>>Good morning and welcome back to Detroit, Michigan. My name is Savannah Peterson and I'm here on set of the cube, my co-host John Farer. How you doing this morning, John? >>Doing great. Feeling fresh. Day two of three days of coverage, feeling >>Fresh. That is that for being in the heat of the conference. I love that attitude. It's gonna >>Be a great day today. We'll see you at the end of the day. Yeah, >>Well, we'll hold him to it. All right, everyone hold 'em accountable. Very excited to start the day off with an internet, a legend as well as a cube og. We are joined this morning by Matt Klein. Matt, welcome to the show. >>Thanks for having me. Good to see you. Yep. >>It's so, what's the vibe? Day two, Everyone's buzzing. What's got you excited at the show? You've been here before, but it's been three years you >>Mentioned. I, I was saying it's been three years since I've been to a conference, so it's been interesting for me to see what is, what is the same and what is different pre and post covid. But just really great to see everyone here again and nice to not be sitting in my home by myself. >>You know, Savannah said you're an OG and we were referring before we came on camera that you were your first came on the Cub in 2017, second Cuban event. But you were, I think, on the first wave of what I call the contributor momentum, where CNCF really got the traction. Yeah. You were at Lift, Envoy was contributed and that was really hyped up and I remember that vividly. It was day zero they called it back then. Yeah. And you got so much traction. People are totally into it. Yeah. Now we've got a lot of that going on now. Right. A lot of, lot of day Zero events. They call 'em co, co-located events. You got web assembly, a lot of other hype out there. What do you see out there that you like? How would you look at some of these other Sure. Communities that are developing, What's the landscape look like as you look out? Because Envoy set the table, what is now a standard >>Practice. Yeah. What's been so interesting for me just to come here to the conference is, you know, we open source Envoy in 2016. We donated in 2017. And as you mentioned at that time, Envoy was, you know, everyone wanted to talk about Envoy. And you know, much to my amazement, Envoy is now pervasive. I mean, it's used everywhere around the world. It's like, never in my wildest dreams would I have imagined that it would be so widely used. And it's almost gotten to the point where it's become boring. You know, It's just assumed that Envoy is, is everywhere. And now we're hearing a lot about Eeb p f and Web assembly and GI ops and you know, AI and a bunch of other things. So it's, it's actually great. It's made me very happy that it's become so pervasive, but it's also fun. Yeah. We mention to, to look around all other stuff >>Like congratulate. It's just a huge accomplishment really. I think it's gonna be historic, historical moment for the industry too. But I like how it progressed. I mean, I don't mind hype cycles as long as it's some vetting. Sure. Of course. You know, use cases that are clearly defined, but you gotta get that momentum in the community, but then you start gotta get down to, to business. Yep. So, so to speak and get it deployed, get traction. Yep. What should projects look like? And, and give us the update on Envoy. Cause you guys have a, a great use case of how you got traction. Right. Take us through some of the early days of what made Envoy successful in your opinion. Great question. >>Yeah. You know, I, I think Envoy is fairly unique around this conference in the sense that Envoy was developed by Lyft, which is an end user company. And many of the projects in this ecosystem, you know, no judgment, for better or worse, they are vendor backed. And I think that's a different delivery mechanism when it's coming from an end user where you're solving a, a particular business case. So Envoy was really developed for Lyft in a, you know, very early scaling days and just, you know, trying to help Lyft solve its business problems. So I think when Envoy was developed, we were, you know, scaling, we were falling over and actually many other companies were having similar problems. So I think Envoy became very widely deployed because many companies were having similar issues. So Envoy just became pervasive among lift peer companies. And then we saw a lot of vendor uptake in the service mesh space in the API gateway space among large internet providers. So, I I I, I think it's just, it's an interesting case because I think when you're solving real problems on the ground, in some ways it's easier to actually get adoption than if you're trying to develop it from a commercial backing. >>And that's the class, I mean, almost, It's almost like open source product market fit. It is in its own way. Cause you have a problem. Absolutely. Other people have the same problem finding >>Too. I mean, it's, it's designed thinking from >>A different, When, when I talk to people about open source, I like to tell people that I do not think it's any different than starting a company. I actually think it's all the same problems finding pro product, market fit, hiring, like finding contributors and maintainers, like doing PR and marketing. Yeah. Getting team together, traction, getting, getting funding. I mean, you have to have money to do all these things. Yeah. So I think a lot of people think of open source as I, I don't know, you know, this fantastic collaborative effort and, and it is that, but there's a lot more to it. Yeah. And it is much more akin to starting a >>Company. Let's, let's just look at that for a second. Cause I think that's a good point. And I was having a conversation in the hallway two nights ago on this exact point. If the power dynamics of a startup in the open source, as you point out, is just different, it's community based. So there are things you just gotta be mindful of. It's not top