>> Hello everyone. Welcome to this CUBE conversations here in Palo Alto, California John Furrier, host of the Cube. I'm here with Jagane Sundar CTO chief technology officer of WANdisco, you get great to see you again. Place we're coming on. >> Thank you for having me, John. >> So the conversation I want to talk to about the technology behind WANdisco and we've had many conversations. So for the folks watching good, our YouTube channel insurgency the evolution of conversations over, I think. Eight, eight, nine years now we've been chatting. What a level up. You guys are now with cloud big announcements around multi cloud live data in particular. So the technology is the gift that keeps giving for WANdisco you guys continuing to take territory now, a big way with cloud, big growth, A lot of changes, a lot of hires. What's going on? >> So, as you well know, WANdisco stands for wide area network distributed, computing on the value ofthe the wide data network aspect is really shining through now because nobody goes to the cloud saying, I'm going to put it in one data center. It's always multiple regions, multiple data centers in each region. Suddenly, problem of having your data consistent, being across multiple cloud windows are on prem to cloud becomes a real challenge. We stepped in. We had something that was a good solution for small users, small data. But we developed it into something that's fantastic for large data volumes on people are running into the problem. The biggest problem that IT providers have is that data scientists do not respect data that's not consistent. If you look at a replica of data and you're not sure whether it's exactly accurate or not the data scientists who spent all his time building algorithms to predict some model gonna look at it and go, that data's not quite right. I'm not going to look at it. So if you use a inconsistent tool or an inadequate tool to replicate your data, you have the problem that nobody is going to respect the replicas. Everybody's going to go back to the source of truth. We solved that problem elegantly and accurately >> State the problem specifically. Is it the integrity of the data? What is the specific problem statement that you guys solve with technology? >> Let me give you an exam you have notifications that come out of cloud object stores when an object this place into the store or deleted from the store that the best effort delivery. If there are logjams in this mechanism used to deliver some notifications, maybe drop the problem with using that notification mechanism to replicate your data is that over a period of time, so you have two three petabytes of data and you're replicating it over a month or month and a half, you'll find that maybe point one percent of your data is not quite accurate anymore. So the value ofthe the replicas essentially zero >> like a leaky pipe. Basically, >> indeed, if you have a leaking pipe, then it's just totally >> we need to have integrity and to end. All right, let's get back to some of the things I want to ask because I think it's a fascinating been following your story. For years, you had a point solution. Multiple wider. You had the replication active, active great for data centers. So disaster recovery not mission critical, but certainly critical. Correct, depending on how it the mission of us. It wasn't this asked Income's Cloud. You mentioned a wide area. Networks and you go back to the old days when I was breaking into the business. That's when they had, you know, dial up modems and front pagers. Not even cell phones. Just starting. Why do your network would have really complicated beast and all the best resource is worked on expensive bandwith, that he had remote offices and you had campus networking then. So why the area networking went through that phase one? Correct. Now we're living in. They win all the time. Cloud is when white area >> correct cloud is when. But there are subtle aspect that people miss all the time. If you go to store an object in Amazon, says three, for example, you pick a region. If it's a complete wide area distributed entity, why do you need to pick a region? The truth is, each cloud vendor hides a number of region specific or local area network specific aspects of their service. Dynamo DB runs and one data centre one one region, two or three availability zones in a region. If you want to replicate that data, you don't really have much help from the cloud vendor themselves. So you need to parse the truth from what has offered what you will find us. The van is still a very challenging problem for a lot of these data application problems. >> Talk about the wide area network challenges in the modern era we're living in, which is cloud computing mentioned some of the nuances around regions and availability zones. Basically, the cloud grew up as building blocks and the plumbing on the neither essentially a mai britt of of certain techniques and networking. Local area network V lands tunneling All these stuff Nets router. So it's obviously plumbing. Yes, what's different now that's important to take that to the next level. Because, you know, there are arguments that saying, Hey, GPR, I might want to have certain regions be smarter, right? So you're starting to see a level up that Amazon and others air going. Google, in particular, talks about this a lot as Ama's Microsoft. What's that next level of when, where the plumbing it's upgraded from basically the other things. >> So the problem really has to be stated in terms ofthe your data architecture. If you look at your data on, figure out that you need the set of data to be available for your business critical applications, then the problem turns into. I need replicas of this data in this region and the other reasons, perhaps in two different cloud render locations because you don't want to be tied down to their availability. One cloud vendor, then the problem tones into How do you hide the complexity of replicating and keeping this data consistent from the users of the data data scientists, the application authors and so on. Now, that's where we step in. We have a transparent replication solution that fits into the plumbing. It's often offered by the IT folks as part of their cloud offering or as part of the hybrid offering. The application. Developers don't really need to worry about those things. A specific example would be hive tables that are users building in one data center an IT Professional from that organization can buy our replication software. That table will be available in multiple data centers and multiple regions available for both Read and write. The user did not do anything or does not need to be a there. So if you have problems such as GDPR requires the data to be here. But this summarized data can be available across all of these regions. Then we can solve the problem elegantly for you without any act application rewiring or reauthoring. >> Talk about the technology that makes all this happen again. This has been a key part of your success that WANdisco love the always love the name wide area there was a big wide area that were fan did that in my early days configuring router tables. You know how it has been. You know, hardcore back then, Distributed systems is certainly large. Scale now is part of the clouds. So all the large scale guys like me when we grew up into computer science days had to think about systems, architecture at scale. We're actually living it now, Correct. So talk about the technology. What specifically do you guys have that that that's your technology and talk about the impact to the scale piece. I think that's a real key technology piece >> indeed. So the core of our algorithm is enhancements and superior implementation. Often algorithm called paxos. Now paxos itself is the only mathematically proven algorithm for keeping replicas in multiple machines or multiple regions. So multiple data centers the other alternatives. Such a raft and zookeeper protocol. These are all compromises for the sake of the ease of implementation. Now we don't feel the cost of implementation. We spent many years doing the research on it, so we have fantastic implementation. Of paxos is extended for use over wide data networks without any special hardware I mentioned without any special hardware piece, because Google Spanner, which is one of our primary competitors, has an implementation that that needs your own specific network and hardware. So the value of >> because they're tired, the clock, atomic clock, actually, to the infrastructure of their timings, that's all synchronized. So it's it's only within Google Cloud? >> Exactly. It cannot even be made available to Google's customers of Google Cloud. That was a feature that they added recently, but it's rolling out in very limited. >> They inherited that from their large scale correct Google. Yes, which is a big table spanner. These are awesome products. >> These are awesome products, but they're very specific >>Tailored for Google. >> Yes, they're great in the Google environment. They're not so great outside of Google. Now we have technology that makes you able to run this across a Google Cloud and Microsoft's Cloud and Amazons Cloud. The value of this is that you have truly cloud neutral solutions. You don't need to worry about when the lock in, you don't need to worry about availability problems in one of the cloud vendors and then you can scale your solution. You can go in with an approach such that when the virtual machines or the compute resource is in one cloud vendor are really inexpensive. Will use that when it's very expensive. Will move our workloads to other locations. You can think up architectures like that, with our solution underpinning your replication >> rights again. I'm gonna ask you the technical quite love these conversations get down and dirty on the hood. So Joel Horowitz was on your new CMO former Microsoft. Keep alumni Richard CEO Talk aboutthe. Same thing. Moving data around the key value probably that's tied right into your legacy of your I P and how that value is with integrity. Moving data from point A to point B. But the world's moving also to identify scenarios where I'm going to move compute rather than through the day, because people have recognized that moving data is hard you got late in C and this cost in band with so two schools of thought not mutually exclusive. When do you pick one? >> Okay, absolutely. They're not mutually exclusive because there are data availability needs that defined some replication scenarios on their computer needs that can be more flexible. If you had the ability to say, have data in Amazon's cloud on in Microsoft's Cloud, You mean Want to use some Amazon specific tools for specific computer scenarios at the same time, used Microsoft tools for other scenarios or perhaps use open source, too, like Hadoop in either one of those clouds? Those are all mechanisms that work perfectly well, but at the core you have to figure out your data architecture. If you can live with your data in one region or in one data center, clearly that's what you should do. But if you cannot have that data, be unavailable, you do have to replicate it. At that point, you should consider replicating to a different cloud window because availability is concerned with all these vendors. >> So two things I hear you say one availability is it's a driver. The other one is user preference Yes. Why not have people who know Microsoft tools and Microsoft software work on Microsoft framework of someone using something else in another cloud? The same data can live in both places. You guys make that happen? Is that what you're saying? Exactly. That's a big deal. >> Absolutely. And we guarantee the consistency that a guarantee that you will not get from any other bender. >> So this basically debunks the whole walk in, Yes, that you guys air solution to to essentially relieve this notion of lock and so me as a customer and say, Hey, I'm an Amazon right now. We're all in an Amazon. But, you know, I've got some temptation to goto Azure or Google. Why wouldn't I if I have the ability to make my data consistent, exact. Is that what you're saying? >> That is exactly what I'm saying. You have this ability to experiment with different cloud vendors. You also have the ability to mitigate some of the cost aspect. If you're going to pay for copies in two different geographic locations, you might as well do it on two different cloud vendor see have the richer subset of applications and better availability. >> So for people who say date is a lock inspect for cloud. It's kind of right if unless they use WANdisco because in a sense, and because you know what really moves with it. I mean, your data's Did you stay there? Yeah, that's kind of common sense. It's not so much technical locket, so there's no real technical lockets. More operational lock and correct with data, if you don't wantto. But if you're afraid of lock in, you go with the WANdisco. That's live data. Multi cloud is that >> that was live data multi cloud on. Does this new ability to actually have active data sets that are available in different cloud bender locations? >> Well, that's a killer app right there. How do you feel? You must You must feel pretty good. You know, you and I have talked many times. Yes, but this's like you been waiting for this moment. This is actually really wide here in a k a cloud. I was a big data problem. Which only getting bigger, exactly. Replication is now the transport between clouds for anti lock. And this is the Holy Grail for home when >> it is the Holy Grail for the industrial. We've been talking about it for years now, and we feel completely redeemed. Now we feel that the industry has gotten to the point back. They understand what we've talked about. I feel very excited, the custom attraction we're seeing on watching our customers light of when we describe the attributes we bring, It's >> exciting and just the risk management alone is a hedge. I mean, if I'm a if I'm someone in the cyber security challenges alone on data, you've got data sovereignty, compliance. Never mind the productivity piece of it, which is pretty amazing. So you guys are changing the data equation. >> Indeed, R R No most excited customers are CEOs because mitigating risk from things like cyber security. As you point out, you may have a breach in one cloud vendor. You can turn that off and use your replica in the other cloud vendor side instantly. Those are comfort. You do not get that other solutions. >> So world having a love fest here. I love the whole multi cloud data. No anti lock. And I think that's a killer feature. Think we'll sell that baby? I'm going to say, OK, that's all good, but I'm going to get you on this one. Security. So no one saw security yet. So if you saw that, then you pretty much got it all. So tell me the securities. Just >> so I'll start by saying, right. Our biggest customer base is the financial industry, banking in companies insurance company's health care. There is no industry in the world that's more security conscious than the banking. And does the government the comment? Perhaps I would. I mean, the banks are really security >> conscious, Their money's money, >> money is money. And and they have, ah, judicially responsibility both governments and to their to their customers. So we've catered to these customers for upwards off a decade. Now, every technical decision we make has security. Ask one of the focus items on DH >> years. A good un security. You >> feel's way insecurity when minute comes to date. Yes. >> Encryption. Is that what this is? It's >> encrypted on the wire. We support all on this data at rest encryption schemes. We support all the the the soup and the cloud vendor security mechanisms. We have a cross cloud product, so the security problems are multiplied and we take care of each of those specifically. So you can be confident that your data secure >> and wire speed security, no overhead involved, >> no overhead involved at all. It's not measurable. >> So well, congratulations on where you guys are a lot more work to do. You guys going to staff? So you hiring a lot of people talk about the talent you're hiring real quick because, you know large skin attracting large scale talent is also one indicator. Yeah, the successful opportunity. I see, the more I think the positioning is phenomenal. Congratulations absent about the hiring, >> as you know, as as David mentioned. A few minutes ago, we hired Joel from IBM for our marketing a department. He cmo wonderful. Higher. We've got Ronchi, who's from the University of Denver. I left the head of that computer science department to come work for us. Another amazing guy. Terrific background. We've got shocked me. Who's another column? UT Austin, phD. He's running engineering for us. We're so pleased to be able to hire talent at this level. As as you well know, it's the people who make these jobs interesting and products interesting. We are. So what are >> some of the things that those guys say when they when they get into really exposed. I mean, why would someone with somewhat what would take someone to quit their ten year professor job at a university, which is pretty much retirement to engage in a growing opportunity? What's the What do they say? >> So the single I mean that you'll find in all of this is very complex, unique technology that has bean refined on it's on the verge of exploding toe, probably something ten to one hundred times the size it is today. People see that when dish when we show them the value ofthe what we've got on the market, that we're taking this too. I'm just getting excited. >> Well, congratulations. You guys have certainly worked hard. Has been great to watch the entrepreneurial journey of getting into that growth stream and just the winds that you're back all that hard work into technologies. Phenomenal again. Multi cloud data not worrying about where your data is is going to give people some East and rest in the other rest of night. Well, because that's the number one of the number one was besides security absolutely Jagane Sundar CTO chief technology officer of WANdisco here inside the CUBE in Palo Alto. I'm John Furrier. Thanks for watching.

(soaring orchestral music) >> Everyone, welcome to this CUBE Conversation here at Palo Alto, California. I'm John Furrier, host of theCUBE. We are here with Joel Horwitz, who's the CMO of WANdisco, Joel, great to see you, formerly of IBM, we've known you for many years, we've had great conversations when you were at IBM, rising star, now at WANdisco, congratulations. >> Thank you, yeah, it's really great to be at WANdisco, and great to be here with theCUBE. So we've had many conversations, again, goin' back, you were a rising star in data, you know the cloud real well, why WANdisco, why leave IBM for WANdisco, what attracted you to the opportunity? >> Yeah, really three things. First and foremost, the people. I've known the WANdisco team now for years. Back in my Hadoop days, when I was at Datamere, I used to, hang out with the WANdisco team at Data After Dark, in New York, which was great, and they had the best marketing there at the time. Two, the product, I mean I won't join a company unless the product is really legit, and they have an absolutely great technology, and they are applying it to some really tough problems. And third is just the potential, really, the potential of this company is not even close to being tapped. So there's a ton of runway there, and so, for me, I'm just totally grateful, and totally honored, to be a part of WANdisco. >> What's the tailwind for them, that wave that they're on, if you will, because you mentioned, there's a lot of runway or headroom, a lot of market growth. Certainly cloud, David Richards will talk about that. But what attracted you, 'cause you knew the cloud game too. >> Yeah, yeah. >> IBM made a big run at the cloud. >> Yeah well, I came in, at IBM, through the data door, so to speak, and then I walked through the cloud door, as well, while I was there. And the reality is that data continues to be the lifeblood of an enterprise, no matter what. And so, what I saw in WANdisco was that they had technology that allowed people to enlarge enterprise to, frankly replicate or manage their data across Hadoop clusters from cluster to cluster. And then we ended up, when I spoke with you last, with David here, we also recognize the opportunity that just how copying data, large-scale data from one Hadoop cluster to another, is challenging, copying data, it's really not that different of copying data from, say, HDFS to an object storage or S3, as pretty similar problem. And so that's why, just this past week, we announced live data for multicloud. >> Explain live data for multicloud, I've read it in the news, got some buzz, it's this great trend, live. We're doing you a lot of live videos on theCUBE, live implies real time. Data's data. Multicloud is clearly becoming one of those enterprise categories. >> Yeah. >> First it was public cloud, then hybrid cloud. >> Yeah. >> Now it's multicloud. How does live data fit into multicloud? >> Yeah, so multicloud, and live data, as I just mentioned, we have live data for Hadoop, so that's fairly obvious, so if you're going multi-cluster you can do that. As well as from, even on-prem, data center to data center, so, multi-site if you will. But multicloud is a really interesting phrase that's kind of cropped up this year. We're seeing it used quite a lot. The focus in multicloud has been mainly focus on applications. And so, talking about, how do you have a container strategy? Or a virtualization strategy, for your applications? And so, I think of it really as a multicloud strategy, as opposed to a multicloud architecture. So we're helping our enterprise clients think about their multicloud strategy. So they're not locked in to any one vendor, so they're able to take advantage of all the great innovations that are happening, if you ask me, on the cloud first, and then ultimately comes down to, at times, on-prem. >> What's the pitfalls between multicloud strategy and multicloud architecture, you just said, customers don't want to get locked in, obviously, no-one wants to get locked in, multi-vendor used to be a big buzzword, during that last wave of computer-to-client server. >> Yeah. >> Now multicloud seems like multi-vendor, what do you mean by architecture versus strategy, how do you parse that? Yeah, so like I said, in terms of your data, right, and it all comes back to your data. If you go all in on, say, one vendor, and you're architecting for that vendor only and you're choosing your migration, your data management tools, for a particular cloud vendor, and, said a different way, if you're only using the native tools from that vendor, then it's very difficult to ever move off of that cloud, or to take advantage of other clouds as they, for example, maybe have new IOT offerings, or have new blockchain offerings, or have new AI offerings, as many others come on the scene. And so, that's what I mean by strategy, is if you choose one vendor for, your certain toolset, then it's going to be very difficult to maintain arbitrage between the different vendors. >> Talk about how you guys are attacking the market, obviously, it's clear that data, has been a fundamental part of WANdisco's value proposition. Moving data around has been a top concern, even back in the Hadoop days, now it's in the cloud. >> Yeah. >> Moving data across the network, whether it's cloud to cloud, or cloud to data center, or to the edge of the network-- >> Yep. Yep. >> Is a challenge. >> You know at IBM, when I was there in 2016, and we're coming up with our strategy when I was in Corp Dev. We talked about four different areas of data, we talked about data gravity, so data has gravity. We talked about data movement, and we talked about data science. And we talked about data governance. And I still think those are still relatively the four major themes around this topic of data. And so, absolutely data has gravity, and not just in terms of the absolute size and weight, if you will. But it also has applications that depend on it, the business itself depends on it, and so, the types of strategies that we've seen to migrate data, say, to the cloud, or have a hybrid data management strategy, has been lift and shift, or to load it on to the back of, I always picture that image of the forklift lifting all those tape drives onto the airplane, you know, the IBM version of that. And that's like a century old at this point, so, we have a way to replicate data continuously, using our patented consensus technology, that's in the lifeblood of our company, which is distributed computing. And so having a way, to migrate data to the cloud, without disrupting your business, is not just marketing speak, but it's really what we are able to do for our clients. How do you guys go to market, how do you guys serve customers, what's the strategy? >> So, primarily we've formed a number of strategic partnerships, obviously one with IBM that I helped spearhead while I was there, we actually just recently announced that we now support Big SQL, so it's actually the first opportunity where, if you are using a database, provided by IBM, you can actually replicate across different databases and still query it with Big SQL. Which is a big deal, right, it means you can still have access to your data while it's in motion, right, that's pretty cool. And then so IBM is there, and then secondly, we've formed a number of other strategic partnerships with the other cloud vendors, of course, Alibaba we have an OEM, Microsoft, we have preferred selling motion with them, AWS, of course, we're in their marketplace. So primarily, we sell through a number of our key partnerships, because, we are, fairly integrated, like I said, into the architecture of these platforms, and, just to comment more deeply on that, when you look at, object storage, on each of these various public cloud vendors. They may look similar on the surface, maybe they all use the same APIs or have some level of, similar interaction, they look like they're the same, the pricing might be the same. We go like one level deeper, and they're all very different, they're all very different flavors of object storage. And so while it might seem like, "Oh, that's trivial to work with," it really isn't, it's extremely non-trivial, so, we help, not only our customers solve that, but we also help our partners significantly, help their clients move to the cloud, to their cloud, faster. >> So you basically work through people who sell your product, to the end user customer, or through their application or service. >> Yeah, that's our main route to market, I would say, the other, obviously, the main, we have a direct sales force, who's out there, working with the best clients in the world. AMD is a great customer of ours, who we recently helped migrate to Microsoft Azure. And we have a number of other large enterprise customers, in retail, and finance, and media. And so really, when it comes down to it, yeah it's those two majors motions, one through the cloud vendors themselves, 'cause frankly, in most cases, they don't have this technology to do it, you know, they're trying to basically take snapshots of data, and they're struggling to convince their customers to move to their cloud. >> It becomes a key feature in platforms. >> Yes it does. >> So that's obviously what attracts sellers, what other things would attract sellers or partners, for you, what motivates them, obviously the IP, clearly, is the number one, economics, what's the other value proposition? >> The end goal isn't to move data to the cloud, the end goal is to move business processes to the cloud, and then be able to take advantage of the other value adds that already exist in the cloud. And so if you're saying, what's the benefit there, well, once you do that move, then you can sell into, clients with all your additional value adds. So that's really powerful, if you are stuck with this stage of "Eh, how do we actually migrate data to the cloud?" >> So IBM Think is coming up, what's your view of what's happening there, what are you guys going to be doing there, as are you, on the IBM side-- >> Yeah. >> Now you're on the other side of the table. You've been on both sides of the table. >> Yeah. >> So what's goin' on at Think, and how does WANdisco, vector, and certainly CUBE will be there. >> Yeah, we'll be there, so WANdisco is a sponsor of IBM Think as well, clearly, as I mentioned, we'll be talking about Big Replicate, which is our Hadoop replication offering, that's sold with IBM. The other one, as I mentioned, is Big SQL, so that's a new offering that we just announced this past month. So we'll be talking about that, and showing a number of great examples of how that actually works, so if you're going to be at Think, come by our booth, and check that out. In addition to that, I mean, clearly, IBM is also talking about multicloud and hybrid cloud, so hybrid data management, hybrid cloud is a big topic. You can expect to see, at IBM Think, a lot of conversations on the application side. In terms of, obviously with their acquisition of Red Hat, you can well imagine they're going to be talking a lot about the software stack, there. But I would say that, we'll be talking, and spending most of our time talking about, how to manage your data across different environments. >> Where's the product roadmap heading, I know you guys don't like to go into specifics in public- >> Yeah. >> Sensitive information, but, generally speaking, where's the main trendlines that you guys are going to be building on, obviously, cloud data, they'll come in together, good core competency there for WANdisco, what's next, what's the next level for you guys? >> So what's really fascinating, and I actually didn't realize this when I joined WANdisco, just to be completely transparent. WANdisco has a core piece of technology called DConE, Distributed Coordination Engine. It essentially is a form of blockchain, really, it's a consensus technology, it's an algorithm. And that's been their secret sauce since the founding of the company. And so they originally applied that to code, through source code management, and then only in this last few years they've applied it to data. So you can guess, at other areas that we might apply it to, and already this past year, we actually filed two patents, in the area of blockchain, or really, distributed ledger technology, as we're starting to hear it called in the actual enterprise that's using it. But you can expand that to any other enterprise asset, really. That's big, right, that has value, and that you want to manage across different environments, so you can imagine, lots of other assets that we could apply this to, not only code, not only data, not only ledgers, but what are the other assets? And so that's essentially what we're working on. >> Is that protectable IP the patents, so those are filed on the blockchain? >> Yeah, yeah. >> For instance? >> So DConE is certainly patented, I'm sure Jagane'll talk more about this. >> Yeah, we'll get into it. >> There's probably a handful of people in the world, and they might all be working at WANdisco at this point. (chuckles) Who actually know how that works, and it's essentially Paxos, which is a really gnarly problem to solve, a really difficult math problem. And as David mentioned earlier, Google, the other smartest company in the world, published their paper on Spanner, and as you said, they used brute force, really, to solve the problem. Where we have a very elegant solution, using software, right? So it's a really great time to be at WANdisco, because I just see that there's so many applications of our technology, but, right now, we're mainly focused on what our customers are asking for. >> You've said a great quote, thanks Joe, final question for you, where do you see it going, WANdisco, what are your plans, do you have anything in mind, do you want to share anything notable, around what you're doing, and what you think WANdisco will be in a few years. >> We have an incredible team, as I mentioned, the people that are joining WANdisco, as David mentioned, I myself, not to say too much there, but, the new folks that have joined our Research and Development Team, but we've been making some great hires, to WANdisco. So I'm really excited about the team, I'm going, actually, to visit, we have a great team in Europe, in the UK, in the United Kingdom, so I'm going to go see them next week. But we have just the company culture is what drives me, I think that's just one of those hard things, really, to find. And so that's what I'm really excited about, so there's a lot of cool stuff happening there. You know, on that note, it's actually kind of funny, because on one of the articles that talked about live data for multicloud, asked the question, and her headline was "Are You Down to Boogie?" So, disco continues to be a great meme for us, with our name. (John chuckles) Unintentional, so, as a marketer, it's a pretty fun time to be at WANdisco. >> Seventies and eighties were great times, certainly I'm an eighties guy, Joel, thanks for comin' on, appreciate the update, Joel Horowitz, CMO, Chief Marketing Officer, WANdisco, really on a nice wave right now, cloud growth, data growth, all comin' together, real IP, lookin' forward to hearing more, what comes down the pipe for those guys, you'll see him at IBM Think. I'm John Furrier here, in the studios at Palo Alto, thanks for watching. (soaring orchestral music)

