>> From Boston, Massachusetts. It's theCUBE. Covering Actifio 2019 Data Driven. (upbeat techno music) Brought to you by Actifio. >> Hello everyone and welcome to Boston and theCUBE's special coverage of Actifio Data Driven 19. I'm Dave Vellante. Stu Miniman is here. We've got a special guest, John Furrier is in the house from from Palo Alto. Guys, theCUBE we love to go out on the ground, you know, we go deep. We're here at this data theme, right? We were there in the early days, John, you called me up and say, "Get your butt here, we're going to cover the first of Doop World". And since then things have moved quite fast. Everybody thought, you know, Hadoop Big Data was going to take over the world. Nobody even uses that term anymore, right? It's kind of, now it's AI, and machine intelligence, and block chain, and everything else. So what do you think is happening? Did the early Big Data days fail? You know, Frank Genus this morning called it The experimentation phase. >> I mean, I don't really think Frank has a good handle on what's going on in my opinion, cause I think it's not an experimentation, it's real. That was a wave that was essentially the beginning of, not an experimentation, of realization and reality that data, unstructured data in particular was real and relevant. Hadoop looked good off the tee, mill the fairway as we say, but the thing about the Hadoop ecosystem is that validated big data. Every financial institution jumped on it. Everyone who knew anything about data or had data issues or had a lot of data, knew the value. It's just that the apparatus to build via Hadoop was too expensive. In comes Cloud computing at scale, so, as Cloud was accelerating, you look at the Amazon Web Services Revenue Chart you can almost see the D mark where the inflection point is on the hockey stick of Amazon's revenue numbers. And that is the point in time where Hadoop was on the declining of failure. Hortonworks sold the Cloudera. Cloudera's earnings are at an all-time low. A lot of speculation of their entire strategy, and their venture back company went public, but bet the ranch to be the next data warehouse. That wasn't the business model. The data business was a completely new industry, completely being re-transformed, and, far from experimentation, it is real and definitely growing like a weed, but changing because of the underpinning infrastructure dynamics of Cloud Native, Microservices, and that's only going to get highly accelerated and the people who talk about context of industry like Frank, are going to be off. Their predictions will be off because they don't really see the new picture clear enough, in my opinion, >> So, >> I think he's off. >> So it's not so much of a structural change like it was when we went from, you know, mainframes to PCs, it's more of a sort of flow, evolution into this new area which is being driven, powered by new technologies, we talk about block chain machine intelligence and other things. >> Well, I mean, the make up of companies that were building quote, "Big Data Solutions", were trying to build an apparatus or mechanisms to solve big data problems, but none of them actually had the big data problem. None of them were full of data. None of them had a lot of data. The ones that had problems were the financial institutions, the credit card companies, the people who were doing a lot of large scale, um, with Google, Facebook, and some of the hyperscalers. They were actually dealing with the data tsunami themselves, so the practitioners ended up driving it. You guys at Wikibomb, we pointed this out on theCUBE many times, that the value was going to come from the practitioners not the suppliers of so called technology. So, you know, the Clouderas of the world who thought Hadoop would be relevant and growing as a technology were right on one side, on the other side of the coin was the Cloud decimation of that sector. The Cloud computer just completely blew away that Hadoop market because you didn't have to hire a PhD, you didn't have to hire specialty skills to stand up Hadoop clusters. You could actually throw it in the Cloud and get agile quickly, and get value out of data very very quickly. That has been real, it has not been an experiment. There's been new case studies, new companies born, new brands, so it's not an experiment, it is reality, and it's only going to get more real every day. >> And I add of course now you've got, you mentioned Cloudera and Hortenworks, you also got Matt Bar reeling Stu. Let's talk about Actifio. So they coined the term Copy Data Management, they created the category, of course they do a lot of backup, I mean, everybody in this space does a lot of backup. And then you saw the Silicon Valley companies come in. Particularly Cohesity and Rubric, you know, to a lesser extent he got some other guys like Zerto and Durva, but it was really those two companies, Cohesity and Rubric, they raised more money in their D round than Actifio has since inception. But yet Actifio keeps, you know, plodding along, growing, you know, word is they're profitable, you know, they're not like this really sectioned very East Coast versus kind of West Coast mentality. What's your take on what's going on? >> Yeah, so, Dave right, you look at the early days of Actifio and you say great, Copy Data Management, I have all these copies of data, how do