you know, And >>Technology. Jeff knows it. Yeah. >>We, we tell you, I'm smarter just by being in Cloudera all those years. And I actually was following what he was saying, Sad and didn't dust my brain. So, Okay, so you're back. So we were talking earlier with Michaels and about the relational database thing. So I kind of pick that up where we left off with you around, you know, he was really excited. It's like, you know, hey, we saw that relational database movement happen. He was part of that. Yeah, yeah. That generation. And then, but things were happening or kind of happening the same way in a similar way, still early. So I was trying to really peg with him, how early are we, like, so, you know, as the curve, you know, this is 1400, it's not the Javit Center yet. Maybe the Duke world, you know, next year might be at the Javit Center, 35,000 just don't go to Vegas. So I'm trying to figure out where we are on that curve. Yeah. And we on the upwards slope, you know, down here, not even hitting that, >>I think, I think, I think we're moving up quicker than previous waves. And actually if you, if you look for example, Oracle, I think it took them 15, 20 years until they, they really became a mature company, VM VMware, which started about, what, 12, 13 years ago. It took them about maybe eight years to, to be a big company, met your company, and I'm hoping we're gonna do it in five. So a couple more years. >>Highly accelerated. >>Yes. But yeah, we see, I mean, I'm, I'm, I've been surprised by the growth. I have been, Right? I've been told, warned about enterprise software and, and that it takes long for production to take place. >>But the consumerization trend is really changing that. I mean, it seems to be that, yeah, the enterprises always last. Why the shorter >>Cycle? I think the shorter cycle is coming from having the, the, the, the right solution for the right problem at the right time. I think that's a big part of it. So luck definitely is a big part of this. Now, in terms of why this is changing compared to a couple of dec decades ago, why the adoption is changing compared to a couple of decades ago. I, I think that's coming just because of how quickly the technology itself, the underlying hardware is evolving. So right now, the fact that you can buy a single server and it has eight cores to 16 cores has 12 hards to terabytes. Each is, is something that's just pushing the, the, the, the limits what you can do with the existing systems and hence making it more likely for new systems to disrupt them. >>Yeah. We can talk about a lot. It's very easy for people to actually start a, a big data >>Project. >>Yes. For >>Example. Yes. And the hardest part is, okay, what, what do I really, what problem do I need to solve? How am I gonna, how am I gonna monetize it? Right? Those are the hard parts. It's not the, not the underlying >>Technology. Yes, Yes, that's true. That's true. I mean, >>You're saying, eh, you're saying >>Because, because I'm seeing both so much. I'm, I'm seeing both. I'm seeing both. And like, I'm seeing cases where you're right. There's some companies that was like, Oh, this Hadoop thing is so cool. What problem can I solve with it? And I see other companies, like, I have this huge problem and, and, and they don't know that HA exists. It's so, And once they know, they just jump on it right away. It's like, we know when you have a headache and you're searching for the medicine in Espin. Wow. It >>Works. I was talking to Jeff Hiba before he came on stage and, and I didn't even get to it cuz we were so on a nice riff there. Right. Bunch of like a musicians playing the guitar together. But like he, we talked about the it and and dynamics and he said something that I thoughts right. On money and SAP is talking the same thing and said they're going to the lines of business. Yes. Because it is the gatekeeper that's, it's like selling mini computers to a mainframe selling client servers from a mini computer team. Yeah. >>There's not, we're seeing, we're seeing both as well. So more likely the, the former one meaning, meaning that yes, line of business and departments, they adopt the technology and then it comes in and they see there's already these five different departments having it and they think, okay, now we need to formalize this across the organization. >>So what happens then? What are you seeing out there? Like when that happens, that mean people get their hands on, Hey, we got a problem to solve. Yeah. Is that what it comes down to? Well, Hadoop exist. Go get Hadoop. Oh yeah. They plop it in there and I what does it do? They, >>So they pop it into their, in their own installation or on the, on the cloud and they show that this actually is working and solving the problem for them. Yeah. And when that happens, it's a very, it's a very easy adoption from there on because they just go tell it, We need this right now because it's solving this problem and it's gonna make, make us much >>More money moving it right in. Yes. No problems. >>Is is that another reason why the cycle's compressed? I mean, you know, you think client server, there was a lot of resistance from it and now it's more much, Same thing with mobile. I mean mobile is flipped, right? I mean, so okay, bring it in. We gotta deal with it. Yep. I would think the same thing. We, we have a data problem. Let's turn it into an >>Opportunity. Yeah. In my, and it goes back to what I said