(upbeat instrumental music) >> Welcome to the special CUBE Conversation here, in Palo Alto, I'm John Furrier, host of theCUBE. I'm here with David Richards the CEO of WANdisco, CUBE alumni, been on many times. WANdisco continues to make the right bets. The bet they recently made has been on cloud many years. We've covered it certainly on theCUBE. But live data is the new hot thing. Multiple clouds is turning out to be the trend. That's your friend. David, good to see you. >> Great to be back. >> Thanks for coming on. So we talk all the time about how you guys have always evolved the business and continued to stay out front in all the major waves. Now again, another good call. You've certainly bet on Cloud. We've talked about that, Open Source, Big Data, Cloud, you saw that coming, positioned for that. But now you got some great momentum and resonance with customers around live data, which is not a stretch, given what you guys have done with replication, things in the past, the core intellectual property. Give us the update. You guys have been in the news lately. >> So, thanks and I think you enumerated the past history over the past two or three years, which we like to say that we're living in dog years. Everything's happening seven times faster than it would do normally. So of course, we started out life by making a prediction that storage arrays would change. People are beginning to store, companies beginning to store structured and unstructured data, mammoth sizes that we've never seen previously. We're going to have to resort to Open Source software, running a commoditized hardware that we'd already seen the social media companies move to. Then we've seen, we began to see a problem emerge, even in that marketplace, where spike computes all the applications which were going to be heavily compute, would need to run in Cloud and Cloud environments where you have complete elastic compute at remarkably low cost. And that leads to a problem. So this iceberg kind of that we like to talk about underneath the oceans, so moving data for static archival data really simple problem. And that's not live data, that's archival data. You just FTP it from point A to point B. But if we're talking about transactional systems where 10, 20, 30, 40, 50 percent of the data set changes all of the time, that creates a humongous problem in moving data from one premises to cloud, either for hybrid cloud or between clouds for multi-cloud. And that's the precise problem that WANdisco solves. And we've seen customer attraction, recently we've just announced the deal, jointly with Microsoft Azure. Where a big healthcare company, who 12 months ago were not talking about cloud suddenly they got over that hump where security keys could be managed by themselves within the cloud, were able to move petabytes-scale data from their on-premise systems into the cloud, without any interruption to service, without any blocking. That's a trend that we're seeing our pipelines now full of companies, all trying to do that. >> It's like you hit the oil gusher with data, because the data tsunami has been there, and we've documented certainly on theCUBE, and our Research team at Wikibon, have been talking about it for years, and now you're starting to see it, and you guys are getting the benefits of it, is that people figured out that it's moving data around is expensive. And it's hard to do so you push compute to the edge, but you still got to move the data around because the key part of the latency piece of the cloud. So how do you do that at scale? So this is the thing that you guys have, and I want you to explain what it is. You guys have live data from multi-cloud. What does that mean? What is all the hubbub about? What's the buzz? Why is this such a hot topic, live data from multi-cloud. >> Okay so let's just take a step back and talk about what multi-cloud actually is in today's definition, which is the vendor's definition, which is very convenient. So what they mean is, moving, putting applications into a container, Kubernetes or whatever, picking it up and shifting it somewhere else. And hey presto, I've got applications running, the same applications running in two different clouds. That is not multi-cloud because you're forgetting about the data, and the iceberg underneath the ocean of this colossal amount of data. If I've got petabyte-scale, multi-terabyte-scale data sets, and I need to run the same applications, or different applications but against the same data set, I need guaranteed consistent data, and that is, by definition, a data consistency problem. It is not a data replication problem. So all of the stuff that we used to use in the past for gigabyte-scale data, for traditional, relational database problems, none of that stuff works in a live data world. And by live data, we're talking about multi-terabyte, petabyte-scale data. Data sets that are so large that we've never seen them before running in end cloud locations. It's different or same applications, but guaranteed consistent data in every location. >> So you guys have had this core composite around integrity around the data, whether it's in replication. Sounds like the same thing's true around moving data. >> Yep. >> You guys are managing the life cycle of end-to-end of data movement. >> Yep. >> Point A to point B. >> Yep. >> The other approach is to move compute to the data. >> Yep. >> We're just seeing Amazon do a deal with VMware on-premise. So there's two schools of thought. When should customers think about each approach? Can you just kind of debunk or just clarify those two positions? >> So it's not really a chicken and egg because we know which comes first. It's definitely the chicken. It's definitely the data. So if I'm going to rebuild my application infrastructure, in the cloud, I'm going to do it piece-by-piece. I can't do lift-and-shift for a thousand applications that are running against this data set and just hope that the data that block for six months because I've got petabyte-scale data, and wait for it to all arrive in the cloud, or put it to the back of you know, use a snowmobile or some physical device to move the data. I need to do this, I need to kind of build the aircraft while it's taking off and flying and that's probably a good analogy. So what we see, is companies the first step is to get consistent data on-premise to cloud, or between different clouds. Then what that enables me to do of course, is to piece-by-piece then rebuild my application infrastructure at the pace that I want to. I mean there's a great add that I keep on seeing on t.v. Where it's migration day. As though I can press a button and then suddenly you know, in this Alice in Wonderland magical world, everything just appears. Realistically, and I saw the CEO of VMware a couple of years ago talk about being in a hybrid cloud scenario for 20 years. I think that's probably accurate. We've got billions of applications. A mix of homegrown stuff, a mix of, you know, actuarial applications in the insurance industry that are impossible to build overnight. This is going to take an elongated period of time. >> I was talking on Twitter with a bunch of thought leaders. We were talking about hybrid cloud and multi-cloud, and the kindergarten class is hybrid, right? >> Yeah. >> So you got some public cloud, then you got some on-premise data center. So getting that operational thing nailed down is great. But as you get old, you know, you progress in the grades, and get smarter, as you increase your I.T. I.Q., you're dealing with multiple, potentially multiple data centers or bigger on site, or an IOT edge, and multiple clouds. >> Yep. >> So that sounds easy on paper, but when you have to move data around the different work loads, that's the core problem that people are talking about today. How do you guys address this problem? Because I buy multi-cloud, I can see that certain tools and certain clouds the right work load and the right cloud, I get that. >> Yeah. It makes a lot of sense to me. The data is the problem. >> Yep. >> So how do you guys address that? This is the number one concern. >> So the closest, people ask me all the time about competition. The closest is Google. Google have got a product called Google Spanner. And Google Spanner is a time-sensitive, active-active WAN-scope data replication solution. That looks on paper very close to what WANdisco does. It enables them to keep active data in all of their different geolocations that they've built for their add services years and years and years ago. The trouble with that is, it only works on their own proprietary network, against their own proprietary applications because they launched a satellite and stuck it in the sky, they put dark fiber under the ocean, and they put GPS atomic clocks on every single one of their servers because it uses time and time accuracy in order to synchronize all of their data. We can do all of that over the public internet. So we're not a hardware solution. This is a pure software solution that can work over the public internet. So we can do that for any cloud vendor, and any provider of applications. And that's what we do. We're licensing our I.P. all over the place at the moment. >> So which clouds are, I imagine there's a great uptake for the clouds. Which one are you working with now? Can you talk about the deals you've done? >> We're very close. We announced the Azure partnership with Microsoft, and their Azure product, and we've been very impressed with the traction that we're seeing with them, particularly an enterprise cloud. I mean the early stage of cloud obviously was dominated by Amazon, Amazon Web Services. And they did a fantastic job of really bringing cloud to the market by accident kind of inventing cloud and then bringing it to market very very quickly. The fastest ever company to, if it's and independent company to 15 billion dollars, but most of those applications and projects and companies were born in the cloud. I mean a lot of the modern companies today were actually of course, you have Airbnb et cetera, were born in the cloud. So that, the second inning of cloud is certainly enterprise. We've also been impressed with the traction that we've seen from Google GCP as being extremely impressive. And of course Amazon continued to thrive. In cloud we also have an OEM deal with Ali, with Alibaba with their cloud as well. So they're really the only full. >> If Google has Spanner, how do you differentiate between Google Spanner? >> So Google Spanner only works on their proprietary network. Which is great for Google and between their data centers, but what about 99.9 percent of the rest of the problem, which is the rest of us right, who operate on the public internet. So we can do what Google Spanner does active-active, geo, one scope replication of data but over the public internet. >> So you guys have been talking active-active for many times. We've had many conversations here on theCUBE. So I get that. How has your business changed with cloud? You had mentioned prior to coming on camera. You made a bet on cloud. It's paying off obviously. People who have made the right bets on cloud at the right time, it's certainly paying off. You're one of them. How does the live data in the multi-cloud change your business? Does it increase your trajectory? Is there a pivot? I mean what does it mean for WANdisco? >> So the very, so my thesis or the company's thesis, I won't take the credit for it, but the company's thesis was really simplistic, which is our bet was in the small data world of gigabyte-scale data, in order to do data replication, small data equals small outage. When you get data sets that are growing exponentially, and you get, you know, data sets through a thousand or a million times greater than what we've seen previously, what was a small outage or small blocking of client applications will become an elongated blocking of client applications that we're talking about, you know, six months to move 20 petabytes of data. You can't block applications, business critical applications for six months. That was the bet that we made. We expected initially to see that happen on-premise in the data like world, in the Hadoop world if you will. That didn't quite happen, or has not happen to date. We don't think that's probably going to happen. We're certainly seeing a huge desire of companies moving those data lakes into cloud, and we've actually innovated, we've got some new inventions coming out that enable you to move in a single pass, massive quantity of data that will be exponentially faster than anything else, and just doing a unidirectional data move into clouds. That was our bet that we said "Okay, companies in order to achieve the kind of scale "that they need to achieve, "they're going to have to do this in cloud." "In order to get to cloud, "they're going to have to move that data there, "and they're not going to be able to block even for a day "in order to move that data to cloud." And that was the bet we made, and it was the right bet. >> Talk about where you guys go from here. Give a company update. What's the status of the company? Get some new personnel? Any changes, notable updates? >> So we, really interestingly, my Co-Founder and Chief Scientist is a genius, Dr. Yeturu Aahlad, Ph.D. from UT, and undergrad from IIT, a new VP of Engineering Sakthi, IIT, Ph.D. at U.T. under Draxler. This fantastic Ph.D. program they did there. My new Head of Research came from, was Chairman of Computer Science at the University of Denver. He's was an IIT undergrad, Ph.D with Aahlad at UT. And I said jokingly to Aahlad: "There must be a fourth guy "that we can bring on board here "that went through the same program." He said, "We can but we can't hire him, "because he's the CTO of Microsoft, so." That was, he was the forth guy. Joel, who I know, is going to be coming on theCUBE shortly. He also has joined us from IBM to run Marketing for us. So we've made some fantastic new hires. The company's doing really well. You know cloud certainly has played a big part in the second half of last year. I think it's going to play a big part. It's definitely going to play a big part in 2019. We've seen a pivot in pipeline, that's moved away from possibly even disaster recovery, data lake in the first half of last year. We pivoted to more of a reliable subscription revenue in the second half of the year. We announced some pretty big deals, big healthcare companies. We've got really good public reference with AMD. We announced a motor vehicle company one of the new used cases there is four petabytes of data per day they're generating. That all has to be moved from on-premise to cloud. So we've got some ginormous deals in pipeline. We'll see how they play out in the coming weeks and months. >> It's great to see the change, and certainly on theCUBE. We've been talking, I think we've known each other for almost, this is our tenth year. >> Yeah. Ever since we first met. It's fun to see how you guys entered the market at Hadoop, staying on the data wave and thinking enterprise, integrity of the data, active-active, the key I.P. And how cloud is just assumed data, and it's not just data, it's large scale. So if you look at the new people you hired, you've got jobs in large scale systems. >> Yep. >> We're talking about a large systems, now data is just given. So you're really nailing the large scale, moving from an enterprise nice feature, certainly table stakes for fault tolerance, and active-active. Just add recovery to mission critical >> Yep. >> Ingredient in large scale cloud. >> Well it's ironic isn't it because our value actually increases with the volume of data. So we're an unusual company in that context where the larger the data site, the greater the problem, and the greater the problem that we solve. See we made a pretty good bet, the active-active replication, that live data would be a critical component of both hybrid cloud and multi-cloud. And that's playing out I think really well for us. >> And certainly a lot more changes to come. Great to have you on. >> Yeah. >> Cloud and multi-cloud. Certainly cloud has proven the economics proven large scale value of moving at cloud speed but now you have multiple clouds. That's going to change the game on applications, work loads. It's not going to change the data equation. There's still more tsunami of data that's not stopping. >> Exactly. >> I think you've got a good wave you're riding. >> Yeah. >> Data cloud wave. David Richards, CEO of WANdisco here in CUBE Conversations here in Palo Alto. I'm John Furrier, thanks for watching. (upbeat instrumental music)

Live from New York, it's theCUBE. Covering theCUBE, New York City 2018. Brought to you by SiliconANGLE Media and its ecosystem partners. >> Okay, welcome back everyone. This is theCUBE live in New York City for our CUBE NYC event, #cubenyc. This is our ninth year covering the big data ecosystem going back to the original Hadoop world, now it's evolved to essentially all things AI, future of AI. Peter Burris is my cohost. He gave a talk two nights ago on the future of AI presented in his research. So it's all about data, it's all about the cloud, it's all about live action here in theCUBE. Our next guest is David Richards, who's been in the industry for a long time, seen the evolution of Hadoop, been involved in it, has been a key enabler of the technology, certainly enabling cloud recovery replication for cloud, welcome back to theCUBE. It's good to see you. >> It's really good to be here. >> I got to say, you've been on theCUBE pretty much every year, I think every year, we've done nine years now. You made some predictions and calls that actually happened. Like five years ago you said the cloud's going to kill Hadoop. Yeah, I think you didn't say that off camera, but it might (laughing) maybe you said it on camera. >> I probably did, yeah. >> [John] But we were kind of pontificating but also speculating, okay, where does this go? You've been right on a lot of calls. You also were involved in the Hadoop distribution business >>back in the day. Oh god. >> You got out of that quickly. (laughing) You saw that early, good call. But you guys have essentially a core enabler that's been just consistently performing well in the market both on the Hadoop side, cloud, and as data becomes the conversation, which has always been your perspective, you guys have had a key in part of the infrastructure for a long time. What's going on? Is it still doing deals, what's? >> Yes, I mean, the history of WANdisco's play and big data in Hadoop has been, as you know because you've been with us for a long time, kind of an interesting one. So we back in sort of 2013, 2014, 2015 we built a Hadoop-specific product called Non-Stop NameNode and we had a Hadoop distribution. But we could see this transition, this change in the market happening. And the change wasn't driven necessarily by the advent of new technology. It was driven by overcomplexity associated with deploying, managing Hadoop clusters at scale because lots of people, and we were talking about this off-camera before, can deploy Hadoop in a fairly small way, but not many companies are equipped or built to deploy massive scale Hadoop distributions. >> Sustain it. >> They can't sustain it, and so the call that I made you know, actions speak louder than words. The company rebuilt the product, built a general purpose data replication platform called WANdisco Fusion that, yes, supported Hadoop but also supported object store and cloud technologies. And we're now seeing use cases in cloud certainly begin to overtake Hadoop for us for the first time. >> And you guys have a patent that's pretty critical in all this, right? >> Yeah. So there's some real IP. >> Yes, so people often make the mistake of calling us a data replication business, which we are, but data replication happens post-consensus or post-agreement, so the very heart of WANdisco of 35 patents are all based around a Paxos-based consensus algorithm, which wasn't a very cool thing to talk about now with the advent of blockchain and decentralized computing, consensus is at the core of pretty much that movement, so what WANdisco does is a consensus algorithm that enables things like hybrid cloud, multi cloud, poly cloud as Microsoft call it, as well as disaster recovery for Hadoop and other things. >> Yeah, as you have more disparate parts working together, say multi cloud, I mean, you're really perfectly positioned for multi cloud. I mean, hybrid cloud is hybrid cloud, but also multi cloud, they're two different things. Peter has been on the record describing the difference between hybrid cloud and multi cloud, but multi cloud is essentially connecting clouds. >> We're on a mission at the moment to define what those things actually are because I can tell you what it isn't. A multi cloud strategy doesn't mean you have disparate data and processes running in two different clouds that just means that you've got two different clouds. That's not a multi cloud strategy. >> [Peter] Two cloud silos. >> Yeah, correct. That's kind of creating problems that are really going to be bad further down the road. And hybrid cloud doesn't mean that you run some operations and processes and data on premise and a different siloed approach to cloud. What this means is that you have a data layer that's clustered and stretched, the same data that's stretched across different clouds, different on-premise systems, whether it's Hadoop on-premise and maybe I want to build a huge data lake in cloud and start running complex AI and analytics processes over there because I'm, less face it, banks et cetera ain't going to be able to manage and run AI themselves. It's already being done by Amazon, Google, Microsoft, Alibaba, and others in the cloud. So the ability to run this simultaneously in different locations is really important. That's what we do. >> [John] All right, let me just ask this directly since we're filming and we'll get a clip out of this. What is the definition of hybrid cloud? And what is the definition of multi cloud? Take, explain both of those. >> The ability to manage and run the same data set against different applications simultaneously. And achieve exactly the same result. >> [John] That's hybrid cloud or multi cloud? >> Both. >> So they're the same. >> The same. >> You consider hybrid cloud multi cloud the same? >> For us it's just a different end point. It's hybrid kind of mean that you're running something implies on-premise. A multi cloud or poly cloud implies that you're running between different cloud venues. >> So hybrid is location, multi is source. >> Correct. >> So but let's-- >> [David] That's a good definition. >> Yes, but let's unpack this a little bit because at the end of the day, what a business is going to want to do is they're going to want to be able to run apply their data to the best service. >> [David] Correct. >> And increasingly that's what we're advising our clients to think about. >> [David] Yeah. >> Don't think about being an AWS customer, per se, think about being a customer of AWS services that serve your business. Or IBM services that serve your business. But you want to ensure that your dependency on that service is not absolute, and that's why you want to be able to at least have the option of being able to run your data in all of these different places. >> And I think the market now realizes that there is not going to be a single, dominant vendor for cloud infrastructure. That's not going to happen. Yes, it happened, Oracle dominated in relational data. SAP dominated for ERP systems. For cloud, it's democratized. That's not going to happen. So everybody knows that Amazon probably have the best serverless compute lambda functions available. They've got millions of those things already written or in the process of being written. Everybody knows that Microsoft are going to extend the wonderful technology that they have on desktop and move that into cloud for analytics-based technologies and so on. The Google have been working on artificial intelligence for an elongated period of time, so vendors are going to arbitrage between different cloud vendors. They're going to choose the best of brood approach. >> [John] They're going to go to Google for AI and scale, they're going to go to Amazon for robustness of services, and they're going to go to Microsoft for the Suite. >> [Peter] They're going to go for the services. They're looking at the services, that's what they need to do. >> And the thing that we'll forget, that we don't at WANdisco, is that that requires guaranteed consistent data sets underneath the whole thing. >> So where does Fusion fit in here? How is that getting traction? Give us some update. Are you working with Microsoft? I know we've been talking about Amazon, what about Microsoft? >> So we've been working with Microsoft, we announced a strategic partnership with them in March where we became a tier zero vendor, which basically means that we're partnered with them in lockstep in the field. We executed extremely well since that point and we've done a number of fairly large, high-profile deals. A retailer, for example, that was based in Amazon didn't really like being based in Amazon so had to build a poly cloud implementation to move had to buy scale data from AWS into Azure, that went seamlessly. It was an overnight success. >> [John] And they're using your technology? >> They're using our technology. There's no other way to do that. I think the world has now, what Microsoft and others have realized, CDC technology changed data capture. Doesn't work at this kind of scale where you batch up a bunch of changes and then you ship them, block shipping or whatever, every 15 minutes or so. We're talking about petabyte scale ingest processes. We're talking about huge data lakes, that that technology simply doesn't work at this kind of scale. >> [John] We've got a couple minutes left, I want to just make sure we get your views on blockchain, you mentioned consensus, I