down. >>Exactly. It's not like, >>Right. You know, go take that hill. It's really consensus based, but it is a startup. All those elements are in place. Absolutely. You need leadership, you gotta have debates, alignment, commit, You gotta commit to a vision. Yep. You gotta make adjustments. Build the trajectory. So based on that, I mean, do you see more end user traction? Cause I was, we were talking also about Intuit, they donated some of their tow code R goes out there. Yep. R go see the CDR goes a service. Where's the end user contributions to these days? Do you feel like it's good, still healthy? >>I, I mean, I, I'm, I'm biased. I would like to see more. I think backstage outta Spotify is absolutely fantastic. That's an area just in terms of developer portals and developer efficiency that I think has been very underserved. So seeing Backstage come outta Spotify where they've used it for years, and I think we've already seen they had a huge date, you know, day one event. And I, I think we're gonna see a lot more out of that >>Coming from, I'm an end user, pretend I'm an end user, so pretend I have some code. I want to, Oh man, I'm scared. I don't am I'm gonna lose my competitive edge. What's the, how do you talk to the enterprise out there that might be thinking about putting their project out there for whether it's the benefit of the community, developing talent, developing the product? >>Sure. Yeah. I would say that I, I would ask everyone to think through all of the pros and cons of doing that because it's not for free. I mean, doing open source is costly. It takes developer time, you know, it takes management time, it takes budgeting dollars. But the benefits if successful can be huge, right? I mean, it can be just in terms of, you know, getting people into your company, getting users, getting more features, all of that. So I would always encourage everyone to take a very pragmatic and realistic view of, of what is required to make that happen. >>What was that decision like at Lyft >>When you I I'm gonna be honest, it was very naive. I I think we've, of that we think we need to know. No, just didn't know. Yeah. I think a lot of us, myself included, had very minimal open source experience. And had we known, or had I known what would've happened, I, I still would've done it. But I, I'm gonna be honest, the last seven years have aged me what I feel like is like 70 or a hundred. It's been a >>But you say you look out in the landscape, you gotta take pride, look at what's happened. Oh, it's, I mean, it's like you said, it >>Matured fantastic. I would not trade it for anything, but it has, it has been a journey. What >>Was the biggest surprise? What was the most eye opening thing about the journey for you? >>I, I think actually just the recognition of all of the non-technical things that go into making these things a success. I think at a conference like this, people think a lot about technology. It is a technology conference, but open source is business. It really is. I mean, it, it takes money to keep it going. It takes people to keep >>It going. You gotta sell people on the concepts. >>It takes leadership to keep it going. It takes internal, it takes marketing. Yeah. So for me, what was most eyeopening is over the last five to seven years, I feel like I actually have not developed very many, if any technical skills. But my general leadership skills, you know, that would be applicable again, to running a business have applied so well to, to >>Growing off, Hey, you put it out there, you hear driving the ship. It's good to do that. They need that. It really needs it. And the results speak for itself and congratulations. Yeah. Thank you. What's the update on the project? Give us an update because you're seeing, seeing a lot of infrastructure people having the same problem. Sure. But it's also, the environments are a little bit different. Some people have different architectures. Absolutely different, more cloud, less cloud edges exploding. Yeah. Where does Envoy fit into the landscape they've seen and what's the updates? You've got some new things going on. Give the updates on what's going on with the project Sure. And then how it sits in the ecosystem vis-a-vis what people may use it for. >>Yeah. So I'm, from a core project perspective, honestly, things have matured. Things have stabilized a bit. So a lot of what we focus on now are less Big bang features, but more table stakes. We spend a lot of time on security. We spend a lot of time on software supply chain. A topic that you're probably hearing a lot about at this conference. We have a lot of software supply chain issues. We have shipped Quicken HTB three over the last year. That's generally available. That's a new internet protocol still work happening on web assembly where ha doing a lot of work on our build and release pipeline. Again, you would think that's boring. Yeah. But a lot of people want, you know, packages for their fedora or their ADU or their Docker images. And that takes a lot of effort. So a lot of what we're doing now is more table stakes, just realizing that the project is used around the world very widely. >>Yeah. The thing that I'm most interested in is, we announced in the last six months a project called Envoy Gateway, which is layered on top of Envoy. And the goal of Envoy Gateway is to make it easier for people to run Envoy within Kubernetes. So essentially as an, as an ingress controller. And Envoy is a project historically, it is a very sophisticated piece of software, very complicated piece of software. It's not for everyone. And we want to provide Envoy Gateway as a way of onboarding more users into the Envoy ecosystem and making Envoy the, the default API gateway or edge proxy within Kubernetes. But in terms of use cases, we see Envoy pervasively with service mesh, API gateway, other types of low balancing cases. I mean, honestly, it's, it's all over the place at >>This point. I'm curious because