>> From the SiliconANGLE media office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Stu Miniman. >> Hi, I'm Stu Miniman, and welcome to theCUBE's Boston-area studio. Happy to welcome back to the program two CUBE alums. To my immediate right is Peter Smails, who's the CMO of Imanis Data, and joining him for the segment is Zeus Kerravala, who is founder and Principal at ZK Research. Gentlemen, thanks so much for joining us. >> Thank you. >> Thanks for having me. >> All right, so, we go out to so many shows, we're talking about massive change in the industry. Last two shows I've gone to, really looking at how hybrid and multi-cloud are shaping up, and change, and just the proliferation of options really seems to define what's happening in our industry. And Zeus, want to start with you because you've got some good research which looks at the data side of it. And of course, I'm an infrastructure guy, >> Yeah. >> but the reason we have infrastructure is to run my apps. And the only reason we have apps, really, is behind the data. And that transformation of data, and data at the core of everything, is something that we've loved to cover the last few years. So, what's new on your world? >> Yeah I, in fact, the word you said there, change, is apropos. Because I think I have never seen a time in IT, and I've been an analyst for 20 years and I was a CIO for a while, but I've never seen a period of change like this before. Where digital transformation is reshaping companies as fast as possible. Now, the key to being a successful digital organization is being able to take advantage the massive amounts of data that you have, and then be able to use some machine learning, or other analytic capabilities, to find those nuggets in there to be able to help you change your business process, make people more productive, improve customer service, whatever you're trying to do. I think it really stems from the analytics, that data. Now, what my research has found is that companies are really, and this shouldn't be a big surprise, but companies are really only using a very small slice of their data. Maybe five to 10% at the most in their data. Most data's kept in what's called secondary storage, and there what's happening is this concept called mass data fragmentation. Where we've always had data fragmentation, but it's becoming worse. Where data's now being stored, not only on local computers and servers, but also in the cloud, on IoT devices, out at the edge, within your organization. And so, this concept of mass data fragmentation has exploded. And it's hampering companies' ability to actually make critical decisions to be able to move fast and keep up with a lot of the cloud-native counterparts. And if they don't get a handle on this, they're going to wind falling further and further behind. I think it's absolutely critical today that this challenge of mass data fragmentation be solved. >> Yeah, Peter, want to pull you into this discussion. You talked to a lot of users, and we've talked to you at some of the Hadoop Shows. We look at what's happening in like the database world and there's so many options. >> Yeah. >> I know our team members that keep up to it, they keep spreadsheets. and they're trying to keep up with all of these, but seems like every week there's a new open-source this and that, >> Right, right. >> that's going to capture this segment of the market. But something that I found interesting from one of the previous interviews we'd done with you and your company is it's not that I took my main vendor of choice and I went to one other. It's that today, the database world is like everything else, I'm using a lot. >> Yeah, yeah. >> And it is, and, and therefore, we know that has ripple effects for what I do for security and what I do for things like data protection. Can you give us a little bit of, just kind of a view as to what customers, you know, why are they going to so many applications? What are some of the leading >> Sure. ones in the space? And we know that in IT nothing ever dies, >> and it's, >> Right. >> it tends to be additive. So, how are they dealing with this? >> Yeah, and it picks up directly on what Zeus was just saying before around this notion of fragmentation. So, Imanis Data, the genesis of Imanis Data was really around, if you look at it in the context of cloud, Could 1.0 was, it was essentially, let me take all my legacy applications, lift and shift. Right, let's just take everything on on-prem and let's put it in the cloud. People quickly realized that they were solving the wrong problem. The real answer to the problem was if I want to take advantage of all my data, if I want to take advantage of hybrid-cloud infrastructure. I've got to move from a traditional monolithic stack, application stack, to more of a microservices-based architecture. That led to a very rapid proliferation of new database platforms, both on the Hadoop side for big data, as well as the on the NoSQL side. So, the synergy here in why we like this research so much is because Hadoop, the key message is that Hadoop and NoSQL have both become significant contributors to the mass data fragmentation challenge. And that's really driven, ultimately, by digital transformation and organizations' desire to move to a true hybrid-cloud-based infrastructure. >> How does cloud and this data fragmentation, how does this all go together? >> Oh, our cloud and data fragmentation actually go hand in hand. People thought the cloud was actually solving a lot of their problems, but in a lot of ways it contributed to it, because, as you said, we never get rid of the old. We keep the old around and we add to it. In fact, what I've seen happens is with so many cloud repositories now, users are storing data in the place they were before and then making copies of it in these new cloud services. And in fact, almost all of the new app collaborative applications have their own cloud repositories. So, we've gone from an environment where we had a handful of storage repositories to manage to that absolutely exploding. And I think the cloud itself has matured. I think people are now starting to figure out how to really, to your point, use the cloud in a much different way than before. And so, they're reliant on it. The companies are dependent on it, but if we don't get a handle on where our data is we're going to wind up in a situation where it just becomes unmanageable. >> Yeah, and just to add to that, from additional researches, that according to recent research, 38% of interviewed companies had more than 25 databases. 20% of those same companies had over 100 databases. So, the point is there is a huge fragmentation issue. And if the problem you're trying to solve, ultimately, is insight to your data and intelligence on your business, you've got to create, you've got to solve this problem of fragmentation, because otherwise, you're never going to have any economies of scale. You're never going to be able to give visibility to all your data. That's ultimately the problem that needs to be solved. >> Yeah, it's funny, 'cause you talked about early cloud, and people thought oh, right, I'm going to move everything there and I'll have one cloud, it'll be the cloud. >> The cloud. >> Ah yeah, things like that. And of course, we understand, there's lots of reasons why I'm going to choose multiple solutions. But, too many companies I talk to, when you figure out how they got there. It wasn't like they said, well this is our strategy and we're going to do this, and this, and this. It was, well, different business units have different reasons. Just like I would build infrastructure for my various applications, I would have different groups with different needs. And then, hey IT, can you help us bring all these pieces together? So, how are we doing as an industry for helping customers get their arms around this? Is this just a mess today? Is there a wave, or a trend, as to how we put together, right? Who solves it from a vendor standpoint, and who, from the customer standpoint, kind of has the, is the champion of helping to solve this issue? >> Yeah, I think one of anything is unrealistic, right? And in fact, customers do want choice and they do want options. So, it's not the industry's job to force customers consolidate to one. In fact, it's better to let them use whatever they want. Now, where it becomes, where the work needs to be done now is creating that middleware layer, if you will, or that management layer, that sits above the infrastructure, that gives you the common view. So, I think this mythical single pane of glass we've been searching for for so long, actually, the cloud drives us in that direction, because we do need something to help us give that visibility. I know one of your partners, Cohesity, does that on the secondary storage side to actually make MDF, or mass data fragmentation, manageable. And there's other vendors that do that in other areas, but I think the concept here isn't to try and drive customers into selective choices, but it's to allow them to use whatever they want and then create a management layer over top that gives them that visibility to it looks like one environment. But in fact, it's whatever they want to use underneath. >> Yeah, and picking up on that, the notion of, if you look at the, you asked the question about, sort of, who owns the mantle of driving all this stuff together? And the answer isn't, you could say, oh, the chief data officer. Certain organizations have gone to the level of saying we have a chief data officer and they're trying to drive towards a consolidated strategy. That's a great idea, but, sort of the federation of how things have evolved is actually, is been a good model. Like, a lot of the folks that, from an Imanis Data standpoint, that we speak to, it's architects, it's developers, it's DevOps. And so, from an organizational standpoint, what's happening is you've got to have, over time, you've got to have the application folks, the DevOps folks, the architects, the DBAs, get more closely aligned with your traditional IT and infrastructure folks. That's evolving. And to Zeus' point there, that's not, you're not going to drive them all to one thing, because they have different viewpoints and such, but you need to provide that common layer. Sort of let them do their own thing, but then on the backend be able to sort of provide that common layer to be able to eliminate the backend silos. >> Okay, and drill us down a little bit. We brought up then that the notion of management being able to see across these environments as a piece of the solution, but what is Imanis doing? What are you seeing out there? And, I'll caution, we know a single pane of glass to solve everything is kind of the holy grail, but reality is we need to solve real problems for customers today, and yeah. >> Yeah, and our piece of the puzzle, our piece of the puzzle is Imanis Data is enterprise data management for Hadoop and NoSQL. That's where we focus. We're basically delivering industry-leading solutions for Hadoop and NoSQL. That has led to a very logical collaboration with Cohesity, who's one of the leaders in hyper-converged secondary storage. So, they're trying to provide that common layer of infrastructure to address mass data fragmentation. We see that as, we're the Hadoop and NoSQL folks, so there's a very logical synergy, whereby the combination of Cohesity's solution and Imanis Data's solution essentially then provides, ultimately will provide that single pane of glass. But also, again, at the end of the day provides a common visibility and a common layer to all of your secondary storage whether traditional, relational, VM-based, cloud-based, whether it's your Hadoop and NoSQL-based data. >> Okay, so, bring us back to the customers. We know that simplification is something we want. You know, the cloud world doesn't feel like it's gotten things any simpler. So, where are we? What needs to happen down the road? What more can you share about customers? >> Yeah, I think that's fair to say it hasn't gotten more simple, and in fact, it's gotten more complicated. Everybody I talk to in IT is drowning today in whatever the task is. And I think the point you made of single pane of glass, of remain largely myth, I think the focus is wrong. I don't believe we actually need a single pane of glass that can manage, that can see everything. I think what we need are separate panes of glass that let us see what we need to see. And in fact, the way you guys do that for NoSQL and Hadoop makes some sense. Cohesity has their own that looks at things at more of a higher level, data plate. So, I think we're really in the early innings here, Stu. I think over the next few years, we will see a rise in better management tools and things to help us simplify. I know I just did some research on IT priority for 2019, and simplification actually is now ahead of even cybersecurity as the number one path for today's CIOs. So, I think we've gotten to the point where we've consumed so much stuff, now it's time to simplify it. And there's no one answer for that, but I think within the different departments within IT, they need to look at what those management tools are to let them do that. >> Yeah, I mean, going back, I think back to when I first became an analyst about nine years ago. A central premise is that enterprise IT doesn't necessarily have the skillset to go architect it. They're not a Google or a Yahoo. So, they will spend money from the vendors and the suppliers to help simplify that for them environment. But Peter, I want to ask you, brought up people who are drowning in information. >> Yeah, yes. >> Definitely, we know that today in 2019 there is more going on than they had a year from now, and when we look forward to 2020, we expect that there will be even more. So, the answer in the industry is AI and ML are going to come solve some of this for us. So, to tell us, how does that fits in to these sorts of solutions? >> Sure, and the answer is machine learning and AI will absolutely need to be. Our view is that they're critical pillars to the future of data management. They have to be, because the volume of data and the complexity of the infrastructure within which you're running. You can't, as human beings, we are drowning, and you need tools, you need help to solve this problem. And machine learning and AI are absolutely going to be key contributors. From an Imanis Data standpoint, our approach has been very much about completely avoiding the whole notion of machine learning whitewash. Let's talk about the practical application of machine learning. So, for example, what we do today is we apply machine learning to do what we call ThreatSense. So, it's very specifically applied to the automation of anomaly detection, okay. Build a model of what normal looks like from a backup and recovery standpoint. Anything that falls outside of normal gets flagged, so that administrators can then do something. Provide a human feedback loop to that machine running algorithm, so it can get smarter. We also recently introduced something that we call smart policies. That's about the automation of backup. So, again, it's not about the holy grail of machine learning. In the case of smart policies, it's instead of creating spreadsheets and having a human being trying to figure out how to address a particular RPO, it's tell us what's your RPO and what data do you want to protect. We'll go build a model and we'll address your RPOs, and if we can't, we'll tell you why we can't. So, very practical for today. To the point you made earlier about that fact that we're still in the early innings, today it's about the practical application of machine learning and AI to help people automate processes. >> I think the fear and doom and gloom around AI is, particularly in the IT circles, is completely misguided. I understand why people might think it's going to take their job, but AI and ML is the IT pro's best friend. There's so much data today, they're so much to do, that people just can't connect the dots between those data points fast enough. >> Right. >> Just like you look, today you wouldn't go to a radiologist that doesn't use machine learning to look at your brain scans, right? You know, it's getting harder and harder to work, to be a customer of a company that doesn't use AI or ML to analyze your data, and it becomes very apparent, because they're just not able to provide the same type of service. >> Yeah, totally agree. We've done some events with MIT and a couple of the professors there, Erik Brynjolfsson and Andy McAfee talk about racing with the machines. >> Yeah. >> So, the people that can actually harness and leverage that, the challenge is, if you're in IT and you're working on stuff that's five to 10 years old, and you can't take advantage of those new tools, well, you need to skill up, and you need to get ready. But most companies I talk to, it's not that they're looking to cut half the workforce, it's just that they can't add many more people, so most of them can be reskilled, or heck, if there's some automation they can have in there. There's lots of projects sittin' on the table that they've been trying to do for years. I don't find anybody that ever said, hey, if I could give ya an extra month in the year that you wouldn't have to figure out. >> The question is, do you want to be strategic to your organization, or tactical? And if you want to be tactical, your job's only as long as that tactic, right, so. >> Peter, when I was hearing you walk through some of that ML piece, things like security and ransomware kind of popped into my head. Is that a part of the solution in offer? >> Yeah, absolutely. So, ThreatSense is, specifically, we talk about as anomaly detection, because overall it really is about, ransomware is essentially about detecting anomalies. So, ransomeware is an application of anomaly detection. So, our ThreatSense capability is built into the product. What happens is, when we do backups, like I said, we build a model of what normal looks like, and then we flag anomalies. My dataset size, all of a sudden spike. My data type, all of a sudden I have a bunch of ZIP files, or something, all of a sudden. Something has changed that's outside of normal, and then we flag that, and you can take action against that. So, absolutely it is, but the initial application is specifically about ransomware. >> All right. Zeus, is there advice that you would want to give users, or when you're talking to customers, what's the profile of somebody that is handling their data, and leveraging it well? >> I don't always really hand it well. (all laughing) But I think the advice I'd give is you want to simplify and automate as much as you can, and ruthlessly automate. I think if you're trying to do things the old way, you're going to wind up falling behind. And so, I suppose to your question, what's the profile of a company that's doin' it well. It's one that's actually able to roll up new services quickly, and you see that in a lot of the big name cloud companies. They always new things comin' and new things goin', and they're able to transform the way they deal with customers and employees. That's the hallmark of a company that's using it's data well. Ones that aren't, frankly, we've seen a lot of 'em go out of business, right, over the last few years. And so, I think from an IT perspective, you want to embrace automation, embrace machine learning, right, embrace this concept of single pane of glass for your particular domain. Because what it lets you do is, it becomes a tool to help you do your job better. There's certain things people are good at and there's certain things people aren't, and connecting the dots, and terabits, petabytes of, bits of data isn't one of 'em. So, I think from an IT perspective, you want to automate, and you want to embrace machine learning, because it's going to be your best friend, and it's going to help you keep your skillset current. >> Yeah, and I would just pick up on that and say that the answer isn't constraining, to a large extent it's really embracing data diversity. Like the answer to mass data fragmentation isn't homogenization of your data, or limiting particular data types. The proliferation of different data types is a direct result of organizations trying to be more agile, and trying to be more nimble. So, the answer isn't sort of constraining data. The answer is making the strategic investments in the right tools, in sort of in some of the right policies and governance, if you will. So, that you keep everybody strategically going in the right direction in this sort of federated diverse type of environment. >> Yeah, if you look at any market in IT, well, really even in the consumer world, where there has been choice, it's create a rising tide for everybody. >> Right. >> The question is, you can't have it be chaotic. >> Right. >> Right, and so you're bringing a level of order to a world that was historically chaotic, and that untethers people to make whatever choice they want and use the best possible tools. >> Yeah. >> Right. >> Peter, I go back to the promise of big data, was that I was going to turn that proliferation of volume, velocity of data from a, oh my god, that's a problem, and flip it on its head, and become an opportunity for how we can leverage data. Give me the final word. How do we connect the dot from where that was a few years ago to this mass data fragmentation world today. >> Yeah, and the answer to that is don't treat, don't make big data sort of the three guys over in the corner who are the data scientist. Embrace big data. Embrace all your data types. So, our message, as the Hadoop and NoSQL data management folks, is simply, look Hadoop and NoSQL are a key part of your overall data strategy. Embrace those, include those in your overall strategy, and make sure you're basically taking the right contextual picture of what you're trying to do. Include all your different data types. Hadoop and NoSQL are contributors to mass data fragmentation, but as part of that salute, if they're part of the problem, then they need to be part of the solution, both from a data standpoint and from a solution standpoint. So, that's really the message that we're driving is that, embrace all your different data types, put the appropriate systems in place, take the right sort of approach to consolidating and solidifying your overall data strategy. >> All right, well, Peter and Zeus, thanks so much for sharing >> Thank you. the latest update. Absolutely, data at the center of it all, and need to embrace those new tools and opportunities out there. All right, I'm Stu Miniman. And be sure to check out thecube.net for all of our research and shows that we'll be at. And thank you, as always, for watching theCUBE. (electronic music)