want to get your thoughts on that because we're seeing blockchain is certainly experimental, it's got, it's certainly powering money, Bitcoin and the international markets, it's certainly becoming a money backbone for countries to move billions of dollars out. It's certainly in the tank right now about 600 million below its mark in January, but blockchain is fundamentally supply chain, you're seeing consensus, you're seeing some of these things that are in your realm, what's your view? >> So first of all, at WANdisco, we separate the notion of cryptocurrency and blockchain. We see blockchain as something that's been around for a long time. It's basically the world is moving to decentralization. We're seeing this with airlines, with supermarkets, and so on. People actually want to decentralize rather that centralize now. And the same thing is going to happen in the financial industry where we don't actually need a central transaction coordinator anymore, we don't need a clearinghouse, in other words. Now, how do you do that? At the very heart of blockchain is an incorrect assumption. So must people think that Satoshi's invention, whoever that may be, was based around the blockchain itself. Blockchain is pieced together technologies that doesn't actually scale, right? So it takes game-theoretic approach to consensus. And I won't get, we don't have enough time for me to delve into exactly what that means, but our consensus algorithm has already proven to scale, right? So what does that mean? Well, it means that if you want to go and buy a cup of coffee at the Starbucks next door, and you want to use a Bitcoin, you're going to be waiting maybe half an hour for that transaction to settle, right? Because the-- >> [John] The buyer's got to create a block, you know, all that step's in one. >> The game-theoretic approach basically-- >> Bitcoin's running 500,000 transactions a day. >> Yeah. That's eight. >> There's two transactions per second, right? Between two and eight transactions per second. We've already proven that we can achieve hundreds of thousands, potentially millions of agreements per second. Now the argument against using Paxos, which is what our technology's based on, is it's too complicated. Well, no shit, of course it's too complicated. We've solved that problem. That's what WANdisco does. So we've filed a patent >> So you've abstracted the complexity, that's your job. >> We've extracted the complexity. >> So you solve the complexity problem by being a complex solution, but you're making and abstracting it even easier. >> We have an algorithmic not a game-theoretic approach. >> Solving the scale problem Correct. >> Using Paxos in a way that allows real developers to be able to build consensus algorithm-based applications. >> Yes, and 90% of blockchain is consensus. We've solved the consensus problem. We'll be launching a product based around Hyperledger very soon, we're already in tests and we're already showing tens of thousands of transactions per second. Not two, not 2,000, two transactions. >> [Peter] The game theory side of it is still going to be important because when we start talking about machines and humans working together, programs don't require incentives. Human beings do, and so there will be very, very important applications for this stuff. But you're right, from the standpoint of the machine-to-machine when there is no need for incentive, you just want consensus, you want scale. >> Yeah and there are two approaches to this world of blockchains. There's public, which is where the Bitcoin guys are and the anarchists who firmly believe that there should be no oversight or control, then there's the real world which is permission blockchains, and permission blockchains is where the banks, where the regulators, where NASDAQ will be when we're trading shares in the future. That will be a permission blockchain that will be overseen by a regulator like the SEC, NASDAQ, or London Stock Exchange, et cetera. >> David, always great to chat with you. Thanks for coming on, again, always on the cutting edge, always having a great vision while knocking down some good technology and moving your IP on the right waves every time, congratulations. >> Thank you. >> Always on the next wave, David Richards here inside theCUBE. Every year, doesn't disappoint, theCUBE bringing you all the action here. Cube NYC, we'll be back with more coverage. Stay with us; a lot more action for the rest of the day. We'll be right back; stay with us for more after this short break. (upbeat music)

(regal music) >> Hi, I'm Peter Burris And welcome to another Cube conversation from our beautiful studios here in Palo Alto, California. Got another great guest today, Jagane Sundar is the CTO of WANdisco Jagane, welcome back to the Cube. >> Good morning, Peter. >> So, Jagane, I want to talk about something that I want to talk about. And I want you to help explicate for our clients what this actually means. So there's two topics that I want to discuss. We've done extensive research in both of them, and one is this notion that we call plastic infrastructure. And the other one, related, is something we call networks of data. Let's start with networks of data because I think that that's perhaps foundational for plastic infrastructure. If we look back at the history of computing, we've seen increasing decentralization of data. Yet today many people talk about data gravity and how the Cloud is going to bring all data into the Cloud. Our belief, however, is that there's a relationship between where data is located and the actions that have to be taken. And data locality has a technical reality to it. We think we're going to see more distribution of data, but in a way that nonetheless allows us to federate. To bring that data into structures that nonetheless can ensure that the data is valuable wherever it needs to be. When you think of the notion of networks of data, what does that make you think about? >> That's a very interesting concept, Peter. When you consider the Cloud, and you talk about S3 for example and buckets of objects, people automatically assume that it's a global storage system for objects. But if you scratch a little deeper under the surface you'll find that each bucket is located in one region. If you want it available in other regions you've got to set up something called cross-region replication, which replicates in an eventual consistent fashion. It may or may not get there in time. So even in the Cloud storage systems, there is a notion of locality of data. It's something that you have to pay attention to. Now you hit the nail on the head when you said networks of data. What does that mean? Where does the data go? How it is used. Our own platform, the Fusion platform for replication of data is a strongly consistent platform which helps you conform to legal requirements and locality of data and many such things. It was built with such a thing in mind. Of course, we didn't quite call it that way, but I like your way of describing it. >> So as we think then about where this is, the idea is, 40 years ago, ARPANET allowed us to create networks of devices in a relatively open application-oriented way. And the web allowed us to create networks of pages of content. But again, that content was highly stylized. More recently social media's allowed us great networks of identities. All very important stuff. Now as we start talking about digital business and the fact that we want to be able to rearrange our data assets very quickly in response to new business opportunities whether it's customer experience or operational-oriented, this notion of networks of data allows us to think about the approach to doing that, so that we can have the data being in service to existing business opportunities, new business opportunities, and even available for future activities. So we're talking about creating networks out of these data sources, but as you said, to do that properly, we need to worry about consistency, we need to worry about cost. The platform for doing this, Fusion is a good one, it's going to require over time, however we think, some additional types of capabilities. The ability to understand patterns of data usage, the ability to stage data in advance and predictably, et cetera. Where do you think this goes as we start conceiving of networks of data as a fundamental value proposition for technology and business? >> Sure, one of the first things that occurs to me when you talk about a network of data, if you consider that as parallel to a network of computers, you don't have a notion of things like read-only computers whereas read-write computers. That's just silly. You want all computers to be roughly equal in the world. If you have a network of servers, and a network of computers, any of them can read. Any of them can write, and any of them can store. Now our Fusion platform brings about that capability to your definition of a network of data. What we call live data is the ability for you to store replicas of the data in different data centers around the world with the ability to write to any of those locations. If one of the locations happens to go down, it's a non-event. You can continue writing and reading from the other locations. That truly makes the first step towards building this network of data that you're talking about feasible. >> But I want to build on that notion a little bit because we are seeing increased specialization for example, AI, or GPUs. >> Sure. >> AI-specific processors, so even though we are still looking forward to general purpose nonetheless we see some degree of specialization. But let me also take that notion of live data and say I expect that we're going to see something similar. So for example, the same data set can be applied to multiple different classes of applications where each application may take advantage of underlying hardware advantages. But you don't have a restriction on how you deploy it built into the data. Have I got that right? >> Absolutely. Our Fusion platform includes the capability to replicate across Cloud vendors. You can replicate your storage between Amazon S3 and Azure Blob store. Now this is interesting because suddenly, you may discover that Redshift is great for certain applications while Azure SQLDW is better for others. We give you the freedom to invent new applications based on what location is best suited for that purpose. You've taken this concept of network of data, you've applied a consistent replication platform, now you have the ability to build applications in different worlds, in completely different worlds. And that's very interesting to us because if we look at data as the primary asset of any company, consider a company like Netflix, their data and the way they manage their data is the most important thing to that company. We bring the capability to distribute that data across different Cloud vendors, different storage systems, and run different applications. Perhaps you have a GPU heavy Cloud that maybe a GPU vendor offers. Replicate your data into that Cloud, and run your AI applications against that particular replica. We give you truly the freedom to invent new applications for your purpose. >> But very importantly, you are also providing, and I think this is essential, a certainty that there's consistency no matter how you do it. And I think that's the basis of the whole, the Paxos algorithms you guys are using. >> Exactly. The fundamental fact is this. Data scientists hate to deal with outdated data. Because all the work they're doing may be for no use if the data that they're applying it to is outdated, invalid, or partially consistent. We give you guarantees that the data is constantly updated, live data, it's completely consistent. If you ask the same question of two replicas of your data, you will get exactly the same answer. There is no other product in the industry today that can offer that guarantee. And that's important for our customers. >> Now building on the foundation, we're going to have to add some additional things to it. So pattern recognition, ML inside the tool. Is that on the drawing board? And I don't want you to go too far in the future, but is that kind of the future that you see too? >> We are a platform company with an excellent plug-in API. And one of the uses of our plug-in API, I'll give you a simple example, we have banking customers and they need to prevent credit card numbers from flying over the wire under certain circumstances. Our plug-in API enables them to do that. Applying an ML intelligence program into the plug-in API, again, a very simple development effort to do that. We are facilitating such capabilities. We expect third-party developers. We already have a host of third-party developers and companies building to our plug-in API. We expect that to be the vehicle for this. We won't claim expertise in ML, but there are plenty of companies that will do that on our platform. >> All right, so that leads to the second set of questions that I wanted to ask you about. We've defined what we call plastic infrastructure as a future for the industry. And to make sense of that, what we've done is we've said let's take a look at three phases of infrastructure, not based on the nature of the hardware, but based on the fundamental capabilities of the infrastructure. Static infrastructure is when we took an application, we wired it to a particular class of infrastructure. New load hits it, often you broke the infrastructure. Elastic infrastructure is the ability to be able to take a set of workloads and have it vary up and down, so that you can consume more and release the infrastructure so it has a kind of a rubber orientation. You hit it with a new load, it will deform for as long as you need it to, then it snaps back into shape. So you've predictability about what your costs are. We think that increasingly digital business is going to have to think about plastic infrastructure. The ability to very rapidly have the infrastructure deform in response to new loads, but persist that new shape, that new structure in response to how the load has impacted the business if in fact that is a source of value for the business. >> Sure. >> What do you think about that notion of plastic infrastructure? >> I love the way you describe it. In our own internal terminology we have this notion of live data and freedom to invent. What you've described is exactly that. The plastic infrastructure matches exactly with our notion of freedom to invent. Once you've solved the problem of making your data consistently available in different Clouds, different regions, different data centers, the next step of course is the freedom to invent new applications. You're going to throw experimental things at it. You're going to find that there are specific business intelligence that you can draw from this by virtue of a new application. Use it to make some critical decisions, improve profitability perhaps. That results in what you describe as plastic infrastructure. I really love that description by the way. Because we've gone from, the Cloud brought us plastic infrastructure, we've replicated, we've built a system that enables innovation and invention of new ideas. That's plastic infrastructure. I really like the idea that you're proposing. >> So as you think about this concept of plastic infrastructure, obviously there's a lot of changes that're going to take place in the industry. But Fusion in particular, by providing consistency, by increasing the availability, more importantly even the delivery of data where it's required facilitates at that data level, that notion of plasticity. >> Absolutely. The notion that you can throw brand new applications at it in a Cloud vendor of your choice, the fact that we can replicate across different Clouds is important for plastic infrastructure. Perhaps there are certain applications that work better in one Cloud versus the other. You definitely want to try it out that. And if that results in some real valuable applications, continue running it. So your definition that elastic becomes plastic infrastructure matches perfectly with that. We love this notion that we take the CIO's problems of mundane data management away and introduce the capability to invent and innovate in their space. >> So let me give you a very, or let me ask you a very practical, simple question. Historically, the back-up and restore people, and the application development people didn't spend a lot of time with each other, and that has created some tension. Are we now because of our ability to do this live data, are we able to bring those two worlds more closely together so that developers can now think about building increasingly complex, increasingly rich applications? And at the same time ensure that the data that they're building and testing with is in fact very close to the live data that they're actually going to use. >> Absolutely. We do bridge that gap. We enabled application developers to think of more complex, more sophisticated applications without actually worrying about the availability or the consistency of data. And the IT administrators and the CIO run operations that need to deliver that, have the confidence that they can in fact deliver it with the levels of consistency and availability that they need. >> So I'm going to give you the last word in this. I talked about a fair amount now, about this notion of networks of data, and infrastructure plasticity, where do you think this kind of matures over the course of the next four or five years? And what's your peer CTOs of large businesses that are thinking about these challenges of data management be focusing on? >> So the first thing that you have to acknowledge is that people need to stop thinking about machines and servers, and consider this as infrastructure that they acquire from different Cloud vendors. Different Cloud vendors because in fact there is going to be a few, a handful of good Cloud vendors that'll give you different capabilities. Once you get to that conclusion, you need your data available in all of these different Cloud vendors perhaps on your on-prem location as well, with strong consistency. Our platform enables you to do that. Once you get to that point, you have the freedom to build new applications, build business-critical systems that can depend on the consistency and availability of data. That is your definition of plasticity and networks of data. I truly like that. >> Yeah, and so we, great, great summary. We would say that we would agree with you, that increasing with the CIO, or the CDO, whoever it's going to be, has to focus on how do I increase returns on my business's data, and to do that they need to start thinking differently about their data, about their data assets, both now and in the future. Very, very important stuff. Jagane, thank you very much for being on the Cube. >> Thank you, Peter. >> And once again, I'm Peter Burris, and this has been a Cube conversation with Jagane Sundar, CTO of WANdisco. Thanks again. (regal music)

(intense orchestral music) >> Hi I'm Peter Burris, welcome to another CUBEConversation. Today we've got a special guest from WANdisco, Jagane Sundar, who's the CTO, Jagane, welcome to theCUBE again! >> Thanks Peter, happy to be here! >> So Jagane, we've got a lot to talk about today, WANdisco's doing a lot of new things, but clearly the industry is, itself, in the midst of a relatively important evolution. Now we at Wikibon and SiliconANGLE have been calling it the transformation to digital business. Everybody talks about this, but we've been pretty specific, we think that it boils down to how a company uses data as an asset, and the degree to which it's institutionalizing, or re-institutionalizing work around those assets. How does WANdisco see this big transformation that we're in the midst of right now? >> So, you're exactly right, businesses are transforming from traditional means to a digital based business, and the most important thing about that is the data. WANdisco is at the forefront of making your data available for your innovation. We start off with the basic use-cases, disaster recovery, that's a traditional problem that people have half-solved in many different ways, but we have the ability to solve that problem, take you to the next stage, which is what we call live data, where you don't worry about the availability or the location of your data anymore. Finally, we take you from that live data platform to a place where you can invent with your data, the freedom to invent phase of our--of what we call. Now, that's what you're calling the digital transformation and there's great synergy between our two terminologies, that's an important aspect here. >> So let me impact that a little bit, if I can. So the core notion is: that every business has to start acknowledging that data is something more than the exhaust that comes out of applications, it really is a core data asset. So let's start with this notion of backup and restore, or disaster recovery, the historical orientation is: I have these very expensive assets, typically in the form of hardware, or maybe applications, and I have to ensure that I can back those assets up. So backup restore used to be back up a device, backup a volume, backup whatever else it might be, and now it's moved to more of a backup of a virtual machine. I think we're talking about something different when we talk about your approach to backup and restore we're really talking about backing up data assets, do I have that right? >> That is correct. You have gone from a place where you are backing up PC's and Macintosh's and cellphones, to a place where the digital assets of your company, that are useful analytics, are far more important. Now, a simple backup, where you take the contents in one data center, push it to another data center, are a half-solution to the problem. What we've come up with is this notion called live data. You have multiple data centers, some of them you own, they're on premise, some of them are Cloud vendor data centers, they definitely reside in different parts of the world. Your data also is generated in different parts of the world, now all of this data goes into this data system, this platform that we've built for you, and it's available under all circumstances. If a region of a Cloud vendor goes down or if your own data center goes down, that's a non-event, because that data is available in other data centers around the world. This gives you the flexibility to treat this as a live data platform. You can write data where you want, you can read and run analytics wherever you want. You've gone from backing up PC's and phones, to actually using your digital assets in a manner such that you can make critical business decisions based on that. Imagine that insurance company that's making-- underwriting policies based on this digital data. If the data's not available, you've got a full halt on the business, that's not acceptable. If the data is not available because a specific data center went down, you can't call a full-stop to your business, you've got to make it available. Those are simple examples of how digital transformation is happening, and regular backup and DR are really inadequate to fuel your digital transformation. >> In fact, we like to think, we're advising our clients, that as they think about digital transformation, the role that data's playing, a digital business is not just backing up and restoring or sustaining or avoiding disasters associated with the data, they're really talking about backing up and restoring their entire business. That's kind of what we mean when we talk about DR in the digital business sense, disaster recovery, or backup and recovery, restore, in a digital business sense. And as you said, this notion of live data increases our ability to do that, but partly that requires a second kind of a step. By that I mean, most people think about storage, they think about where data's located in terms of persisting the data. When we talk about this new approach, we're talking about ensuring that we can deliver the data. Restore takes on more importance than backup than it has before, would you agree with that? That really talking about live data is really about being able to restore data wherever it's needed. >> It's an interesting new approach where we don't really define a primary and a backup. One of the important things about our Paxos-based replication system is that each location, or each instance, replica of your data, is exactly equal. So if you have a West Coast data center, and an East Coast data center, and a Midwest data center, and your West Coast data center happens to go down, none of the activities that you perform on your data will stop, you can continue writing your data to your Midwest and your East Coast data center, you continue writing and reading, running your applications against this data set. Now there wasn't a definition that the West Coast is primary and East Coast is backup. When a disaster strikes, we will cut over to the backup, we'll start using that, when the primary comes back, now we have to reconcile it, that's the traditional way of doing things, and it brings about some really bad attributes. Such as you need to have all your data pumped into one data center, that's counter to our philosophy. We believe that live data is where each of these replicas is equal, we build a platform for you where you can write to any of these, you can run your analytics against any of those. Once you get past that mental hurdle, what you've got is the freedom to innovate. You can look at it and go: I've got my data available everywhere, I can write to it, I can read from it, what can I do with this data? How can I quickly iterate so I can make more interesting business decisions, more relevant business decisions that will result in better business, profits and revenue. This interesting outcome is because you're now, not concerned about the availability of data or the primary, backup, and failover and failback, all those disappear from your radar. >> So let me build on that a little bit too, Jagane. So the way we would describe that is that a digital business, most have those data assets, those crucial data assets available, so that they can be delivered to applications and new activities, so we think in terms, what we call data zones, where the idea, you take a look at what your digital business value proposition is, what activities are essential to delivering on that value proposition, and then, whether or not the data is in a zone approximate to that activity, so that activity can actually be executed. So that means, from a physical standpoint, it needs to be there, from a legal standpoint, from a intellectual property control, from cost, but also from a consistency standpoint, you don't want dramatically different behaviors in your business just because the data that's over there is not consistent with the data that's over here, that's kind of what you guys are looking at. Now, ultimately that means, going out a little bit, but ultimately that means that this notion of deploying data so it serves your business now, has to also include a futures orientation. That we want to choose technologies that give us high value options on data futures as well. Is that what you mean by effectively, freedom to invent? >> It's definitely one aspect of our definition of freedom to invent. We are focused fully on complying with some of these requirements that you talked about. Regions of data, for example, there are parts of the world where you cannot take the data from that part of the world outside but often you need to do analytics in a global manner, such that if you detect a flaw or a problem that is surfaced by data in one part of the world, the chances are very good that that'll apply to this restricted zone as well. You want to be able to apply your analytics against that. Critical business decisions may need to be made, yet you cannot export that data out of that country, we facilitate such capabilities. So we've gone from a simpler primary backup type of system to a live data platform. And finally, we've given you the freedom to invent because you can now take a look at it and go I can start building applications that are in the critical business path because I'm confident of the availability of my data, the fact that we comply with all regulatory consilience things like aging out data after a certain number of months or days, we can help you do that really well with our platform. So yes, in fact the notion that data resides in different pools, in different areas, replicated consistently, available under all circumstances, enables business to think about their data in a completely different manner, up-level it. >> And satisfying physical, legal, intellectual property, and cost realities. >> Exactly. Those are all consilience that need to be addressed by this replication platform. >> So as we think about where customers are going with this clearly they've started around this backup and restore, but it sounds like you guys are helping them today conceive of what it means to do backup and restore and analytics, that is a particularly sensitive issue for a lot of businesses right now that are trying to marry together data science and good practices associated with IT. How is that playing out, can you give us some insight into how customers are doing a better job of that? >> Sure. A global auto maker that has acquired our software can do replication started off by using it for two very simple use-cases. They were looking at migrating from an older version of a data system to a newer version, we enabled them to do that without downtime, that was a clear win for us. The second thing they wanted to do was enable a disaster recovery type scenario. Once we got to that stage, we showed them how easy it was for them to continue writing to what was originally notionally the backup system, that made about twice as much compute resources available for them, because their original notion was that the backup system would just be a backup system, nothing could be done on it. Light bulbs went off in our customers head, they looked at it and went I can continue writing here, even if my primary goes down, there's no real notion of a backup, there's no real notion of failover and failback, that opened their minds to a whole bunch of new ideas. Now, they are in a position to build some business critical applications. Gone are the days when an analytics thing meant you run a report once a week and send it off to the CIO, it's not that anymore, it's up to minute accuracy, people are making things like insurance companies making underwriting decisions, and healthcare companies tracking the spread of diseases based on up to the minute information that they're getting. These are not weekly once analytics applications anymore, these are truly businesses that are based on their digital data. >> So a fundamental promise of live data is that wherever the data is, the application is live? >> Jagane: Yes, absolutely. >> Alright one more thing I think we want to talk about very quickly Jagane is there is some differences in mindset that a CIO has to apply here, again the CIO used to look at the assets and say machines, the hardware, yes, and maybe the applications, and now, to really see the value of this, they have to think of this in terms of data being the asset. How are your customers starting to evolve that notion so that they see the problem differently? >> So, I think the first thing that happened was the Cloud, we can't take credit for that, of course, but it helped our costs a great deal because people looked at infrastructure with a completely different viewpoint. They don't look at it as I'm going to buy a server with this size to run my Oracle, that mentality went away, and people started looking at, I have to store my data here and I can run an elastic application on this, I can grow our resources on demand and surrender those resources back to the Cloud when I don't need that. We take that to the next step, we enable them to have consistent replicas of their data across multiple regions of Cloud vendors, across different Cloud vendors. Suddenly they have the ability to do things like, I can run this analytics on Redshift here in Amazon really well, I can use this same data to run it on Azure SQL DW here, which is a better application for this specific use-case. We've opened up the possibilities to them, such that, they don't worry about what data they're going to use, how much resources they're going to get, resources are truly elastic now, you can buy and surrender resources, as per your demand, so it's opening up possibilities that they never had before. >> Excellent! Jagane Sundar, CTO of WANdisco, talking about live data, and the journey the customers are on to make themselves more fully digital businesses. >> Thanks, Peter. >> Once again this is Peter Burris from theCUBE, CUBEConversation with Jagane Sundar of WANdisco. (intense orchestral music)