I reduce my cost, get greater utilization than I have and leverage the data? I love the title of the show here, Data Driven. You know, we know at the center of digital transformation if you can't become data driven, like the CMO Brian Regan got up on stage talk about that industrialization of data. How am I going along that journey being this, I collected data versus now, you know, data, you know, is the reason that I make decisions, how I make decisions, I get smarter. The Cloud of course is a huge enabler of this, there's all these services that I can instantly access to be able to get greater insight, and move along with that environment, and if you look underneath all of these backup companies, it's really how I can change that data into business value and drive my business, the metadata underneath and all those pieces, not just the wonky storage and technical solutions that make things better, and I get a faster ROI. It's that data at the core of what we do and how do I get that as a business to accelerate. Because we know IT needs to be able to respond back to the business and data needs to be that rocket fuel. >> Is it the case of data haves and data have-nots? I mean, Amazon has data >> I mean, you're right-- >> and Facebook has data. >> We're talking about Actifio, you brought that up, okay, on this segment, on the inside segment, which is cool, they're here at the event, but they have a good opportunity but they also, they got some challenges. I mean, the thing about Actifio is, to my earlier point, which side of the wave are they on? Are they out too much out front with virtualization and Amazon, the Cloud will take them away, or are they riding the Cloud wave, making that an enabler? And I think what really I like about Actifio is because they have a lot of virtualization capabilities, the question is can they scale that Stu, to containers and microservices, because, the real opportunity in this market, in my opinion, is going to build on the virtualization trend, and make container aware, microservices capabilities because if they don't, then that would be a tell sign. Now either way it's a hot M&A market right now, so I think being in the market, horse on the track as you say. You look at the tableau sales force deal monster numbers we are in clearly a hot IPO market and a major roll up market on the M&A side. I think clearly there's two types of companies, old and new, and that is really what people are looking at, are they part of the old guard, are they the new guard. So, you know, this to me is going to be a tell sign of what they do next, can they make the data driven value proposition, you articulated Stu, actually a reality It's going to come from the technology underneath. >> Well I think it's a really interesting point you're making because, Stu as you probably know, that Amazon announced the Amazon backup service right, and you talked about the backup guys and they're like, "Ah yeah it's backup, but it really doesn't do recovery, it's really not that robust". It's part of me says, "Uh oh"... >> Watch out. >> You better move fast", because Amazon has stated, "Hey if you don't move fast we're going to just keep gobbling", and you've seen Amazon do this. What are your thoughts on that? Can these specialists, can they survive, John's talking about M&A. Can the market support all these guys along with the big, you know, traditional guys like Veritas, and Dell EMC, and IBM and Combol? >> Right, well so Actifio started very much in the data center. They were before this Could wave really took off. It's really only in the last year that they've been sassifying their product. So the question is, does that underlying IP, which wasn't tied to hardware, but, you know, sat at really more of, you know, reminded us of that storage virtualization battles that we talked about for years, Dave, but now they are going in the Cloud. They've got all the partnerships in the Cloud, but they are competing against those new vendors that you talked about like Cohesity and Rubric out there, and there's big money chasing this environment. So, you know, I want to talk to the customers here and find out, you know, where they are using them, and especially some of those first customers using this--. >> Well they clearly need a Cloud play cause that's clearly where the action is. But if you look at what's going on with Amazon, Azure, and Google you see a lot of on premises, Stu, because that's where the customers are. So just because the customers are currently not migrating their existing workloads to the Cloud doesn't mean it's not going to happen. So I think there's an opportunity for any company like Actifio, who may or may not be on the curve on the tech side, one little misfire on a tech bet could cripple the company and also make the company. There's a lot of high risk, reward ratio. How they handle containers. How they build on virtualizations. Virtualization going to to be part of the future with Cloud. These are the kind of the dynamics that are going to be in play, and they got some time on their hands because the on premises growth is because the clients are trying to figure out what to do and they're not going to be migrating, lifting, and shifting workloads all off to the Cloud. New will be Cloud based, but enterprises have proven why we are in multi-Cloud and hybrid-Cloud