earlier, the right solution for the right problem at the right time. Like when they, when you have larger amounts of unstructured data, there isn't anything else out there that can even touch what had, can >>Do. So Amar, I need to just change gears here a minute. The gaming stuff. So we have, we we're featured on justin.tv right now on the front page. Oh wow. But the numbers aren't coming in because there's a competing stream of a recently released Modern Warfare three feature. Yes. Yes. So >>I was looking for, we >>Have to compete with Modern Warfare three. So can you, can we talk about Modern Warfare three for a minute and share the folks what you think of the current version, if any, if you played it. Yeah. So >>Unfortunately I'm waiting to get back home. I don't have my Xbox with me here. >>A little like a, I'm talking about >>My lines and business. >>Boom. Water warfares like a Christmas >>Tree here. Sorry. You know, I love, I'm a big gamer. I'm a big video gamer at Cloudera. We have every Thursday at five 30 end office, we, we play Call of of Beauty version four, which is modern world form one actually. And I challenge, I challenge people out there to come challenge our team. Just ping me on Twitter and we'll, we'll do a Cloudera versus >>Let's, let's, let's reframe that. Let team out. There am Abalas company. This is the geeks that invent the future. Jeff Haer Baer at Facebook now at Cloudera. Hammerer leading the charge. These guys are at gamers. So all the young gamers out there am are saying they're gonna challenge you. At which version? >>Modern Warfare one. >>Modern Warfare one. Yes. How do they fire in? Can you set up an >>External We'll >>We'll figure it out. We'll figure it out. Okay. >>Yeah. Just p me on Twitter and We'll, >>We can carry it live actually we can stream that. Yeah, >>That'd be great. >>Great. >>Yeah. So I'll tell you some of our best Hadooop committers and Hadoop developers pitch >>A picture. Modern Warfare >>Three going now Model Warfare three. Very excited about the game. I saw the, the trailers for it looks, graphics look just amazing. Graphics are amazing. I love the Sirius since the first one that came out. And I'm looking forward to getting back home to playing the game. >>I can't play, my son won't let me play. I'm such a fumbler with the Hub. I'm a keyboard controller. I can't work the Xbox controller. Oh, I have a coordination problem my age and I'm just a gluts and like, like Dad, sorry, Charity's over. I can I play with my friends? You the box. But I'm around big gamer. >>But, but in terms of, I mean, something I wanted to bring up is how to link up gaming with big data and analysis and so on. So like, I, I'm a big gamer. I love playing games, but at the same time, whenever I play games, I feel a little bit guilty because it's kind of like wasted time. So it's like, I mean, yeah, it's fun and I'm getting lots of enjoyment on it makes my life much more cheerful. But still, how can we harness all of this, all of these hours that gamers spend playing a game like Modern Warfare three, How can we, how can we collect instrument, all of the data that's coming from that and coming up, for example, with something useful with predicted. >>This is exactly, this is exactly the kind of application that's mainstream is gaming. Yeah. Yeah. Danny at Riot G is telling me, we saw him at Oracle Open World. He's up there for the Java one. He said that they, they don't really have a big data platform and their business is about understanding user behavior rep tons of data about user playing time, who they're playing with. Yeah, Yeah. How they want us to get into currency trading, You know, >>Buy, I can't, I can't mention the names, but some of the biggest giving companies out there are using Hadoop right now. And, and depending on CDH for doing exactly that kind of thing, creating >>A good user experience >>Today, they're doing it for the purpose of enhancing the user experience and improving retention. So they do track everything. Like every single bullet, you fire everything in best Ball Head, you get everything home run, you do. And, and, and in, in a three >>Type of game consecutive headshot, you get >>Everything, everything is being Yeah. Headshot you get and so on. But, but as you said, they are using that information today to sell more products and, and, and retain their users. Now what I'm suggesting is that how can you harness that energy for the good as well? I mean for making money, money is good and everything, but how can you harness that for doing something useful so that all of this entertainment time is also actually productive time as well. I think that'd be a holy grail in this, in this environment if we >>Can achieve that. Yeah. It used to be that corn used to be the telegraph of the future of about, of applications, but gaming really is, if you look at gaming, you know, you get the headset on. It's a collaborative environment. Oh yeah. You got unified communications. >>Yeah. And you see our teenager kids, how, how many hours they spend on these things. >>You got play as a play environments, very social collaborative. Yeah. You know, some say, you know, we we're saying, what I'm saying is that that's the, that's the future work environment with Skype evolving. We're our multiplayer game's called our job. Right? Yeah. You know, so I'm big on gaming. So all the gamers out there, a has challenged you. Yeah. Got a big data