>> Voiceover: Live from the Moscone Center, it's theCUBE. Covering AWS Summit San Francisco 2018. Brought to you by Amazon Web Services. >> Welcome back, I'm Stu Miniman and this is theCUBE's exclusive coverage of AWS Summit here in San Francisco. Happy to welcome back to the program Jagane Sundar, who is the CTO of WANdisco. Jagane, great to see you, how have you been? >> Well, been great Stu, thanks for having me. >> All right so, every show we go to now, data really is at the center of it, you know. I'm an infrastructure guy, you know, data is so much of the discussion here, here in the cloud in the keynotes, they were talking about it. IOT of course, data is so much involved in it. We've watched WANdisco from the days that we were talking about big data. Now it's you know, there's AI, there's ML. Data's involved, but tell us what is WANdisco's position in the marketplace today, and the updated role on data? >> So, we have this notion, this brand new industry segment called live data. Now this is more than just itty-bitty data or big data, in fact this is cloud-scale data located in multiple regions around the world and changing all the time. So you have East Coast data centers with data, West Coast data centers with data, European data centers with data, all of this is changing at the same time. Yet, your need for analytics and business intelligence based on that is across the board. You want your analytics to be consistent with the data from all these locations. That, in a sense, is the live data problem. >> Okay, I think I understand it but, you know, we're not talking about like, in the storage world there was like hot data, what's hot and cold data. And we talked about real-time data for streaming data and everything like that. But how do you compare and contrast, you know, you said global in scope, talked about multi-region, really talking distributed. From an architectural standpoint, what's enabling that to be kind of the discussion today? Is it the likes of Amazon and their global reach? And where does WANdisco fit into the picture? >> So Amazon's clearly a factor in this. The fact that you can start up a virtual machine in any part of the world in a matter of minutes and have data accessible to that VM in an instant changes the business of globally accessible data. You're not simply talking about a primary data center and a disaster recovery data center anymore. You have multiple data centers, the data's changing in all those places, and you want analytics on all of the data, not part of the data, not on the primary data center, how do you accomplish that, that's the challenge. >> Yeah, so drill into it a little bit for us. Is this a replication technology? Is this just a service that I can spin up? When you say live, can I turn it off? How do those kind of, when I think about all the cloud dynamics and levers? >> So it is indeed based on active-active replication, using a mathematically strong algorithm called Paxos. In a minute, I'll contrast that with other replication technologies, but the essence of this is that by using this replication technology as a service, so if you are going up to Amazon's web services and you're purchasing some analytics engine, be it Hive or Redshift or any analytics engine, and you want to have that be accessible from multiple data centers, be available in the face of data center or entire region failure, and the data should be accessible, then you go with our live data platform. >> Yeah so, we want you to compare and contrast. What I think about, you know, I hear active-active, speed of light's always a challenge. You know globally, you have inconsistency it's challenging, there's things like Google Spanner out there to look at those. You know, how does this fit compared to the way we've thought of things like replication and globally distributed systems in the past? >> Interesting question. So, ours great for analytics applications, but something like Google Spanner is more like a MySQL database replacement that runs into multiple data centers. We don't cater to that and database-transaction type of applications. We cater to analytics applications of batch, very fast streaming applications, enterprise data warehouse-type analytics applications, for all of those. Now if you take a look inside and see what kind of replication technology will be used, you'll find that we're better than the other two different types. There are two different types of existing replication technologies. One is log shipping. The traditional Oracle, GoldenGate-type, ship the log, once the change is made to the primary. The second is, take a snapshot and copy differences between snapshots. Both have their deficiencies. Snapshot of course is time-based, and it happens once in a while. You'll be lucky if you can get one day RTO with those sorts of things. Also, there's an interesting anecdote that comes to mind when I say that because the Hadoop folks in their HTFS, implemented a version of snapshot and snapdiff. The unfortunate truth is that it was engineered such that, if you have a lot of changes happening, the snapshot and snapdiff code might consume too much memory and bring down your NameNode. That's undesirable, now your backup facility just brought down your main data capability. So snapshot has its deficiencies. Log shipping is always active/passive. Contrast that with our technology of live data, whereat you can have multiple data centers filled with data. You can write your data to any of these data centers. It makes for a much more capable system. >> Okay, can you explain, how does this fit with AWS and can it live in multi-clouds, what about on-premises, the whole you know, multi and hybrid cloud discussion? >> Interesting, so the answer is yes. It can live in multiple regions within the same cloud, multiple reasons within different clouds. It'll also bridge data that exists on your on-prem, Hadoop or other big data systems, or object store systems within Cloud, S3 or Azure, or any of the BLOB stores available in the cloud. And when I say this, I mean in a live data fashion. That means you can write to your on-prem storage, you can also write to your cloud buckets at the same time. We'll keep it consistent and replicated. >> Yeah, what are you hearing from customers when it comes to where their data lives? I know last time I interviewed David Richards, your CEO, he said the data lakes really used to be on premises, now there's a massive shift moving to the public clouds. Is that continuing, what's kind of the breakdown, what are you hearing from customers? >> So I cannot name a single customer of ours who is not thinking about the cloud. Every one of them has a presence on premise. They're looking to grow in the cloud. On-prem does not appear to be on a growth path for them. They're looking at growing in the cloud, they're looking at bursting into the cloud, and they're almost all looking at multi-cloud as well. That's been our experience. >> At the beginning of the conversation we talked about data. How are customers doing you know, exploiting and leveraging or making sure that they aren't having data become a liability for them? >> So there are so many interesting use cases I'd love to talk about, but the one that jumps out at me is a major auto manufacturer. Telematics data coming in from a huge number, hundreds of thousands, of cars on the road. They chose to use our technology because they can feed their West Coast car telematics into their West Coast data center, while simultaneously writing East Coast car data into the East Coast data center. We do the replication, we build the live data platform for them, they run their standard analytics applications, be it Hadoop-sourced or some other analytics applications, they get consistent answers. Whether you run the analytics application on the East Coast or the West Coast, you will get the same exact answer. That is very valuable because if you are doing things like fault detection, you really don't want spurious detection because the data on the West Coast was not quite consistent and your analytics application was led astray. That's a great example. We also have another example with a top three bank that has a regulatory concern where they need to operate out of their backup data centers, so-called backup data center, once every three months or so. Now with live data, there is no notion of active data center and backup data center. All data centers are active, so this particular regulatory requirement is extremely simple for them to implement. They just run their queries on one of the other data centers and prove to the regulators that their data is indeed live. I could go on and on about a number of these. We also have a top two retailer who has got such a volume data that they cannot manage it in one Hadoop cluster. They use our technology to create the live data data link. >> One of the challenges always, customers love the idea of global but governance, compliance, things like GDPR pop up. Does that play into your world? Or is that a bit outside of what WANdisco sees? >> It actually turns out to be an important consideration for us because if you think about it, when we replicate the data flows through us. So we can be very careful about not replicating data that is not supposed to be replicated. We can also be very careful about making sure that the data is available in multiple regions within the same country if that is the requirement. So GDPR does play a big role in the reason why many of our customers, particularly in the financial industry, end up purchasing our software. >> Okay, so this new term live data, are there any other partners of yours that are involved in this? As always, you want like a bit of an ecosystem to help build out a wave. >> So our most important partners are the cloud vendors. And they're multi-region by nature. There is no idea of a single data center or a single region cloud, so Microsoft, Amazon with AWS, these are all important partners of ours, and they're promoting our live data platform as part of their strategy of building huge hybrid data lakes. >> All right, Jagane give us a little view looking forward. What should we expect to see with live data and WANdisco through the rest of 2018? >> Looking forward, we expect to see our footprint grow in terms with dealing with a variety of applications, all the way from batch, pig scripts that used to run once a day to hive that's maybe once every 15 minutes to data warehouses that are almost instant and queryable by human beings, to streaming data that pours things into Kafka. We see the whole footprint of analytics databases growing. We see cross-capability meaning perhaps an Amazon Redshift to an Azure or SQL EDW replication. Those things are very interesting to us, to our customers, because some of them have strengths in certain areas and other have strengths in other areas. Customers want to exploit both of those. So we see us as being the glue for all world-scale analytics applications. >> All right well, Jagane, I appreciate you sharing with us everything that's happening at WANdisco. This new idea of live data, we look forward to catching up with you and the team in the future and hearing more about the customers and everything on there. We'll be back with lots more coverage here from AWS Summit here in San Francisco. I'm Stu Miniman, you're watching theCUBE. (electronic music)

>> Announcer: Live from Las Vegas It's theCube covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. >> Welcome back to our live coverage. theCube here at AWS re:Invent 2017 Our fifth year covering Amazon Web Services and their massive growth. I'm John Furrier, my co-host Lisa Martin. Here our next guest is CTO of WANdisco, Jugane Sundar. Welcome back to theCube. >> Thank you John. >> You guys are everywhere. WANdisco around the table and all these deals so you guys have been doing extremely well with (indistinct talking) property. What's new? You got some news? >> Yes we do, we recently announced integration with Amazon's AWS Snowball device which gives you the ability to do migration of on-premises workload into the Cloud without down time, and then the end result is a hybrid cloud environment that you can have an active for right environment on both sides. That's a unique capability, nobody else can do that today. >> What does it mean for AWS and their customers 'cause they're very customer focused. What are you guys bringing to the table? >> We bring a whole lot of big data workloads, analytics workloads, IoT workloads into their Cloud. And the beauty of the cloud is that you may have a 20 node cluster on-premises but you can run analytics with a 1000 nodes up in the Cloud on demand and pay just for that use. We think it's a very powerful value proposition. >> Where are you seeing the most traction? We've talking about the massive growth at 18 billion dollar annual runway that fit AWS and Andy's conversation with you John the other day said we haven't gotten that big on startups alone. So even some of the things like the advertising that AWS is now starting to do suggests they're going up the stack to the Enterprise and to the Sea Suites. Where are you guys seeing the most traction with AWS? Is it in the Enterprise space, is it in the start up space, both? >> So somewhat because of our route, what we're finding is that the large majority of Big Data customers and analytics customers from the last two, three years are all considering some form of addition of a cloud to their environment. If it's not a wholesale migration, it's a hybrid environment. It's bursting out into the cloud type of use case and what you're finding is that growth of on-premise Big Data and analytics systems is slowing down because once you get to the Cloud, the plethora of tools you have, the facilities that the scale brings to you is just unmatched. That's the trend we really see in the market. >> We've seen a lot of people go and use it in the marketplace. Juniper Networks for instance, are seeing some activity at the network. Who would have thought a network player is gonna to pick it in the Cloud, but this is what industrial-strength cloud looks like. You guys have the active active. Where does that fit in for the customers who wanna leverage the apps, and don't wanna worry about the networks? >> Exactly, the traditional model of thinking was use the Cloud for back up. You have your on-premise stuff. The cheapest way to back it up is into the Cloud. But that's really just scratching the tip of the iceberg. Once you put your data up in the Cloud, you have the ability to have it strongly consistently replicated then you can do amazing things from the Cloud. You can do a whole new analytics system. Perhaps you want to experiment with Spark in the Cloud and have it on on high on-premise that works very well. Now that both sides are actively writeable, you can create partitions of your data that are dynamically generated written to both sides. These are things that people did not consider. Once they stumble upon it, it just opens their mind to a whole new way of operating. >> Business Park, I've heard some rumors and rumblings in the developer community here that they're running Spark on Lando. People always hacking with new stuff. So Lando server list I think is coming down. How does that relate to some of things that are driving WANdisco's, how do you relate to that? Does that help you? Does that hurt you guys? >> It helps us, the way we look at it. We're all about strong replication of storage. Lando is no storage, you talk to the underlying storage of some kind. It's S3, it's EBS volumes whatever. So long as the storage comes through our system. Any growth, any simple easy way for applications to be written is hugely positive for us. >> What are the start ups out there? We've seen a lot of start ups really missed the mark. They misfired on the Cloud and you seen some stars that have played it well. They've got in the tornadoes as we say. In fact, Geoffrey Moore, I think is rewriting his book Inside the Tornado, which is a management paradigm. But there really seems to be a new business model. You guys are like ever green at WANdisco because you're unique (indistinct talking) property. How are you guys working with that business model and what are some of the things you're seeing with start ups and companies who are trying to play the cloud but are misfiring? >> Right so WANdisco as you know stands for Wide Area Network Distributed Computing, and the Cloud is like a huge bonus to it. It's all about the Wide Area Network. We are now consolidating a bunch of work in the cloud, but guess what? It's gonna go back to going to go into the edge in some way 'cause the edges are getting smarter. You need replication between those. We see a lot of that coming up in the next two, three, five years. IoT workloads and use cases all involve somewhat of edge smart computing. We replicate between those really well. >> Lisa, we always talk about the trend is your friend. In your case, Cloud is your friend. >> Indeed, it is. The Cloud is all about wide area network computing and we are the ones who can really replicate-- >> How does a customer know what to do when it comes down to getting involved with WANdisco? It's not obvious. Spell it out, why do they need you guys? When do you get involved? What specific things should be red flags to a potential customer or a customer who says I'm gonna go in on the Cloud. Unpack that. >> Let me give you a simple example. We look at Amazon S3, it's a Cloud service storage. But do you know that it's actually on a per region basis. When you create a bucket to put objects into the bucket, it's located in one region. If you want it replicated elsewhere, they have cross-region replication which is an eventually consistent replication system that doesn't give you the consistent results that you want. If you have such a situation employing our technology immediately gives you consistent replication. Be it Cloud regions, Cloud to Cloud or on-premise to Cloud. The end result is the minute you step into replication across the land, every solution out there doesn't do it consistently and that's our core-- >> And that's your unique IP. >> Indeed, it is. >> Okay so I'm seeing Amazon racing their roll out regions. They got one coming in China, one in the Middle East. That's a big part of the strategy. Does that help you or what does that do? >> Absolutely it helps us a great deal, partly because customers now do not look at their applications as a single region applications. That doesn't fly anymore. The the notion that my banking app cannot work because a data center went down is just not acceptable in the modern world anymore. The fact that we depend so much on the services means they need to be up all the time. More regions, more data replication. That's why we step in. >> So that sounds like a lot of symbiosis here. You talk about S3 and replication challenges. So tell us how WANdisco is actually helping AWS. That's one example but help you us understand the symbiosis with your relationship with AWS. >> The best example I can give you is a large travel service company in the internet. They had to Adobe infrastructure that was growing out of control. They wanted to manage costs by moving some workloads to Amazon but didn't really know where to start, because you can't do such a thing as take a copy of the data, ship it off on a Snowball into the Cloud and tell the users of that data, stop writing to it now. It's gonna be available in the Cloud, a week, 10 days from now. Then you can start writing again. That's just not acceptable. This is live data problem. The problem here is that you need to be able to ship out your data on Snowballs, continue to write the on-premise storage. When it shows up in the Cloud, start writing that. Both are consistently replicated, you have a proper hybrid Cloud environment. So this was a great bonus to them. As for AWS, they watched this and they look at it as a easy way to move vast majority of data from on-premise big Data analytics systems. >> Have they been a fuel to your fire, in a sense that they've been on this incredible acceleration of their innovation and as Andy Joci said many times to you John. It's speed and customer focus. So how has their accelerated pace of innovation helped fuel WANdisco's so that like you were saying the unique value. How have they really ignited that? >> So they started off with just plain Snowball two years ago. Last year they announced Snowball Edge which is a pretty improved device. Now they have in the works, capability to do some compute on those boxes. That's very interesting to us. Now our services can decide on the Snowball, It arrives at a customer site. He plugs it in, turns it on instant replication capabilities Those are fueled both by Amazon's drive and extreme speed and our own capabilities. So Amazon is a wonderful partner for us partly because their charge to us innovation is quite amazing. >> Snowball, snow mobile, it's gonna be a white Christmas for you guys. Business is good. >> Business is great. >> Okay, final question. What's the conversations you're having here this year, share with us some of the quick conversations you're having in the hallways, meetings, Amazon got execs, partners. >> So most of the conversation are about moving workloads from on-premise into the Cloud. I personally am very interested in IoT use cases because I see the volume of data and the ability for us to do some interesting replications at being critical. That's where our focus is right now. >> Jugane Sundar, CTO of WANdisco. Big announcement, partnership with Amazon Web Services and Snowball replication active active. Great solution for replication. You got regions across regions. Check out WANdisco. Thanks for coming by, great to see you again. Congratulations on all your success. This is theCube, live coverage day one. It's coming down to an end. The halls open, we got two more days of packed two Cubes. Stay tuned for more, we got some great guest coming up, stay with us. (uptempo techno music)