you mentioned it's expanded beyond your wildest dreams. Yeah. And how could you have even imagined what Envoy was gonna do? Is there a use case or an application that really surprised you? >>You know, I've been asked that before and I, it's hard for me to answer that. It's, it's more that, I mean, for example, Envoy is used by basically every major internet company in China. I mean, like, wow. Everyone in China uses Envoy, like TikTok, like Alibaba. I mean like everyone, all >>The large sale, >>Everyone. You know, and it's used, it's used in the, I'm just, it's not just even the us. So I, I think the thing that has surprised me more than individual use cases is just the, the worldwide adoption. You know, that something could be be everywhere. And that I think, you know, when I open my phone and I'm opening all of these apps on my phone, 80 or 90% of them are going through Envoy in some form. Yeah. You know, it's, it's just that pervasive, I blow your mind a little bit sometimes >>That does, that's why you say plumber on your Twitter handle as your title. Cause you're working on all these things that are like really important substrate issues, Right. For scale, stability, growth. >>And, you know, to, I, I guess the only thing that I would add is, my goal for Envoy has always been that it is that boring, transparent piece of technology. Kind of similar to Linux. Linux is everywhere. Right? But no one really knows that they're using Linux. It's, it's justs like Intel inside, we're not paying attention. It's just there, there's >>A core group working on, if they have pride, they understand the mission, the importance of it, and they make their job is to make it invisible. >>Right. Exactly. >>And that's really ease of use. What's some of the ease of use sways and, and simplicity that you're working on, if you can talk about that. Because to be boring, you gotta be simpler and easier. All boring complex is unique is not boring. Complex is stressful. No, >>I I think we approach it in a couple different ways. One of them is that because we view Envoy as a, as a base technology in the ecosystem, we're starting to see, you know, not only vendors, but other open source projects that are being built on top of Envoy. So things like API Gateway, sorry, Envoy Gateway or you know, projects like Istio or all the other projects that are out there. They use Envoy as a component, but in some sense Envoy is a, as a transparent piece of that system. Yeah. So I'm a big believer in the ecosystem that we need to continue to make cloud native easier for, for end users. I still think it's too complicated. And so I think we're there, we're, we're pushing up the stack a bit. >>Yeah. And that brings up a good point. When you start seeing people building on top of things, right? That's enabling. So as you look at the enablement of Envoy, what are some of the things you see out on the horizon if you got the 20 mile stare out as you check these boring boxes, make it more plumbing, Right? Stable. You'll have a disruptive enabling platform. Yeah. What do you see out there? >>I am, you know, I, again, I'm not a big buzzword person, but, so some people call it serverless functions as a service, whatever. I'm a big believer in platforms in the sense that I really believe in the next 10 to 15 years, developers, they want to provide code. You know, they want to call APIs, they want to use pub subsystems, they want to use cas and databases. And honestly, they don't care about container scheduling or networking or load balancing or any of >>These things. It's handled in the os >>They just want it to be part of the operating system. Yeah, exactly. So I, I really believe that whether it's an open source or in cloud provider, you know, package solutions, that we're going to be just moving increasingly towards systems likes Lambda and Fargate and Google Cloud Run and Azure functions and all those kinds of things. And I think that when you do that much of the functionality that has historically powered this conference like Kubernetes and Onvoy, these become critical but transparent components that people don't, they're not really aware of >>At that point. Yeah. And I think that's a great call out because one of the things we're seeing is the market forces of, of this evolution, what you just said is what has to happen Yep. For digital transformation to, to get to its conclusion. Yep. Which means that everything doesn't have to serve the business, it is the business. Right. You know it in the old days. Yep. Engineers, they serve the business. Like what does that even mean? Yep. Now, right. Developers are the business, so they need that coding environment. So for your statement to happen, that simplicity in visibility calling is invisible os has to happen. So it brings up the question in open source, the trend is things always work itself out on the wash, as we say. So when you start having these debates and the alignment has to come at some point, you can't get to those that stay without some sort of defacto or consensus. Yep. And even standards, I'm not a big be around hardcore standards, but we can all agree and have consensus Sure. That will align behind, say Kubernetes, It's Kubernetes a standard. It's not like an i e you know, but this next, what, what's your reaction to this? Because this alignment has to come after debate. So all the process contending for I am the this of that. >>Yeah. I'm a look, I mean, I totally see the value in like i e e standards and, and there's a place for that. At the same time, for me personally as a technologist, as an engineer, I prefer to let the, the market as it were sort out what are the defacto standards. So for example, at least with Envoy, Envoy has an API that we call Xds. Xds is now used beyond Envoy. It's used by gc, it's used by proprietary systems. And I'm a big believer that actually Envoy in its form is probably gonna go away before Xds goes away. So in some ways