live from New York it's the cube covering the cube New York City 2018 brought to you by silicon angle media and its ecosystem partners i'm jeff workday Villante we're here nine years our nine years of coverage two days live in New York City and our next two guests shot Mrazek CEO amana stayed at fiendish males CMO mystic good to see you again welcome back thank you bad to be here guys so obviously this show we've been here nine years we were the first original Hadoop world we've seen a change Hadoop was gonna change the world it kind of didn't but we get the idea of it did not it did didn't but it would change our world it brought open source and the notion of low-cost Hardware into the big data game and then the big data became so much more powerful around these new tools but then the cloud comes in full throttles and while they can get horsepower that compute you can stand up infrastructure for analytics all this data goodness starts to change machine learning then becomes the the real utility that's showing this demand for using data right now not the set up using data this is a fundamental big trend so I don't get you guys reaction what do you see this evolving more cloud like how do you guys see the trend in this as data science certainly becoming more mainstream and productivity users to hardcore users and then you got cloud native developers doing things like kubernetes we've heard kubernetes here it's like a cloud is a data science what's going on what's your view of the market so I came from a company that was in an tech and we were built on big data and in looking at how big data is evolved and the movement towards analytics and machine learning it really being enabled by Big Data people have rushed to build these solutions and they've done a great job but it was always about what's the solution to my problem how do i leverage this data and they built out these platforms and in our context what we've seen is that enterprises get to a certain point where they say okay i've got all these different stacks that have been built these apps that have been built to solve my bi and analytics problems but what do I do about how do I manage all these and that's what I encounter my last company where we built everything ourselves and then so wait a minute but what we see at an enterprise level is fascinating because when I go to a large company I go you know we work with no sequel databases and Hadoop and you know how much Couchbase do you have how much Mongo etc the inevitable answer is yes and five of each right and they're cutting to this point where I've got all this distributed data distributed across my organization how am I going to actually manage it and make sure that that data is protected that I can migrate to the cloud or in a hybrid cloud environment and all these questions start to come up at an enterprise level we actually have had some very high-level discussions at a large financial institution here in New York where they literally brought 26 people to the meeting the initial meeting this was literally a second call where we were presenting our capability because they're they're now at the point where it's like this is mission-critical data this is not just some cool stuff somebody built off in one of our divisions it matters to the whole enterprise how do we make sure that data is protected backed up how do we move data around and that's really the the trend that we're tapping into and that the founders of our company saw many years ago and said I need to I need to we need to build a solution around this it's interesting you know you think about network data as a concept or data in general it's kind of got the same concepts we've seen in networking and/or cloud a control plane of some sorts out there and you know we're networking kind of went wrong as the management plane was different than the control plane so management and control or huge issues I mean you bring up this sprawl of data these companies are data full it's not like hey we might have data in the future right they got data now they're like bursting with data one what's the control plane look like what's the management plane look like these are all there's a technical concepts but with that with that in mind this is a big problem what our company is doing right now what are what are some of the steps that are taking now to get a handle on the management the data management it's not just your grandfather's data management so we anymore it's different it looks different your thoughts on on this chain of management so they're approaching the problem now and that's our sweet spot but I don't think they have in their minds yet come to exactly how to solve it it's there's this realization about we need to do this at this point and and and in fact doing it right is something that our founders when they built Lee said look if this problem of data management across big data needs to be solved by a data we're platform built on big data so let's use big data techniques to solve the problem all right so let's before getting some of the solution you guys are doing take a minute to explain what you guys are doing for the company the mission you know the value proposition status what do you guys do how are people gonna consume your product I mean take a particular type gen simple elevator pitch and we were enterprise data management focused specific than had you been no sequel so everyone's familiar with the traditional space of data management in the relational space relational world very large market very mature market well we're tapping into is what John was just saying which is you've got this proliferation but Dupin no sequel and people are hitting the wall they're hitting the ceiling because they don't have the same level of operational tools that they need to be able to mainstream these deployments whether it's data protection whether it's orchestration whether it's migration whatever the case may be so what we do that's essentially our value prophecy at a management for a Dupin no sequel we help organizations essentially drive that control plane really around three buckets data protection if it's business critical I got to protect it okay disaster recovery falls into protection bucket good old stuff everyone's familiar with but not in Hadoop in no single space orchestrations the second big bucket for us which is I'm moving to an agile development model how do i do things like automated test dev how do i do things like GD are the compliance management how do i do things like cloud migration you tut you know john touched on this one before a really interesting trend that we're seeing is you said what are customers doing they're trying to create a unified taxonomy they're trying to create a unified data strategy which is why 26 people end up in the but in lieu of that there's this huge opportunity because of what they need they know that it's got to be protected and they have 12 different platforms and they also want to be able to do things like one Cosmo I'm on go today but I'll be cosmos tomorrow I'm a dupe today but I might be HD inside tomorrow I want to just move from one to the other I want to be able to do intelligence so essentially the problem that we solve is we give them that agility and we give them that protection as they're sort of figuring this all out so we have this right you basically come in and say look it you can have whatever platform you want for your day there whether it's Hadoop and with most equals get unstructured and structured data together which makes sense but protections specifically does it have to morph and get swapped out based upon a decision correct make well now we're focused specifically Hadoop and no sequel so we would not be playing like if you we're not the 21st vendor to be helping s AP and Oracle you know customers backup their data it's basically if your Hadoop renewal sequel that's the platform regardless of what Hadoop distribution you're doing or where it's no see you know change out your piece what they do as they evolve and are correct I feel exactly right you're filling white space right because when this whole movement started it was like you were saying commodity Hardware yeah and you had this this idea of pushing code to data and oh hey his life is so easy and all of a sudden there's no governance there's no data protection no business continuity is all his enterprise stuff I didn't you heard for a long time people were gonna bring enterprise grade to Hadoop but they really didn't focus on the data protection space correct or the orchestra either was in those buckets and you touch them just the last piece of that puzzle value wise is on the machine learning piece yeah we do protection we do orchestration and we're bringing machine learning to bear to automate protection what amazing we hear a lot and that's a huge concern because the HDFS clusters need to talk speech out there right so there's a lot of nuances and Hadoop that are great but also can create headache from a user human standpoint because you need exact errors can get folded I gotta write scripts it creates a huge problem on multiple fronts the whole notion of being eventually being clustered in the first base being eventually consistent in the second place it creates a huge opportunity for us because this notion of being a legs we get the question asked the question why well you know there are a lot of traditional vendors they're just getting into the space and then what do that that's actually good because it rises you know rises all boats if you will because we think we've got a pretty significant technology mode around our ability to provide protection orchestration for eventually consistent clustered environments which is radically different than the traditional I love the story about the 26 people showing them me take me through what happened because that's kind of like what your jonquil fishbowl what do they do it they sit in their auditing they take a node so they really raising their hand they peppering you with questions what what happened in that meeting tell us so so it's an interesting microcosm what's happening in these organizations because as the various divisions and kind of like the federated IT structure started building their own stuff and I think the cloud enabled that it's like you know basically giving a the middle finger to central IT and so I can do all this stuff myself and then the organization gets to this realization of like no we need a central way to approach data management so in this meeting basically so we had an initial meeting with a couple of senior people and said we are we are going about consolidating how we manage all this data across all these platforms we want you to come in and present so when we presented there was a lot of engagement a lot of questions you could also see people still though there's an element of I want to protect my world and so this organizational dynamic plays out but you know when you're at a fortune 50 company and data is everything there's the central control starts to assert itself again and that's what we saw in this because the consequences of not addressing it is what is potentially massive data you know data loss loss of millions hundreds of millions of dollars you know data is the gold now right is the new oil so the central organizations are starting to assert that so we say that see that playing out and that's why all these people were in this meeting which is good in a way because then we're not like okay we got to sell ten different groups or ten different organizations it's actually being so there's there's kind of this pull back to the center it's happened in the no sequel world of your perspectives on this I mean early on you had guys like Mongo took off because it was so simple to use and capture unstructured data and now you're hearing everybody's talking about you know acid compliance and enterprise you know great capabilities that's got to be a tailwind for you guys could you bring it in the data protection and orchestration component but yeah what do you see it in that world what do you guys support today and maybe give us a glimpse of the future sure so that what we see as well a couple different things we are we are agnostic to the databases in the sense that we are definitely in Switzerland we were we you know we support all commerce so it's you know it's follow the follow the follow of the market share if you will Cassandra Mongo couch data stacks right on down the line on the no sequel side and what's interesting so they have very there have all varying degrees of maturity in terms of what their enterprise capabilities are some of them offer sort of rudimentary backup type stuff some fancy they have more backup versus others but at the end of the day you know their core differentiation they each it's fascinating to each have sort of a unique value prop in terms of what they're good at so it's a very fragmented market so that's a challenge that's an opportunity for us but it's a challenge from a marketplace networkers they've got to carve out there they all want the biggest slice of the pie but it's very fragmented because each of them is good at doing something slightly different yeah okay and so that like the the situation described before is they've got yes so you got one of everything yeah so they've got 19 different backup and recovery right coordinate processes approach or the or nothing or scripting law so that they do have to they've got a zillion steps associated with that and they're all scripted and so their probability of a failure you know very you drop a mirror that's a human error to is another problem and you use the word tailwind and I think that's very appropriate because with most of these vendors they're there they've got their hands full just moving their database features forward right you know where the engagement so when we can come in and actually help them with a customer who's now like okay great thank you database platform what do you do for backup well we have a rudimentary thing we should belong with it but there is one of our partners a manas who can provide these like robust enterprise it really helps them so with some of those vendors were actually a lot of partner traction because they see it's like that's not what their their strength is and they got to focus on moving their database so I'll give you some stats I'm writing a piece right now a traditional enterprise back in recovery but I wonder if you could comment on how it applies to your world so these are these are research that David flora did and some survey work that we've done on average of global 2000 organizations will have 50 to 80 steps associated with its backup and recovery processes and they're generally automated with scripts which of course a fragile yeah right and their prefer own to era and it's basically because of all this complexity there's a 1 in 4 chance of encountering an error on recovery which is obviously going to lead to longer outages and you know if you look at I mean the average cost the downtime for a typical global global 2000 companies between 75 thousand and two hundred fifteen thousand dollars an hour right now I don't know is your world because it's data it's all digitally the worst built as a source is it probably higher end of the spectrum all those numbers go AHA all those numbers go up and here's why all those metrics tie back to a monolithic architecture the world is now micro services based apps and you're running these applications in clusters and distributor architectures drop a note which is common I mean think you know you're talking about you're talking about commodity hardware to come out of the infrastructure it's completely normal to drop notes drops off you just add one back in everything keeps going on if your script expects five nodes and now there's four everything goes sideways so the probability I would I don't have the same stats back but it's worse because the the likelihood of error based upon configuration changes something as simple as that and you said micro-services was interesting to is is that now is it just a data lake kind of idea of storing data and a new cluster with microservices now you're having data that's an input to another app check so now so that the level of outage 7so mole severity is multiple because there could be a revenue-generating app at good young some sort of recommendation engine for e-commerce or something yeah something that's important like sorry you can't get your bank balance right now can't you any transfers because the hadoo closes down okay this is pretty big yes so it's a little bit different than say oh well to have a guy go out there and add a new server maybe a little bit different yeah and this is the you know this is the type of those are the types of stats that organizations that we're talking to now are caring a lot more it speaks to the market maturity do you run into the problem of you know it's insurance yeah and so they don't want to pay for insurance but a big theme in that you know the traditional enterprises how do we get more out of this data whether it's helping manage you know this I guess where that that's where your orchestration comes in cloud management maybe cloud migration