example. What else are we seeing? So let's talk about the, the software. So we, one of the things you were talking about that I really liked, you were going down the list. So on Mike's slide he had all the new features. So around the core, can you just go down the core and rattle off your version of what, what it means and what it is. So you start off with say H Base, we talked about that already. What are the other ones that are out there? >>So the projects that we have right there, >>The projects that are around those tools that are being built. Cause >>Yeah, so the foundational, the foundational one as we mentioned before, is sdfs for storage map use for processing. Yeah. And then the, the immediate layer above that is how to make MAP reduce easier for the masses. So how can, not everybody knows how to learn map, use Java, everybody knows sql, right? So, so one of the most successful projects right now that has the highest attach rate, meaning people usually when they install had do installed as well is Hive. So Hive takes sequel and so Jeff Harm Becker, my co-founder, when he was at Facebook, his team built the Hive system. Essentially Hive takes sql so you don't have to learn a new language, you already know sql. And then converts that into MAP use for you. That not only expands the developer base for how many people can use adu, but also makes it easier to integrate Hadoop through all DBC and JDBC integrated with BI tools like MicroStrategy and Tableau and Informatica, et cetera, et cetera. >>You mentioned R too. You mentioned R Program R >>As well. Yeah, R is one of our best partnerships. We're very, very happy with them. So that's, that's one of the very key projects is Hive assisted project to Hive ISS called Pig. A pig Latin is a language that ya invented that you have to learn the language. It's very easy, it's very easy to learn compared to map produce. But once you learn it, you can, you can specify very deep data pipelines, right? SQL is good for queries. It's not good for data pipelines because it becomes very convoluted. It becomes very hard for the, the human brain to understand it. So Pig is much more natural to the human. It's more like Pearl very similar to scripting kind of languages. So with Peggy can write very, very long data pipelines, again, very successful projects doing very, very well. Another key project is Edge Base, like you said. So Edge Base allows you to do low latencies. So you can do very, very quick lookups and also allows you to do transactions. So you can do updates in inserts and deletes. So one of the talks here that had World we try to recommend people watch when the videos come out is the Talk by Jonathan Gray from Facebook. And he talked about how they use Edge Base, >>Jonathan, something on here in the Cube later. Yeah. So >>Drill him on that. So they use Edge Base now for many, many things within Facebook. They have a big team now committed to building an improving edge base with us and with the community at large. And they're using it for doing their online messaging system. The live mail system in Facebook is powered by Edge Base right now. Again, Pro and eBay, The Casini project, they gave a keynote earlier today at the conference as well is using Edge Base as well. So Edge Base is definitely one of the projects that's growing very, very quickly right now within the Hudu system. Another key project that Jeff alluded to earlier when he was on here is Flum. So Flume is very instrumental because you have this nice system had, but Hadoop is useless unless you have data inside it. So how do you get the data inside do? >>So Flum essentially is this very nice framework for having these agents all over your infrastructure, inside your web servers, inside your application servers, inside your mobile devices, your network equipment that collects all of that data and then reliably and, and materializes it inside Hado. So Flum does that. Another good project is Uzi, so many of them, I dunno how, how long you want me to keep going here, But, but Uzi is great. Uzi is a workflow processing system. So Uzi allows you to define a series of jobs. Some of them in Pig, some of them in Hive, some of them in map use. You can define a series of them and then link them to each other and say, only start this job when these other jobs, two jobs finish because I'm waiting for the input from them before I can kick off and so on. >>So Uzi is a very nice framework that will will do that. We'll manage the whole graph of jobs for you and retry things when they fail, et cetera, et cetera. Another good project is where W H I R R and where allows you to very easily start ADU cluster on top of Amazon. Easy two on top of Rackspace, virtualized environ. It's more for kicking off, it's for kicking off Hadoop instances or edge based instances on any virtual infrastructure. Okay. VMware, vCloud. So that it supports all of the major vCloud, sorry, all of the me, all of the major virtualized infrastructure systems out there, Eucalyptus as well, and so on. So that's where W H I R R ARU is another key project. It's one, it's duck cutting's main kind of project right now. Don of that gut cutting came on stage with you guys has, So Aru ARO is a project about how do we encode with our files, the schema of these files, right? >>Because when you open up a text file and you don't know how to what the columns mean and how to pars it, it becomes very hard to