Xds has become a defacto standard. It's not an i e e standard. Yeah. We, we, we have been asked about whether we should do that. Yeah. But I just, I I think the >>It becomes a component. >>It becomes a component. Yeah. And then I think people gravitate towards these things that become de facto standards. And I guess I would rather let the people on the show floor decide what are the standards than have, you know, 10 people sitting in a room figure out >>The community define standards versus organizational institutional defined standards. >>And they both have places a >>Hundred percent. Yeah, sure. And, and there's social proof in both of them. Yep. >>Frankly, >>And we were saying on the cube that we believe that the developers will decide the standard. Sure. Because that's what you're basically saying. They're deciding what they do with their code. Right. And over time, as people realize the trade of, hey, if everyone's coding this right. And makes my life easier to get to that state of nirvana and enlightenment, as we would say. Yeah. Yeah. >>Starting strong this morning. John, I I love this. I'm curious, you mentioned Backstage by Spotify wonderful example. Do you think that this is a trend we're gonna see with more end users >>Creating open source projects? Like I, you know, I hope so. The flip side of that, and as we all know, we're entering an uncertain economic time and it can be hard to justify the effort that it takes to do it well. And what I typically counsel people when they are about to open source something is don't do it unless you're ready to commit the resources. Because opensourcing something and not supporting it. Yeah. I actually can be think, I think it'd be worse. >>It's an, it's insult that people, you're asking to commit to something. Exactly. Needs of time, need the money investment, you gotta go all in and push. >>So I, so I very much want to see it and, and I want to encourage that here, but it's hard for me to look into the crystal ball and know, you know, whether it's gonna happen more >>Or less at what point there were, are there too many projects? You know, I mean, but I'm not, I mean this in, in a, in a negative way. I mean it more in the way of, you know, you mentioned supply chain. We were riffing on the cube about at some point there's gonna be so much code open source continuing thundering away with, with the value that you're just gluing things. Right. I don't need the code, this code there. Okay. What's in the code? Okay. Maybe automation can help out on supply chain. Yeah. But ultimately composability is the new >>Right? It is. Yeah. And, and I think that's always going to be the case. Case. Good thing. It is good thing. And I, I think that's just, that's just the way of things for sure. >>So no code will be, >>I think, I think we're seeing a lot of no code situations that are working great for people. And, and, but this is actually really no different than my, than my serverless arguing from before. Just as a, as a, a slight digression. I'm building something new right now and you know, we're using cloud native technologies and all this stuff and it's still, >>What are you building? >>Even as a I'm, I'm gonna keep that, I'm gonna keep that secret. I know I'm, but >>We'll find out on Twitter. We're gonna find out now that we know it. Okay. Keep on mystery. You open that door. We're going down see in a couple weeks. >>Front >>Page is still an angle. >>But I, I was just gonna say that, you know, and I consider myself, you know, you're building something, I'm, I see myself an expert in the cloud native space. It's still difficult, It's difficult to, to pull together these technologies and I think that we will continue to make it easier for people. >>What's the biggest difficulties? Can you give us some examples? >>Well, just, I mean, we still live in a big mess of yammel, right? Is a, there's a, there's a lot of yaml out there. And I think just wrangling all of that in these systems, there's still a lot of cobbling together where I think that there can be unified platforms that make it easier for us to focus on our application logic. >>Yeah. I gotta ask you a question cuz I've talked to college kids all the time. My son's a junior in CS and he's, you know, he's coding away. What would you, how does a student or someone who's learning figure out where, who they are? Because there's now, you know, you're either into the infrastructure under the hood Yeah. Or you're, cuz that's coding there option now coding the way your infrastructure people are working on say the boring stuff so everyone else can have ease of use. And then what is just, I wanna just code, there's two types of personas. How does someone know who they are? >>My, when I give people career advice, my biggest piece of advice to them is in the first five to seven to 10 years of their career, I encourage people to do different things like every say one to two to three years. And that doesn't mean like quitting companies and changing companies, it could mean, you know, within a company that they join doing different teams, you know, working on front end versus back end. Because honestly I think people don't know. I think it's actually very, Yeah. Our industry is so broad. Yeah. That I think it's almost impossible to >>Know. You gotta get your hands dirty to jump >>In order to know what you like. And for me, in my career, you know, I've dabbled in different areas, but I've always come back to infrastructure, you know, that that's what I enjoy >>The most. Okay. You gotta, you gotta taste everything. See what you, what >>You like. Exactly. >>Right. Last question for you, Matt. It's been three years since you were here. Yep. What do you hope that we're able to say next year? That we can't say this year? Hmm. Beyond the secrets of your project, which hopefully we will definitely be discussing then. >>You know, I I, I don't have anything in particular. I would just say that I would