maybe talk about some of the non insurance value add to our components and how that's resonating with with cost yeah yeah I so I'll jump in but the yeah the non protection stuff the orchestration bucket we're actually seeing it comes back to the to the problem sting we just said before which is they don't have it's not a monolithic stack it's a micro services based stack they've got multiple data sources they've got multiple data types it's sort of a it's the it's the byproduct of essentially putting power into into divisions hands to drive these different data strategies so you know the whole cloud let me double click on cloud migrations is a is a huge value problem that we have we talked about this notion of being data where so the ability to I'm here today but I want to be somewhere else tomorrow is a very strong operational argument that we hear from customers that we also also hear from the SI community because they hear it from the other community the other piece of that puzzle is you also hear that from the cloud folks because you've got multiple data for platforms that you're dealing with that you need agility to move around and the second piece is you've got the cloud obviously there's a massive migration to the cloud particularly with the dubidouxs sequel workloads so how do I streamline that process how do I provide the agility to be able to go from point A to point B just from of migration standpoint so that's a very very important use case for us has a lot of strategic value like it's coming it's sort of the markets talking to us like no no no we have this is him but we have to be able to do this and then simple things like not simple but you know automated test step is a big deal for us everybody's moved agile development so they want to spin up you know I don't want it I don't want to basically I want 10% of my data set I want to mask out my PII data I want to spin it up on Azure and I want to do that automatically every hour because I'm gonna run 16 I'm gonna run six builds today clouds certainly accelerates your opportunity big-time it forces everything to the table right yeah everybody's you can't hide anymore right what are you gonna do right you gotta answer the questions these are the questions so okay my final question I want to get on the table is for you in the segment is the product strategy how you guys looking at as an assassin gonna be software on premise cloud how's that look at how people consume the OP the offering and to opportunities because you guys are a young growing company you're kind of good good time you don't have the dog'll or the bagging it's Hadoop has changed a lot certainly there's a use case that neurons getting behind but clouds now a factor that product strategy and then when you're in deal why are you being called in why would someone want to call you rotor signs that would say you know call you guys up when with it when would a customer see signals and what signals would that be and to give you guys a ring or a digital connection product so the primary use cases are talking about recovery there's also data migration and the test step we have a big account right now that we're in final negotiations with where their primary use case is they're they're in health care and it's all about privacy and they need to securely mask and subset the data to your specific question around how are we getting called in basically you've got two things you've got the the administrators either the database architect or the IT or infrastructure people who are saying okay I need a backup solution I'm at a point now where I really need to protect my data as one and then there's this other track which is these higher-level strategic discussions where we're called in like the twenty six person meeting it's like okay we need an enterprise-wide data strategy so we're kind of attacking it both at the use case and at the higher level strategic and and and obviously the more we can drive that strategic discussion and get more of people wanting to talk to us about that that's gonna be better for our business and the stakeholders in that strategic discussion or whomever CIT is involved CIO maybe use their chief data officer and yeah database architect enterprise architecture head of enterprise architecture you know various flavors but you basically it kind of ways comes down to like two polls there's somebody who's kind of owns infrastructure and then there's somebody who kind of owns the data so it could be a chief data officer data architect or whatever depending on the scale of your and they're calling you because they're full they had to move the production workloads or they have production workloads that are from a bond from what uncared-for undershirt or is that the main reason they're in pain or you're the aspirin are you more others like we had a day loss and we didn't have any point in time recovery and that's what you guys provide so we don't want to go through this again so that's that's a huge impetus for us it is all about to your point it is mature its production workloads I mean the simple qualifying are you are you running a duper no sequel yes are you running in production yes you have a backup strategy sort of tip of the spear now to just briefly answer your question before we before we run out of time so it's an it's it's not a SAS basement we're software-defined solution will run in bare mantle running VMs will run in the cloud as your Google whatever you want to run on so we run anywhere you want we're sorry for be fine we use any storage that you want and basically it's an annual subscription base so it's not a SAS consumption model that may come down the road but it's basically in a license that you buy deploy it wherever you want customers choose what to do basically customers can do you know it's complete flexible flexible but back to you so let's go back to something you said you said they didn't have a point in time recovery what their point in time recovery was their last full backup or they just didn't have one or they just didn't have one all of the above you know see we've seen both yeah there's a market maturity issues so it's represented yeah you know that a lot its clustered I you know I just replicate my data and replication is not earth and truth be told my old company that was our approach we had a script but still it was like and the key thing is even if you write that script as you point out before the whole recovery thing so you know having a recovery sandbox is really in thing about this we designed everything exactly extract the value and show the use case prove it out yeah dupes real the history is repeating itself in that regard if you refuel a tional space there's a very in correlation to the Delton between the database platforms of the data mention logical hence they are involved coming in okay let's look at this in the big picture let's dad what's the recovery strategy how we gonna scale this exactly it's just a product Carson so your granularity for a point in time is you offer any point in time any point in time is varying and we'll have more news on that in the next couple weeks okay mantas data here inside the cube hot new startup growing companies really solving a real need need in the marketplace you're kind of an aspirant today but you know growth opportunity for as they scale up so congratulations good luck with the opportunity to secure bringing you live coverage here is part of Cuban YC our ninth year covering the big data ecosystem starting originally 2010 with a dupe world now it's a machine learning Hadoop clusters going at the production guys thanks for coming I really appreciate it this is the cube thanks for watching day one we'll be here all day tomorrow stay with us for more tomorrow be right back tomorrow I'll see you tomorrow

>> Live from San Jose in the heart of Silicon Valley, it's the Cube. Covering Dataworks Summit 2018 brought to you by Hortonworks. (upbeat music) >> Welcome back to The Cube's live coverage of Dataworks here in San Jose, California. I'm your host Rebecca Knight along with my co-host James Kobielus. We're joined by Peter Smails. He is the vice president of marketing at Imanis Data. Thanks so much for coming on The Cube. >> Thanks for having me, glad to be here. >> So you've been in the data storage solution industry for a long time, but you're new to Imanis, what made you jump? What was it about Imanis? >> Yep, so very easy to answer that. It's a hot market. So essentially what Imanis all about is we're an enterprise data management company. So the reason I jumped here is because if I put it in market context, if I take a small step back, I put it in market context, here's what happening. You've got your traditional application world, right? On prem typically already a mas based applications, that's the old world. New world is everybody's moving to the microservices based applications for IOT, for customer 360, for customer analysis, whatever you want. They're building these new modern applications. They're building those applications not in traditional RDMS, they're building them on microservices based architectures built on top of FEDOOP, or built on sequel databases. Those applications, as they go mainstream, and they go into production environments, they require data management. They require backup. They require backup and recovery. They require disaster recovery. They require archiving, etc. They require the whole plethora of data management capabilities. Nobody's touching that market. It's a blue ocean. So, that's why I'm here. >> Imanis as you were saying is one of the greatest little company no one's ever heard of. You've been around five years. (laughter) >> No, the company is not new. So, the thing that's exciting as a marketeer, what's exciting is that we're not sort of out there just pitching our wears untested technology. We have blue chip, we're getting into customers that people would die to get into. Big, blue chip companies because we're addressing a problem that's materialist. They roll out these new applications, they've got to have data management solutions for them. The company's been around five years. And I've only been on about a month, but what that's resulted is that over the last five years what they've had the opportunity, it's an enterprise product. And you don't build an enterprise product overnight. So they've had the last five years to really gestate the platform, gestate the technology, prove it in real world scenarios. And now, the opportunity for us as as a company is we're doubling down from a marketing standpoint. We're doubling down from the sales infrastructure standpoint. So the timing's right to essentially put this thing on the map, make sure everybody does know exactly what we do. Because we're solving a real world problem. >> Your backup and restore but much more. When you lay out the broad set of enterprise data and management capabilities, the mana state currently supports in your product portfolio on where you're going, on how you're going in terms of evolving in what you offer. >> Yeah, that's great. I love that question. So, think of us as the platform itself is this highly scalable distributed architecture. Okay, so we scale on multiple, and I'll come directly to your question. We scale on a number of different ways. One is we're infinitely scalable just in terms of computational power. So we're built for big data by definition. Number two is we're very, we scale very well from a storage efficiency standpoint. So we can store very large volumes of storage, which is a requirement. We also scale very much for the use case standpoint. So we support use cases throughout the life cycle. The one that gets all sort of the attention is obviously backup recovery. Because you have to protect your data. But if I look at it from a life cycle standpoint, our number use case is Test Def. So a lot of these organizations building these new apps now they want to spin up subsets of their data, cause they're supporting things like CICD. Okay, so they want to be able to do rapid testing and such. >> Develop Dev Opps and stuff like that. >> Yeah, Dev Opps and so worth. So, they need Test Def. So we help them automate the process and orchestrate the process of Test Def. Supporting things like sampling. I may have a one petabyte dataset, I'm not going to do Test Def against that. I want to do 10 percent of that and spin that up, and I want to do some masking of personal, PII data. So we can do masking and sampling against that Sport Test Def. We do backup and recovery. We do disaster recovery. So some customers, particularly in the big data space, they may for now say, well, I have replica so for some of this data it's not permanent data, it's transient data, but I do care about DR. So, DR is a key use case. We also do archiving. So if you just think of data through the life cycle, we support all of those. The piece in terms of where we're going is that what's truly unique, in addition to everything I just mentioned, is that we're the only data management platform that's machine learning based. Okay, so machine learning gets a lot of attention, and all that type of stuff, but we're actually delivering machine learning and abled capabilities today, so. >> And we discussed this before this interview. There's a bit of an anomaly detection. How exactly are you using machine learning? What value does it provide to a enterprise data administrator? They have ML inside your tool. >> Inside our platform, Great question. Very specifically, the product we're delivering today essentially there's a capability in the product called threat sets. Okay, so the number one use cases I mentioned is backup and recovery. So within backup and recovery, threat sense, what it will do with no user intervention whatsoever, what it will do is it will analyze your backups, as they go forward. And what it will do is it will learn what a normal pattern looks like across like 50 different metrics. The details of which I couldn't give you right now. But essentially, a whole bunch of different metrics that we look at to establish this is what a normal baseline looks like for you or for you, kind of thing. Great, that's number one. Number two is then we look and constantly analyze is anything occurring that is knocking things outside of that? Creating an anomaly, does something fall outside of that, and when it does, we're notifying the administrators. You might want to look at this, something could've happened. So the value very specifically is around ransomware typically one of the ways you're going to detect ransomware is you will see an anomaly in your backup set, because your data set will change materially. So we will be able to tell you, >> Cause somebody's holding for ransom is what you're saying. >> Correct, so something's going to happen in your data pattern. >> You've lost data that should be there, or whatever it might be. >> Correct, it could be that you lost data. Your change rate went way up, or something. >> Yeah, gotcha. >> There's any number of things that could trigger it. And then we let the administrator know, it happened here. So today we don't then turn around and just automatically solve that. But your point about where we're going. We've already broken the ice on delivering machine learning and abled data management. >> That might indicate you want to check point your backups to like a few days before this was detected. So the least you have, you know what data is most likely missing, so yeah, I understand. >> Bingo, that's exactly right now where we're going with that. As you could imagine, having a machine learning power data management platform at our core, how many different ways we can go with that. When do I backup? What data do I backup? How do I create the optimal RTO and IRPO? From a storage management standpoint, when do I put what data wear? There's all kinds of the whole library science of data management. The future of data management is machine learning based. There's too much data. There's too much complexity for humans to just be able to, you need to bring machine learning into the equation to help you harness the power of your data. We've broken the ice, we've got a long way to go. But we've got the platform to start with. And we've already introduced the first use case around this. And you can imagine all the places we can take this going forward. >> Very exciting. >> So you were the company that's using machine learning right now. What in your opinion will separate the winners from the losers? >> In terms of vendors, or in terms of the customers? >> Well, in terms of both. >> Yeah, let me answer that two ways. So, let me answer it sort of the inward/outward versus how we are unique. We are very unique, and since we're infinitely scalable, We are a single pane of glass for all of your distributed systems. We are very unique in terms of our multi-staged data reduction. And we're the only vendor that's doing, from a technology differentiation standpoint, we're the only vendor that's doing machine learning based stuff. >> Multi-stage data reduction, I want to break that down. What does that actually mean in practice? >> Sure, so we get the question frequently. Is that compression or duplication or is there something else in there? >> There's a couple different things actually. So why does that matter? So a lot of customers will ask a question, well by definition, no sequel or redo based environments, it's all based on replica, so how to back things up. First of all, replication isn't backup. So that's lesson number one. Point in time backup is very different than replication. Replication replicates bad data just as quickly as it replicates good. When you back up these very large data sets, you have to be incredibly efficient in how you do that. What we do with multi-stage data reduction is one, we will do de duplication, we'll do variable length, de duplication, we will do compression, we will do erasure coding, but the other thing that we'll also do in there, is what we call a global de plication pool. So when we're de duping your data, we're actually de duping it against a very large data set. So there's value in, this is where size matters. So the larger the data set, your data's all secured. But the larger the size of the data that I'm actually storing, the higher percentage I could get of de duplication. Because I've got a higher pool to reduce against. So the net result is we're incredibly efficient when you're talking about petabyte scale data management. We're incredibly efficient to the tune of 10 X easily 10 X over traditional de duplication, and multi X over technologies that are more current, if you will. So back to your question about, we are confident that we have a very strong head start. Our opportunity now is we got to drive why we're here. Cause we got to drive awareness. We got to make sure everybody knows who we are and how we're unique and how we're different. And you guys are great. Love being on The Cube. From a customer standpoint, the customers are going to win, and this is sort of a cliche, but it's true, the customer's the best harness of their data. They're the ones that are going to win. They're going to be more competitive, they're going to be able to find ways to be differentiated. And the only way they're going to do that is they're make the appropriate investments in their data infrastructure, in their data lakes, in their data management tool, so that they can harness all that data. >> Where do you see the future of your Hortonworks partnership going? So Hortonworks is, so we support a broad ecosystem. So, Hortonworks is just as important as any of our other data source partners. So, we are where we see that enfolding, is they're going to, we play an important part in, we feel our value, let me put it that way. We feel our value in helping Hortonworks, is as more and more organizations go mainstream with these applications. These are not corner cases anymore. This is not sort of in the lab. This is like the