conversation, that... The enterprise on premises is not going away anytime soon. >> I want to ask you guys, John you specifically, about this sort of new Silicon Valley growth model and how companies are achieving escape velocity. When you and I made our first trip to Barcelona, I was having dinner with David Scott who was the CEO of 3PAR and he said to me, When I came to 3PAR the board said, "Hey we're willing to invest 30 million dollars in this company". And David Scott said to them, "I need way more, I need 80 million dollars". Today 80 million dollars is nothing. You saw, you know, Pure Storage hit escape velocity, was just throwing money, and growing at the problem. You're seeing Cohesity-- >> Well you can debate that. I mean, If you have to build a rocket ship, hit critical mass and you want to fund that, you're going to to need an enterprise. However, there's arguments on the south side that you can actually get fly wheel effect going early with less capital. So again, that's 3PAR-- >> But so that's my point. >> Well so that's 3PAR, that was 2009. >> So, yeah that was early days so that's ancient history. But software is generally supposed to be a capital efficient market, yet these companies are raising many hundreds and hundreds of millions, you know, half a billion dollar raises and they are putting it largely in promotion. Is that the new model, is that sustainable, in your view? >> Well I think you're conflating capital market dynamics with viable companies to invest in. I think there's a robust seed in series A market but the series A market and Silicon Valley is you know, 15 to 25 million, it used to be 3 to 5. So the dynamics are changing on funding. There's just not enough companies, horses on the track, to deploy capital at tranches of 30, 50, 80 million. So the capital markets are clearly going to have the money available so it's a market for the startups and the broke companies. That's separate from actually winning. So you've got slacks going public this weeks, you have other companies who have built business on a sass fly wheel, and then everything else is gravy in terms of the go to market, they got a couple hundred million. I think slack got close to a billion dollars in cash that they've raised. So they're flooded with cash, they'll never spend it all. So there are some companies that can achieve success like that. Others have to buy market share, they got to push and build out a sales force, and it's going to be a function of the role of customer, customization, specialism, and whatnot. But with AI machine leaning there's more efficiencies coming in so I think the modern company can do more with less. >> What do you think of the ride sharing on IPOs, Uber and Lift, do you abol? Do you like 'em or do you think it's just, they're losing too money and can't sustain it? >> I was thinking about that this morning after looking at the article in the Wall Street Journal in our coverage on Silicon angle. You look at Zoom communications, I like models that actually can take a simple concept and an existing mature market and disrupt it by being Cloud efficient and completely sass and data driven. That is an example of success. That to me, Zoom Communications and Zscaler, another company that we talk to, these are companies that were built with a specific value proposition that made the product and they were targeting mature markets with leaders in it. Video conferencing, Webex, Citrix, Zoom came out of nowhere, optimized on simple value proposition, used Cloud scale and data, and crushed it. Uber, Lift, little bit different issue. They're losing money but I would bet on the long term that that is going to be the used case for how people will have transportation. I think that's the long game and I think that without regulatory kind of pressure, without, there's regulatory issues that's really the big risk. But I believe that Uber and Lift absolutely will be long brands and just like Facebook was early on, although they threw off a lot of cash, those guys are building for penetration, and that's where the funding matters. Penetration is critical. Now they're the standard, and people really don't take taxis anymore, but they're really using the ride sharing. And you get the scooters, you get the bikes, they're all sequencing into these adjacent markets which drains more cash but builds the brand, builds the footprint. >> Well that's what I want to ask you. So people compare the early Uber, Lift, Taxi, Ride sharing to Amazon selling books, but there's all these other adjacencies. You have a thought on this? >> Well, just, you know, right, Uber Eats is a huge opportunity for that environment and autonomous vehicles everybody talks about, but it's still quite a ways out. So there are a lot of different- >> Scooters are the same, we're in San Diego, there are 8 gazillion scooters. >> San Diego had fun, you know, going around on their electronic scooters, boy, talk about the gig economy, they pay people at the night, to like go pay by the recharge you do on that, what is the future of work, >> Yeah, that's a great point. >> and how can we have that-- >> Uber going to look a lot like Amazon. You subsidize the front end retail side of the business, but look at the data that they throw up. Uber's data that they're gathering on, not only customer behavior, but just mapping services, 3-D mapping