like to see more movement towards projects that are synthesizing and making it easier to use a lot of the existing projects that we have today. So for example, I'm, I'm very bullish on backstage. Like I, I've, I've always said that we need better developer UIs that are not CLIs. Like I know it's a general perception among many people. Totally agree with you. Frankly, you're not a real systems engineer unless you type on the command line. I, I think better user interfaces are better for humans. Yep. So just for a project like Backstage to be more integrated with the rest of the projects, whether that be Envo or Kubernete or Argo or Flagger. I, I just, I think there's tremendous potential for further integration of some >>Of these projects. It just composability That makes total sense. Yep. Yep. You're, you're op you're operating and composing. >>Yep. And there's no reason that user experience can't be better. And then more people can create and build. So I think it's awesome. Matt, thank you so much. Thank you. Yeah, this has been fantastic. Be sure and check out Matt on Twitter to find out what that next secret project is. John, thank you for joining me this morning. My name is Savannah Peterson and we'll be here all day live from the cube. We hope you'll be joining us throughout the evening until a happy hour today. Thanks for coming. Thanks for coming. Thanks for watching.

>>It's my pleasure to be one of the hosts of the cube on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years, the cube has been following the trail of data. And with the relentless March of data growth, this idea of a single version of the truth has become more and more elusive. Moreover data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is many sued as the CTO and co-founder of Reltio Maneesh. Welcome to the program. >>Thank you, Dave. It's a pleasure to be here. >>Okay. Let's start with, let's go back to you and your co-founders when you started Reltio it was back in the early days of the big data movement cloud was kind of just starting to take off, but what problems did you see then and what are enterprises struggling with today, especially with, with data as a source of digital innovation. >>They, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started Reltio in 2011, there were a few secular trends that were coming to life. One was a cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making, uh, compute capabilities available at scale to solve large data problems was becoming real impossible. The second thing that we saw was, uh, this big trend of, uh, you know, you can not have a wall to wall, one single application that solves your entire business problem. Those visions have come and gone. And, uh, we are seeing more of the best of breed application type of a landscape where even if you look within a specific function, let's say sales or marketing, you have more than a dozen applications that any company is using today. >>And that trend was starting to emerge where we knew very well, that the number of systems that we would have to work with would continue to increase. And, uh, that created a problem of where would you get the single source of truth or the single best version of a customer, a supplier, a product that you're trying to sell those types of critical pieces of information that are core to any business that's out there today. And, um, you know, that created the opportunity for us at Reltio to think about the problem at scale for every company out there, every business who needed this kind of a capability and for us to provide this capability in the cloud as a software, as a service, uh, uh, offering. So that's where, uh, you know, the foundation of Reltio started. And the core problem that we wanted to solve was to bridge the gap that was created by all these data silos and create a unified view of the core critical information that these companies run on. >>Yeah. I mean, the cloud is this giant, you know, hyper distributed system data by its very nature is distributed. It's interesting what you were sort of implying about, you know, the days of the monolithic app are gone by my business partner years ago, John furrier and the cube said data is going to become the new development kit. And we've certainly seen that with the, the pandemic, but tell us more about Reltio and how you help customers deal with that notion of data, silo, data silos, data fragmentation, how do you solve that problem? >>So, data fragmentation is what exists today. And, um, you know, with the Reltio, uh, software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented, siloed, uh, applications or data sources that they have within their enterprise at the same time. Um, there's a lot of dependence on the third party data. You know, when you think about, uh, different problems that you're trying to solve, you have, uh, for B2B type of information that in Bradstreet type of data providers in life sciences, you have IQ via type of data providers. Um, you know, as you look at other verticals, there is a specialized third-party data provider for any, and every kind of information that most of the enterprise businesses want to combine with their in-house data or first party data to get the best view of who they're dealing with, who are they working with, you know, who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. >>Um, and that's where Reltio fits in as the only platform that can help stitch together, this kind of, uh, information and create a 360 degree view that spans all the data silos and provides that for real-time use for BI and analytics to benefit from, for data science to benefit from. And then this emerging notion of, uh, data in itself is a, um, you know, key starting point that is used by us, uh, in order to make any decisions, just like, uh, we go, you know, if I, they wanted to look at information about you, I would go to places like LinkedIn, look up the information. And