real deal. This is mainstream enterprises running business critical applications. The value we bring is you're not going to rely on those platforms without an enterprise data management solution that delivers what we deliver. So our value there is we can go to market, too. There's all kinds of ways we can go to market together. But net and that our value there is that we provide a very important enterprise data management capability that's important for customers that are deploying in these business critical environments. >> Great. >> Very good, as more of the data gets persisted out at the edge devices and the Internet of things, and so forth, what are the challenges in terms of protecting that data, backup and restore, de duplication, and so forth, and to what extent is your company's Imanis data maybe addressing those kinds of more distributed data management requirements going forward? Do you see that on the rise? Are you hearing that from customers? They want to do more of that? More of an edge cloud environment? Or is that way too far in the future? >> I don't think it's way too far in the future, but I do think there's an inside out. So my position on that is that it's not that there isn't edge work going on. What I would contend is that the big problem right now from an enterprise mainstreaming standpoint, is more getting the house is order, just your core house in order, from you move from sort of a traditional four wall data center to a hybrid cloud environment. Maybe not quite as edge. Combination of how do I leverage on prem and the cloud, so to speak. And how do I get the core data lake and the case of Hortonworks, how do I get that big data lake sorted out? You're touching on, I think, a longer discussion, which is where is the analysis going on? Where is the data going to persist? You know, where do you do some of that computational work? So you get all this information out at the edge. Does all that information end up going into the data lake? So, do you move the storage to where the lake is? Do you start pushing some of the lake functionale out to the edge where you have to then start doing some of the, so it's a much more complicated discussion. >> I know we had this discussion over lunch. This may be outside your wheelhouse, but let me just ask it anyway. We've seen more at Wikibon, I cover AI and distributed training and distributed inference and things so the edges are capturing the data and for more and more, there's a trend to where they're performing local training of their models, their embedded models, from the data they capture. But quite often, edge devices don't have a ton of storage and they're not going to retain that long. But some of that data will need to be archived. Will need to be persisted in a way and managed as a core resource, so we see that kind of requirement maybe not now, but in a few years time distributed training in persistence of that data, protection of that data, becoming a mainstream enterprise requirement. Where AI and machine learning, the whole pipeline is a concern. That's like I said, that's probably outside you guys wheelhouse. That's probably outside the realm for your customers But that kind of thing is coming out, as the likes of Hortonworks and IBM and everybody else, is starting to look at it and implement it, containerization of analytics and data management out to all these micro devices. >> Yes, and I think you're right there. And to your point about the, we're kind of going where the data is, if you will in volumes, kind of thing. And it's going that direction. And frankly, where we see that happening is, that's where the cloud plays a big role as well, because there's edge, but how do you get to the edge? You can get to the edge through the cloud. So, again, we run on AWS. We run on GCP, we run on Asher. So, to be clear, in terms of the data we can rotect, we got a broad portfolio, broad ecosystem of adute based big data, data sources that we support as well as no sequel. If they're running on AWS or GCP or Asher, we support ADLS, we support Asher's data lake stuff, HD Inside, we support a whole bunch of different things both from a cloud standpoint as on prem. Which is where we're seeing some of that edge work happening. >> Great, well Peter thank you so much for coming on The Cube. It's always a pleasure to have you on. >> Yes, thanks for having me and I look forward to being back sometime soon. >> We'll have you. >> Thank you both. >> When the time is right. >> Indeed, we will have more from The Cube's live coverage of Dataworks just after this. (upbeat music)

(bright music) >> Hi, this is Donald Klein with CUBEConversations, coming to you from our Palo Alto studios. We're here doing a special series on CMOs and the challenges of digital marketing, and today we're here with Peter Smails, who is the former chief marketeer at DatosIO. Welcome, Peter. >> Thanks for having me, always fun to be here. >> Good, good. Well look, so, I wanted to set aside this time and have a discussion with you, because you're somebody who's had a long marketing career, you've been in big companies, you've been in small companies, most recently with Datos. >> Yup. >> You've been in companies where you've had established brands with proven product stories. You've also been in situations where you've got companies that were sort of unknown to the broader world, and you had to find a way to make them known and prove out that proposition-- >> Put 'em on the map. >> Put 'em on the map. So talk to us a little bit about how you've approached that challenge when you've been in some of the smaller companies. >> Sure. Sure, happy to do that. And yeah, my past has been an interesting mix of big companies and small, and the small companies present a bunch of unique challenges, but there's nothing more fun than having the opportunity of having a company that's got some great technology, some great people, and essentially the fun job of any marketeer is, how do you put them on the map? And we've been talking a lot about, what are the levers you can pull? What can you do? And one of the challenges with being a small company is you don't have any money. >> Mm. >> I mean, you might, but you don't have a ton of money. So, that's where social, right off the bat, if I sort of look at the levers I can pull initially, when you look at your strategy, OK, I need to put the company on the map so I've got to drive thought leadership, I've got to drive awareness. You know, I've also got to drive demand-gen. So what are the levers I can use, what are the vehicles that I can use to drive that? And I think that's where social has, a lot of people think of social as the new demand-gen vehicle. I don't necessarily see it that way, I think social has actually become an ideal complement to all the other traditional levers that you still want to use. And again, there's segmentation that comes into this as well, in terms of what organizations you're trying to target. Are you going after SNB, are you going after the enterprise, et cetera. In my case, it's primarily been going after the enterprise. >> Mm-hmm. >> So, when I look at that from a social standpoint, social media in general sort of the value of it is really as a complement to the other traditional levers that you have in your arsenal. Whether that be events, industry events, whether that be traditional demand-gen things, outcome type things, social becomes an ideal complement for promoting those things, and then social also becomes a very important pillar in the sense it removes sort of the barrier to entry in terms of being relevant if you will, because it's a very cost-effective way of creating a drum-beat of news. And again, we can get into more specifics, of the different aspects of that, whether it's traditional social, like the twitters, whether it's videos and that type of things, the different pieces you could use in there. >> OK. So, now, talk a little about the role of events. One of the challenges with the smaller companies, you don't have the big event budgets, you don't have the big booths, but still now, you say digital, you often hear some companies talk about how we're going to try to go all digital. Because that's a place where we can play, because even if we don't have the money. But digital is a crowded space, so did you strike a balance between events and digital? What was your thinking? >> That's a great question. And balance is exactly the right word. It's going to vary, there's no sort of exact science, but you have to be selective, again, going into an enterprise clientele, you have to be selective about the events that you're going to do, number one. Digital is a very good instrument, particularly as a small company, this is a point I didn't make before, the whole notion of inbound versus outbound as well. Where digital can play a very key role from an inbound standpoint, think simple things like SEO and SEM. Can people find you? Are you relevant? The early adopters are the people that know they have a problem, so they're going to look for something. So you can very cost-effectively make yourself relevant there if they know what they're looking for. And particularly, that's what's fun about creating a segment, is if you're doing something nobody else is doing, then you're playing in a potential blue ocean, where you're not competing at a very high cost, you're not bidding at a very high cost for some of the things you do, form say Google Ad Words or that type of stuff. So you've got your ability to be effective from an inbound standpoint, number one. To your point about the events, you absolutely need to do those events. Your core set of whatever segment you're in, whatever business you're in, you've got to be focused on those core events, because I still find that to be, that's where a lot of, enterprises, they still use events as one of the key places they go to learn, to educate themselves, to find out what's happening in the marketplace. The key is, how do you maximize your presence at those events? How do you leverage social to promote the fact that you're going to be there? >> Right. >> What do you do at the event? What can you do? And again, this is where we can come back and talk about things specifically like theCUBE, you know, where you can use vehicles like theCUBE very effectively, because, one, I can drive a lot of influence in-show, but then as well I can create a much longer tail, I can maximize my presence, I can maximize the IP that I bring to that show by capturing that in digital medium, like video, and then being able to use it post. Simply put, you go to a show these days, if you're not on theCUBE, then you're missing the boat. It's just sort of like a regular pillar of all the core industry shows. So that's great for driving influence, not only to customers, but within the industry, but then it also is a great way for creating assets that I can then use for longer tail. For thought leadership, or demand-gen, or whatever I may want to use. >> OK, understood, understood. So let's talk a little bit about this notion of complement. So what you're saying is that, you want to go to the events, that's where the belly-to-belly interaction is, that's where things are happening, right, and then you're using social to leverage up your presence at those events. >> Correct. Or to promote the fact that you're going to be there. Drive interest in people showing when you do a contest, or there's, you know, creative things you can do, but yeah, you're using social to basically drive awareness to the fact that you're going to be there. You're using social to promote you're in the session. You're on theCUBE, or whatever it is you might be doing. You're hosting an event that evening, an offsite event, use that as a way to complement the fact that you're at the event doing your belly-to-belly, great term, you're doing your traditional belly-to-belly get-together. >> Understood. Because we've heard people talk about it and say, social's great, digital is great, but it's also very crowded out there. And where you've got people's attention, where you've got people's mind chair is in and around events. >> Yeah, I would agree with that. I would agree with that. And it's, you know, social is a great way, it removes the barriers to entry, but the flip side of that, for good or for bad, is that it also creates a lot of noise. So how do you separate the noise? How do you rise above the noise? And that really is, leveraging social, leveraging digital overall, in the appropriate high-credibility, high-integrity ways, to drive influence within the industry, to drive relevance of what you're doing, and then also use that as a vehicle for helping other demand-gen sites. So it's the new normal kind of thing. It's not the ideal platform, social, per se, is not the ideal demand-gen platform, but it is a complementary piece, but also to your point, creates a tremendous amount of noise, so then the challenge becomes, how do you basically stand above the noise? And that comes down to influence, that comes down to credibility. >> OK. >> Are you telling your credible narrative, are you talking to credible people, are you in the appropriate forums, that type of thing. >> OK, and so let's talk about video and how that kind of fits into that digital strategy. Cause that's kind of the new realm in terms of everybody wanting to kind of create digital content, in video form, what's been your experience in terms of the challenges of creating that content, and then getting it out in digestible forms? >> A couple different aspects to that. The creation of content is getting, it depends on what you're trying to accomplish. The creation of video content is getting easier, if you will, in the sense of the cost of, you know, you can put a studio and a small business together reasonably inexpensively, but then what content are you creating there? Well, what content I'm creating there is essentially I'm going to promote what we're doing as a company, we're going to create some short little blurb about the recent launch or something, or potentially have a customer, although typically you have a customer, and you go visit the customer and do it there. But that's the stuff where you're sort of the self-promotional stuff. You know, where I find the events, in particular what you guys are doing with theCUBE in Silicon Valley, what I like about that is that the content that I'm creating, it's by no means sort of a pre-canned, sort of has a black and white beginning and end. It's very topical, it's very sound bite-ish in a good way, not a bad way, if you will, and it's also very topical. Very topical, which is key, because again, back to the whole influence, it's not just about hammering away at the customer, hey look at me, look at me, look how great I am. It's basically, you have to build a community, you have to build an eco-system, you have to build a community of people that know you, that trust you, and we talked earlier about the whole earned media versus paid media, if you build that credibility, you build that influence, like hey, saw you on theCUBE. Get an email from Fortune or Forbes, like, oh yeah, I saw you on theCUBE, we'd be interested in doing this, that, and the other thing and it all comes down to building that arsenal, if you will, or that library of high-credibility, high-integrity, high-influence content. Which is all video-based, because video is the way people consume information. >> So I think we'd agree with you, right, having content which is based on authentic interactions between a vendor and his customers, between vendors and partners, between vendors and analysts, right, that's really the key to making good, engaging content. Now what about, in terms of, how do you find getting that content out to individuals in a way that is kind of consistent with the way people are consuming content now in social media? I think we're seeing, there's a whole debate out there, long-form versus short-form content, clips, et cetera, what's been your experience? >> I don't know the number, but I'm quite certain that the average attention span of people in general is dramatically down. There'd be an interesting metric on that. So the world leans absolutely heavily towards, as I said earlier, more sound bite-oriented. But not sound bite in a bad way, it's just sort of, just look at the landscape we live in now, it's like, until recently, we lived in a 140 character world kind of thing. And you can convey a lot more through spoken word than you can just typing, but people consume things in very short bursts of information. So one, you want to take advantage of that. Two, the other thing I would say to this, is that one of the things I like about short-form video is again, I'm a big meta-data guy. In one five-minute, just in the conversation we're having now, we've covered eight different topics. >> Right. >> So to me, as a marketeer, I'm like OK, great, that's eight different-- >> Donald: That's eight different clips. >> Kind of thing, great, and I can use that for any number of different things I want to. One of those pieces that maybe was the part about so what are you doing now? Maybe the plug part could be, we could promote that, that could actually be a demand-gen thing. Or if you're talking about a segment where you're just like well how are you guys uniquely differentiated? You could use that for consideration. You know, there's all different ways, but the notion of sort of highly granular video content has huge value. >> Donald: Interesting, OK. >> It just creates a lot of leverage. >> So this has kind of been a blocking and tackling for marketeers kind of conversation, so kind of sum up your main points here, so one you were saying, use social to complement your presence at events and other types of-- >> And not just events, use it as a way of supporting demand-gen, use it as a way of staying relevant, join all the appropriate communities you need to be joining. You have to stay relevant, you have to stay within the noise, sort of as the table stakes, then beyond that, you got to figure out how do you rise above the noise, how do you use it strategically, to actually rise above the noise of everybody else's banging away on social as well. >> OK, agree with that. Second point then, use authentic content. Try to mix in relevant-- >> People are tired of just talking heads. People are tired of, I don't need to see another video on how great you are, or whatever, so back to your point, that's my interpretation of authentic content. Do what you do. Share what you do. Put it in context and smart people will figure out, and then obviously share it in the appropriate communities so that people can find it, but they very naturally, I think there's a very low appetite now for BS, 'cause there's so much noise. People are so hungry for just getting to the relevance of the information that they want, which again is where the sound bite-level stuff, and the more you can index and be intelligent about that data, the faster you can help people find information they're looking for. >> OK, excellent, alright, well we're going to have to wrap it up on that point but I think that was exactly right, I think we're seeing that in some of the customers we work with as well. So, leverage to social, focus on authentic content, get it out there in forms that people are willing to digest. >> Peter: Absolutely correct. >> Alright, well thank you everyone, this has been Donald Klein here with Peter Smails, former chief marketeer at DatasIO, with CUBEConversations. (bright music)