is going to be huge, so you've got these cars that are essentially bots on the road, providing massive mapping and traffic analysis. So you're going to start to see data driven, like Actifio slogan here, be a big part of all design decisions and value proposition from any company out there. And if they're not data driven I think they're going to be toast. >> Probably could because there's that data and that machine learning underneath, that can optimize, you know, where the people are, how I use the system, such a huge wave that we're watching. >> How about one last topic which is heavily data driven, it's Facebook. Facebook is obviously a data driven company, the Facebook crypto play, I love it, I love Facebook. I'm a bull on Facebook, I think it's been beat up. I think, two billion users is hard to replicate, but what's your thoughts on their crypto play? >> Well it's kind of a middle finger to the United States of America but it's a great catalyst for the international market because crypto needed a whale to come in and bring all those users in. Bad timing, in my mind, for Facebook, because given all the anti-trust and regulatory conversations, what better way to show your threat to the world order when you say we're going to run a banking system with a collection of international companies. I think the US is going to look at this and say, "Oh my God! They can't even be trusted to handle personal information and we're going to now let them run a banking system? Run monetary, basically World Bank equivalent infrastructure?" No frickin way! I think this is going to to be a major road to home. I think Facebook has to really make this an ecosystem play if they want to make it work, that's their telegraphic move they're saying, "Hey we want to do for the community but we got our own wallet and we got our own network". But they bring a lot to the table so it's going to be a really interesting dynamic to see the coalescing around Facebook because they could make the market. Look what Instagram did to Snapchat. They literally killed the company, took all their users. That is what's going to happen in the digital money economy when Facebook brings billions of users user experience with money. What happened with Snapchat with Instagram is going to happen to the World Bank if this continues. >> Where do you stand on the government breaking up big tech? >> So Dave, you know, you look in these companies, it's not easy to pull those apart. I don't think our government understands how most of big tech works. You know, take Amazon and AWS, that's one company underneath it. You know, Facebook, Microsoft. You know, Microsoft went through all these issues. Question Dave, we've had lots of debates on Twitter you know, are they breaking the law, are they not doing trust? I have some trust issues with Facebook myself, but most of the big companies up there I don't think the anti-trust kicks in, I don't think it makes sense to pull them apart. >> Stu, the Facebook story and the YouTube story are simply this, they have been hiding under the platform rules, of the Digital Millennium Copyright Act, and they are an editing platform so you can't sue them. Okay, once they become a publisher they could be sued. Just like CNN, Fox News, and everybody else. And we're publishers. So they've been hiding behind the platform. That gig is up. They're going to have to address are you a platform or are you a publisher? You're making editing decisions around what users can see with software, you are essentially editing the feed, that is a publisher role, with that becomes responsibility, and then obviously regulartory. >> Well Facebook is conflicted right now. They're trying to figure out which side of the fence to go on. >> No no no! They want one side! The platform side! They're make billions of dollars! >> Yeah but so they're making decisions about you know, which content to show and whether they monetize it. And when it's controversial content, they'll turn down the ads a little bit but they won't completely eliminate it sometimes. >> So, Dave, the only thing that the partisans in politics seem to agree on though is that big tech has too much power. You know, What's your take on that? >> Well so I think that if they are breaking the law then they should be moderated. But I don't think the answer is to go hard after Elizabeth Warren. Hard after them and break them up. I think you got to start with okay, because you break these companies up what's going to happen is they're going to be worth more, it's going to be AT&T all over again. >> While you guys were at Sysco Live, we covered this at Amazon Web Service and Public Sector Summit. The real issue in government, Stu, is there's too much tech for bad on the PR side, and there's not enough tech for good. Tech is not bad, tech is good. There's not enough promotion around the apps around there. There's real venture funds being created to promote tech for good. That's going to where the tide will turn. When does the tech industry start doing good stuff, not bad stuff. >> All right we've got to wrap. John, thanks for sitting in. Thank you for watching. Be right back, we're here at Actifio Data Driven 2019. From Boston this is theCUBE, be right back. (upbeat techno music)