>> Announcer: Live from midtown Manhattan, it's theCUBE, covering BigData New York City 2017, brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Okay welcome back everyone here live in New York City. This is theCUBE special presentation of our annual event with theCUBE and Wikibon Research called BigData NYC, it's our own event that we have every year, celebrating what's going on in the big data world now. It's evolving to all data, cloud applications, AI, you name it, it's happening. In the enterprise, the impact is huge for developers, the impact is huge. I'm John Furrier, cohost of the theCUBE, with Peter Burris, Head of Research, SiliconANGLE Media and General Manager of Wikibon Research. Our next guest is Jagane Sundar, who's the CTO of WANdisco, Cube alumni, great to see you again as usual here on theCUBE. >> Thank you John, thank you Peter, it's great to be back on theCUBE. >> So we've been talking the big data for many years, certainly with you guys, and it's been a great evolution. I don't want to get into the whole backstory and history, we covered that before, but right now is a really, really important time, we see you know the hurricanes come through, we see the floods in Texas, we've seen Florida, and Puerto Rico now on the main conversation. You're seeing it, you're seeing disasters happen. Disaster recovery's been the low hanging fruit for you guys, and we talked about this when New York City got flooded years and years ago. This is a huge issue for IT, because they have to have disaster recovery. But now it's moving more beyond just disaster recovery. It's cloud. What's the update from WANdisco? You guys have a unique perspective on this. >> Yes, absolutely. So we have capabilities to replicate between the cloud and Hadoop multi data centers across geos, so disasters are not a problem for us. And we have some unique technologies we use. One of the things we do is we can replicate in an active-active mode between different cloud vendors, between cloud and on-prem Hadoop, and we are the only game in town. Nobody else can do that. >> So okay let me just stop right there. When you say the only game in town I got a little skeptic here. Are you saying that nobody does active-active replication at all? >> That is exactly what I'm saying. We had some wonderful announcements from Hortonworks, they have a great product called the Dataplane. But if you dig deep, you'll find that it's actually an active-passive architecture, because to do active-active, you need this capability called the Paxos algorithm for resolving conflict. That's a very hard algorithm to implement. We have over 10 years' experience in that. That's what gives us our ability to do this active-active replication, between clouds, between on-prem and cloud. >> All right so just to take that a step further, I know we're having a CTO conversation, but the classic cliche is skate to where the puck is going to be. So you kind of didn't just decide one morning you're going to be the active-active for cloud. You kind of backed into this. You know the world spun in your direction, the puck came to you guys. Is that a fair statement? >> That is a very fair statement. We've always known there's tremendous value in this technology we own, and with the global infrastructure trends, we knew that this was coming. It wasn't called the cloud when we started out, but that's exactly what it is now, and we're benefiting from it. >> And the cloud is just a data center, it's just, you don't own it. (mumbles) Peter, what's your reaction to this? Because when he says only game in town, implies some scarcity. >> Well, WANdisco has a patent, and it actually is very interesting technology, if I can summarize very quickly. You do continuous replication based on writes that are performed against the database, so that you can have two writers and two separate databases and you guarantee that they will be synchronized at some point in time because you guarantee that the writing of the logs and the messaging to both locations >> Absolutely. >> in order, which is a big issue. You guys put a stamp on the stuff, and it actually writes to the different locations with order guaranteed, and that's not the way most replication software works. >> Yes, that's exactly right. That's very hard to do, and that's the only way for you to allow your clients in different data centers to write to the same data store, whether it's a database, a Hadoop folder, whether it's a bucket in a cloud object store, it doesn't matter. The core fact remains, the Paxos algorithm is the only way for you to do active-active replication, and ours is the only Paxos implementation that can work over the >> John: And that's patented by you guys? >> Yes, it's patented. >> And so someone to replicate that, they'd have to essentially reverse engineer and have a little twist on it to not get around the patents. Are you licensing the technology or are you guys hoarding it for yourselves? >> We have different ways of engaging with partners. We are very reasonable with that, and we work with several powerful partners >> So you partner with the technology. >> Yes. >> But the key thing, John, in answer to your question is that it's unassailable. I mean there's no argument, that is, companies move more towards a digital way of doing things, largely driven by what customers want, your data becomes more of an asset. As you data becomes more of an asset, you make money by using that data in more places, more applications and more times. That is possible with data, but the problem you end up with consistency issues, and for certain applications, it's not an issue, you're basically writing, or if you're basically reading data it's not an issue. But the minute that you're trying to write on behalf of a particular business event or a particular value proposition, then now you have a challenge, you are limited in how you can do it unless you have this kind of a technology. And so this notion of continuous replication in a world that's going to become increasingly dependent upon data, data that is increasingly distributed, data that you want to ensure has common governance and policy in place, technologies like WANdisco provides are going to be increasingly important to the overall way that a business organizes itself, institutes its work and makes sure it takes care of its data assets. >> Okay, so my next question then, thanks for the clarification, it's good input there and thanks for summarizing it like that, 'cause I couldn't have done that. But when we last talked, I always was enamored by the fact that you guys have the data center replication thing down. I always saw that as a great thing for you guys. Okay, I get that, that's an on-premise situation, you have active-active, good for disaster recovery, lot of use cases, people should be beating down your door 'cause you have a better mousetrap, I get that. Now how does that translate to the cloud? So take me through why the cloud now fits nicely with that same paradigm. >> So, I mean, these are industry trends, right. What we've found is that the cloud object stores are very, very cost effective and efficient, so customers are moving towards that. They're using their Hadoop applications but on cloud object stores. Now it's trivial for us to add plugins that enable us to replicate between a cloud object store on one side, and a Hadoop on the other side. It could also be another cloud object store from a different cloud provider on the other side. Once you have that capability, now customers are freed from lock-in from either a cloud vendor or a Hadoop vendor, and they love that, they're looking at it as another way to leverage their data assets. And we enable them to do that without fear of lock-in from any of these vendors. >> So on the cloud side, the regions have always been a big thing. So we've heard Amazon have a region down here, and there was fix it. We saw at VMworld push their VMware solution to only one western region. What's the geo landscape look like in the cloud? Does that relate to anything in your tech? >> So yes, it does relate, and one of the things that people forget is that when you create an Amazon S3 bucket, for example, you specify a region. Well, but this is the cloud, isn't it worldwide? Turns out that object store actually resides in one region, and you can use some shaky technologies like cross-region replication to eventually get the data to the other region. >> Peter: Which just boosts the prices you pay. >> Yes, not just boost the price. >> Well they're trying to save price but then they're exposed on reliability. >> Reliability, exactly. You don't know when the data's going to be there, there are no guarantees. What we offer is, take your cloud storage, but we'll guarantee that we can replicate it in a synchronous fashion to another region. Could be the same provider, could be another provider. That gives tremendous benefits to the customers. >> So you actually have a guarantee when you go to customers, say with an SLA guarantee? Do you back it up with like money back, what's the guarantee? >> So the guarantees are, you know we are willing to back it up with contracts and such like, and our customers put us through rigorous testing procedures, naturally. But we stand up to every one of those. We can scale and maintain the consistency guarantees that they need for modern businesses. >> Okay, so take me through the benefits. Who wants this? Because you can almost get kind of sucked into the complexities of it, and the nuances of cloud and everything as Peter laid out, it's pretty complex even as he simplified it. Who buys this? (laughs) I mean, who's the guy, is it the IT department, is it the ops guy, is it the facilities, who... >> So we sell to the IT departments, and they absolutely love the technology. But to go back to your initial statement, we have all these disasters happening, you know, hopefully people are all doing reasonably okay at the end of these horrible disasters, but if you're an enterprise of any size, it doesn't have to be a big enterprise, you cannot go back to your users or customers and say that because of a hurricane you cannot have access to your data. That's sometimes legally not allowed, and other times it's just suicide for a business >> And HPE in Houston, it's a huge plant down there. >> Jagane: Indeed. >> They got hit hard. >> Yep, in those sort of circumstances, you want to make sure that your data is available in multiple data centers spread throughout the world, and we give you that capability. >> Okay, what are some of the successes? Let's talk through now, obviously you've got the technology, I get that. Where's the stakes in the ground? Who's adopting it? I know you do a lot of biz dev deals. I don't know if they're actually OEM-type deals, or they're just licensing deals. Take us through to where your successes are with this technology. >> So, biz dev wise, we have a mix of OEM deals and licenses and co-selling agreements. The strong ones are all OEMs, of course. We have great partnerships with IBM, Amazon, Microsoft, just wonderful partnerships. The actual end customers, we started off selling mostly to the financial industry because they have a legal mandate, so they were the first to look into this sort of a thing. But now we've expanded into automobile companies. A lot of the auto companies are generating vast amounts of data from their cars, and you can't push all that data into a single data center, that's just not reasonable. You want to push that data into a single data store that's distributed across the world in just wherever the car is closest to. We offer that capability that nobody else can, so that we've got big auto manufacturers signed up, we've got big retailers signed up for exactly the same capability. You cannot imagine ingesting all that data into a single location. You want this replicated across, you want it available no matter what happens to any single region or a data center. So we've got tremendous success in retail, banking, and a lot of this is through partnerships again. >> Well congratulations, I got to ask, you know, what's new with you guys? Obviously you have success with the active-active. We'll dig into the Hortonworks things to check your comment around them not having it, so we'll certainly look with the Dataplane, which we like. We interviewed Rob Bearden. Love the announcement, but they don't have the active-active, we're going to document that, and get that on the record. But you guys are doing well. What's new here, what's in New York, what are some of your wins, can you just give a quick update on what's going on at WANdisco? >> Okay, so quick recap, we love the Hortonworks Dataplane as well. We think that we can build value into that ecosystem by building a plugin for them. And we love the whole technology. I have wonderful friends there as well. As for our own company, we see all of our, a lot of our business coming from cloud and hybrid environments. It's just the reality of the situation. You had, you know, 20 years ago, you had NFS, which was the great appender of all storage, but turned out to be very expensive, and you had 10 years, seven years ago you had HDFS come along, and that appended the cost model of NFS and SANs, which those industries were still working their way through. And now we have cloud object stores, which have appended the HDFS model, it's much more cost-efficient to operate using cloud object stores. So we will be there, we have replication products for that. >> John: And you're in the major clouds, you in Azure? >> Yes, we are in Azure. >> Google? >> Jagane: Yes, absolutely. >> AWS? >> AWS, of course. >> Oracle? >> Oracle, of course. >> So you got all the top four companies. >> We're in all of them. >> All right, so here's the next question is, >> And you're also in IBM stuff too. >> Yes, we're built tightly into IBM >> So you've got a pretty strong legacy >> And a monopoly. >> On the mainframe. >> Like the fiber channel of replication. (John and Jagane laugh) That was a bad analogy. I mean it's like... Well, I mean fiber channel has only limited suppliers 'cause they have unique technology, it was highly important. >> But the basic proposition is look, any customer that wants to ensure that a particular data source is going to be available in a distributed way, and you're going to have some degree of consistency, is going to look at this as an option. >> Yes. >> Well you guys certainly had a great team under your leadership, it's got great tech. The final question I have for you here is, you know, we've had many conversations about the industry, we like to pontificate, I certainly like to speculate, but now we have eight years of history now in the big data world, we look back, you know, we're doing our own event in New York City, you know, thanks to great support from you guys and other great friends in the community. Appreciate everyone out there supporting theCUBE, that's awesome. But the world's changed. So I got to ask you, you're a student of the industry, I know that and knowing you personally. What's been the success formula that keeps the winners around today, and what do people need to do going forward? 'Cause we've seen the train wreck, we've seen the dead bodies in the industry, we've kind of seen what's happened, there've been some survivors. Why did the current list of characters and companies survive, and what's the winning formula in your opinion to stay relevant as big data grows in a huge way from IoT to AI cloud and everything in between? >> I'll quote Stephen Hawking in this. Intelligence is the capability to adapt to changes. That's what keeps industries, that's what keeps companies, that what keeps executives around. If you can adapt to change, if you can see things coming, and adapt your core values, your core technology to that, you can offer customers a value proposition that's going to last a long time. >> And in a big data space, what is that adaptive key focus, what should they be focused on? >> I think at this point, it's extracting information from this volume of data, whether you use machine learning in the modern days, or whether it was simple hive queries, that's the value proposition, and making sure the data's available everywhere so you can do that processing on it, that remains the strength. >> So the whole concept of digital business suggests that increasingly we're going to see our assets rendered in some form as data. >> Yes. >> And we want to be able to ensure that that data is able to be where it needs to be when it needs to be there for any number of reasons. It's a very, very interesting world we're entering into. >> Peter, I think you have a good grasp on this, and I love the narrative of programming the world in real time. What's the phrase you use? It's real time but it's programming the world... Programming the real world. >> Yeah, programming the real world. >> That's a huge, that means something completely, it's not a tech, it's a not a speed or feed. >> Well the way we think about it, is that we look at IoT as a big information transducer, where information's in one form, and then you turn it into another form to do different kinds of work. And that big data's a crucial feature in how you take data from one form and turn it into another form so that it can perform work. But then you have to be able to turn that around and have it perform work back in the real world. There's a lot of new development, a lot of new technology that's coming on to help us do that. But any way you look at it, we're going to have to move data with some degree of consistency, we're still going to have to worry about making sure that if our policy says that that action needs to take place there, and that action needs to take place there, that it actually happens the way we want it to, and that's going to require a whole raft of new technologies. We're just at the very beginning of this. >> And active-active, things like active-active in what you're talking about really is about value creation. >> Well the thing that makes active-active interesting is, again, borrowing from your terms, it's a new term to both of us, I think, today. I like it actually. But the thing that makes it interesting is the idea that you can have a source here that is writing things, and you can have a source over there that are writing things, and as a consequence, you can nonetheless look at a distributed database and keep it consistent. >> Consistent, yeah. >> And that is a major, major challenge that's going to become increasingly a fundamental feature of our digital business as well. >> It's an enabling technology for the value creation and you call it work. >> Yeah, that's right. >> Transformation of work. Jagane, congratulations on the active-active, and WANdiscos's technology and all your deals you're doing, got all the cloud locked up. What's next? Well you going to lock up the edge? You're going to lock up the edge too, the cloud. >> We do like this notion of the edge cloud and all the intermediate steps. We think that replicating data between those systems or running consistent compute across those systems is an interesting problem for us to solve. We've got all the ingredients to solve that problem. We will be on that. >> Jagane Sundar, CTO of WANdisco, back on theCUBE, bringing it down. New tech, whole new generation of modern apps and infrastructure happening in distributed and decentralized networks. Of course theCUBE's got it covered for you, and more live coverage here in New York City for BigData NYC, our annual event, theCUBE and Wikibon here in Hell's Kitchen in Manhattan, more live coverage after this short break.

>> Narrator: Live from Manhattan, it's theCUBE, covering AWS Summit New York City 2017, brought to you by Amazon Web Services. >> And welcome back to New York, here. AWS Summit, theCUBE continue our coverage of what's happening here in the Big Apple. I'm John Walls along with Stu Miniman, and what this is is maybe not the most prolific CUBE guest of all time, but he's in the hall of fame. He really is a CUBE MVP for sure. It's good to have David Richards with us, the president, chairman, CEO of WANdisco. Good to see you, sir. >> It's a pleasure to be back again. It feels like home. >> It is like home. We need to get you your own microphone, I think, you know? >> David: I know it. I need my name on the back of the seat or something. >> This isn't quite a home game for you. All right, so you've got an office in Sheffield, England. >> David: Yeah. >> You've got an office out in the valley, Silicon Valley. We got ya right in the middle, I think. >> David: Yeah. >> Almost, don't we? So-- >> Exactly. >> We kind of split the difference for you this one. >> I always tell people I'm recolonizing the United States. I've been here for about 20 years. I can change the accent. >> Right. >> I'll get you all, eventually. >> All right, well, another year or two, we'll see how that works for ya. Big, big, I guess six, seven months for you, right? As far as some acquisitions you've done, some vice partnerships and arrangements you've done. >> Yes, as a business, we've really progressed well in the first half of the year. I've got to be a little bit careful. We've got results coming out September the sixth in London, but we did do a pre-announcement of a business update. We signed a record big data cloud contract with a very large bank for over four million dollars. That was our largest ever contract win. We signed a major retailer who we can't name, obviously, which is another sort of cloud ObjectStore on premises. A big data win, and interestingly, we stopped burning cash and investors really like this kind of perfect storm of, 175%, 173% growth in our cloud big data revenue, booking, sorry, combined with a flat cost-base, which meant, first half of last year, burning five point four million dollars down to virtually zero, just $600,000 in the first half. So, investors really like that. We really like that, and it demonstrates that perfect storm of flat cost-base and growing sales. >> David, I'm curious, does working with Amazon, and your customers being on Amazon, does the speed and agility and everything like that contribute to that profitability? >> Well, Amazon kind of changes the game for all vendors, right? Because nobody, it used to be this sort of big four, five, six, whatever it is these days, consulting companies that had to implement ERP systems and all those complex applications. I don't necessarily think they're the people, they're not the go-to people anymore for cloud. So, it's down to uniqueness of technology. Amazon have got such a wide array, we were talking earlier about some of their announcements out today as they continue to go up the stack with applications and so on. So, it does lend itself very well to small vendors with sticky, unique intellectual property and unique products and services that are going to really thrive in this kind of cloud environment. So, we've really enjoyed working with Amazon, but we're also working with the other cloud vendors, as well, and I have to say, when we first saw the Snowmobile and the Snowball, well, actually, the Snowmobile, drive out on stage in New York, was it 12, 18 months ago? It's dog years, so everything goes seven times faster. >> John: Right, right, right. >> I was laughing. I was like, "How on Earth can you possibly use a truck to move data?" But a customer came to us, a prospect came to us the other day, he wanted to move a hundred petabytes of data. Now, if you're going to use the public internet to do that, that's going to take a hell of a long time. So, this idea of a mix between physical and digital data movement I think is, when moving to cloud, is actually fascinating. I think it's a really fascinating subject area. One that customers are definitely going to use. >> Yeah, you've got a great vantage point looking at customers' migrations. >> David: Yeah. >> It was actually something big in the keynote talking about, there are so many migrations out there that Amazon released an AWS Migration Hubs. So, obviously, physics is always a challenge, my legacy mindset. Customers, we heard a customer up onstage and it's usually not lift and shift maybe for the private cloud, but for public cloud, I usually, I need to rewrite, I need to do micro-services. What is the friction for customers, and how are you and Amazon and the other clouds helping customers work through those challenges? >> OK, so, just to take a step back and think about the problems that happen at hyper-scale data movement. So, small-scale data, gigabyte-scale data, the stuff that you typically see in a relational database, they're not particularly big problems. It's kind of minimal outage, press pause, move data, make it consistent, and you're done. You can have a sort of, a small outage, maybe 15 minutes or even a day to move data, but when it gets to hyper-scale, when it gets to petabyte-scale, multi-terabyte-scale data moves, that's when you have a problem, and that's really the problem that we solve. So, the idea that you can move data that's moving and changing without an interruption to service from on-premise to cloud and support a hybrid cloud topology for an elongated period of time is fascinating. I was listening at an investor conference to the CEO of VMware who was talking about, we're going to be in a situation of hybrid cloud for the next 20, 25 years because, overnight, not everybody can just repurpose every single application that they're running on-premise, whether it's in the main frame application, or a relational data application, or wherever it is in the OP application, and repurpose that in cloud overnight. So, we're going to have to gradually move and migrate those applications over. So, it's highly likely we're going to be in a hybrid cloud environment for the foreseeable future, and that's actually fantastic news for us. We're moving, as I said, at scale companies into cloud with transactional data, and nobody else can touch us in terms of the uniqueness of the IP, which is fantastic news for us. >> In terms of just big data in general, Stu has one use for it, I have a different use for it. It's going to live in a lot of different places. How are you responding to different needs within your clients and trying to make them more effective, make them more efficient? And yet, when you're dealing with more and more data, that's a big storm to handle. >> That's a great question. I went to speak a couple of months ago to a new customer of ours who is a major healthcare provider on the east coast, and I kind of said to him, "OK, you've had this deep cluster for the past three years. Why are you calling us? Why now?" Which is the question that I always ask our customers. Why? What changed? Why are you doing this right now?" And maybe for the past three years they've been putting legal data into the system. That's data, but who cares if you can't get access to it? We can move to telephone. We can move to e-mails. We can go into an archive, into a paper archive even, to find it, but the why now is that they're now putting patient record data, patient information with regulated SLA's into this system, and that really is our sweet spot. As you get to, remember that investment thesis, small-scale gigabyte outage is small outage, when you get into petabyte, exabyte-scale, when you've got data sets that are a thousand, a million times greater, it's linear to the quantum of data. That outage becomes a thousand or a million times greater. So, that's kind of intolerable. So, we love it when strategic applications, regardless of what the use case is, we could all have different, it might be patient data, it might be retail information, it might be banking data, it might be customer retention information, when those strategic applications move onto this hyper-scale infrastructure, you have to support RTO and RTP, and that's what we do. >> And is a byte a byte a byte? You have these thousands of needles in haystacks, right? How do you assign value to one as opposed to another? >> So, this is another great question and one that investors kind of ask me a lot. So, we used to model our business from kind of the ground up. So, we take the classic enterprise sales team, you have a sales and marketing organization that's quite large, you would multiply that by their quota and then multiply it by 66% because that's how many of them are going to be successful in selling product. Well, we completely threw that away when we launched WANdisco Fusion, our new technology, early 2016. Then, we moved to a channel-based approach. So, we have IBM, we have an OAM, 5,000 quarter-carrying enterprise sales guys at IBM selling our products. That was a fantastic deal for us. We signed it in April 2016, and they've done the first half of this year, and made at least six million dollars in sales that we have also announced, and then, we've got strategic partnerships with Amazon, with Microsoft, with Google, and we model our business by those channels. So, we're not looking for needles in haystacks. We don't, we could never hire another, I mean, if we had to come into the market and say, "We need to go and hire 5,000 enterprise sales guys," we'd have to be raising, doing fund-raisers like Uber or something. We'd just be untenable. We couldn't do it. So, we have a product that lends itself very well to a channel-based approach, and that's working very nicely for us. So, we're not looking for, we're just looking for haystacks. Somebody else can go and find the needles. >> John: Find me and you, right? >> Right. >> David, how are your customers managing the pace of change these days? We've said Amazon is an example. It's like everyday there's three new services coming out. Are they excited? Are they completely overwhelmed? What do you see these days? >> So, I think it's classic sort of products and option lifecycle stuff. The sort of technical enthusiasts, they love all this change. The early-stage companies that are implementing this new cloud-based technology, ObjectStore technology and so on, they're managing very well. It's the later-stage companies you might go to and say, "ObjectStore," and they'll go, "What's ObjectStore? We're just getting our head around Hadoop, and Hive, and Pig, and all this other stuff that you were talking about three years ago," and sales guys go in there now and say, "Oh, no, no, no, don't worry about Hadoop. Nobody's going to run Hadoop in the cloud." It's like, "Well, that's what you told me three years ago." So, I think the market's certainly divided. I think you're going to see, as we move up products and option lifecycle, you're going to see lots and lots and lots of interesting moves happen. The companies that seem to be owning cloud, I think Alibaba is coming up really fast. We're seeing them doing some interesting things. Obviously, they've got dominoes in the Chinese market. Amazon First-Mover, Microsoft's futures dependent on cloud. So, they all have their different spin and different take on applications that they're going to run in cloud. I think there is, I think it's a bit like the cellphone industry. There's lot and lots of different plans, lots and lots of different confusing nomenclature, but that's going to settle out in the next couple of years, but there's unquestionably, if you look at the audience here today, unquestionably large-scale movement of applications and data to cloud. >> Well, we appreciate the time, as always. Great to see you. Another notch in your CUBE belt. (laughing) So, congratulations for that, and maybe you can settle in to New York for a day or two. You said your travels have had you flip-floppin' back and forth between England and here. So, maybe you can settle in for a day or two. >> Yeah, I need to replicate myself. I need to put myself in at least two different places at the same time. >> Live data replication right here. (laughing) All right, David, thanks for bein' with us. David Richards. >> Thank you. Thanks guys. >> Back with more here on theCUBE, we continue our coverage of AWS Summit from New York City right after this break. (upbeat music)