>> Announcer: Live from Las Vegas, it's the CUBE. Covering AWS re:Invent 2017. Presented by: AWS, Intel, and our ecosystem of partners. >> Well, welcome back to the Sands Expo. Here we are in Las Vegas in re:Invent with just about 50 000 of our closest friends. Big AWS community gathering here all week long and it's a pleasure to be here with you on the CUBE, along with Keith Townsend. I'm John Walls and we're now joined by Peter Smails, who is the vice president of marketing and business developing at Datos IO. Peter, good to see ya. >> Thanks for having me and glad to be back. I love being on the CUBE. >> You were just last week, right? >> Keith: Yeah. >> CUBE conversations with John Fury or so we're going to have to start charging you rent. (laughs) >> I only have two numbers in my head right now: 18 billion, 40% CAGR. Those are the only two numbers I have in my head right now. For those of you not in the know, those are the numbers that AWS was talking about in terms of revenue and growth. Crazy times, crazy show, good stuff. >> This show really does embody that. It certainly illustrates that. We've only been here for... the doors have been open for about a half hour or so. Already wall-to-wall traffic. >> People were queuing up to get into the expo floor, which I don't think I've seen that. >> I swung by our booth, 2825. I swung by there at 11:20 and it was standing room only. It's great. I mean, the buzz, you can feel it. If you're not down on the floor, come down to the floor, cause you can just feel the energy. >> And even still, just walking up here, if you've been here to the Sands, you've got these giant hallways. I was here probably two hours ago and it was already wall-to-wall people and it was just packed. I was really impressed. >> The conference started in full tilt at seven o'clock this morning. People were just out and just engaging. >> So you guys, you're here, your relationship obviously at AWS, we're gonna get into that >> Yeah. You got the booth here, 2825? >> 2825. Yes sir. >> So let's talk about, first off, about your presence here. >> Peter: Yeah >> What brings you into this community? You've been here for a while now. >> Peter: Yeah. >> And maybe the evolution of that from the three or four years-- >> Sure. back to where you are now. Yeah, so our view of the world aligns incredibly well with AWS. The whole notion of the world's moving to the cloud. We've been in business since 2014. We are a cloud data management company with primary use cases around backup and recovery. There's all those things like data mobility and essentially our view of the world and our strategy is that as the world moves to the cloud, organizations are building net new applications. They're building modern applications that they're running on hybrid cloud environments. Those applications need a fundamentally new approach to data management. That's what we do. About 50% of our customers run natively on AWS. So this is a very logical show for us. We've got customers building these new modern applications. They're hosting them natively in AWS. They need backup and recovery. They need data mobility. That's what we do. It's just a perfect fit for us. >> So Peter, let's talk a little bit about data mobility. You guys are unapologetically cloud first. We've had this conversation in the past just offline. Talk to me about that conversation with customers. How that's evolved from three, four years ago to now. >> (chuckles) I'll use another quote from Andy, from earlier this week, or I guess this is from Jeff Basil, so theoretically it's the whole thing about they're willing to be misunderstood for a while. You go back four years, early days, yeah, we were doing cloud first, backup and recovery for modern applications built on the MongoDB's, the Cassandra's, the non relational databases. It's going to a non relational world. In the early days people would laugh and they'd be like, "Why you doing that?" We were steadfastly believing then, as we do now, that the world is moving to the cloud. The world is moving largely to a non relational world and so there's going to be a huge opportunity to provide data management solutions. Data aware, data management solutions for that. So we've stuck to that. We've been steadfast in that. But your point about maturity, what's been really exciting for us as an organization is that, I go back even a year, and you talk about, so what do you do? And you give 'em the pitch and there was a fair amount of nuance to it and they'd be like (garbles). They'd sort of give you the "hmm". They'd kind of ask questions or whatever and then once you talk through it, maybe it was a 10 minute elevator pitch, if you will. You had to go like 20 floors. They got it but it was a little bit more nuanced. Now it's, okay great, are you moving to the cloud? No brainer. Are you building modern applications? Are you importing your old applications, building these new modern applications in a non relational world. Absolutely. Are they running a production? Yes. How are you protecting those applications? We have no idea, kinda thing or we're using native tools or we're scripting or we're not doing anything. So it varied to your point. The conversation has become much less, it's not even nuanced anymore. The qualifying questions are incredibly simple and our value proposition is incredibly easy. If you're running applications, if you've built net new modern applications running in the cloud, or on-prem that you want to back up to the cloud, you need modern data protection. That's what we do. >> Let's talk about this hybrid IT scenario. I was at dinner last night with a couple Fortune 500 AWS customers and I was talking to them about the excitement of this whole category, data protection. They were like, backup? How is that sexy at at all? Then we got into this use case of data mobility, of I've built something really big on-prem and I need John Hastings term: "I need a multi-cloud strategy." >> Yeah, John's not a huge multi... He pressed me last week on the whole multi-cloud. >> Kevin: Fourier is-- Yeah, oh yeah, sorry (laughs) >> John: I don't want you to reach over and back slap me here. >> Peter: So you're all in on multi-cloud. It's Fourier we gotta worry about. >> John: My whole life. >> Talk to us about the importance of using what we would have traditionally called backup as a data mobility strategy. >> Cool. Absolutely. It all kinda comes down to for us, being data aware. If you think about it, we're a cloud data management company. Our number one use case is backup and recovery because the first thing you have to do is you gotta capture the data, you've gotta. >> Backup recovery of my VMs right? >> Good question. We are unlike traditional backup and recovery. We're not infrastructure-centric. We're application-centric. We're actually agnostic to the underlying infrastructure. So if you're running bare metal on-prem, if you're running on EC2, if you're leveraging S3, wherever you're running, we're fine because we integrated the application level, the database level. Hence our focus on non relational. Our number one use case is protecting that data. Because we are application aware, because we're data aware and we integrated the database level, we understand the underlying scheme. We are aware of the data structures within the databases that people are protecting first and foremost. But in the context of data mobility to your point, the number two use case for us is that organizations want to protect their data but then they want to do things like, I wanna spin up copies or sub-copies of my data, of my backup copies for test F, for QA, for performance testing, for cloud instantiation, for archiving, for BI, for whatever I want to do. The key is, we're not a migration company. AWS has migration services. If you need to move two petabytes of data from on-prem and you're now gonna host it in the cloud, that's not us, but if you built these new applications and you want to basically intelligently use subsets of your data for those workloads I was talking about, we enable you to be incredibly intelligent about only recovering if you will or only moving the data that you need. For example, simple things like, with our RecoverX 2.5 that we just announced. We do something called quierably recovery. What that means is, I can do everything from star dot Peter star or I can pick individual rows and columns. >> John: Just pick and choose? >> I can pick and choose based upon my database scheme. I can mast columns of data if I have to do GDPR compliance or PII. So from a used case standpoint, it's all about being aware of the data that you actually in the first place you're backing up, but then what data you wanna move so that you can be incredibly intelligent and efficient about the data that you're moving. >> So in traditional systems, I can encrypt data at rest. I can back it up. My tapes can be encrypted. My discs that's holding that back up data can be encrypted. When I think about that, when it comes to backing up object storing into the cloud, how do I do that with...? >> Great question. Again, because we're not infrastructure based, we're not LUN based, we're not block based, we integrate at the database level. We're completely transparent to encryption. We work perfectly fine with encrypted data. We work perfectly fine with compressed data. We invented something called semantic de-duplication. If you're familiar with traditional de-duplication. >> Keith: Right. >> It works in a block level. Fixture varying length block. In a clustered database environment or in a compressed or encrypted data environment, it kinda throws the capabilities of traditional de-dup out the window. Semantic de-duplication understands the scheme of the underlying database. We are highly efficient de-duplication for encrypted data, for compressed data. We're transparent to that, if you will. So again, back to our cloud first model, we built that in from day one. It's a fundament, our underlying architecture, the platform that we've built is fundamentally unlike anything else from a traditional backup and recovery or data management platform. >> So make sure I get it right before we say good-bye. Datos IO 2825? >> 2825, correct. www.DatosIO If you are running applications in the cloud and need to protect those apps, please talk to us. We'd love to help you out. If you're looking for data mobility solutions, come talk to us. >> John: There's the pitch. >> Love to chat. >> Peter, thanks for being with us. Next week you're off, all right? >> We'll have to cancel that one because I'm back next week. >> John: Back to back cupers, but maybe we'll give you a week off. >> Thanks for having me, always like being here. Appreciate it. >> Thanks for being with us. Back for more here at re:Invent. We're in Las Vegas live here on the CUBE. Back with more right after this.

(light orchestral music) >> Hello, everyone, and welcome to the Cube Conversation here at the Palo Alto studios for theCUBE. I'm John Furrier, the co-founder of SiliconANGLE Media. We're here for some news analysis with Peter Smails, the CMO of Datos.IO D-a-t-o-s dot I-O. Hot new start up with some news. Peter was just here for a thought leader segment with Chris Cummings talking about the industry breakdown. But the news is hot, prior to re:Invent which you will be at? >> Absolutely. >> RecoverX is the product. 2.5, it's a release. So, you've got a point release on your core product. >> Correct. >> Welcome to this conversation. >> Thanks for having me. Yeah, we're excited to share the news. Big day for us. >> All right, so let's get into the hard news. You guys are announcing a point release of the latest product which is your core flagship, RecoverX. >> Correct. >> Love the name. Love the branding of the X in there. It reminds me of the iPhone, so makes me wanna buy one. But you know ... >> We can make that happen, John. >> You guys are the X Factor. So, we've been pretty bullish on what you guys are doing. Obviously, like the positioning. It's cloud. You're taking advantage of the growth in the cloud. What is this new product release? Why? What's the big deal? What's in it for the customer? >> So, I'll start with the news, and then we'll take a small step back and sort of talk about why exactly we're doing what we're doing. So, RecoverX 2.5 is the latest in our flagship RecoverX line. It's a cloud data management platform. And the market that we're going after and the market we're disrupting is the traditional data management space. The proliferation of modern applications-- >> John: Which includes which companies? >> So, the Veritas' of the world, the Commvault's of the world, the Dell EMC's of the world. Anybody that was in the traditional-- >> 20-year-old architected data backup and recovery software. >> You stole my fun fact. (laughs) But very fair point which is that the average age approximately of the leading backup and recovery software products is approximately 20 years. So, a lot's changed in the last 20 years, not the least of which has been this proliferation of modern applications, okay? Which are geo-distributed microservices oriented and the rapid proliferation of multicloud. That disrupts that traditional notion of data management specifically backup and recovery. That's what we're going after with RecoverX. RecoverX 2.5 is the most recent version. News on three fronts. One is on our advanced recovery, and we can double-click into those. But it's essentially all about giving you more data awareness, more granularity to what data you wanna recover and where you wanna put it, which becomes very important in the multicloud world. Number two is what we call data center aware backup and recovery. That's all about supporting geo-distributed application environments, which again, is the new normal in the cloud. And then number three is around enterprise hardening, specifically around security. So, it's all about us increased flexibility and new capabilities for the multicloud environment and continue to enterprise-harden the product. >> Okay, so you guys say significant upgrade. >> Peter: Yep. >> I wanna just look at that. I'm also pretty critical, and you know how I feel on this so don't take it personal, multicloud is not a real deal yet. It's in statement of value that customers are saying-- It's coming! But cloud is here today, regular cloud. So, multicloud ... Well, what is multicloud actually mean? I mean, I can have multiple clouds but I'm not actually moving workloads across clouds, yet. >> I disagree. >> Okay. >> I actually disagree. We have multiple customers. >> All right, debunk that. >> I will debunk that. Number one use case for RecoverX is backup and recovery. But with a twist of the fact that it's for these modern applications running these geo-distributed environments. Which means it's not about backing up my data center, it's about, I need to make a copy of my data but I wanna back it up in the cloud. I'm running my application natively in the cloud, so I want a backup in the cloud. I'm running my application in the cloud but I actually wanna backup from the cloud back to my private cloud. So, that in lies a backup and recovery, and operation recovery use case that involves multicloud. That's number one. Number two use case for RecoverX is what we talk about on data mobility. >> So, you have a different definition of multicloud. >> Sorry, what was your-- Our definition of multicloud is fundamentally a customer using multiple clouds, whether it be a private on-prem GCP, AWS, Oracle, any mix and match. >> I buy that. I buy that. Where I was getting critical of was a workload. >> Okay. >> I have a workload and I'm running it on Amazon. It's been architected for Amazon. Then I also wanna run that same workload on Azure and Google. >> Okay. >> Or Oracle or somewhere else. >> Yep. >> I have to re-engineer it (laughs) to move, and I can't share the data. So, to me what multicloud means, I can run it anywhere. My app anywhere. Backup is a little bit different. You're saying the cloud environments can be multiple environments for your solution. >> That is correct. >> So, you're looking at it from the other perspective. >> Correct. The way we define ourselves is application-centric data management. And what that essentially means is we don't care what the underlying infrastructure is. So, if you look at traditional backup and recovery products they're LUN-based. So, I'm going to backup my storage LUN. Or they're VM-based. And a lot of big companies made a lot of money doing that. The problem is they are no LUN's and VM's in hybrid cloud or multicloud environment. The only thing that's consistent across application, across cloud-environments is the data and the applications that are running. Where we focus is we're 100% application-centric. So, we integrate at the database level. The database is the foundation of any application you create. We integrate there, which makes us agnostic to the underlying infrastructure. We run, just as examples, we have customers running next generation applications on-prem. We have customers running next generation applications on AWS in GCP. Any permutation of the above, and to your point about back to the multicloud we've got organizations doing backup with us but then we also have organizations using us to take copies of their backup data and put them on whatever clouds they want for things like test and refresh. Or performance testing or business analytics. Whatever you might wanna do. >> So, you're pretty flexible. I like that. So, we talked before on other segments, and certainly even this morning about modern stacks. >> Yeah. >> Modern applications. This is the big to-do item for all CXOs and CIOs. I need a modern infrastructure. I need modern applications. I need modern developers. I need modern everything. Hyper, micro, ultra. >> Whatever buzz word you use. >> But you guys in this announcement have a couple key things I wanna just get more explanation on. One, advanced recovery, backup anywhere, recover anywhere, and you said enterprise-grade security is the third thing. >> Yep. >> So, let's just break them down one at a time. Advanced recovery for Datos 2.5, RecoverX 2.5. >> Yep. >> What is advanced recovery? >> It's very specifically about providing high levels of granularity for recovering your data, on two fronts. So, the use case is, again, backup. I need to recover data. But I don't wanna necessarily recover everything. I wanna get smarter about the data I wanna recover. Or it could be for non-operational use cases, which is I wanna spin up a copy of data to run test dev or to do performance testing on. What advanced recovery specifically means is number one, we've introduced the notion of queryble recovery. And what that means is that I can say things like star dot John star. And the results returning from that, because we're application-centric, and we integrated the database, we give you visibility to that. I wanna see everything star dot John star. Or I wanna recover data from a very specific row, in a very specific column. Or I want to mask data that I do not wanna be recovered and I don't want people to see. The implications of that are think about that from a performance standpoint. Now, I only recover the data I need. So, I'm very, very high levels of granularity based upon a query. So, I'm fast from an RTO standpoint. The second part of it is for non-operational requirements I only move the data that is select to that data set. And number three is it helps you with things like GDPR compliance and PII compliance because you can mask data. So, that's query-based recovery. That's number one. The second piece of advanced recovery is what we call incremental recovery. That is granular recovery based upon a time stamp. So, you can get within individual points in time. So, you can get to a very high level of granularity based upon time. So, it's all about visibility. It's your data and getting very granular in a smart way to what you wanna recover. So, if I kind of hear what you're saying, what you're saying is essentially you built in the operational effectiveness of being effective operationally. You know, time to backup recovery, all that good RTO stuff. Restoring stuff operationally >> Peter: Very quickly. >> very fast. >> Peter: In a smart way. >> So, there's a speed game there which is table stakes. But you're real value here is all these compliance nightmares that are coming down the pike, GDPR and others. There's gonna be more. >> Peter: Absolutely. I mean, it could be HIPPA, it could be GDPR, anything that involves-- >> Policy. >> Policies. Anything that requires, we're completely policy-driven. And you can create a policy to mask certain data based upon the criteria you wanna put in. So, it's all about-- >> So you're the best of performance, and you got some tunability. >> And it's all about being data aware. It's all about being data aware. So, that's what advanced recovery is. >> Okay, backup anywhere, recover anywhere. What does that mean? >> So, what that means is the old world of backup and recovery was I had a database running in my data center. And I would say database please take a snapshot of yourself so I can make a copy. The new world of cloud is that these microservices-based modern applications typically run, they're by definition distributed, And in many cases they run distributed across they're geo-distributed. So, what data center aware backup and recovery is, use a perfect example. We have a customer. They're running their eCommerce. So, leading online restaurant reservations company. They're running their eCommerce application on-prem, interestingly enough, but it's based on Cassandra distributed database. Excuse me, MongoDB. Sorry. They're running geo-distributed, sharded MongoDB clusters. Anybody in the traditional backup and recovery their head would explode when you say that. In the modern application world, that's a completely normal use case. They have a data center in the U.S. They have a data center in the U.K. What they want is they wanna be able to do local backup and recovery while maintaining complete global consistency of their data. So again, it's about recovery time ultimately but it's also being data aware and focusing only on the data that you need to backup and recovery. So, it's about performance but then it's also about compliance. It's about governance. That's what data center aware backup is. >> And that's a global phenomenon people are having with the GO. >> Absolutely. Yeah, you could be within country. It could be any number of different things that drive that. We can do it because we're data aware-- >> And that creates complexity for the customer. You guys can take that complexity away >> Correct. >> From the whole global, regional where the data can sit. >> Correct. I'd say two things actually. To give the customers credit, the customers building these apps or actually getting a lot smarter about what they're data is and where they're data is. >> So they expect this feature? >> Oh, absolutely. Absolutely. I wouldn't call it table stakes cause we're the only kids on the block that can do it. But this is in direct response to our customers that are building these new apps. I wanna get into some of the environmental and customer drivers in a second. I wanna nail the last segment down. Cause I wanna unpack the whole why is this trend happening? What's the gestation period? What's the main enabler for you? But okay, final point on the significant announcements. My favorite topic enterprise-grade security. What the hell does that mean? First of all, from your standpoint the industry's trying to solve the same thing. Enterprise-grade security, what are you guys providing in this? >> Number one, it's basically security protocol. So, TLS and SSL. This is weed stuff. TLS, SSL, so secure protocol support. It's integration with LDAP. So, if organizations are running, primarily if they're running on-prem and they're running in an LDAP environment, we're support there. And then we've got Kerberos support for Kerberos authentication. So, it's all about just checking the boxes around the different security >> So, this is like in between >> and transport protocol. >> the toes, the details around compliance, identity management. >> Peter: Bingo. >> I mean we just had Centrify's CyberConnect conference, and you're seeing a lot of focus on identity. >> Absolutely. And the reason that that's sort of from a market standpoint the reason that these are very important now is because the applications that we're supporting these are not science experiments. These are eCommerce applications. These are core business applications that mainstream enterprises are running, and they need to be protected and they're bringing the true, classic enterprise security, authentication, authorization requirements to the table. >> Are you guys aligning with those features? Or is there anything significant in that section? >> From an enterprise security standpoint? It's primarily about we provide the support, so we integrate with all of those environments and we can check the boxes. Oh, absolutely TLS. Absolutely, we've got that box checked because-- >> So, you're not competing with other cybersecurity? >> No, this is purely we need to do this. This is part of our enterprise-- >> This is where you partner. >> Peter: Well, no. For these things it's literally just us providing the protocol support. So, LDAP's a good example. We support LDAP. So, we show up and if somebody's using my data management-- >> But you look at the other security solutions as a way to integrate with? >> Yeah. >> Not so much-- >> Absolutely, no. This has nothing to do with the competition. It's just supporting ... I mean Google has their own protocol, you know, security protocols, so we support those. So, does Amazon. >> I really don't want to go into the customer benefits. We'll let the folks go to the Datos website, d-a-t-o-s dot i-o is the website, if you wanna check out all their customer references. I don't wanna kind of drill on that. I kind of wanna really end this segment on the real core issue for me is reading the tea leaves. You guys are different. You're now kind of seeing some traction and some growth. You're a new kind of animal in the zoo, if you will. (Peter laughs) You've got a relevant product. Why is it happening now? And I'm trying to get to understanding Cloud Oss is enabling a lot of stuff. You guys are an effect of that, a data point of what the cloud is enabled as a venture. Everything that you're doing, the value you create is the function of the cloud. >> Yes. >> And how data is moving. Where's this coming from? Is it just recently? Is it a gestation period of a few years? Where did this come from? You mentioned some comparisons like Oracle. >> So, I'll answer that in sort of, we like to use history as our guide. So, I'll answer that both in macro terms, and then I'll answer it in micro terms. From a macro term standpoint, this is being driven by the proliferation of new data sources. It's the easiest way to look at it. So, if you let history be your guide. There was about a seven to eight year proliferation or gap between proliferation of Oracle as the primary traditional relational database data source and the advent of Veritas who really defined themselves as the defacto standard for traditional on-prem data center relational data management. You look at that same model, you'll look at the proliferation of VMware. In the late 90s, about a seven to eight year gestation with the rapid adoption of Veeam. You know the early days a lot of folks laughed at Veeam, like, "Who's gonna backup VMs? People aren't gonna use VMs in the enterprise. Now, you looked at Veeam, great company. They've done some really tremendous things carving out much more than a niche providing backup and recovery and availability in a VM-based environment. The exact same thing is happening now. If you go back six to seven years from now, you had the early adoption of the MongoDBs, the Cassandras, the Couches. More recently you've got a much faster acceleration around the DynamoDBs and the cloud databases. We're riding that same wave to support that. >> This is a side effect of the enabling of the growth of cloud. >> Yes. >> So, similar to what you did in VMware with VMs and database for Oracle you guys are taking it to the next level. >> These new data sources are completely driven by the fact that the cloud is enabling this completely distributed, far more agile, far more dynamic, far less expensive application deployment model, and a new way of providing data management is required. That's what we do. >> Yeah, I mean it's a function of maturity, one. As Jeff Rickard, General Manager of theCube, always says, when the industry moves to it's next point of failure, in this case failure is problem and you solve. So, the headaches that come from the awesomeness of the growth. >> Absolutely. And to answer that micro-wise briefly. So, that was the macro. The micro is the proliferation of, the movement from monolithic apps to microservices-based app, it's happening. And the cloud is what's enabling them. The move from traditional on-prem to hybrid cloud is absolutely happening. That's by definition the cloud. The third piece which is cloud-centric is the world's moving from a scale up world to an elastic-compute, elastic storage model. We call that the modern IT stack. Traditional backup and recovery, traditional data management doesn't work in the new modern IT stack. That's the market we're planning. That's the market we're disrupting is all that traditional stuff moving to the modern IT stack. >> Okay, Datos IO announcing a 2.5 release of RecoverX, their flagship product, their start up growing out of Los Gatos. Peter Smails here, the CMO. Where ya gonna be next? What's going on-- I know we're gonna see you re:Invent in a week in a half. >> Absolutely. So, we've got two stops. Well, actually the next stop on the tour is re:Invent. So, absolutely looking forward to being back on theCUBE at re:Invent. >> And the company feels good about those things are good. You've got good money in the bank. You're growing. >> We feel fantastic. It's fascinating to watch as things develop. The conversations we have now versus even six months ago. It's sort of the tipping point of people get it. You sort of explain, "Oh, yeah it's data management from modern applications. Are you deploying modern applications?" Absolutely. >> Share one example to end this segment on what you hear over and over again from customers that illuminates what you guys are about as a company, the DNA, the value preposition, and their impact on results and value for customers. >> So, I'll use a case study as an example. You know, we're the world's largest home improvement retailers. Old way, was they ran their multi-billion dollar eCommerce infrastructure. Running on IBM Db2 database. Running in their on-prem data center. They've moved their world. They're now running, they've re-architected their application. It's now completely microservices-based running on Cassandra, deployed 100% in Google cloud platform. And they did that because they wanted to be more agile. They wanted to be more flexible. It's a far more cost effective deployment model. They are all in on the cloud. And they needed a next generation backup and recovery data protection, data management solution which is exactly what we do. So, that's the value. Backup's not a new problem. People need to protect data and they need to be able to take better advantage of the data. >> All right, so here's the final, final question. I'm a customer watching this video. Bottom line maybe, I'm kind of hearing all this stuff. When do I call you? What are the signals? What are the little smoke signals I see in my organization burning? When do I need to call you guys, Datos? >> You should call Datos IO anytime, if you're doing anything with development of modern applications, number one. If you're doing anything with hybrid cloud you should call us. Because you're gonna need to reevaluate your overall data management strategy it's that simple. >> All right, Peter Smails, the CMO of Datos, one of the hot companies here in Silicon Valley, out of Los Gatos, California. Of course, we're in Palo Alto at theCube Studios. I'm John Furrier. This is theCUBE conversation. Thanks for watching. (upbeat techno music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering Dell EMC World 2017. Brought to you by Dell EMC. >> Okay, welcome back everyone. We are here live at Dell EMC World 2017. This is our eighth year of coverage of formerly known as EMC World but is now Dell World. First year of the combined companies. Some say Dell bought EMC, some say EMC bought Dell. Either way, the merger and the acquisition, or combination, however you want to call it, certainly working out. This is Cube coverage of the first year. I'm John Furrier with my co-host, Keith Townsend, CTO advisor. Our next guest is Tarun Thakur, co-Founder and CEO of Datos IO, big news and as well, Peter Smails, Vice President of Marketing and Business Development, a former EMCer, been in the industry. Guys, congratulations, welcome to The Cube. >> Thank you, John. Thank you Keith. >> Thank you very much. >> It's a pleasure to be here. >> Big bang news at the Dell-E, so tons of stories here. Obviously the big story is the combination, but you guys have some really amazing news. Funding, traction, give us the update on the hard news. >> Excellent, thank you, John. First, thank you guys. Thank you very much for the opportunity to be here. The last couple of weeks have been just amazing for us. Last week was all about product, which Peter is going to talk about. Our journey from our one portal to our two portals. That journey is all driven by customers and where the market is headed. But this week was all about enterprise adoption. It's a&bout enterprise activity. You have these two industry stallworths, 200 billion dollars of market cap, recognizing the value of what we have been-- >> John: And so the hard news is, what, Cisco and NetApp have invested? >> Cisco and Neuron Motor invested in Datos today. >> So this is a round of funding from corporate investors. Any VC's coming in as well, or-- >> Both, you know, the investors were already in the company, they claimed their ownership-- >> John: Okay, so they did their pro-rata. They re-upped. Okay so, new corporate investors, that's validation. >> Yes, yes, yes. >> Why are they investing? My masses wants to know, why the hell are they investing? Why don't they just do it themselves? >> Yeah, so you know, look, I think this looks very, very clear that this industry of the data management, or this industry of enterprise with option to the cloud is just massive-paced right now, right? The acceleration is at it's highest gear, so to speak, and we've been working with both those companies for the last few months. They recognize at fundamental level what we've built, like, the application-centric nature of the product, build it fundamentally for cloud ready applications, helping existing customers mobilize their applications to the cloud. You know, you have to-- we have, now, three year lead, into the space, right, and it's best to join forces. >> Well, we had our Cube conversation in our studio in Palo Alto too, and you kind of smiling then, certainly smiling now. The big funding, big fat financing, as they say, but you really kind of coy about not sharing the news to me, which I thought was cool, kept the secret, but you guys have shell-- >> Tarun: I had valid reasons. >> But, the cloud is certainly accelerating. You guys have the tiger by the tail. But, if you look at the VC funding landscape, we were saying yesterday on our opening that, it's a canary in a coal mine. It's a really leading indicator of what's going on in the marketplace. If you're a storage start-up, you're DOA. No one is funding that. They're re-pivoting always. You see, "I got scale out, scale up storage," pivot, pivot, pivot but all of these companies, data management, data backup, and protection are all booming. Massive up, Rubrik, Cohesity, billion dollar valuations. Why are these companies getting such big funding? Why are you guys being so-- Is cloud just creating massive scale for what was normally a white space? >> No, sir. The answer-- I'll go first. >> Go for it. I'll jump in. >> Because you come from this all most recently. (laughter) >> Look, John, there has been no innovation in the space of backup and recovery for the last three years. We've been still living in the world of four-wall data center media-server based architectures, and backup and recovery products that were truly return for tape architectures. That world ain't exist in this cloud world. There has been no innovation, and now you see complete replacing of good companies. Great follow up companies to be p6art of. All of us recognize the disruption of opportunity, and recognize what we all do for the next 10, 20 years. >> And I'll jump on that. So, if you net it out, there's really two things happening. You know, 70% of CIO's have a cloud-first strategy. So, enterprise, one of the reason we're here. Enterprises have a cloud-first strategy. They're moving to the cloud. They're doing two things. One, they're either building net, new applications in the cloud. Geo-distributed, highly scaled applications. You need a fundamentally different approach for protecting those applications. That's number one. Number two is those same customers are saying, "I want to move as many of my non-recovery workloads from my traditional four wall data center off prim. I want to leverage the cloud. I want to put my data where I want to put it when I want to put it there." There has not been any good solution to do that. So, for us, that's cloud data management. We're about protect. If you have stuff in the cloud, we'll protect it. If you want to move stuff to the cloud, from the cloud, within the cloud, that's mobility to us. That's what we do. Ultimately, this is why there's so much attention being paid to cloud data management, because everybody's moving to the cloud. The one thing we have heard consistently-- >> John: It never existed before, really. >> They're not taking traditional tools to the cloud, simply put. >> You know what, go to the website, I don't see anything about backup. I don't see anything about, you know, there's data protection, but in an enterprise, when we go to the cloud for the first time, a couple of things we figure out first. Backup is hard, because, you know, I can't point my data domain to S3, and backup S3 or some type of &object storage. I also find out that these traditional architectures within the data center just don't translate to the cloud. So, where are you guys at in the education cycle of the enterprise, and helping them understand the value of the application-centric model, and where do you need to go? >> Yeah, so... Keith, that's a good question. You actually hit the nail on the head. You have these proprietary backup appliances. We used to call data domain, really a PPB appliance. You have these media-server based architectures with the likes of Vericlass and Condor. Perfect for four walls, right, in the cloud geo-distributor applications, right? You look at those, sort, that scale, the application centricity, and we started, what we did in our strategy, we started with absolutely green field. What does that mean? That means the cloud-native applications, the non-relatable databases, right? The analytics, the IO key applications. So you go towards the use-case where the world and the customers are already thinking cloud-native. Coaching and training customers, as you rightly called, is a very hard journey. It is a crossing the chasm. It takes time. You need to start with earlier doctors, the innovators, who will then latch onto you and take you forward. So, our strategy of picking the space, which was completely green field ablution, couldn't have served us better. >> So, what's that next step after we've figured out backup, because we have to back the data up. Data management is way more than backup. Now, as I've blown away the limits of my data center, and I can access data from anywhere in the world, what have you helped customers understand that they can do with their applications and data, now that I can access it anywhere in the world? >> Tarun: Excellent question. >> Yeah, so, I can take that. So, to your point, if you look at protect-- our three pillars: protect, mobilize, monetize. You'll