work for it. So ARU allows you to do that much more easily. It's also useful for doing rrp. We call rtc remove procedure calls for having different services talk to each other. ARO is very useful for that as well. And the list keeps going on and on Maha. Yeah. Which we just, thanks for me for reminding me of my house. We just added Maha very recently actually. What is that >>Adam? I'm not >>Familiar with it. So Maha is a data mining library. So MAHA takes some of the most popular data mining algorithms for doing clustering and regression and statistical modeling and implements them using the map map with use model. >>They have, they have machine learning in it too or Yes, yes. So that's the machine learning. >>So, So yes. Stay vector to machines and so on. >>What Scoop? >>So Scoop, you know, all of them. Thanks for feeding me all the names. >>The ones I don't understand, >>But there's so many of them, right? I can't even remember all of them. So Scoop actually is a very interesting project, is short for SQL to Hadoop, hence the name Scoop, right? So SQ from SQL and Oops from Hadoop and also means Scoop as in scooping up stuff when you scoop up ice cream. Yeah. And the idea for Scoop is to make it easy to move data between relational systems like Oracle metadata and it is a vertical and so on and Hadoop. So you can very simply say, Scoop the name of the table inside the relation system, the name of the file inside Hadoop. And the, the table will be copied over to the file and Vice and Versa can say Scoop the name of the file in Hadoop, the name of the table over there, it'll move the table over there. So it's a connectivity tool between the relational world and the Hadoop world. >>Great, great tutorial. >>And all of these are Apache projects. They're all projects built. >>It's not part of your, your unique proprietary. >>Yes. But >>These are things that you've been contributing >>To, We're contributing to the whole ecosystem. Yes. >>And you understand very well. Yes. And >>And contribute to your knowledge of the marketplace >>And Absolutely. We collaborate with the, with the community on creating these projects. We employ committers and founders for many of these projects. Like Duck Cutting, the founder of He works in Cloudera, the founder for that UIE project. He works at Calera for zookeeper works at Calera. So we have a number of them on stuff >>Work. So we had Aroon from Horton Works. Yes. And and it was really good because I tell you, I walk away from that conversation and I gotta say for the folks out there, there really isn't a war going on in Apache. There isn't. And >>Apache, there isn't. I mean isn't but would be honest. Like, and in the developer community, we are friends, we're working together. We want to achieve the, there's >>No war. It's all Kumbaya. Everyone understands the rising tide floats, all boats are all playing nice in the same box. Yes. It's just a competitive landscape in Horton. Works >>In the business, >>Business business, competitive business, PR and >>Pr. We're trying to be friendly, as friendly as we can. >>Yeah, no, I mean they're, they're, they're hying it up. But he was like, he was cool. Like, Hey, you know, we know each other. Yes. We all know each other and we're just gonna offer free Yes. And charge with support. And so are they. And that's okay. And they got other things going on. Yes. But he brought up the question. He said they're, they're launching a management console. So I said, Tyler's got a significant lead. He kind of didn't really answer the question. So the question is, that's your core bread and butter, That's your yes >>And no. Yes and no. I mean if you look at, if you look at Cloudera Enterprise, and I mentioned this earlier and when we talked in the morning, it has two main things in it. Cloudera Enterprise has the management suite, but it also has the, the the the support and maintenance that we provide to our customers and all the experience that we have in our team part That subscription. Yes. For a description. And I, I wanna stress the point that the fact that I built a sports car doesn't mean that I'm good at running that sports car. The driver of the car usually is much better at driving the car than the guy who built the car, right? So yes, we have many people on staff that are helping build had, but we have many more people on stuff that helped run Hado at large scale, at at financial indu, financial industry, retail industry, telecom industry, media industry, health industry, et cetera, et cetera. So that's very, very important for our customer. All that experience that we bring in on how to run the system technically Yeah. Within these verticals. >>But their strategies clear. We're gonna create an open source project within Apache for a management consult. Yes. And we sell support too. Yes. So there'll be a free alternative to management. >>So we have to see, But I mean we look at the product, I mean our products, >>It's gotta come down to product differentiation. >>Our product has been in the market for two years, so they just started building their products. It's >>Alpha, It's just Alpha. The >>Product is Alpha in Alpha right now. Yeah. Okay. >>Well the Apache products, it is >>Apache, right? Yeah. The Apache project is out. So we'll see how it does it compare to ours. But I think ours is way, way ahead of anything else out there. Yeah. Essentially people to try that for themselves and >>See