then our, my next set of decisions with that information, if somebody wanted to look up information on Reltio, they would go to, let's say Crunchbase as an example, and look up, uh, who are the investors? How much money have we raised all those details that are available? It's not a CRM system by itself, but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide, uh, as a part of the Reltio platform capabilities. >>Awesome. Thank you. And I want to get into the, to the tech, but before we do, maybe we just cut to the chase and maybe you can talk about some of the examples of, of Reltio and action. Some of the customers that you can talk about, maybe the industries that are, that are really adopting this. W what can you tell us there, Maneesh, >>Um, we work across a few different verticals, some of the key verticals that we work in our life sciences, um, and travel and hospitality and financial services, insurance, um, S uh, retail, as an example, those are some of the key verticals for us, but, uh, to give you some examples of, uh, the type of problems that customers are solving with Reltio as the data unification platform, um, let's take CarMax as an example, CarMax is a customer who's in the business of, uh, buying used cars, selling used cars, servicing those used cars. And then, um, you know, you as a customer, don't just transact with them. Once you, you know, you've had a car for three years, you go back and look at what can you trade in that car for, but in order for CarMax to provide a service to you that, uh, goes across all the different touch points, whether you are visiting them at their store location, uh, trying to test drive a car or viewing, uh, information about the various vehicles on their website, or just, uh, you know, punching in the registration number of your car, just to see what is the appraisal from them in terms of how much will they pay for your car? >>This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points and the type of information that they use, uh Reltio for aggregating, unifying, and then making available across all these touch points is all of the information about the customers, all of the information about, uh, the, uh, household, uh, you know, the understanding that they're trying to achieve because, uh, life events can, uh, be buying signals, uh, for, uh, consumers like uni, as well as, uh, who was the, um, associate who helped you either in the selling of a car buying of a car, because business is all about building relationships for the longer term lifetime value that they want to capture. And in that process, um, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy yourself, uh, there is a lot of information in order to price it, right, that needs to be gathered, uh, from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio, and then made available, uh, through API APIs or through other methods, and means to the various applications can be either built on top of that information, or can consume that information in order to better aid and assist the processes, business processes that those applications have to run end to end. Well, it sounds like >>That's come along. Sorry. >>I was just going to say it that's one example and, uh, you know, across other verticals that are other similar examples of how companies are leveraging, Reltio >>Just say, can come a long way from simple linear clickstream analysis of a website. I mean, you're talking about really rich information and, and, you know, happy to dig into some other examples, but, but I wonder how does it work? I mean, what's the magic behind it? What's the, the tech look like, I mean, obviously you leveraging AWS, maybe you could talk about how so, and maybe some of the services there and some of your unique IP. >>Yeah. Um, you know, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And, uh, you know, if you think about, uh, the problem itself, uh, the problem has been around as long as you have had more than one system to run your business, but the magnitude of the problem has expanded several fold. Um, you know, for example, I have been in this area was, uh, responsible for creating some of the previous generation capabilities and, uh, most of the friction in those previous generation MDM or master data management type of solutions, um, as the, you know, the technical term that is used to refer to this area, uh, was that those systems could not keep pace with the increasing number of sources or the depth and breadth of the information that, uh, customers want to capture, whether it is, uh, you know, about a patient or a product, or let's say a supplier that you're working well. >>Uh, there is always additional information that you can capture and, uh, you know, use to better inform the decisions for the next engagement and, uh, that kind of model where the number of sources we're always going to increase the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use at scale compute capabilities in the cloud, um, with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information, just locking it in a data warehouse has been sort of the problem in the past. And you talked about the clickstream analysis, uh, analytics has a place, but most of the analytics is a rear view mirror picture of the, uh, you know, work that you have to do, versus everybody that we talked to, uh, as a potential customer, wanted to solve the problem of what can we do at the point of engagement, how can we influence decisions? >>So, you know, I'll give you an example. I think, uh, everybody's familiar with Quicken loans, um, as the mortgage lender and, uh, in the mortgage lending business, uh, Quicken loans is the customer who's using Reltio as the customer data, um, unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time window, um, you know, anywhere from 10 minutes to about an hour, where if somebody expresses an interest in refinancing or getting a mortgage, they have to close