>>Hi everybody. We're back. This is Dave Volante from Wiki bond.org. We're live at strata in Santa Clara, California. This is Silicon angle TVs, continuous coverage of the strata conference. So Riley media or Raleigh media is a great partner of ours. And thanks to them for allowing us to be here. We've been going all week cause it's day three for us. I'm here with Jeff Kelly Wiki bonds that lead big data analysts. And we're here with Jack Norris. Who's the VP of marketing at Matt bar Jack. Welcome to the cube. Thank you, Dave. Thanks very much for coming on. And you know, we've been going all week. You guys are a great sponsor of ours. Thank you for the support. We really appreciate it. How's the show going for you? >>Great. A lot of attention, a lot of focus, a lot of discussion about Hadoop and big data. >>Yeah. So you guys getting a lot of traffic. I mean, it says I hear this 2,500 people here up from 1400 last year. So that's >>Yeah, we've had like five, six people deep in the, in the booth. So I think there's a lot of, a lot of interests. There's interesting. >>You know, when we were here last year, when you looked at the, the infrastructure and the competitive landscape, there wasn't a lot going on and just a very short time, that's completely changed. And you guys have had your hand in that. So, so that's good. Competition is a good thing, right? And, and obviously customers want choice, but so we want to talk about that a little bit. We want to talk about map bar, the kind of problems you're solving. So why don't we start there? What is map are all about? And you've got your own distribution of, of, of enterprise Hadoop. You make it Hadoop enterprise ready? Let's start there. >>Okay. Yeah, I mean, we invested heavily in creating a alternative distribution one that took the best of the open source community with the best of the map, our innovations, and really it's, it's about making Hadoop more applicable, broader use cases, more mission, critical support, you know, being able to sit in and work in a lights out data center environment. >>Okay. So what was the problem that you set out to solve? Why, why do, why do we need another distribution of Hadoop? Let me ask it that way. Get nice and close to. >>So there, there are some just big issues with, with the duke. >>One of those issues, let's talk about that. There's >>Some ease of use issues. There's some deep dependability issues. There's some, some performance. So, you know, let's take those in order right now. If you look at some of the distributions, Apache Hadoop, great technology, but it requires a programmer, right? To get access to the data it's through the Hadoop API, you can't really see the data. So there's a lot of focus of, you know, what do I do once the data's in there opening that up, providing a full file based access, right? So I can look at it and treat it like enterprise storage, see the data, use my standard tools, standard commands, you know, drag and drop from a file browser. You can do that with Matt bar. You can't do that with other districts >>Talking about mountain HDFS as a NFS correct >>Example. Correct. And then, and then just the underlying storage services. The fact that it's append only instead of full random read-write, you know, causes some, some issues. So, you know, that's some of the, the ease of use features. There's a whole lot. We could discuss there. Big picture for reliability. Dependability is there's a single point of failure, multiple single points of failure within Hadoop. So you risk data loss. So people have looked at Hadoop. Traditionally is, is batch oriented. Scratchpad right. We were out to solve that, right? We want to make sure that you can use it for mission critical data, that you don't have a risk of a data loss that you've got full high availability. You've got the full data protection in terms of snapshots and mirroring that you would expect with the enterprise products. >>It gets back to when you guys were, you know, thinking about doing this. I'm not even sure you were at the company at the time, but you, your DNA was there and you're familiar with it. So you guys saw this big data movement. You saw this at duke moon and you said, okay, this is cool. It's going to be big. And it's gonna take a long time for the community to fix all these problems. We can fix them. Now let's go do that. Is that the general discussion? Yeah. >>You know, I think, I think the what's different about this. This is the first open source package. The first open source project that's created a market. If you look at the other open source, you know, Linux, my SQL, et cetera, it was really late in the life cycle of a product. Everyone knew what the features were. It was about, you know, giving an alternative choice, better Unix. Your, your, the focus is on innovation and our founders, you know, have deep enterprise background or CTO was at Google and charge of big table, understands MapReduce at scale, spent time as chief software architect at Spinnaker, which was kind of the fastest clustered Nazanin on the planet. So recognize that the underlying layers of Hadoop needed some rearchitecture and needed some deep investment and to do that effectively and do that quickly required a whole lot of focus. And we thought that was the best way to go to market. >>Talk about the early validation from customers. Obviously you guys didn't just do this in a vacuum, I presume. So you went out and talked to some