essentially, John, when I asked Arro why does the world need Hortonwork? You know, eventually the answer we got was, well it's free. It needs to be more open. Had needs to be more open. >>No, there's, >>It's going to be, That's not really the reason why Warton >>Works. >>No, they want, they want to go make money. >>Exactly. We wasn't >>Gonna say them you >>When I kept pushing and pushing and that's ultimately the closest we can get cuz you >>Just listens. Not gonna >>12 open source projects. Yes. >>I >>Mean, yeah, yeah. You can't get much more open. Yeah. Look >>At management >>Consult, but Airs not shooting on all those. I mean, I mean not only we are No, no, not >>No, no, we absolutely >>Are. No, you are contributing. You're not. But that's not all your projects. There's other people >>Involved. Yeah, we didn't start, we didn't start all of these projects. Yeah, that's >>True. You contributing heavily to all of them. >>Yes, we >>Are. And that's clear. Todd Lipkin said that, you know, he contributed his first patch to HPAC in 2008. Yes. So I mean, you go back through the ranks >>Of your people and Todd now is a committer on Edge base is a committer on had itself. So on a number >>Of you clearly the lead and, and you know, and, but >>There is a concern. But we, we've heard it and I wanna just ask you No, no. So there's a concern that if I build processes around a proprietary management console, Yes. I'm gonna end up being locked into that proprietary management CNA all over again. Now this is so far from ca Yes. >>Right. >>But that's a concern that some people have expressed. And, and, and I think one of the reasons why Port Works is getting so much attention. So Yes. >>Talk about that. It's, it's a very good, it's a very good observation to make. Actually, >>There there is two separate things here. There's the platform where all the data sets and then there's this management parcel beside the platform. Now why did we make the management console why the cloud didn't make the management console? Because it makes our job for supporting the customers much more achievable. When a customer calls in and says, We have a problem, help us fix this problem. When they go to our management console, there is a button they click that gives us a dump of the state, of the cluster. And that's what allows us to very quickly debug what's going on. And within minutes tell them you need to do this and you to do that. Yeah. Without that we just can't offer the support services. There's >>Real value there. >>Yes. So, so now a year from, But, but, but you have to keep in mind that the, the underlying platform is completely open source and free CBH is completely a hundred percent open source, a hundred percent free, a hundred percent Apache. So a year from now, when it comes time to renew with us, if the customer is not happy with our management suite is not happy with our support data, they can, they can go to work >>And works. People are afraid >>Of all they can go to ibm. >>The data, you can take the data that >>You don't even need to take the data. You're not gonna move the data. It's the same system, the same software. Every, everything in CDH is Apache. Right? We're not putting anything in cdh, which is not Apache. So a year from now, if you're not happy with our service to you and the value that we're providing, you can switch. There is no lock in. There is no lock. And >>Your, your argument would be the switching costs to >>The only lock in is happiness. The only lock in is which >>Happiness inspection customer delay. Which by, by the way, we just wrote a piece about those wars and we said the risk of lockin is low. We made that statement. We've got some heat for it. Yes. And >>This is sort of at scale though. What the, what the people are saying, they're throwing the tomatoes is saying if this is, again, in theory at scale, the customers are so comfortable with that, the console that they don't switch. Now my argument was >>Yes, but that means they're happy with it. That means they're satisfied and happy >>With it. >>And it's more economical for them than going and hiding people full-time on stuff. Yeah. >>So you're, you're always on check as, as long as the customer doesn't feel like Oracle. >>Yeah. See that's different. Oracle is very, Oracle >>Is like different, right? Yeah. Here it's like Cisco routers, they get nested into the environment, provide value. That's just good competitive product strategy. Yes. If it they're happy. Yeah. It's >>Called open washing with >>Oracle, >>I mean our number one core attribute on the company, the number one value for us is customer satisfaction. Keeping our people Yeah. Our customers happy with the service that we provide. >>So differentiate in the product. Yes. Keep the commanding lead. That's the strategist. That's the, that's what's happening. That's your goal. Yes. >>That's what's happening. >>Absolutely. Okay. Co-founder of Cloudera, Always a pleasure to have you on the cube. We really appreciate all the hospitality over the beer and a half. And wanna personally thank you for letting us sit in your office and we'll miss you >>And we'll miss you too. We'll >>See you at the, the Cube events off Swing by, thanks for coming on the cube and great to see you and congratulations on all your success. >>Thank >>You. And thanks for the review on Modern Warfare three. Yeah, yeah. >>Love me again. If there any gaming stuff, you know, I.