>> Narrator: You are Cube Alumni. Live from Silicon Valley, it's the Cube. Covering Google Cloud Next 17. >> Welcome back to the Cube's coverage of Google Next 2017. Having a lot of conversations as to how enterprises are really grappling with cloud. You know, move from on premises to public cloud, multi-cloud, hybrid-cloud, all those pieces in between. Happy to welcome to the program a first time guest, Paul Scott-Murphy who's the vice president of product management at WANdisco, thanks so much for joining us. >> Yeah, thanks very much, it's great to be here and join your program. >> Alright, so you know, Paul, I think a lot of our audience probably is familiar with WANdisco, we've had many of your executives on, really dug into your environment for the last few years, usually see you guys a lot of not only the big data shows, we've got Strata coming up next week, last time I did an interview with you guys was at AWS re:Invent. So you know, WAN, replication, data, all those things put together, you've got a big bucket of big data in cloud. Tell us a little bit about kind of your background, your role at the company. >> Okay. So I've been at WANdisco now for about two and a half years. I previously worked for TIBCO Software for a decade. Working out of Asia-Pacific, held the CTO role there for APJ. And joined WANdisco two and half years ago, just as we were entering into the big data market with our replication capabilities. I now run product management for the company and work out of our headquarters here in the Bay area. >> Stu Miniman: Great. And connect with us you know, what you guys are doing at Google, what's the conversations you're having with customers that are attending. >> Yeah, so Google is definitely one of the key strategic partners for WANdisco, obviously particularly in the Cloud space for us. We're hosting a booth fair for the conference and using that as an opportunity to speak to other vendors and the customers that we have attending the Google conference. Particularly around what we're doing for replication between on premises and cloud environments, and how we support Google Cloud. Dataproc, and Google Cloud Storage as well. >> Can you help unpack for us a little bit, where are your customers, give us a tip of the customers, you know they're saying hey, I want to start using this cloud stuff, how are they figuring out what applications stay on premises, what goes to the public cloud, and that data piece is a challenging thing, moving data is not easy, there's a whole data gravity piece that fits into it, maybe you can help walk us through some of the scenarios. >> Yeah, as we're progressing the technology, we're certainly finding a broader and broader range of customers getting interested in what they can do around data replication. The sorts of organizations that we deal with primarily are those who are looking to leverage both on premises and cloud infrastructure. All those who are moving from a situation where they've been toying with these environments and moving into production-ready scenarios where the demands or enterprise level SLAs or availability, or the needs around disaster recovery, backup and migration use cases become a lot more dominant for them. The organizations that we work with typically they are larger organizations, we deal a lot with retail, with financial services, telecommunications, with research institutions as well. All of whom have larger needs around taking advantage of cloud infrastructure. Of course they all share the same challenge of the availability of their data, where it's sourced from, isn't always necessarily in the cloud, taking advantage of cloud infrastructure then requires them to think about how they make their information available both to their on premises systems and to the cloud environment where they can run perhaps larger analytic workloads against it, or use the cloud services that they would otherwise not have access to. >> One of the challenges we've seen is when we've got kind of that hybrid or multi-cloud environment, you know, manages my data, kind of the holes, you know, orchestrating pieces and getting my arms around how I take care of it and leverage it can be challenging. Is that something you guys help with or are there other partners that get involved, how are customers helping to sort out and mature these environments? >> Yeah it's a big question of course, you've touched on the management of data as a whole and what they means, and how organizations handle that. WANdisco's role in supporting organizations with those challenges is in ensuring that when they need to take advantage of more than one environment or when they need their data to be available in more than one place. They can do that seamlessly and easily. What we aport to do and what we encourage our customers to do with our technology is rather than keeping one copy of data on premises and using it solely there, or copying your data to another location in order that you can act upon it there, we treat those environments as the same and say well, have the best of both worlds. Have your data available in each location, let your applications use it at the local speed and do that without regard to the need for retaining a workflow by which you exchange data between environments. WANdisco's technology can take care of all of that, and to do so it has to do some very smart things under the covers, around consistency and making it work across wide-area networks. Makes it particularly suited to cloud environments where we can leverage those underlying capabilities in conjunction with the scale of the cloud which is a native home for data at scale. >> Can you give us some, you know, where do you see customers kind of in this maturation, Dan Green made a statement that today 5% of the data is in the public cloud, so what are some of those barriers that are stopping people from getting more data in the Cloud, is it something that we will just see a massive adoption of data in the cloud, or what's your guys viewpoint as to where data's going to live, how that movement is happening. >> Yeah, I think longer term the economic advantages of using cloud environments are undeniable. The cost advantages of hosting information in the cloud and the benefits that come from the scalability of those environments is certainly far surpassing the capabilities that organizations can invest in themselves through their own data centers. So that natural migration of data to the cloud is a common theme that we see across all sorts of organizations. But as many people say, data has gravity, and if the majority of your application information resides today in your own environments or in environments outside of the cloud, whether that's internet connected devices, or in points of ingest that reside outside of cloud environments, there's a natural tendency for data to remain in place where they're either ingested or created. What you need to do to better take advantage of cloud environments then is the ability to easily access that data from cloud infrastructure. So the sorts of organizations that are looking to that are those with either burgeoning problems around consuming data at multiple points. They might operate environments that span multiple contents. They might have jurisdictional restrictions around where their data can reside but need to control its flow between separate environments as well. So WANdisco can certainly help with all of those problems, the underlying replication technology that we bring to bear is very well suited to it. But we are a part of the overall solution. We're not the full answer to everything. We certainly deal very well with replication and we believe we cover that very well. >> I'm curious when you talk about kind of the dispersion of data and where it's being created, of course edge-use cases for things like IOT, are quite a hot topic at that point. Is that something you guys are touching on yet, gets involved in discussions, you know, where does that sit? >> Yeah, definitely. The interesting thing about WANdisco's approach to data replication is that we base it on this foundation of consistency. And using a mathematically proven approach to distributed consensus to guarantee that changes made in one environment are represented in others equally, regardless of where those changes occur. Now when you apply that to batch based data storage or streaming environments, or other forms of ingest is relatively irrelevant as long as you have that same underlying capability to guarantee consistency regardless of where changes occur. If you're talking about high IT environments where you naturally have infrastructure sitting outside of the cloud, and this is the type of infrastructure that needs to reside out of the cloud, right, your edge points where data are captured, where your consuming information are generating it from devices perhaps from an automotive vehicle or from an embedded device, some sort of sensor array, whatever that happens to be, these are the types of environments where it means you're generating data outside of the cloud. So if you're looking to use that inside of the cloud itself, you need some way of moving data around, and you need to do that with some degree of consistency between those environments to make sure you're not just challenged with extra copies of information. >> The other really interesting topic around data that's being discussed at the Google Cloud event is artificial intelligence, machine learning, I'm curious, are your customers involved in that, where do you see that kind of on the radar today? >> Yeah, it's obviously an absolutely critical part of where the IT industry in general is going, and the type of solution that's fed off data. These systems are better as your data set grows. The more information you have, the better they work, and the more capable they become. It's certainly an aspect of how well machine learning technique and artificial intelligence approaches have been adopted in the industry, and the rapid rate of change in that side of IT is driving a lot of the demand for increasing access to data sets. We see some of our customers using that for really interesting things. You might've seen some of the recent news around our involvement in a research project led through the University of Sheffield, looking to use data sets captured from a variety of research institutions and medical environments to solve the problem of identifying and responding to dementia. And it's a great outcome from that type of environment. Through which machine learning techniques are being applied across data sets. What you find though is that because there's a large set of institutions sharing access to data, no single data set is sufficient to support those outcomes, regardless of what intelligence you can place against the machine learning models that you build up. So by enabling the ability to bring those data sets together, have them available in a single location, being the cloud, where larger models can be assessed against the data sets means much better outcomes for those types of environments. >> Okay. Paul, in your role of product management, we've been through some of the hot buzz terms out there, how do you help the company identify those trends, focused on the ones that are important to your customers and the kind of feedback loops that you get from them. >> I guess a lot of work in the end is how we do it but we need to listen to customers directly of course, understand what they're looking to do with their information systems. What they're aiming for. Their goals at a business level, what type of value that they want to get out of their data, and how they're approaching that. That's really critical. We also need to look to the industry in general. We're obviously in a very rapidly changing environment where technologies, the organizations that build IT systems, are increasingly adopting new approaches and building systems that simply weren't available days ago. You look at the announcements from Google of late around their video intelligence APIs as a service, their image APIs as well, all new capabilities that organizations today now have access to. So bringing those things together, understanding where the general IT trends are, how that applies to our customers, and what WANdisco can do with the unique value that we bring is really key to the product management role. >> Alright, and Paul, you've been at the show, curious, any cool things you saw, interesting customer conversations that may want to give our audience a flavor of what's going on, why 10 thousand people are excited to be at the event. >> Yeah well it is a very exciting event, just the scale of these types of events run by Google and similar organizations is something in itself to behold. We're really excited to be a part of that. The things that are really interesting for me out of the show tend to be where we see customers or opportunities coming to us, identifying challenges that they can't address without the type of technology that we bring to bear. Those tend to be areas where either they're looking to do migration from on premises systems into the cloud which is obviously very strong interest for Google themselves, they need to bring customers in to take better advantage of the services that they have. WANdisco can play a strong role in that. We're seeing a lot of interesting things around the edge too, so all of the ways in which data can be used are always exciting and interesting to see. The combination of technologies like artificial intelligence, like virtual reality, the type of work that WANdisco does also, is certainly going to bring forward I think a new wave of applications and systems that we just hadn't considered even a few years ago. >> Yeah. Lots of really interesting things. There's personal assistants at home and personal assistants that are listening. Okay Google, subscribe to SiliconANGLE on Youtube. We'll be back with lots more coverage here from the Cube, talking about Google Next 2017. You're watching the Cube.

>> Announcer: Live from New York, it's theCUBE covering BigData New York City 2016, brought to you by headline sponsors Cisco, IBM, Nvidia, and our ecosystem sponsors. Now here are your hosts, Dave Vellante and Peter Burris. >> Welcome back to theCUBE everybody. This is BigData NYC and we are covering wall to wall, we've been here since Monday evening. We we're with Nvidia, Nvidia talking about deep learning, machine learning. Yesterday we had a full slate, we had eight data scientists up on stage yesterday and then we covered the IBM event last night, the rooftop party. Saw David Richards there, hanging out with him, and wall to wall today and tomorrow. Jagane Sundar is here, he is the CTO of WANdisco, great to see you again Jagane. >> Thanks for having me Dave. >> You're welcome. It's been a while since you and I sat down and I know you were on theCUBE recently at Oracle Headquarters, which I was happy to see you there and see the deals that are going on you've got good stuff going on with IBM, good stuff going on with Oracle, the Cloud is eating the world as we sort of predicted and knew but everybody wanted to put their head in the sand but you guys had to accommodate that didn't you. >> We did and if you remember us from a few years ago we were very very interested in the Hadoop space but along the journey we realized that our replication platform is actually much bigger than Hadoop. And the Cloud is just a manifestation of that vision. We had this ability to replicate data, strongly consistent, across wide area networks in different data centers and across storage systems so you can go from HDFS to a Cloud storage system like S3 or Azure Wasabi and we will do it with strong consistency. And that turned out to be a bigger deal than actually providing just replication for the Hadoop platform. So we expanded beyond our initial Hadoop Forex and now we're big in the Cloud. We replicate data to many Cloud providers and customers use us for many use cases like disaster recovery, migration, active/active, Cloud bursting, all of those interesting use cases. >> So any time I get you on theCUBE I like to refresh the 101 for me and for the audience that may not be familiar with it but you say strongly consistent, versus you hear the term eventual consistency, >> Jugane: Correct. >> What's the difference, why is the latter inadequate for the applications that you're serving. >> Right so when people say eventually consistent, what they don't remember is that eventually consistent systems often have different data in the different replicas and once in a while, once every five minutes or 15 minutes, they have to run an anti-entropy process to reconcile the differences and entropy is the total randomness right if you go back to your physics, high school physics. What you're really talking about is having random data and once every 10 minutes making it reconcile and the reconciliation process is very messy, it's like last right winds and the notion of time becomes important, how do you keep time accurate between those. Companies like Google have wonderful infrastructure where they have GPS and atomic clocks and they can do a better job but for the regular enterprise user that's a hard problem so often you get wrong data that's reconciled. So asking the same query you may get different answers and your different replicas. That's a bad sign, you want it consistent enough so you can guarantee results. >> Dave: And you've done this with math, right? >> Exactly, our basis is an algorithm called Paxos, which was invented by a gentleman called Leslie Lamport back in '89 but it took many decades for that algorithm to be widely understood. Our own chief scientists spent over a decade developing those, adding enhancements to make it run over the wide area network. The end result is a strongly consistent system, mathematically proven, that runs over the wide area network and it's completely resistant to failure of all sorts. >> That allows you to sort of create the same type of availability, data consistency as you mentioned Google with the atomic clocks, Spanner I presume, is this fascinating, I mean when the paper came out I was, my eyes were bleeding reading it and but that's the type of capability that you're able to bring to enterprises right? >> That's exactly right, we can bring similar capabilities across diverse networks. You can have regular networking gear, time synchronized by NTP, out in the Cloud, things are running in a virtual machine where time adrift most of the time, people don't realize that VMs are pretty bad at keeping time and all you get up in the Cloud is VMS. Across all those enviroments we can give you strongly consistent replication at the same quality that Google does with their hardware. So that's the value that we bring to the Fortune 500. >> So increasingly enterprises are recognizing that data has an, I don't want to say intrinsic value but data is a source of value in context all by itself. Independent of any hardware, independent of any software. That it's something that needs to be taken care of and you guys have an approach for ensuring that important aspects of it are better taken care of. Not the least of which, is that you can provide an option to a customer who may make a bad technology choice one day to make a better technology choice the next day and not be too worried about dead ending themselves. I'm reminded of the old days when somebody who was negotiating an IBM main frame deal would put an Amdahl coffee cup in front of IBM or put an Oracle coffee cup in front of SAP. Do you find customers metaphorically putting a WANdisco coffee cup in front of those different options and say these guys are ensuring that our data remains ours? >> Customers are a lot more sophisticated now, the scenarios that you pointed out are very very funny but what customers come to us for is the exact same thing, the way they ask it is, I want to move to Cloud X, but I want to make sure that I can also run on Cloud Y and I want to do it seamlessly without any downtime on my on-prem applications that are running. We can give them that. Not only are they building a disaster recovery environment, often they're experimenting with multiple Clouds at the same time and may the better Cloud win. That puts a lot of competition and pressure on the actual Cloud applications they're trying. That's a manifestation in modern Cloud terms of the coffee cup competitor in the face that you just pointed out. Very funny but this how customers are doing it these days. >> So are you using or are they starting to, obviously you are able to replicate with high fidelity with strong fidelity, strong consistency, large volumes of data. Are you starting to see customers, based on that capability actually starting to redesign how they set up their technology plant? >> Absolutely, when customers were talking about hybrid Cloud which was pretty well hyped a year or so ago, they basically had some data on-prem and some other data in the Cloud and they were doing stuff but what we brought to them was the ability to have the same data both on-prem and in the Cloud, maybe you had a weekly analytics job that took a lot of resources. You'd burst that out into the Cloud and run it up there, move the result of that analytics job back on-prem. You'd have it with strong consistency. The result is that true hybrid Cloud is enabled when only when you have the same exact data available in all of your Cloud locations. We're the only company that can provide that so we've got customers that are expanding their Cloud options because of the data consistency we offer. >> And those Cloud options are obviously are increasing >> Jugane: They are. >> But there's also a recognition that it's as we gain more experience with Cloud, that different workloads are better than others as we move up there. Now Oracle with some of their announcements last week may start to push the envelope on that a little bit but as you think about where the need for moving large volumes of data with high, with strong consistency what types of applications do you think people are focusing on? Is it mainly big data or are there other application styles or job types that you think are going to become increasingly important? >> So we've got much more than big data, one of the big sources of leads for us now is our capability to migrate netapp filers up into the Cloud and that has suddenly become very important because an example I'd like to give is a big financial firm that has all of its binaries and applications and user data and netapp filers, the actual data is in HDFS on-prem. They're moving their binaries from the netapp up into the Cloud in a specific Cloud windows equal into the filer and the big data part of it from HDFS up into Cloud object store, we are the only platform that can deal with both in the strong consistent manner that I've talked about and we're a single replication platform so that gives them the ability to make the sort of a migration with very low risk. One of the attributes of our migration is that we do it with no downtime. You don't have to take your online, your on-prem environment offline in order to do the migration so they are doing that so we see a lot of business from that sort of migration efforts where people have data in mass filers, people have data in other non-HDFS storage systems. We're happy to migrate all of those. Our replication platform approach, which we've taken in the last year and a half or so is really paying off in that respect. >> And you couldn't do that with conventional migration techniques because it would take too long, you'd have to freeze the applications? >> A couple of things, one you'd probably have to take the applications offline, second you'd be using tools of periodic synchronization variety such as RSYNC and anybody in the devops or operations whose ever used RSYNC across the wide area network will tell you how bad that experience is. It really is a very bad experience. We've got capability to migrate netapp filer data without imposing a load on the netapp's on-prem so we can do it without pounding the crap out of the netapp's server such that they can't offer service to their existing customers. Very low impact on the network configuration, application configuration. We can go in, start the migration without downtime, maybe it takes two, three days for the data to get up over there because of mavenlink. After that is done, you can start playing with it up in the Cloud. And you can cut over seamlessly so there's so real downtime, that's the capability we've seen. >> But you've also mentioned one data type, binaries, they can't withstand error propagation. >> Jugane: Absolutely. >> And so being able to go to a customer and say you're going to have to move these a couple times over the course of the next n-months or years, as a consequence of the new technology that's now available and we can do so without error propagation is going to have a big impact on how well their IT infrastructure, their IT asset base runs in five years. >> Indeed, indeed. That's very important. Having the ability to actually start the application, having the data in a consistent and true form so you can start, for example, the data base and have it mount the actual data so you can use it up in the Cloud, those are capabilities that are very important to customers. >> So there's another application. If you think about, you tend to be more bulk, the question I'm going to ask is and at what point in time is the low threshold in terms of specific types of data movement. Here's why I'm asking. IOT data is a data source or is a use-case that has often the most stringent physical constraints possible. Time, speed of light, has an implication but also very importantly, this notion of error propagation really matters. If you go from a sensor to a gateway to another gateway to another gateway you will lose bits along the way if you're not very careful. >> Correct. >> And in a nuclear power plant, that doesn't work that way. >> Jugane: Yeah. >> Now we don't have to just look at a nuclear power plant as an example but there's increasingly industrial IOTs starting to dramatically impact not just life and death circumstances but business success or failure. What types of smaller batch use-cases do you guys find yourselves operating in, in places like IOT where this notion of error or air control strong consistency is so critical? >> So one of the most popular applications that use our replication is Spark and Spark Streaming which as you can imagine is a big part of most IOT infrastructure, we can do replication such that you ingest into the closest data center, you go from your server or your car or whatever to the closest data center, you don't have to go multiple hops. We will take care consistency from there on. What that gives you is the ability to say I have 12 data centers with my IOT infrastructure running, one data center goes down, you don't have a downtime at all. It's only the data that was generated inside the data center that's lost. All client machines connecting to that data center will simply connect to another data center, strong replication continues, this gives you the ability to ingest at very large volumes while still maintaining the consistency and IOT is a big deal for us, yes. >> We're out of time but I got a couple of last minute questions if I may. So when you integrate with IBM, Oracle, what kind of technical issues do you encounter, what kind of integration do you have to do, is it lightweight, heavyweight, middleweight? >> It's middleweight I would say. IBM is a great example, they have a deep integration with our product and some of the authentication technology they use was more advanced than what was available in open source at that time. We did a little of work, and they did a little bit of work to make that work, but other than that, it's a pretty straight forward process. The end result is that they have a number of their applications where this is a critical part of their infrastructure. >> Right, and then road map. What can you tell us about, what should we look for in the future, what kind of problems are you going to be solving? >> So we look at our platform as the best replication engine in the world. We're building an SDK, we expect custom plugins for different other applications, we expect more high-speed streaming data such as IOT data, we want to be the choice for replication. As for the plugins themselves, they're getting easier and easier to build so you'll see wide coverage from us. >> Jugane, thanks so much for coming to theCUBE, always a pleasure to have you. >> Thank you for having me. >> You're welcome. Alright keep it right there everybody, we'll be back to wrap. This is theCUBE, we're live from NYC. We'll be right back. (upbeat electronic music)