customers. Yeah. >>What sorts of conversations with customers, why we're in stealth mode? We're probably the loudest stealth >>As you were nodding. And I mean, what were they telling you at the time? Yeah, please go do this. >>The, what we address weren't secrets. I there've been gyrus for open for four or five years on, on these issues. >>Yeah. But at the same time, Jack, you've got this, you got this purist community out there that says, I don't want to, I don't want to rip out HDFS. You know, I want it to be pure. What'd you, what'd you say to those guys, you just say, okay, thank you. We, we understand you're not a prospect. >>And I think, I think that, you know, duke has a huge amount of momentum. And I think a lot of that momentum is that there isn't any risks to adopting Hadoop, right? It's not like the fractured no SQL market where there's 122 different entrance, which one's going to win. Hadoop's got the ecosystem. So when you say pure, it's about the API APIs, it's about making sure that if I create a MapReduce job, it's going to run an Apache. It's going to run a map bar. It's going to run on the other distributions. That's where I think that the heat and the focus is now to do that. You also have to have innovation occurring up and down the stack that that provides choice and alternatives for. >>So when I'm talking about purists, I don't, I agree with you the whole lock-in thing, which is the elephant in the room here. People will worry about lock-in >>Pun intended. >>No, no, but good one good catch. But so, but you're basically saying, Hey, where we're no more locked in than cloud era. Right. I mean, they've got their own >>Actually. I think we're less because it's so easy to get data in and out with our NFS. That there's probably less so, >>So, and I'm gonna come back to that. But so for instance, many, when I, when I say peers, I mean some users in ISV, some guys we've had on here, we had an Abby Mehta from Triceda on the other day, for instance, he's one who said, I just don't have time to mess with that stuff and figure out all that API integration. I mean, there are people out there that just don't want to go that route. Okay. But, but you're saying I'm, I'm inferring this plenty who do right. >>And the, and by the API route, I want to make sure I understand what you're saying. You >>Talked about, Hey, it's all about the API integration. It's not >>About, it's not the, it it's about the API APIs being consistent, a hundred percent compatible. Right. So if I, you know, write a program, that's, that's going after HDFS and the HDFS API, I want to make sure that that'll run on other distributions. Right. >>And that's your promise. Yeah. Okay. All right. So now where I was going with this was th again, there are some peers to say, oh, I just don't want to mess with all that. Now let's talk about what that means to mess with all that. So comScore was a big, high profile case study for you guys. They, they were cloud era customer. They basically, in my understanding is a couple of days migrated from Cloudera to Mapbox. And the impetus was, let's talk about that. Why'd they do that >>Performance data protection, ease of use >>License fee issues. There was some license issues there as well, right? The, the, your, your maintenance pricing was more attractive. Is that true? Or >>I read more mainly about price performance and reliability, and, you know, they tested our stuff at work real well in a test environment, they put it in production environment. Didn't actually tell all their users, they had one guys debug the software for half a day because something was wrong. It finished so quickly. >>So, so it took him a couple of days to migrate and then boom, >>Boom. And they've, they handle about 30 billion objects a day. So there, you know, the use of that really high performance support for, for streaming data flows, you know, they're talking about, they're doing forecasts and insights into web behavior, and, you know, they w the earlier they can do that, the better off they are. So >>Greg, >>So talk about the implications of, of your approach in terms of the customer base. So I'm, I'm imagining that your customers are more, perhaps advanced than a lot of your typical Hadoop users who are just getting started tinkering with Hadoop. Is it fair to say, you know, your customers know what they want and they want performance and they want it now. And they're a little more advanced than perhaps some of the typical early adopters. >>We've got people to go to our website and download the free version. And some of them are just starting off and getting used to Hadoop, but we did specifically target those very experienced Hadoop users that, you know, we're kind of, you know, stubbing their toes on, on the issues. And so they're very receptive to the message of we've made it faster. We've made it more reliable, you know, we've, we've added a lot of ease of use to the, to the Hindu. >>So I found this, let me interrupt, go back to what I was saying before is I found this comment that I found online from Mike Brown comScore. Skipio I presume you mean, he said comScore's map our direct access NFS feature, which exposes a duke distributed file system data as NFS files can then be easily mounted, modified, or overwritten. So that's a data access simplification. You also said we could capitalize on