that, uh, business within that, uh, Hart window, the conversion ratios are exponentially better in that hot window versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage, uh, at. And, uh, they've been able to use this notion of real time data, where as soon as you come in through the website, or if you come in through the rocket mortgage app, or you're talking to a broker by calling the one 800 number, they are able to triangulate that it's the same person coming from any of these different channels and respond to that person, whether an offer, uh, ASAP so that, uh, there is no opportunity for the competition to get in and present you with a better offer. >>So those are the types of things where the time to, uh, conversion or the time to action is being looked at. And everybody's trying to shrink that time down, uh, that ability to respond in real time with the capabilities was sort of the last mile missing out of this equation, which didn't exist with previous generation capabilities. And now customers are able to benefit from that. >>That is an awesome example. I know at firsthand, I'm a customer of Quicken and rocket, and when you experience that environment, it's totally different than anything you've ever seen before. So it's helpful to hear you explain, like what's behind that because it's, it's truly disruptive. And I, and I'll tell you, the other thing that, that sort of triggered a thought was that we use the word realtime a lot, and we try to develop years ago. We said, what does real-time really mean? And the, the answer we CA we landed on was before you lose the customer, and that's kind of what you just described. Uh, and that is what gives as an example, a quick and a real advantage again, having experienced it firsthand. It's, it's pretty, pretty tremendous. So that's a nice, that's a, that's a nice reference. Um, so, and the other thing that struck me is that what I wanted to ask you, how it's different from sort of legacy master data management solutions, and you sort of described that they've seized to me, they got to take their, their traditional on-prem stack, rip it out, stick it in the cloud is okay, we got our stack in the cloud. >>Now your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a, from an CTO's perspective, what's your, >>Yeah. The clean sheet of paper is the luxury that we have, you know, having seen this movie before having, um, you know, looked at solving this problem with previous generation technologies, it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, um, you know, across all of our customers, we are today managing, um, uh, about 6.5 billion consolidated profiles of people, organizations, product locations, um, you know, assets, uh, those kinds of details. And these are, these are the types of, uh, crown jewels of the business that every business runs on. You know, for example, if you wanted to, um, let's say you're a large company, like, uh, you know, Ford and you wanted to figure out how much business are you doing, where the, uh, you know, another large company, because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. >>It's been a very difficult answer to understand what is the total book of business that they have with that other, um, big, uh, customer and, uh, you know, being able to have the right, uh, unified, uh, relevant, rich clean as the starting point that gives you visibility to that data, and then allows you to run precise analytics on top of that data, or, uh, you know, drive, uh, any kind of, uh, conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run. Um, you have to have that foundation of clean data to work with in order to get to those answers. >>Nice. Uh, and then I had questions on just the model is this, it's a SAS model. I presume, how, how is it priced? Do you have a, do you have a freemium? How do I get started? Maybe you could give us some color. >>Yeah, we are a SAS provider. We do everything in the cloud, uh, offer it as a SAS offering, um, for customers to leverage and benefit from our pricing is based on the volume of, uh, uh, consolidated profiles. And the, I use the word profiles because this is not the traditional, uh, data model where you have rows columns, foreign keys. This is a, you know, a profile of a customer, regardless of attribution or any other details that you want to capture. And, um, you know, that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Uh, customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles, uh, you know, off these different types of data domains, customer, patient provider, uh, product, uh, asset, those types of details. But, uh, then they grow and some of the customers, uh, HP Inc, as a customer is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use the single source of truth capabilities provided by Reltio. >>And your relationship with AWS you're, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. >>Yeah. AWS has been a key partner for us, uh, since the very beginning, uh, we are now on the marketplace. Uh, customers can start with the free version of the product, um, and start to play with the product, understand it better, uh, and then move into the paid tier, um, you know, as they bring in more data, uh, into Reltio. And, uh, you know, we also, uh, have, uh, the partnership with AWS where, uh, you know, customers can benefit from the relationship where they are able to, um, uh, use the, the spend against Reltio to offset the commitment credits that they have for AWS, um, you know, as a cloud provider. So, uh, you know, we are working closely with AWS on key verticals, like life sciences, travel and hospitality as a starting point. >>Nice that love, love, those credits, um, company update, uh, you know, head count funding, revenue trajectory, what kind of metrics are you comfortable sharing? >>So, uh, we are currently, uh, at about, um, you know, slightly North of 300 people, uh, overall at rail queue, we will, uh, grow from 300 