(silence) (upbeat techno music) >> Narrator: Live from New York, it's theCUBE, covering Big Data NYC 2016, brought to you by headline sponsors: Cisco... IBM... Nvidia, and our ecosystem sponsors. Now, here are your hosts, Dave Vellante and Peter Burris. >> Welcome back to New York City, everybody. This is theCUBE, the worldwide leader in live tech coverage. David Richards is here. He's the CEO of WANdisco, a long time CUBE alum. Great to see you again. >> Great to be back. >> It was good fun hanging out with last night and a good surprise at the IBM event. There was good action across the street. >> Yeah, you're both looking surprisingly well, actually. >> (Dave laughs) Yes. >> Well, we also heard about the WANdisco versus theCUBE golf tournament, that apparently theCUBE just did really, really well in it and WANdisco went running away with their tail between their legs. >> Well, I talked to Furrier last night. I said, "David Richards was telling me "that he kicked your butt on the golf course." He goes, "Yeah, that's true, actually." (laughter) >> I think I've got some video proof that he actually gave me $20 live on air because, of course, his wallet was empty. (laughter) He was blowing the dust off it, you know? >> Of course, yeah, the body swerve. >> Alligator arms. >> So David, it's, again, great to see you again. You guys have been in this business since day one, and things are evolving. How are things changing for WANdisco? >> So, when we first came into this market, back in the mid-2006, 2007, and then we obviously made a bunch of acquisitions around 2011 and 2012 that took us headlong into the big data marketplace. We pretty much had a completely different business model to our business model now. Then, we had a product called Non-Stop NameNode... My God, can you imagine that? (Dave laughs) That was very focused on the Hadoop marketplace because, at that time, we believed, like everybody else, that Hadoop was going to take over the world, people were going to move to commoditized servers, open-source software, and solve the huge storage problems that they were going to have from both a cost and efficiency perspective. What I think has happened, or is happening right now, is this evolution, and it really is more of a revolution than an evolution is taking place, where workloads, and we were discussing this last night, are moving at massive scale to cloud, and people are really skipping that step, where we thought they were going to have 5, 10,000 sort of clusters on-premise, but now they have some clusters on-prem, but the bulk of the workloads are actually moving into cloud. I was just discussing with George, off-camera a few minutes ago, why that is happening, and there's a lot of applications that are very efficient. The cloud packs are up there ready to use, off the shelf, and it becomes very simplistic, and to be quite frank, do we really care anymore about all these different open-source components? Is the CIO waking up in the middle of the night thinking, oh, my God, am I going to use Ignite, am I going to use Spark, am I going to use Pig, am I going to use Hive, et cetera, et cetera, et cetera? Of course they're not. They really just want to-- Let's inverse the question to ourselves. If you were going to start a competitor to Uber tomorrow, would you go and build a data center (Dave laughs) or would you just throw up a thousand servers up in the cloud and have done with it, and use all the apps that are up there? Of course, the answer's simple, so that's really what's happening. >> Well, one of the things that I... I wrote a piece of research a million years ago in which I prognosticated, the Dictionary Word of the Day, that the value of middleware was inversely proportional to the degree to which anybody knew anything about it. (Dave laughs) CIOs are waking up and asking those questions today, which is an indication that they're creating a problem. >> Yep. >> Infrastructure has to do no harm in the organization. I had a CIO friend for years who still asks his chief CTO, "To what degree is infrastructure creating a problem "for me today?" >> Yeah. >> And if it's creating a problem, it's a problem. >> Mm-hmm. >> You don't want to have to know about this stuff, and so what degree are you helping companies mask some of those... that visibility, so that people can spend less time worrying about the infrastructure? >> So, what we're focused on is a business model that has gone from direct, where we were hiring out a very large direct sales force enterprise, the classic enterprise sales guys that would go knock on doors, knock deals down, go and sell to the Global 1000s, to an indirect model, and we announced that OAM, recently with IBM, IBM Big Replicate, that is under the covers, is WANdisco Fusion, which is a great deal for us. So, our focus very much is on data movement, and data movement between data centers, for companies that want to stay on-prem, and between data centers and in and out of cloud seamlessly, and the word there is seamlessly. So, we worked very hard for the past 18 months on our product such that anybody can go to, if you want to go to the AWS Marketplace, you can, in a few clicks, begin to replicate petabyte-scale in and out of cloud, and we think, and we were discussing this last night, that the hybrid-cloud model is really fascinating, so the ability to take data on-premise, query it in cloud, get complete consistency between on-prem and cloud, but also have all the efficiency in the cloud economics, the elasticity, all the applications that exist in cloud, and I think that model is really interesting, and what's interesting is, I'm not sure that the little guys can execute in that model other than, like we're doing, veer on OAM, an indirect model. So, I'm not sure whether or not, just to go back to the conversation, CIOs are as concerned as they used to be about which Hadoop distribution, for example, they're using. I never hear that question anymore. That question was a 2012, 2013 question. What the CIOs are now concerned about is the economics of cloud, and how do I get that less than $5 per terabyte of data economics that I get in a cloud environment. >> Well, but also increasingly, they're talking about the use cases. >> David: Yeah. >> They want to get their people... They don't want to replicate the Linux or Unix versus NT wars of the 1990s, which was made possible because they were focused on what accounting package am I going to run? Am I going to run it-- >> Yeah. >> on this or that? You know, it was known process, unknown technology. In today's universe, it's unknown process, and they don't want to know as much about the technology, so they're focused on how do I get my men and women focused on use cases that are delivering value for their business. >> Exactly, and the economics question is really simple. Am I going to build a massive, partially used, elastic infrastructure on-premise or am I just going to go and use the elastic infrastructure that already exists in the cloud? That's a no-brainer. That's already happening, and the good news for us, the good news for WANdisco, is it's precisely what we do. It's a data movement problem. Now, I'm bound to say that, but it is actually a data movement problem. In this idea that you have data that changes, active transactional data, as we call it, so the active transactional data movement is a really hard problem. You can't just take a snapshot, right? A file scan and then a snapshot and then move the data, and that's the problem that all the other data replication guys have got. That's what IBM, OAM, that's why we've got strategic partnerships with companies like Oracle, like Amazon, and why I'm sure we'll be announcing things in due course with the other cloud vendors, like Google, for example, and Microsoft with their Azure products. They all have that problem, so data movement, in and out of cloud, if it's batch, if it's static, if it's archival data, easy problem to solve. There's a million and one different replication products. >> Dave: Right. >> You can use rsync if you really wanted to do that, but active transactional data, data that changes, data that moves, you know, at petabyte scale, hard problem. That's the problem that we solve. >> Because you've got speed of light problems and you're exposing yourself to data loss-- >> Yep. >> if something goes wrong. >> Peter: Fidelity is a problem. >> An eventual consistency replication model-- >> Yeah, it... >> doesn't work. You can't... If I'm query... We've got a customer that's trying to look at cardiographs, right, in and out of cloud. I mean, would you really feel comfortable in your cardiograph eventually getting into the cloud and being analyzed? You know, would you? You've got to be absolutely crystal clear that the data is completely consistent from the stuff that I'm generating on-premise versus the models that I'm building in cloud. It's vitally important. >> Well, I would imagine there's regulations, in certain industries anyway, that-- >> Oh, yeah, absolutely. >> require that eventual consistency doesn't fit, right? >> Yeah. Well, I mean, at the moment, without us, that's all you got, I'm afraid... >> Okay. >> Well, so, I'm on a mission, let me and I want to get your take on it, that we always talk about elastic infrastructure, which is a given workload, being able to scale up and scale down. >> David: Yeah. >> I think it's time to start talking about plastic infrastructure-- >> David: Oh, yeah, I like it. >> where a given workload, but a reconfiguration of how that workload is applied because of the value of data, because of integration, because of the need to be able to move in response to business needs. So we talk about plastic infrastructure, where we are reconfiguring based on policy and rules and some other things. What do you think about that? >> I love it, and the reason I love it is because, just to take a step back, the definition of hybrid cloud is... You would imagine it would be relatively simple, but to me, a hybrid means that you have... You know, it's a bit like a hybrid golf club. It's neither a driver nor an iron. It's somewhere in between. So, you have the same workload that can exist both on-premise and in the cloud. I can use both the cloud and on-premise interchangeably. What hybrid cloud actually means, for all the vendors, and this is their dirty little secret, it means that you have some workloads running against some data in the cloud and others that will run against some data on-premise. Now, why do they do that? Because they have to. Because they can't guarantee complete consistency between on-premise and cloud. Our definition of hybrid cloud is exactly the same data, if you want, between on-premise and cloud, and I love this plastic phrase, the idea of repurposing all of those applications, and they can live anywhere. It doesn't matter 'cause it's the same data. >> Yeah, so we have two terms we have to copyright here, plastic infrastructure. >> Plastic... >> What was the other one we heard? >> Data portfolio. >> Data portfolio, yeah. We'll run the tape back >> Plastic infrastructure. (laughter) >> Plastic infrastructure. >> I'm going to steal it (laughs). >> Please do, you know? But the key thing is, as these technologies get more deeply embedded within business and how the business runs, it's incumbent upon the technology leadership to be able to rapidly be able to reconfigure the infrastructure in response to what the business needs. That's not elasticity. >> Yeah. >> That's plasticity. >> I love it, absolutely. (Peter laughs) And I think you're touching on something that's changing, and what we discussed earlier, which is that CIOs aren't waking up in the middle of the night thinking, am I going to use Pig or Hive or any of those other open source components. They're thinking about the applications that they're going to build. How am I actually going to start using this data? And I think the agenda's kind of moved on, and walking around the whole... There's still a little bit of confusion. You still have people talking about infrastructure like it really still matters. I'm not absolutely sure it does. >> Well, so let's talk about that. We got a few minutes or something like that. >> Dave: It matters when it breaks, you know? >> What's that? >> It matters when it breaks. >> It sure does matter when it breaks. >> You know, but otherwise, nobody wants to think about it. >> No, yeah, because like I said earlier, it's the degree to which-- >> We have time, but I want to explore the new distribution model as well. >> Yeah, go ahead. >> Let me do that, get that out, tick that box, if I can. Help me understand, David, how it all works. So you, the partnership with IBM and others, you mentioned Amazon, how does it work? You are in the IBM cloud offering? IBM is actually selling that offering? Is it a branded IBM product? >> So, it's in the big data analytics and cloud offerings. So, at the moment, IBM are very focused, as you know, on owning the platform. IBM, as a company, have the own the platform. >> Dave: Yeah, absolutely. >> So, I'm delighted to say that we're embedded into their platform. Now, they had a big launch of some products last night. >> Yeah. >> I know that they were talking about IBM Big Replicate, which is 100% white label OAM of WANdisco Fusion to solve some very specific problems, primarily around data movement. So, at the hybrid cloud, how do I punch data out into clouds, run the analytics against it, and be sure that I'm going to get the right results? That's what Big Replicate solves, and also, they're moving into mixed environments, whether they're NetApp, just kind of Teradata environment, SAS-based environments, or whether a customer already has an existing distribution of, say, Cloudera or Hortonworks, so they can live alongside that, so we can replicate data between existing deployments, where they may have already made a strategic decision to go with one of those distributions, and also be able to migrate not just into IBM Big Insights, but also into their cloud offering, so that's a great deal for us. We're not... They're selling it themselves. I mean, obviously we've done a lot of field enablement, trained 5,000 or so IBM sales rep, and, you know, if a small company like WANdisco, or a small company like virtually any of the vendors in there that are not in the Global 1000 list, the go-to market has to be indirect. >> And so you're... Totally agree, and so you're basically, if I understand it correctly, you're moving what are conventional filers into the cloud. Customers are doing that. >> Oh. >> How fast is that happening and why are they doing that? >> My, God. I mean, we have not announced this product yet, but we're in the middle of launching it. It's, at scale, moving petabyte-scale data from, and this is transactional data, so it's a hard problem to solve, right, so it's an active data... It's an active transactional data replication problem. So, a lot of... The dirty little secret in the cloud is that a lot of those NFS filers have not moved yet-- >> Right. >> And why haven't they moved? 'Cause they can't. Because you can't just... You know, if you were to travel, one of the customaries of banks and travel companies is they can't press pause in their organization, do a file scan that's going to take six months, and then turn it back on again, and hey, presto, it's in the cloud. You can't do that. So, you kind of have to... At every single migration of those filers, of any sort of data, is a hybrid model, so you have to be able to run both on-prem and cloud while that migration is happening, and there, I can tell you, are a lot, a hell of a lot of NetApp filers that are going to move very soon here, in time. >> Dave: Oh, 'cause that's the problem that you solve. Otherwise, you'd have to freeze everything, which would kill your business, so you can't do it. >> Yeah, so when human beings imagine things, we're always imagining small use cases, small sets, like moving a few files into Dropbox or something, and that's okay that I can't edit those files for the few seconds it takes to move. I took a look at a deal the other day that was 3 billion files. (Dave laughs) Right, 3 billion. You can't even... My brain can't even calculate that, right? That's a three to six month data movement, and Amazon, for example, thought of this product called Snowball, which-- >> Yeah. >> You know, no techy ever believes this story, but, of course, they FedEx a box, a ruggedized hard drive to you essentially, a ruggedized server that you pour your data into it and then you mail it back to them and they can put it there. That doesn't work, of course, for transactional data, for data that changes all the time. >> These are hard problems to solve, and I go to market, getting back to your question, it is all about indirect, you know? So, AWS, a strategic partnership, that, Oracle, a strategic partnership, that, IBM... And as I said, I'm sure that we'll be doing things with Google and Microsoft soon, and they're the five partnerships that I really care about, to be quite frank with you. >> Mm-hmm. and this comes back to this notion of infrastructure, the value of infrastructure, and just to touch on it for a second, so many years ago, when we were doing client-server, >> David: Mm-hmm. >> We would test it on a local area network and deploy it on a WAN (David laughs) and wonder why it blew up. >> David: Yeah. >> The realities of the speed of light and the practical limitations have a real impact on design, and so where infrastructure still matters is we still have to worry about design, we still have to worry about legacy financial assets, how we're deploying those assets, and I want to come back to this because we were talking earlier about data as an asset, the value of data within the business, and you don't want to be limited by the legacy as you try to find new ways of generating value out of your data, and what you guys are trying to allow is that the data can be moved in response to the use case as opposed to the use case not being made possible because of the legacy decisions about where to put your data. >> David: That's precisely it, and I don't think that any CIO, in their right mind, wants to continue with the huge maintenance costs, maintenance payments they have to make to some of those vendors, some of those NFS-based vendors. They need to shut them down. They have to figure out a way to move them into cloud so you get cloud economics, and also be able to query the data in a massively efficient way. You simply cannot do that at the moment. They simply cannot do that at the moment, so, as I said, as we continue to launch these products in the marketplace, I'm sure you'll see, at scale, some pretty large companies surprising-- You know, the two that spring to my mind are that the regulators in the US and the UK, Fenero and the FCA, are both in the process of their moving all into cloud, 100% into cloud, and I would expect to see that trend continue. I mean, the re:Invent... I don't want to talk about another-- and we're here at Strata, but the AWS re:Invent, I would expect to see several major financial service companies announcing cloud strategy. >> Yeah, and Fenero's a big user of the AWS cloud. They talk about it pretty aggressively, and really interesting use case there. So, yeah, so we got to end. What's next for you guys? You've mentioned you're going to be at re:Invent, you're going to be at World of Watson (laughs)? Where are we going to find you next? >> Both of those. Obviously, the white label with IBM is a really interesting deal for us. I can't talk about deal flow yet 'cause it's our end of quarter at the moment, but I can tell you that they're doing a pretty damn good job of selling, so we're in execution mode at the moment, where we've already announced some key partnerships. There'll be more key partnerships to come, I'm sure. We're obviously chasing deals down with some of the other cloud vendors, and I'd expect to see us announcing some interesting new customer wins in the coming days and weeks. >> Dave: Great. Well, congratulations on the momentum and the renewed strategy. I love it, and I appreciate you coming to theCUBE. >> Always a pleasure. >> All right, keep it right there, buddy. We'll be back with our next guest. This is theCUBE. We're live at Big Data NYC, Strata and Hadoop World. Be right back. (spacey electronica music)

>> Announcer: Live from San Jose, in the heart of Silicon Valley, it's theCUBE. Covering AWS Summit 2016. (upbeat electronic music) >> Hello everyone, welcome to theCUBE. Here, live in Silicon Valley, at Amazon Web Services, AWS Summit, in Silicon Valley. I'm John Furrier, this is theCUBE, our flagship program. We go out to the events and extract the signal from the noise. I'm here with my co-host. Introducing Lisa Martin on theCUBE, new host. Lisa, you look great. Our first guest here is David Richards, CEO of WANdisco. Welcome to theCUBE, good to see you. >> Good to see you, John, as always. >> So, I've promised a special CUBE presentation, $20 bill here that I owe David. We played golf on Friday, our first time out in the year. He sandbagged me, he's a golfer, he's a pro. I don't play very often. There's your winnings, there you go, $20, I paid. (smooching) (laughing) I did not well challenge your swing, so it's been paid. Great fun, good to see you. >> It was great fun and I'm sorry that I cheated a little bit, mirror in the bathroom still running through your ears. >> I love the English style. Like all the inner gain and playing music on the course, it was great a great time. When we went golfing last week, we were talking, just kind of had a social get-together but we were talking about some things on the industry mind right now. And you had some interesting color around your business. We talked about your strategy of OEMing your core technology to IBM and also you have other business deals. Can you share some light on your strategy at WANdisco with your core IP, and how that relates to what's going on in this phenom called Amazon Web Services? They've been running the table on the enterprise now and certainly public cloud for years. $10 billion, Wikibon called that years ago. We see that trajectory not stopping but clearly the enterprise cloud is what they want. Do you have a deal with Amazon? Are you talking to them and what is that impact your business? >> Well I mean the wonderful thing is if you go to AWS Marketplace, you go to that front page, we're one of the feature products on the front page of the AWS Marketplace, so I think that tells you that we're pretty strategic with Amazon. We're solving a big problem for them which is the movement of data in and out of public cloud. But you asked an interesting question about our business model. When we first came into the whole big date marketplace we went for the whole direct selling thing like everybody does, but that doesn't give you a lot of operational leverage. I mean we're in accounts with IBM right now, you mentioned earlier, MR technology. At a big automotive company they have 72 enterprise sales guys, 72. We could never get to that scale any time soon. >> And you have relationships too. So it's not like they like, you know, just knocking on doors selling used cars. They are strategic high-end enterprise sales. >> Exactly. That gives us a tremendous amount of operational leverage and AWS is one of the great stories, will be one of the great IT stories of the century. To go from zero to 15 billion. If AWS was an independent company, faster than any other enterprise software company in the history of mankind, is just incredible. >> Yeah, well, enterprise obviously, they care about hybrid cloud, which you know all about through your IBM relationship. Andy Jassy at Amazon, the CEO now of Amazon. Newly announced title, he's certainly SVP, basically he's been the CEO of Amazon. He's been on record, certainly on stage, and on theCUBE saying, why do even companies need data centers? That kind of puts you out of business. You have a data center product, or is the cloud just one big data center? Will there ultimately be no data center at all? What's your thoughts? >> That's a great question. We see the cloud as just one great big data center or actually many great big data centers. And how you actually integrate those together, how you move data between data centers, how you arbitrage been cloud vendors. Are you really going to put all your eggs into one basket? You're going to put everything into AWS. Everything into Azure. I don't think you will. I think you'll need to move data around between those different data centers and then how about high availability? How do you solve that problem? Well WANdisco solves that problem as well. >> So a couple of questions for you David. One of the things that Dr. Wood said in the keynote today was friends don't let friends build data centers. So I wanted to get your take on that as well as from an IBM perspective. We just talked about the OEM opportunity that you're working there to get to those large enterprises. Does that mean that you're shifting your focus for enterprise towards IBM? Where does that leave WANdisco and Amazon as we see Amazon making a big push to the enterprise? >> So I think that was some big news that came out last week that was missed largely by the industry, which was the FCA, the financial regulatory authority in the United Kingdom, came out and said, we see no reason why banks cannot move to cloud from a regulatory perspective. That was one of the big fears that we all had which is are banks actually going to be able to move core infrastructure into a public cloud environment? Well now it turns out they can. So we're all in on cloud. I mean, we can see, if you look at the partnerships that we're focused on, it's the sort of four/five cloud vendors. It's the IBM, the AWS, Azure, Oracle, when they finally built that cloud, and so on. They're the key partnerships that we see in the marketplace. That will be our go-to market strategy. That is our go-to market strategy. >> So one of the things that's clear is the data value and you do a lot of replications. So one of the things that, I forget which CUBE segment we've done over the years, that's Hurricane Sandy I think it was, in New York City. You guys were instrumental in keeping the up-time and availability. >> Lisa mentioned, Amazon vis-a-vis IBM, obviously two different strategies, kind of converging in on the same customer. Amazon's had problems with availability zones and they're rushing and running like the wind to put up new data centers. They just announced a new data center in India just recently. Andy Jassy and team were out there kicking that off. So they're rushing to put points of presence, if you will, for lack of a better word, around the world. Does that fit into your availability concept and how do customers engage with you guys with specifically that kind of architecture developing very fast? >> I think that's a really great question. There are problems, there have been historic problems with general availability in cloud. There are lots of 15-minute outages and so on that cost billions and billions of dollars. We're working very closely and I can't say too much about it with the teams that are focused on enabling availability. Clearly the IBM OEM is very focused on the movement of data from the hybrid cloud, I'm from a data availability perspective. But there's a great deal of value in data that sits in cloud and I think you'll see us do more and more deals around general cloud availability moving forward. >> Is there a specific on that front project that you can share with us where you've really helped a customer gain significant advantage by working with AWS and facilitating those availability objectives, security compliance? >> So, one of the big use cases that we see, and it's kind of all happening at once really, is I built an on-premise infrastructure to store lots and lots of data, now I need to run compute and analytics against that data and I'm not going to build a massive redundant infrastructure on-premise in order to do that, so I need to figure out a way to move that data in and out of cloud without interruption to service. And when we are talking about large volumes of data, you simply can't move transactional data in and out of cloud using existing technology. AWS offers something called Snowball where you put it into a rugged ICE drive and then you ship it to them, but that's not really streaming analytics is it? Most of our use cases today are either involved in either the migration of data from on-premise into cloud infrastructure, or the movement of data for an atemporal basis so I can run compute against that data and taking advantage of the elastic compute available in cloud. They are really the two major use cases that web, and we're working with a lot of customers right now that have those exact problems. >> So majority of your customers are more using hybrid cloud versus all in the public cloud? >> Hybrid falls into two categories. I'm going to use hybrid in order to migrate data because I need to keep on using it while it's moving. And secondly I need to use hybrid because I need to build a compute infrastructure that I simply can't build behind firewall. I need to build it in cloud. >> So the new normal is the cloud. There was a tweet here that says, database migration, now we can have an Oracle Exadata data dispute that we're ready to throw into the river. (David laughs) Database migration is a big thing and you mentioned it on the first question that moving in and out of the cloud is a top concern for enterprises. This is one of those things, it's the elephant in the room, so to speak. No pun intended AKA Hadoop. Moving the data around is a big deal and you don't want to get a roach motel situation where you can check in and can't check out. That is the lock-in that enterprise customers are afraid of with Amazon. You're thoughts there, and what do you guys offer your customers. And if you can give some color on this whole database migration issue, real, not real? >> The big problem that the Hadoop market has had from a growth perspective is applications. And why they had a problem, well it's the concept of data gravity. The way that the AWS execs will look at their business the way that the Azure execs will look at their business at Microsoft. They will look at how much data they actually have. Data gravity. The implication being if I have data then the applications follow. The whole point of cloud is that I can build my applications on that ubiquitous infrastructure. We want to be the kings of moving data around right? Wherever the data lands is where the applications follow. If the applications follow, you have a business. If the applications don't follow, then it's probably a roach motel situation, as you so quaintly put it. But basically the data is temporal. It will move back to where the applications are going to be. So where the applications are, and it's who is going to be the king of applications, will actually win this race. >> So, question, in terms of migration, we're hearing a lot about mass migration. Amazon's even doing partner competency programs for migration. Not to trivialize it, talk to us about some of the challenges that you are helping customers overcome when they sort of don't know where to start when it comes to that data problem? >> If it's batch data, if it's stuff that I'm only going to touch if it's an archive, that I only going to touch once in a blue moon, then I can put it into Snowball and I can ship my Snowball device. I can sort of press the pause button akin to when I'm copying files into a network drive where you can't edit them, and then wait for two months, three months. Wait for them to turn up in AWS and that's fine. If it's transactional data where maybe 80% of my data set changes on a daily basis and I've got petabyte scale data to move, that's a hard problem. That requires active transactional data migration. That's a big mouthful, but that's really important for run-time transactional data. That's the problem that we solve. We enable customers, without interruption to service to move a massive scale active transactional data into cloud without any interruption of service. So I can still use it while it's moving. >> One of the things we were talking about before you came on was the whole global economy situation. I think a year and a half ago, or two years ago, you predicted the housing bubble bursting in London. You're in the London Exchange, you're a public company. Brexit, EU. These are huge issues that are going to impact, certainly North America looking healthy right now but some are saying that there's a big challenge and certainly the uncertainty of the U.S. presidency