the purchase of map bar with an annual maintenance charge versus a yearly cost per node. NFS allowed our enterprise systems to easily access the data in the cluster. So does that make sense to you that, that enterprise of that annual maintenance charge versus yearly cost per node? I didn't get that. >>Oh, I think he's talking about some, some organizations prefer to do a perpetual license versus a subscription model that's >>Oh, okay. So the traditional way of licensing software >>And that, that you have to do it basically reinforces the fact that we've really invested in have kind of a, a product, you know, orientation rather than just services on top of, of some opensource. >>Okay. So you go in, you license it and then yeah. Perpetual license. >>Then you can also start with the free edition that does all the performance NFS support kick the tires >>Before you buy it. Sorry. Sorry, Jeff. Sorry to interrupt. No, no problem >>At all. So another topic, a lot of interest is security making a dupe enterprise ready. One of the pillars, there is security, making sure access controls, for instance, making sure let's talk about how you guys approach that and maybe how you differentiate from some of the other vendors out there, or the other >>Full Kerberos support. We Lincoln to enterprise standards for access eldap, et cetera. We leveraged the Linux, Pam security, and we also provide volume control. So, you know, right now in Hindu in Apache to dupe other distributions, you put policies at the file level or the entire cluster. And we see many organizations having separate physical clusters because of that limitation, right? And we'd provide volume. So you can define a volume. And in that volume control, access control, administrative privileges data protection class, and, you know, in a sense kind of segregate that content. And that provides a lot of, a lot of control and a lot more, you know, security and protection and separation of data. >>That scenario, the comScore scenario, common where somebody's moving off an existing distribution onto a map are, or, or you more going, going, seeing demand from new customers that are saying, Hey, what's this big data thing I really want to get into it. How's it shake out there >>Right now? There's this huge pent up demand for these features. And we're seeing a lot of people that have run on other distributions switched to map our >>A little bit of everything. How about, can you talk a little bit about your, your channel? You go to market strategy, maybe even some of your ecosystem and partnerships in the little time. >>Sure. So EMC is a big partner of the EMC Greenplum Mr. Edition is basically a map R you can start with any of our additions and upgrade to that. Greenplum with just a licensed key that gives us worldwide service and support. It's been a great partnership. >>We hear a lot of proof of concepts out there >>For, yeah. And then it just hit the news news today about EMC's distribution, Mr. Distribution being available with UCS Cisco's ECS gear. So now that's further expanded the, the footprint that we have about. >>Okay. So you're the EMC relationship. Anything else that you can share with us? >>We have other announcements coming out and >>Then you want to pre-announce in the queue. >>Oops. Did I let that slip >>It's alive? So be careful. And so, in terms of your, your channel strategy, you guys mostly selling direct indirect combination, >>It's it? It, it's kind of an indirect model through these, these large partners with a direct assist. >>Yeah. Okay. So you guys come in and help evangelize. Yep. Excellent. All right. Do you have anything else before we gotta got a roll here? >>Yeah, I did wonder if you could talk a little bit about, you mentioned EMC Greenplum so there's a lot of talk about the data warehouse market, the MPB data warehouses, versus a Hadoop based on that relationship. I'm assuming that Matt BARR thinks well, they're certainly complimentary. Can you just touch on that? And, you know, as opposed to some who think, well, Hadoop is going to be the platform where we go, >>Well, th th there's just, I mean, if you look at the typical organization, they're just really trying to get their, excuse me, their arms around a lot of this machine generated content, this, you know, unstructured data that just growing like wildfire. So there's a lot of Paducah specific use cases that are being rolled out. They're also kind of data lakes, data, oceans, whatever you want to call it, large pools where that information is then being extracted and loaded into data warehouses for further analysis. And I think the big pivot there is if it's well understood what the issue is, you define the schema, then there's a whole host of, of data warehouse applications out there that can be deployed. But there's many things where you don't really understand that yet having to dupe where you don't need to find a schema a is a, is a big value, >>Jack, I'm sorry. We have to go run a couple of minutes behind. Thank you very much for coming on the cube. Great story. Good luck with everything. And sounds like things are really going well and market's heating up and you're in the right place at the right time. So thank you again. Thank you to Jeff. And we'll be right back everybody to the strata conference live in Santa Clara, California, right after this word from our.