hear us say that over and over and over again. We started with protection. It's a business-critical use case. You cannot have a cloud-first strategy if you don't protect your data. Got it. Second piece around the mobility piece is, like you said, giving. What have we done by being application-centric data management? What do we do that nobody else does,6 is we enable you to, very intelligently and very efficiently, move data sets, in native format, where ever you want. To any cloud that you want. We don't normalize data. We don't change formats. So, for example, I'll give you one great example of application centricity. I have an on-prim workload. I want to run a query against that. Star, not Peter star. That resulting data said, "That's all I want to move to the cloud, "because I want to run BIA against it. "I want to do something that helps me "monetize my data in the cloud. "That data set, I want to move." One, you can run a query against that database. Two, we'll intelligently and efficiently only move that data, in native format. Spin it up in the cloud as metadata set. All your metadata's there. Do whatever you want to that data. When you're done, move it back if you want. Do whatever you want. So, essentially, we've eliminated any silos from a cloud standpoint. So what we've done is, we've given people complete cloud freedom to move what they want when they want, where they need to. That's the essence of what we've done. >> Let's talk about the monetize portion of-- cause, you guys have me curious. If I can move the data to the cloud natively, that's great. That's really value add, but on top of that, I need to figure out really tough problem, which is metadata. I have global data, worldwide. I have data scientists wanting to pound against that in a completely new way. Do you guys provide a new way to access this data other than my legacy tools? >> Absolutely, Keith. So I really hit on those two points in the statement you made. Moving data efficiently, Keith, is a very hard problem. What we have done by being, only protecting what you need to protect, why back up an entire database when you only care about a couple of tables? Remember, we're going from traditional monalithic architectures to micro-services in the cloud, right? DBAs and augments, they only care about couple of tables. I want to run a BI query against certain part of the data. What we have fundamentally done, to the first part of your question, move data very highly efficient, which is 10x dedup of what data domain could do. We have significantly modified to be protected around that decon. The second piece around metadata question. What we've really done, Keith, in our, sort of, scale-out elastic data protection, to the tune of elastic compute and elastic storage, you need to extend that to elastic data management, is your metadata catalog can't back up, at the end of the day hasn't catalog. The golden nugget. >> Right. >> That catalog used to be siloed. If I had 10 media servers, I had that catalog siloed around that. >> Keith: No value met. >> No value met. >> Correct. >> Our catalog log is now distributed, stretched across cloud boundaries. If I have a Datos running on prim, and a Datos running on Amazon, those are two instances of the same software, two nodes, the metadata catalog can see each other. You back up here. John can see that backup in the cloud. He can spin up his sequence already in the cloud. You couldn't do that past. You couldn't do that back in the old world. The golden nugget. You need to stretch your metadata catalog and you need to make it distribute it across cloud boundaries, which is fundamentally what-- >> What's the impact to the application developers, because now, are you freeing up-- What is the ultimate value to the customers? I mean you're basically freeing up the hassles for the app developer to say, "whatever?" Give us the bottom line. >> So, you know, absolutely John. Look, I'll give you a customer's real scenario, okay? A world's leading e-commerce platform where we go, and wife's go spend a lot of money buying clothes, so I'm just going to leave it at that, right? They are moving from a monolithic architecture, the Oracle DB2, to the cloud-native architecture. Application developers want to take their CICD. I'm writing new code, I want to bring new catalog items on the website. I want to test my code changes, and I want to go from the data, not two days ago, which was the old backup world, every day you bring a backup. Now they want what we call, to your question of we don't call it backup, what we call it versioning. I want a version one hour ago, because I want to test my code changes. I want to deploy those code changes on the e-commerce platform driving a billion dollars in revenue, so-- >> So you're enabling more and more coolness with the developer from a data, stale verses fresh data. I mean to certain levels, I mean not-- >> But I want to jump on that as well, because the thing that sometimes goes over looked is that, one of the things that the cloud has done that people sort of don't always acknowledge, is it's created, we've pushed the silo problem from on-prim to the cloud. Clouds don't talk to each other. You know, the notion of that. So the notion of the universal file system, such as the cloud, which some of the competitive landscape tries to-- >> John: Wait a minute. We're supposed to have multi-clouds. >> Yeah we're supposed to, but no. To your point, we do have multi-cloud. But its amazing how difficult it is to deal with that. So to your point-- >> In the future they might be talking to each other, but today they're not. >> But, but, and my point is that we enable you to do that. So, the ultimate value to the customer? I'm the marketing guy, yes, but the notion of cloud freedom is a direct business value to the customer-- >> John: So that's legit from your standpoint. Cloud freedom... >> Put it where you need to put it, when you want to put it there. Bring it back when you want to bring it back. So, from an app standpoint, a lot more flexibility. A lot more agility in terms of app development. From a cost standpoint, from an IT standpoint, I can dramatically reduce my cost, cause I can leverage the cloud versus having everything on prim. From an operational standpoint, I ensure everything's protected, so-- >> And we know cloud-native developers are very, like, they won't tolerate a lot of the old baggage and dogma of IT. >> Peter: Right, right. Are ya freakin' kidding me? >> Tarun: Well, well all-- >> Peter: That's actually, can I take that one? >> Tarun: Please, please. >> That's actually a good-- >> You see how fired up he is? >> I don't know how many hours we have to talk on The Cube because that's a fascinating topic. >> Just pause. Can I pause you for a second? >> Yes. >> That's only 30 days since he left EMC. (laughter) >> Alright, alright. Anyway, the point is, but the problem is new, but there is a persona, what I refer to as basically like a persona innovator's dilemma, that we're also helping address, because there's a convergence of personalities of people involved in the protection and management of data. So, to your point, we've been dealing with a lot of the new personas going after cloud-native data protection, but you're watching the organizations. The enterprises, they're going through it and they are rapidly transforming these personas. So, part of our jobs, to your education point earlier, is making sure that the left hand knows what the right hand is doing,% and marrying those two different pieces. That's ultimately, and that's value to the customer, and we help drive that process. >> Well, Tarun and Peter, congratulations, and good to see the journey continuing to accelerate. >> Thank you. Thank you. >> Entrepreneurial journey, and we'll keep in touch. Love the name, Datos OS. We believe, and Wikibon believes, and they're firm on this, that the business value of data is ultimately going to be a major, major disruptor for business. Not necessarily technology, but having that data operating system, that Datos, as you call it, is going to be fundamental. Congratulations. >> Thank you, John. >> Just keep it live here at Dell EMC World 2017. More live coverage, stay with us. More after this short break. (upbeat music)

(motivating electronic music) >> Hello everyone, welcome to theCUBE. I'm John Furrier, the co-host and co-founder of Silicon Angle Media. We're here for a CUBE Conversation in our studios in Palo Alto, California. Here with two great guests inside the industry, to help illuminate the cloud computing conversation, really around what's coming up with Amazon re:Invent. But more importantly, the major advances happening in the digital transformation around IT and around developers and around cloud, and how that's impacting business. Our guests are Chris Comings, who's with the Chasm Group, consult and they help people, and former industry executive at NetApp, and (mumbles) the storage company. Peter Smails, the CMO of Datos.io data, and then he's the CMO there. Now, new progressive solutions. So guys, great solution. And Peter, I know you got news. We're gonna do another segment on your big news coming out, so we're gonna hold that off. >> Cool. >> The game has changed, right? >> Mm-hmm (affirmative). >> And we talked, with Chris and I had a one on one about this. But the industry conversation, there's people that are in the know, and people who are trying to figure out what's happening and how it impacts their business. CIO, CEOs, CDOs, chief data officers, chief security officers. There's a lot of things on the plate of businesses. >> Right. >> Big time. >> Right. >> So let's unpack this, and let's illuminate what it means. So cloud computing, Peter, what's your take on this, because Datos just takes a unique approach? I love your solution. A lot of people are liking this solution, but it's nuanced, because it's cloud-- >> Yeah. >> That's driving you. >> Yeah. >> What's the big driver? >> So the big driver, you said at the top of the discussion, the big driver is digital transformation. Digital transformation. Organizations are trying to be more data-driven. Okay, this is completely throwing, throwing traditional IT amok, because we're not living in the traditional world anymore of all my data sits within a single data center, I run my traditional monolithic applications. That's changed. The world is no longer running in a traditional four wall data center, and the world's moved away from the traditional view of scale-up architectures to elastic compute, shared nothing, elastic storage environment. So what's happening is, you've got the challenge of trying to essentially support traditional transformation initiatives, and it's just throwing all the underlying infrastructure foundations that an entire generation of IT professionals has known (laughs) into disarray. So everything's a little bit caddywhompus right now. >> Mm-hmm (affirmative), Chris? >> Well, and like you said, those people all have gone from being implementers to, they're moving to being developers. >> Right. >> And it completely changes their, it has to be a big change in their mindset. And it changes the management folks, the CIOs, the CDOs, the people that you interact with on a daily basis, right? >> Absolutely. >> Because these people are all trying to kind of come up to the next generation and get there. >> So you talked about, we got re:Invent coming up in a couple of weeks and, I think reinvent's a perfect term for this entire conversation, because everybody is reinventing themselves. The customer's reinventing themselves, the IT organizations are reinventing themselves, the individual roles within organizations are changing, and the whole evolution of dev ops versus traditional roles, so it is really-- >> And the vendors are all trying to reinvent themselves, too. >> Yeah, absolutely, absolutely. >> Well there's a lot of noise, so the customer's being bombarded with pitches. And if I here one more digital transformation pitch, without substance, I still don't understand. So in the spirit of trying to understand, first of all, I believe in digital transformation, but you can't just say the word, you gotta to prove it. But there's hard to prove a new approach or they've never seen it before. It's kind of like Steve Jobs would say, "If you want a Blackberry, that's a phone, "but the iPhone's not what you've seen before." But everyone loved it, changed the industry. That dynamic's happening in the cloud where for instance, your solution, some might not have seen before, but it's highly relevant to the user behavior expectations of the new environment. Okay, so this is the issue. What is the new environment specifically around digital transformation? Because I have an investment in storage. If I'm a customer, I bought a zillion drives from NetApp and EMC. I got data domain backup and, I got a perimeter, I have all this stuff, and now I've got this cloud thing bursting, and I got some analytics running there, and then I got the hot shot young developers banging out apps, and they want to put it in the cloud and... and security, I mean, what's going on? >> You wanna take that one first? And then I'll jump in. >> Can't I just buy more storage? >> Yeah. (Men laugh) Hey, just, no John, you don't just buy more storage, you upgrade from spinning to flash. I mean, that's really, >> There you go. >> That's really, really cutting edge right there. No I think what a lot of you see what they're doing is basically saying listen, for all this secondary, tertiary, quaternary, I mean, I didn't even know what that word was. But your second, your third, your fourth cuts of that data, move that all to the cloud, get that out of my environment. I'm not gonna be submersed in dealing with all of that anymore. Then maybe I can clear out some of my headaches, so I can actually focus on that primary cut, and what do I do about that primary cut? And that's where these completely new approaches come into play, and I, Peter I don't know if you call that hybrid, or multi-aire or what? But it is basically just trying to get some of that noise out of their system, so they can focus on the thing that's most valuable. >> So the way I would make that tangible John, is sort of, to us it all rolls down to the notion of the modern IT stack, okay? So essentially, the way you respond to digital transformation which, is all about being more agile, and some of the buzzwords you hear, but they're trying to be more, customers are trying to be, vendors are trying to be, or excuse me, customers or organizations are trying to be more customer-centric. They're trying to be more business driven, more data driven, okay great. If that's their initiative-- >> That's a mission. That's a mission. >> That's a mission. >> Yep. >> What that means for IT specifically is a fundamental rearchitecture of the underlying stack, okay, along a couple vectors, which is, organizations are building these new applications. They're fundamentally rearchitecting applications. What used to be a monolithic-oriented, traditional, relational, on-prem database is now running in a microservices, highly distributed configuration. That's vector number one, implication. Implication number two is we're absolutely in the mainstream of hybrid cloud, okay? You may be running all your apps on-prem, but you're still connected in some way to the cloud, for archiving, for BI, for TASDAV, whatever the case may be. And number three is the world just moved completely to an elastic, compute, shared nothing world. So we call that the modern IT stack. So the modern IT stack, modern infrastructure today-- >> Share nothing, you said? >> Shared nothing, the cloud is-- >> Oh, shared nothing. >> Yeah, shared nothing, shared nothing storage, shared nothing compute, that's that's, those are the foundations of a cloud based architecture. >> Is that called serverless? >> You could call it serverless as well. >> Okay. >> But, if you look at the modern IT stack, so to your point, the modern IT stack, modern infrastructure today is EC2. >> Mm-hmm (affirmative). >> Modern storage is S3. It could be object prem, object storage sitting on-prem. You know, modern applications are IOT. Modern, or our customer 360, IOT. Modern databases are dynamo DB. It's MongoDB, it's the number two-- >> Right. >> database in the cloud. So to answer your question very specifically, to make it tangible, that's to us the fundamental indication is, that new modern IT stack, throws storage into disarray, it throws data management into disarray-- >> It's an operational disruption. >> It's an operational disruption. >> All right, so let's backup for a second, because I think you nailed the thread I was trying to connect on. So let's take MongoDB, your reference to that being, where'd that come from? We all know why, the LAMP stack, it was one of the drivers. But developers drove that. >> That's right. >> So it wasn't the IT department recommending Mango. >> Right (laughs). >> so the developers were driving that because of ease of use. Now there's some scalability with Mango, we all know about, but what that means is, no one gives a crap if it can scale, because you already hit your product market fit. Then you could rearchitect, so you're seeing this use case of developers driving some of the behavior. >> Yes. >> Yes. >> Mm-hmm (affirmative). >> Hence containers, docker containers, and the role of Kubernetes. >> Kubernetes, yep. >> So if that's the case, how does an enterprise customer deal with that vector? Because now the developers are dictating the stacks. >> Mm-hmm (affirmative). >> Well, I-- >> Is it a free-for-all right now? I mean, this is... >> I think both of those guys are, think of it as they used to be warring factions, dev and ops, and the fact that we say the word dev ops right now is kind of a, it's kind of an oxymoron, right? Because they don't actually know each other and actually don't naturally talk to one another, and they go, "That's the other guy who's holding me back." >> Yeah, it's the old-- >> They look at, yeah, yeah. >> Goes over the fence. >> And so now, you've got folks that are really trying to, trying to bring it together a little bit more on that front and I think that, we're starting to see some technologies where people can say, "Not only can I use that "to accelerate my developments," so meets the dev criteria, but also the ops people say, "You know what, that stuff's not so bad. "I could actually work with that." >> Right, and then there's IT going, "Uh-oh," because they're basically sitting there on the catcher's side, so to your point it's, the dev ops, it is very much of an application-led environment. The tip of the spear for the new IT stack is absolutely application-led. And IT is challenged with essentially aligning to that, collaborating with that, and keeping up with that pace of change. >> And John, on this point, I think this is where, back to re:Invent, and really the role of AWS. This all started because of that. When a developer can just say, "I don't even know who those IT people are over there, "But I can spin up my S3 instance, "and I can start working against it." They start moving down the path, they show it to somebody, someone says, "Wow, that's great stuff, I want that." >> John: Yeah, right. >> Guess what? We need to make sure that that's enterprise class and scalable and then that's where that whole thing starts, and then it becomes that pull-ya-apart, "Oh God, what did these developer people do? "I'm gonna inherit this? "What the heck am I gonna do with it?" Now it's, we've gotta move that to be more symbiotic up front. >> I remember talking to both Pat Gelsinger and Andy Jassy years ago, I think maybe five years ago, and I asked the question, "What enables developers?" What is enabling point? Does infrastructure dictate developer behavior? Or do developers dictate infrastructure behavior? This was years ago, when the dev ops was an early-on movement. Clearly the vote is there. Developers are driving infrastructure. Hence