candidates that are lack of thereof. The general sentiment in the U.S. We're in a world of turmoil. So specifically the Brexit situation. You guys are in London. What does this impact your business and is that going to happen? Or give us some color and insight into what the countrymen are thinking over there. >> Okay, so, I get asked by, I live here of course, and I've lived here for 19 years. It feels like I'm recolonizing sometimes, I have to say. No, I'm joking. I get asked by a lot of Americans what the situation is with Brexit and why it happened. And for that you have to look at economics. If you sort of take a step back, in Northern Europe nine of the 10 poorest parts of Northern Europe are in the U.K. And one, only one of the top 10 richest parts is in the U.K. and that's London. So basically outside of London the U.K. has a really big problem. Those people are dissatisfied. When people are dissatisfied, if they're not benefiting from an economic upturn, if governments make it, like the conservative government for the past four years made huge cuts, those people don't benefit, and they really feel pissed off and they will vote against the government. >> John: So protest vote pretty much? >> Brexit was really, I think, a protest vote. It's people dissatisfied. It's people voting basically anti-immigration which is, being in the U.S., is a really foreign thing to us. >> But there are some implications to business. I mean obviously there's filings, there's legal issues, obviously currency. Have you been impacted positively, negatively and what is the outlook on WANdisco's business going forward with the Brexit uncertainty and/or impact? >> We're in great shape because we buy pounds. We buy labor that's now discounted by 20% in the U.K. I just got back from the U.K. If you want to go on vacation, Americans, anywhere, go to London this summer and go shopping because everything is humongously discounted for us American's right now. It's a great time to be there. So from a WANdisco perspective-- >> John: How does that affect the housing bubble too? >> I said to you about a year ago that the London housing market was akin to the jewelry shops that existed in Hong Kong a few years ago, where the Chinese used to come over and basically launder money by buying huge diamonds and bars of gold and things. If you look at the London housing market it is primarily fueled by the Saudis and by the Russians who have been buying Hyde Park Corner 100 million pounds, $160 million, well $140 million now, apartments and so on in London. Now seven, and I repeat seven housing funds in the U.K. last week canceled redemptions. Which means that they can foresee liquidity problems coming in those funds. I think you're about to see a housing crash in London, the like of which we've never seen before, and I think it would be very sad and I think that will make people really question the Brexit decision. >> John: So sell London property now people? >> Yes. >> Before the crash. >> And go shopping, I heard the go shopping. So following along that, you talked about the significant differential between London and the rest of the U.K. You're from Sheffield, you're very proud of that. You've also been proud of your business really helping to fuel that economy. How do you think Brexit is going to affect WANdisco in your home area of Sheffield. >> I don't think it really will. I think our employees there, relative terms, very well paid. They're working on interesting things. They're working very closely with the AWS team, for example, the S3 team, the MR team. And building our technology, we're liaising very closely with them. They're doing lots of interesting things. I suspect their vacations into Europe and their vacations to the United States have just gone up by about 20% which will reduce the amount of beer that they can drink. It's a big beer drinking part of the world in Sheffield. Sheffield is, in terms of cost of living, is relatively low compared to the rest of the U.K. and I think those people will be pretty happy. >> David, I appreciate you coming on theCUBE. I want to give you the final word here on the segment because you're a chief executive officer of a public company. You've been in the industry for awhile. You've seen the trials and tribulations of the Hadoop ecosystem. Now basically branded as the data ecosystem. As Hortonworks has recently announced, Hadoop Summit is now being called Data Works Summit. They're moving from the word Hadoop to Data. Clearly that's impacting all the trends. Cloud data, mobile is really the key. I want you, and I'm sure you get this question a lot, I would like you to take a minute and explain to the audience that's watching, what's this phenom of Amazon Web Services really all about? What's all the hub-bub about? Why is everyone fawning over Amazon now? When you go back five years ago, or 10 years ago when it started, they were ridiculed. I remember when this started I loved it, but they were looked at as just a kind of a tinkering environment. Now they're the behemoth and just on an unstoppable run and certainly the expansion has been fantastic under Andy Jassy's leadership. How do you explain it to normal people what's going on at Amazon? Take a minute please. >> So Amazon is, and that's a brilliant question, by the way. Amazon is the best investor-relation story ever, and I mean ever. What Bezos did is never talked about the potential size of the market. Never talked about this thing was going to generate lots of cash. He just said, you know what, we're building this little internet thing. It might, it might not work. It's not going to make any money. And then in the blink of an eye, it's a $15 billion revenue business growing faster than any other part of his business and throwing off cash like there's no tomorrow. It is just the most non-obvious story in technology, in business, of any public company ever. I mean AWS, arguably, as a stand alone entity, is almost worth as much as Oracle. An unbelievable, an unbelievable story and to do that with all the complexity. I mean mean running a public company with shareholder expectations, with investor relations where you have to constantly be positive about what's going on. For him to do that and never talk about making a profit, never talk about this becoming a multi-billion dollar segment of their business, is the most incredible thing. >> So they've been living the agile. Certainly that's the business story, but they've been living the agile story relative to announcing the slew of new products. Basic building blocks S3, EC2 to start with, as the story goes from Andy Jassy himself, and then a slew of new services. It's a tsunami of every event of new services. What is the disruptive enabler? What's the disruption under the hood for Amazon? How do you explain that? >> Well, I mean what they did is they took a really simple concept. They said, okay, storage, how do we make storage completely elastic, completely public, in a way that we can use the public internet to get data in and out of it. Right? That sounds simple. What they actually built underneath the covers was an extremely complex thing called object store. Everybody else in the industry completely missed this. Oracle missed it, Microsoft missed it, everybody missed it. Now we're all playing catch-up trying to develop this thing called object store. It's going to take over, I mean, somebody said to me, what's the relevance of Hadoop in cloud? And you have to ask that question. It's a relevant question. Do you really need it when you've got object store? Show me side-by-side, object store versus every, you know, Net Apple, Teradata, or any of those guys. Show me side-by-side the difference between the two things. There ain't a lot. >> Amazon Web Service is a company that can put incumbents out of business. David, thanks so much. As we always say, what inning are we in? It's really a double-header. Game one swept by Amazon Web Services. Game two is the enterprise and that's really the story here at Amazon Web Services Summit in Silicon Valley. Can Amazon capture the enterprise? Their focus is clear. We're theCUBE. I'm John Furrier with Lisa Martin. We'll be right back with more after this short break. (techno music)

>> Narrator: From San Jose, California, in the heart of Silicon Valley, it's theCUBE. Covering Hadoop Summit 2016. Brought to you by Hortonworks. Here's your host, John Furrier. >> Welcome back everyone. We are here live in Silicon Valley at Hadoop Summit 2016, actually San Jose. This is theCUBE, our flagship program. We go out to the events and extract the signal to the noise. Our next guest, David Richards, CEO of WANdisco. And Joel Horowitz, strategy and business development, IBM analyst. Guys, welcome back to theCUBE. Good to see you guys. >> Thank you for having us. >> It's great to be here, John. >> Give us the update on WANdisco. What's the relationship with IBM and WANdisco? 'Cause, you know. I can just almost see it, but I'm not going to predict. Just tell us. >> Okay, so, I think the last time we were on theCUBE, I was sitting with Re-ti-co who works very closely with Joe. And we began to talk about how our partnership was evolving. And of course, we were negotiating an OEM deal back then, so we really couldn't talk about it very much. But this week, I'm delighted to say that we announced, I think it's called IBM Big Replicate? >> Joel: Big Replicate, yeah. We have a big everything and Replicate's the latest edition. >> So it's going really well. It's OEM'd into IBM's analytics, big data products, and cloud products. >> Yeah, I'm smiling and smirking because we've had so many conversations, David, on theCUBE with you on and following your business through the bumpy road or the wild seas of big data. And it's been a really interesting tossing and turning of the industry. I mean, Joel, we've talked about it too. The innovation around Hadoop and then the massive slowdown and realization that cloud is now on top of it. The consumerization of the enterprise created a little shift in the value proposition, and then a massive rush to build enterprise grade, right? And you guys had that enterprise grade piece of it. IBM, certainly you're enterprise grade. You have enterprise everywhere. But the ecosystem had to evolve really fast. What happened? Share with the audience this shift. >> So, it's classic product adoption lifecycle and the buying audience has changed over that time continuum. In the very early days when we first started talking more at these events, when we were talking about Hadoop, we all really cared about whether it was Pig and Hive. >> You once had a distribution. That's a throwback. Today's Thursday, we'll do that tomorrow. >> And the buying audience has changed, and consequently, the companies involved in the ecosystem have changed. So where we once used to really care about all of those different components, we don't really care about the machinations below the application layer anymore. Some people do, yes, but by and large, we don't. And that's why cloud for example is so successful because you press a button, and it's there. And that, I think, is where the market is going to very, very quickly. So, it makes perfect sense for a company like WANdisco who've got 20, 30, 40, 50 sales people to move to a company like IBM that have 4 or 5,000 people selling our analytics products. >> Yeah, and so this is an OEM deal. Let's just get that news on the table. So, you're an OEM. IBM's going to OEM their product and brand it IBM, Big Replication? >> Yeah, it's part of our Big Insights Portfolio. We've done a great job at growing this product line over the last few years, with last year talking about how we decoupled all the value-as from the core distribution. So I'm happy to say that we're both part of the ODPI. It's an ODPI-certified distribution. That is Hadoop that we offer today for free. But then we've been adding not just in terms of the data management capabilities, but the partnership here that we're announcing with WANdisco and how we branded it as Big Replicate is squarely aimed at the data management market today. But where we're headed, as David points out, is really much bigger, right? We're talking about support for not only distributed storage and data, but we're also talking about a hybrid offering that will get you to the cloud faster. So not only does Big Replicate work with HDFS, it also works with the Swift objects store, which as you know, kind of the underlying storage for our cloud offering. So what we're hoping to see from this great partnership is as you see around you, Hadoop is a great market. But there's a lot more here when you talk about managing data that you need to consider. And I think hybrid is becoming a lot larger of a story than simply distributing your processing and your storage. It's becoming a lot more about okay, how do you offset different regions? How do you think through that there are multiple, I think there's this idea that there's one Hadoop cluster in an enterprise. I think that's factually wrong. I think what we're observing is that there's actually people who are spinning up, you know, multiple Hadoop distributions at the line of business for maybe a campaign or for maybe doing fraud detection, or maybe doing log file, whatever. And managing all those clusters, and they'll have Cloud Arrow. They'll have Hortonworks. They'll have IBM. They'll have all of these different distributions that they're having to deal with. And what we're offering is sanity. It's like give me sanity for how I can actually replicate that data. >> I love the name Big Replicate, fantastic. Big Insights, Big Replicate. And so go to market, you guys are going to have bigger sales force. It's a nice pop for you guys. I mean, it's good deal. >> We were just talking before we came on air about sort of a deal flow coming through. It's coming through, this potential deal flow coming through, which has been off the charts. I mean, obviously when you turn on the tap, and then suddenly you enable thousands and thousands of sales people to start selling your products. I mean, IBM, are doing a great job. And I think IBM are in a unique position where they own both cloud and on-prem. There are very few companies that own both the on-prem-- >> They're going to need to have that connection for the companies that are going hybrid. So hybrid cloud becomes interesting right now. >> Well, actually, it's, there's a theory that says okay, so, and we were just discussing this, the value of data lies in analytics, not in the data itself. It lies in you've been able to pull out information from that data. Most CIOs-- >> If you can get the data. >> If you can get the data. Let's assume that you've got the data. So then it becomes a question of, >> That's a big assumption. Yes, it is. (laughs) I just had Nancy Handling on about metadata. No, that's an issue. People have data they store they can't do anything with it. >> Exactly. And that's part of the problem because what you actually have to have is CPU slash processing power for an unknown amount of data any one moment in time. Now, that sounds like an elastic use case, and you can't do elastic on-prem. You can only do elastic in cloud. That means that virtually every distribution will have to be a hybrid distribution. IBM realized this years ago and began to build this hybrid infrastructure. We're going to help them to move data, completely consistent data, between on-prem and cloud, so when you query things in the cloud, it's exactly the same results and the correct results you get. >> And also the stability too on that. There's so many potential, as we've discussed in the past, that sounds simple and logical. To do an enterprise grade is pretty complex. And so it just gives a nice, stable enterprise grade component. >> I mean, the volumes of data that we're talking about here are just off the charts. >> Give me a use case of a customer that you guys are working with, or has there been any go-to-market activity or an ideal scenario that you guys see as a use case for this partnership? >> We're already seeing a whole bunch of things come through. >> What's the number one pattern that bubbles up to the top? Use case-wise. >> As Joel pointed out, that he doesn't believe that any one company just has one version of Hadoop behind their firewall. They have multiple vendors. >> 100% agree with that. >> So how do you create one, single cluster from all of those? >> John: That's one problem you solved. >> That's of course a very large problem. Second problem that we're seeing in spades is I have to move data to cloud to run analytics applications against it. That's huge. That required completely guaranteed consistent data between on-prem and cloud. And I think those two use cases alone account for pretty much every single company. >> I think there's even a third here. I think the third is actually, I think frankly there's a lot of inefficiencies in managing just HDFS and how many times you have to actually copy data. If I looked across, I think the standard right now is having like three copies. And actually, working with Big Replicate and WANdisco, you can actually have more assurances and actually have to make less copies across the cluster and actually across multiple clusters. If you think about that, you have three copies of the data sitting in this cluster. Likely, an analysts have a dragged a bunch of the same data in other clusters, so that's another multiple of three. So there's amount of waste in terms of the same data living across your enterprise. That I think there's a huge cost-savings component to this as well. >> Does this involve anything with Project Atlas at all? You guys are working with, >> Not yet, no. >> That project? It's interesting. We're seeing a lot of opening up the data, but all they're doing is creating versions of it. And so then it becomes version control of the data. You see a master or a centralization of data? Actually, not centralize, pull all the data in one spot, but why replicate it? Do you see that going on? I guess I'm not following the trend here. I can't see the mega trend going on. >> It's cloud. >> What's the big trend? >> The big trend is I need an elastic infrastructure. I can't build an elastic infrastructure on-premise. It doesn't make economic sense to build massive redundancy maybe three or four times the infrastructure I need on premise when I'm only going to use it maybe 10, 20% of the time. So the mega trend is cloud provides me with a completely economic, elastic infrastructure. In order to take advantage of that, I have to be able to move data, transactional data, data that changes all the time, into that cloud infrastructure and query it. That's the mega trend. It's as simple as that. >> So moving data around at the right time? >> And that's transaction. Anybody can say okay, press pause. Move the data, press play. >> So if I understand this correctly, and just, sorry, I'm a little slow. End of the day today. So instead of staging the data, you're moving data via the analytics engines. Is that what you're getting at? >> You use data that's being transformed. >> I think you're accessing data differently. I think today with Hadoop, you're accessing it maybe through like Flume or through Oozy, where you're building all these data pipelines that you have to manage. And I think that's obnoxious. I think really what you want is to use something like Apache Spark. Obviously, we've made a large investment in that earlier, actually, last year. To me, what I think I'm seeing is people who have very specific use cases. So, they want to do analysis for a particular campaign, and so they may just pull a bunch of data into memory from across their data environment. And that may be on the cloud. It may be from a third-party. It may be from a transactional system. It may be from anywhere. And that may be done in Hadoop. It may not, frankly. >> Yeah, this is the great point, and again, one of the themes on the show is, this is a question that's kind of been talked about in the hallways. And I'd love to hear your thoughts on this. Is there are some people saying that there's really no traction for Hadoop in the cloud. And that customers are saying, you know, it's not about just Hadoop in the cloud. I'm going to put in S3 or object store. >> You're right. I think-- >> Yeah, I'm right as in what? >> Every single-- >> There's no traction for Hadoop in the cloud? >> I'll tell you what customers tell us. Customers look at what they actually need from storage, and they compare whatever it is, Hadoop or any on-premise proprietor storage array and then look at what S3 and Swift and so on offer to them. And if you do a side-by-side comparison, there isn't really a difference between those two things. So I would argue that it's a fact that functionally, storage in cloud gives you all the functionality that any customer would need. And therefore, the relevance of Hadoop in cloud probably isn't there. >> I would add to that. So it really depends on how you define Hadoop. If you define Hadoop by the storage layer, then I would say for sure. Like HDFS versus an objects store, that's going to be a difficult one to find some sort of benefit there. But if you look at Hadoop, like I was talking to my friend Blake from Netflix, and I was asking him so I hear you guys are kind of like replatforming on Spark now. And he was basically telling me, well, sort of. I mean, they've invested a lot in Pig and Hive. So if you think it now about Hadoop as this broader ecosystem which you brought up Atlas, we talk about Ranger and Knox and all the stuff that keeps coming out, there's a lot of people who are still invested in the peripheral ecosystem around Hadoop as that central point. My argument would be that I think there's still going to be a place for distributed computing kind of projects. And now whether those will continue to interface through Yarn via and then down to HDFS, or whether that'll be Yarn on say an objects store or something and those projects will persist on their own. To me that's kind of more of how I think about the larger discussion around Hadoop. I think people have made a lot of investments in terms of that ecosystem around Hadoop, and that's something that they're going to have to think through. >> Yeah. And Hadoop wasn't really designed for cloud. It was designed for commodity servers, deployment with ease and at low cost. It wasn't designed for cloud-based applications. Storage in cloud was designed for storage in cloud. Right, that's with S3. That's what Swift and so on were designed specifically to do, and they fulfill most of those functions. But Joel's right, there will be companies that continue to use-- >> What's my whole argument? My whole argument is that why would you want to use Hadoop in the cloud when you can just do that? >> Correct. >> There's object store out. There's plenty of great storage opportunities in the cloud. They're mostly shoe-horning Hadoop, and I think that's, anyway. >> There are two classes of customers. There were customers that were born in the cloud, and they're not going to suddenly say, oh you know what, we need to build our own server infrastructure behind our own firewall 'cause they were born in the cloud. >> I'm going to ask you guys this question. You can choose to answer or not. Joel may not want to answer it 'cause he's from IBM and gets his wrist slapped. This is a question I got on DM. Hadoop ecosystem consolidation question. People are mailing in the questions. Now, keep sending me your questions if you don't want your name on it. Hold on, Hadoop system ecosystem. When will this start to happen? What is holding back the M and A? >> So, that's a great question. First of all, consolidation happens when you sort of reach that tipping point or leveling off, that inflection point where the market levels off, and we've reached market saturation. So there's no more market to go after. And the big guys like IBM and so on come in-- >> Or there was never a market to begin with. (laughs) >> I don't think that's the case, but yes, I see the point. Now, what's stopping that from happening today, and you're a naughty boy by the way for asking this question, is a lot of these companies are still very well funded. So while they still have cash on the balance sheet, of course, it's very, very hard for that to take place. >> You picked up my next question. But that's a good point. The VCs held back in 2009 after the crash of 2008. Sequoia's memo, you know, the good times role, or RIP good times. They stopped funding companies. Companies are getting funded, continually getting funding. Joel. >> So I don't think you can look at this market as like an isolated market like there's the Hadoop market and then there's a Spark market. And then even there's like an AI or cognitive market. I actually think this is all the same market. Machine learning would not be possible if you didn't have Hadoop, right? I wouldn't say it. It wouldn't have a resurgence that it has had. Mahout was one of the first machine learning languages that caught fire from Ted Dunning and others. And that kind of brought it back to life. And then Spark, I mean if you talk to-- >> John: I wouldn't say it creates it. Incubated. >> Incubated, right. >> And created that Renaissance-like experience. >> Yeah, deep learning, Some of those machine learning algorithms require you to have a distributed kind of framework to work in. And so I would argue that it's less of a consolidation, but it's more of an evolution of people going okay, there's distributed computing. Do I need to do that on-premise in this Hadoop ecosystem, or can I do that in the cloud, or in a growing Spark ecosystem? But I would argue there's other things happening. >> I would agree with you. I love both areas. My snarky comment there was never a market to begin with, what I'm saying there is that the monetization of commanding the hill that everyone's fighting for was just one of many hills in a bigger field of hills. And so, you could be in a cul-de-sac of being your own champion of no paying customers. >> What you have-- >> John: Or a free open-source product. >> Unlike the dotcom era where most of those companies were in the public markets, and you could actually see proper valuations, most of the companies, the unicorns now, most are not public. So the valuations are really difficult to, and the valuation metrics are hard to come by. There are only few of those companies that are in the public market. >> The cash story's right on. I think to Joel' point, it's easy to pivot in a market that's big and growing. Just 'cause you're in the wrong corner of the market pivoting or vectoring into the value is easier now than it was 10 years ago. Because, one, if you have a unicorn situation, you have cash on the bank. So they have a good flush cash. Your runway's so far out, you can still do your thing. If you're a startup, you can get time to value pretty quickly with the cloud. So again, I still think it's very healthy. In my opinion, I kind of think you guys have good analysis on that point. >> I think we're going to see some really cool stuff happen working together, and especially from what I'm seeing from IBM, in the fact that in the IT crowd, there is a behavioral change that's happening that Hadoop opened the door to. That we're starting to see more and more It professionals walk through. In the sense that, Hadoop has opened the door to not thinking of data as a liability, but actually thinking about data differently as an asset. And I think this is where this market does have an opportunity to continue to grow as long as we don't get carried away with trying to solve all of the old problems that we solved for on-premise data management. Like if we do that, then we're just, then there will be a consolidation. >> Metadata is a huge issue. I think that's going to be a big deal. And on the M and A, my feeling on the M and A is that, you got to buy something of value, so you either have revenue, which means customers, and or initial property. So, in a market of open source, it comes back down to the valuation question. If you're IBM or Oracle or HP, they can pivot too. And they can be agile. Now slower agile, but you know, they can literally throw some engineers at it. So if there's no customers in I and P, they can replicate, >> Exactly. >> That product. >> And we're seeing IBM do that. >> They don't know what they're buying. My whole point is if there's nothing to buy. >> I think it depends on, ultimately it depends on where we see people deriving value, and clearly in WANdisco, there's a huge amount of value that we're seeing our customers derive. So I think it comes down to that, and there is a lot of IP there, and there's a lot of IP in a lot of these companies. I think it's just a matter of widening their view, and I think WANdisco is probably the earliest to do this frankly. Was to recognize that for them to succeed, it couldn't just be about Hadoop. It actually had to expand to talk about cloud and talk about other data environments, right? >> Well, congratulations on the OEM deal. IBM, great name, Big Replicate. Love it, fantastic name. >> We're excited. >> It's a great product, and we've been following you guys for a long time, David. Great product, great energy. So I'm sure there's going to be a lot more deals coming on your. Good strategy is OEM strategy thing, huh? >> Oh yeah. >> It reduces sales cost. >> Gives us tremendous operational leverage. Getting 4,000, 5,000-- >> You get a great partner in IBM. They know the enterprise, great stuff. This is theCUBE bringing all the action here at Hadoop. IBM OEM deal with WANdisco all happening right here on theCUBE. Be back with more live coverage after this short break.