the dev ops infrastructure, >> Absolutely. >> Yeah. >> as code model, that's proven. Jassy was interesting because he looked at it that way and said, "Yeah, we saw the same thing," and they've never wavered, Amazon's stayed on the course, and they've just been running like a machine, like a, just pounding it out. I asked Pat Gelsinger, he once positioned the AWS as the developer cloud. Kinda in, I wouldn't say depositioning them, but he was basically pointing out, they have a developer cloud. Now Amazon's the enterprise cloud. >> Mm-hmm (affirmative). >> Because they've developers are now a big driver of that, and the scale with data is actually turning out to be a better security environment. >> Right. >> For cyber. >> Right, it might just-- >> So it's cloud's winning. >> Cloud is winning and just sort of just take that one step further. It's always ultimately, the winner's going to, it's Darwinism, it's like the winner's gonna be the one with the richest ecosystem. And AWS is becoming that enterprise eco. And you could argue, I mean, GCP's fighting to be in there, Oracle's not going to go quietly into that dark night. You've got multiple public cloud vendors. >> That's right. >> Yeah. >> But the reality is that he who has the biggest, he or she who has the biggest ecosystem is gonna win, and that's right now is AWS driving that bus. >> All right, so I need to see those glasses for a second, and then want to go into another line of question here. (men laugh) >> You may use those. >> Oh who's, oh you put them on, all right good, as long as he's wearing them. >> He that wear-- >> You know, on that front too, on that front too, I would think we started back where VM was the big new thing, and here we go with VM's, and then all of a sudden we're coming up and we're saying, "Yeah, now there's containers." And so now we're gonna see this move to, we want to micro-package these services, and be able to aggregate them. Well you know the average IT shop that I would be talking to out there is just still trying to figure out, how do they put together their on-prem and their AWS instance? So this notion of hybrid is where most of these large enterprises are. We see a lot of terminology out there and a lot of vendors talking about multi-cloud. But multi-cloud is really just taking an option on the future and saying, "I'm not locked into you, AWS, "even though I am locked into you 100% right now. "I don't want to be forever in the future." >> It's a value statement that they're gesturing. >> That's right. >> Good segue. >> Chris: But it's not a practical implementation piece. >> I got my nerd glasses on so-- >> Peter: Strap in for something, here we go. I got my nerd glasses, so next question, we'll go a little nerdy, because this is important one. I put out at my crowd chat for Amazon, so to crowdchat.net/awsreinvent it's open, I have a lot of questions on there. Feel free to weigh in, it's an influencer-only chat, so no consumers, so I asked the question, and this is to the value statement, because multi-cloud is basically telegraphing lock-in. We don't want lock-in. >> Right. >> But we want love choice. If you have good choice and good value, we'll go there so it's a value equation. So the question I said is, where do you, this is a question I put on crowd-chat, I'll ask you guys. Where do you see the value that cloud creates for customers in the next 24 months? #cloud So the first response was from Subbu Allamaraju, who's the CIO at Expedia. He writes, "Agility from the service "ecosystem and rapid second-order architecture "architectural changes thereby clearing technical debt." And the second one from Grant Chase, "Born on the cloud apps already here. "Next wave migrating of existing apps." And then Maddoux Tsukahara said, "Legacy SASS applications will be disrupted "by cloud microservices, serverless, "and AI and machine learning." So we start to see the pattern. Your thoughts? Value creation, in the cloud, is gonna be what? >> So I think they're hitting on the right trends. I would go back to the first one which is "How do I get this on-prem stuff "that's driving me crazy, consuming all of my resources "in terms of maintenance and upgrades? "And then optimizing my environment for that." Which ones of those are core? And which ones of those are really kind of ancillary? I've gotta have them, but I really don't want them. If I didn't have to use them, I'd get rid of them. Take all, just do that homework. Separate the two cleanly. Move ancillary to the cloud, and move on. >> Peter: Yeah, yeah. >> So service ecosystem he nailed, I love, by the way, I agree with you, that was my favorite answer. And rapid second-order architecture changes. This speaks to what datos.io is doing. Because you guys, what you're in, the tornado that you're in, kind of just a play on the Chasm group here. You guys have a solution that has got visibility into some of the real dynamics of the environmental environment. >> Check. >> People, tech, stack, et cetera. >> Yeah, yeah. >> So what are some of the things that you're seeing that point to these second or level architectural changes? >> Well you mentioned, a couple different things, which is, you mentioned the notion of technical debt, which is indirectly what you were just talking about, the ability to get rid of my technical debt. It's an easy way, it eliminates my barrier to answering to creating net new applications. So without having to sort of, I avoid the innovator's dilemma if you will, because I can build these net new applications, which are the things I have to to drive my digital transformation, et cetera. I can do that in a very cost-effective and agile way. Meanwhile, sort of ignoring the old world. Then what I'll do is I'll go back, and I'll worry about the old stuff, and I'll start migrating some of that old stuff to the cloud. So in the context of, yeah, so what we see from a Datos IO perspective, in the context of data management, is that one, applications drive the stack, like you said earlier, it's absolutely, the application's at the tip of the spear, driving the stack. Organizations are building net new applications that are cloud native, okay? And they're built on the new modern IT stack, and at the same time, they're also taking their legacy application, so I like that second answer as well which is, modern cloud applications are here. The interesting thing is, you say modern cloud apps, modern cloud apps don't have to run in the cloud. >> That's right. >> We've got customers that are running their next gen app-- >> It's an operating model. >> It's an operating model. We've got customers running 100% on-prem. Their econ number stuff runs on-prem, then you have people that run in the cloud. So it's a mindset, it's an operating model. So you've got folks absolutely deploying these cloud-native apps. >> Well, it's an architectural model too, it's how they are deploying and servicing apps. >> And ultimately, it comes down to the architectural model. That's what shifted, and that world is very infrastructure. The other thing I would add to the cloud thing is if you do it right, the cloud actually can give you architectural independence and cloud independence, but you can't be focused on the infrastructure level. You've gotta focus at the application level, because then you can be agnostic, until they're online. >> So Peter you, you guys are disrupting a very large space, backup and recovery in the cloud which you guys are doing. >> Check. >> And the application database layer is a very progressive solution. So I love your approach, but you're talking about disrupting the data domains of the world. We're talking about big whales. >> Yeah. >> Big incumbents that are built around four walls in the data center. >> Check. >> Mm-hmm (affirmative), yep. >> What are you seeing? What's the makeup? What's the personnel of the customers look like? If dev ops is happening, which we agree it is, and the the evidence is there clearly, they're not 50 year old backup and recovery guys. They're young guns, they're probably not thinking about waking up every day with their coffee, say, "Hmm, what am I gonna do with backup today?" >> Yeah. >> Mm-hmm (affirmative). >> They're waking up saying, "Hey, I'm gonna drive some more machine learning "and AI in my apps." >> Yep. >> "And I'm gonna provide workflow movement to--" >> And you said breakfast was some, you said that. >> Adopt this microservice. >> I had the craziest dream last night. It was microservices, what? >> Yeah. >> Yeah, so I can answer that two ways. There's the technology side of it. Fun little tidbit, average age of the traditional backup and recovery software architecture, about 20 years. >> Hmm. >> Architected well before the mainstream advent of the cloud or certainly modern applications. >> Hold on, the person's 20 years old? Or it's 20 years of architecture? >> No, the architecture of the software. >> Okay. >> The solutions, or come up, the point is they've been around for awhile. >> It's old. It's old. >> It's old, fair enough. >> Yeah, and 20 years-- >> So on the technology side, that's a dilemma. On the persona side, you're absolutely right as well. These are, it's the application folks that are driving the conversation, that our applications dictate the IT stack. They're building these new architectures, which have all these implications on the infrastructure. >> All right, so I'm gonna play devil's advocate, just because I want to connect the dots. And again, illuminate what I think the problem is that you have. One is, okay I'm a CIO. Hey, he's my storage guy. Who the hell are you, young gun? Complaining about your backup and recovery. He recommends all flash arrays in the data center provisioned in a VSAN environment, whatever that's going on. Who are you? You're just nothing to me. You don't make that decision. >> I'm the guy that can give you all the visibility to your data to make you smarter and more agile as a company. I can save you money. I can make this company more market-- >> So what do I need to do differently? If I'm the CIO, I don't want to make these, or these architectural calls based upon old dogma or old reporting lines. This is an example. I go to him, he's my storage guy. Who are you? I already built you the dev ops environment. He runs storage and so, you're impacted as a developer. So how do you guys talk to that guy? What does the CXO have to do differently to adapt to the new environment? >> I'll take that and then you can-- >> Please. >> You know, jump in. So I think what you see is, you see the proliferation of new personas. Like you see chief transformation officers, you see chief digital officers. You see system architects and DBAs getting a more prominent role in the conversation. So the successful CIOs and technology officers are the ones that are essentially gonna get the cowboys and the Indians to collaborate more closely, because they have to, because the folks that were over in the corner that used to get laughed at, building these, oh mangos and these new applications and such, they're the ones holding the keys to the future. So the successful technologists are gonna be the ones that marry those personas from the application side of the house with the traditional storage, infrastructure folks as well. You successfully do that, then you can be more, then you can move more quickly forward. >> Yeah, that's right. >> What do you think? >> Well I think some of it's gonna come back down to economics, too. And I agree with that move which is, I talked to over a hundred CIOs and their staff in the last year. I had one conversation where the person said, "You know what? "The chief complaint about me as CIO "is I'm not spending enough money." And I thought to myself, "Sounds like a company that I should put some bucks into, "because they must be doing really, really well." Everybody else is looking at it saying, "You know what? "I'm under pressure to adopt the cloud, "because there's a belief out there "that the cloud is gonna be so much less expensive "than what they've done in the past." And then I think they find that it's not, that it's not just the one size fits all answer to that. >> Right. >> And so as a consequence, you're gonna have people say, Listen, this money printing operation, or this funnel out the door to, whether it's EMC or NetApp 4, or whatever it may be, whatever storage vendor for backup architecture, they've got to stop that funnel. Because they've got to take what they were spending there and move it to the things that are going to make money for them, not just gonna hold on to it, and de-risk their enterprise. >> I'm here with two industry leaders, Chris Comings and Peter Smails, talking about the impact of infrastructure technologies, and app development in the cloud for businesses. It's a great conversation, and our final point, I wanna just get to, I know we're running on some time here but we wanna go a little further. I think this is awesome. That's for taking the time to share it out. >> It's great. >> One of my other questions I put on my crowd chat was, a true or false and comment question. Here's the statement: Serverless computing will become mainstream, will come to mainstream private cloud, true or false, comment. Subbu said, "False, adoption and success "of serverless patterns depend almost entirely "on the strength of the ecosystem "that the data center lacks." Interesting comment. I was kinda leaning, I go, "I was leaning towards true." But I don't have enough insight on this, because I'm waffling between true or false. I love serverless, I love the idea of, notion of resources that are just programmable. But what is the state of serverless? I mean, is he right? Is that that there's not enough ecosystem in the data center areas or... >> You wanna go first? >> Well, I'd just say that I would, I would just call out two things on that front. One is, I think you need a lot more germination of microservices that are out there in order to be able to put that all together. That's one aspect. We're seeing that growth come rapidly. The other thing is, now your security is beholden to the lowest common denominator. The security of that individual microservice. So I think you're gonna have some fits and starts here as we move down that path because, boy oh boy, the last thing I wanna do is get all modern but at the same time, put myself at a greater amount of risk. >> I thought the comment at the end was, I think it's true. I thought it was interesting what he said at the end. He said, "The ecosystem that the data center lacks." I would contend that potentially, the ecosystem that the cloud has would support that. >> Yeah. >> Because the cloud, by definition is, it's a shared-nothing world. >> Right. >> You know? >> So, he also comments, someone said, Lambda, "My Expedia is that Lambda's growth "is almost entirely due to the power "of the ecosystem of services, "which is one of the key points," and he points to his blog post. Stu Miniman, our Wikibon analyst weighed in, because Stu's on this big time. "Service will definitely be used for edge applications. "Currently don't see use case for general data center usage." >> Mm-hmm (affirmative). >> So edge of the network. Again, good point? This edge of the network thing helps you, because most people are using cloud for edge. >> Peter: Right. >> So this IOT, which is, an iterative things, is an edge of the network. >> Yeah, yeah. >> Whether it's devices, sensors, industrial equipment, or people's devices on their bodies. >> Yeah. >> It's a huge data source. >> Absolutely. >> Cloud's rolling that up. Or a cloud-like infrastructure. >> Well but it's not necessarily rolling it up. It's just connecting all the dots as to where you can put storage and you can put compute where the data is. Or you can move the data to where the storage and the compute is. So it's not, I mean, yes there's core and edge, that's absolutely true, but the notion of rollup isn't necessarily true. It's not necessarily the cloud enables me to do all this colossal aggregation. It's I basically distribute my compute, I distribute my storage. >> Well, when I say rollup, I'm assuming there's some sort of architectural thing. >> Okay, fair. >> But this fits into your wheelhouse, I think. But I just connecting the dots. That's why it's a question for you is, it would make sense for a solution like DATOS to be there because, That's a application so you-- >> Absolutely. >> You back up IOT? >> Oh absolutely. We backup IOT, but we basically backup any modern cloud application. And by definition, what does that mean? >> So IOT's and app for you. >> IOT, absolutely IOT's-- >> Not necessarily a-- >> So the technically where we plug in is, we plugin at the database level. And the databases basically, are the underlying infrastructure that support the applications. So in the case of IOT, those are typically very highly distributed across GIOS, absolutely we protect them. >> So we were just talking earlier about the words flexibility, manageability, agility. That's kind of vanilla words that everyone uses these days. But in essence, you're actually really doing it. Right, so. >> Thanks for that setup. Yes, we actually do all those buzz words. >> So Chris recommends, I recommend that you call it, hyper flexibility. >> Yeah. >> Or microflexibility. >> Or ultra. >> Or ultra flexibility. >> Or go mega. Just go mega right now. Or uber and steal a little of that, although that's kind of out of favor right now. >> Not, uber is-- >> Uber we wanna let that one kind of fly by. >> But remember we also talked before, we thought we were spot on with our product being branded RecoverX. We thought we were really in the spot with the whole, you know. >> Your name is awesome. RecoverX is a great brand. >> So we're gonna stick with that for now before we-- >> Good branding, RecoverX, Data IOS. Chris, thanks for coming on. Final comment, any words on the storage industry as it evolved? You mentioned earlier, just call it flash. Certainly, all flash arrays are doing well. Pure Storage went public. Flash is a standard. >> Yeah. >> It has benefits. Where does the flash storage go with all this cloud value coming over the top? >> Well I think, you know, there's gonna be a couple. I have one comment on that which is, we see what flash is doing at the array level, and now we're gonna see what NVME does at the cash layer, for allowing this access to information. You think about, I want to run a singular query, but some of that data is here, there, everywhere, but I've gotta have a level of performance that allows me to actually run it, and get an answer from it. And so that's where that comes into play. I think we're gonna see a whole host of folks flooding into that space, to try and improve performance, but not only improve performance, but enable that whole distribution model. >> Yeah, and I would just pick up on more persona-centric thing which is, the message to the traditional IT shops is it is all about collaboration. The folks over in the corner, the application folks, it is absolutely all about getting more closely aligned, because cloud is here. >> Yeah. >> Multicloud, hybrid cloud, call it whatever you want, is here. The traditional IT stack is absolutely being disrupted, and it's all about embracing this application-centric, data-driven view of the world. That's the future, traditional IT's got to align with that, and collaborate and drive that whole thing forward. >> That's a great, I agree 100% what you guys just said, great comment. I would just say Wikibon calls it unigrid, which is, I'll rename it hypergrid, meaning it's just one system, to your point. Private, public, it's all cloud-like. >> Absolutely. >> Yeah, it doesn't matter where it goes. Okay guys, thanks for the thought leadership. Peter Smails and Chris Cummings here, breaking down the industry landscape on storage infrastructure, application developers, in context the cloud. This is theCUBE conversation. I'm John Furrier, thanks for watching. (motivating electronic music)