to about 400 people this year, uh, itself. Uh, we are, uh, uh, you know, we just put out a press release, uh, where we mentioned some of the subscription ARR we finished last year at about $74 million in ARR. And we are, uh, looking at, uh, crossing the a hundred million dollar ARR, um, uh, threshold, uh, later this year. So we're on a great growth trajectory and, uh, the businesses, uh, performing really well. And we are, uh, looking at working with more customers and helping them solve this, uh, uh, you know, data silo, fragmentation of data problem by having them leverage the Reltio capability at scale across their enterprise. >>That's some impressive growth. Congratulations, w w we're, I'm sure adding a hundred people you're hiring all over the place, but where we get some of your priorities. >>So, um, you know, the, as the business is growing, we are spending equally both on the R and D side of the house, uh, investing more there, but at the same time, also on our go to market, uh, so that we can extend our reach, make sure that, uh, more people know about, uh, Reltio and can start leveraging the benefit of, uh, the technology that we have built on top of, uh, AWS. >>Yeah. I mean, it sounds like you've obviously nailed product market fit, and now you're, you know, scaling and scaling the go to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. Why, why, what was prompted that move >>Problems of luxury, uh, you know, as I like to call them, uh, once you know, that you're on a great growth trajectory and, uh, the business is performing well, it's all about, uh, figuring out ways of, uh, you know, making sure that you can drive harder and faster towards that growth, uh, milestones, uh, that you want to achieve. And, uh, you know, for us, uh, the story is no different. Uh, the team has done a wonderful job of, uh, making sure that we can build the right platform, um, you know, work towards this opportunity, that PC, which by the way, um, they just to share with you, uh, MDM or master data management has always been underestimated as a, uh, you know, yes, there is a problem that needs to be solved, but the market sizing was, uh, in a, not as clear, but some of the most recent, uh, estimates from analysts like Gartner, but the, uh, you know, sort of the new incarnation of, uh, data unification and master data management at about a $30 billion, uh, you know, uh, Tam or this market. >>So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wide array of customers. And with that, uh, I looked at, uh, you know, how could we scale the business faster and have the right team to work, uh, help us maximize the opportunity. And that's why, uh, you know, we decided, uh, that it was the right point in time for me to bring in somebody who's, uh, worked, uh, at, uh, the stretch of, you know, taking a company from just a a hundred million dollars in ARR to, uh, you know, half a billion dollars in ARR and doing it at a global scale. So Chris Highland, uh, you know, has had that experience and having him take on the CEO role, uh, really puts us on a tremendous, uh, our path to tremendous growth and achieving that, uh, with the right team. >>Yeah. And I think I appreciate your comments on the Tam. I love to look at the Tam and to do a lot of Tam analysis. And I think a lot of times when you define the future Tam based on sort of historical categories, you sometimes under count them. I mean, to me, you guys are in the, the, the digital business business. I mean, the data transformation, the company transformation business, I mean, that could be order of magnitude even bigger. So I think the future is bright for your company. Reltio Maneesh. And thank you so much for coming on the program really appreciate. >>Well, thanks for having me, uh, really enjoyed it. Thank you. >>Okay. Thank you for watching. You're watching the cubes startup showcase. We'll be right back.

(upbeat music) >> It's my pleasure, to be one of the hosts of theCUBE on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years theCUBE has been following the trail of data. And with the relentless match of data growth this idea of a single version of the truth has become more and more elusive. Moreover, data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand, the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is Manish Sood the CTO and co-founder of Reltio. Manish, welcome to the program. >> Thank you, Dave. It's a pleasure to be here. >> Okay, let's start with, let's go back to you and your co-founders when you started Reltio it was back in the early days of the big data movement, cloud was kind of just starting to take off, but what problems did you see then and what are enterprises struggling with today, especially with data as a source of digital innovation. >> Dave, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started Reltio in 2011 there were a few secular trends that were coming to life. One was a cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making compute capabilities available at scale to solve large data problems was becoming real and possible. The second thing that we saw was this big trend of you know, you can not have a wall to wall, one single application that solves your entire business problem. Those visions have come and gone and we are seeing more of the best of breed application type of a landscape where even if you look within a specific function let's say sales or marketing, you have more than a dozen applications that any company is using today. And that trend was starting to emerge where we knew very well that the number of systems that we would have to work with would continue to increase. And that created a problem of where would you get the single source of truth or the single best origin of a customer, a supplier, a product that you're trying to sell, those types of critical pieces of information that are core to any business that's out there today. And, you know, that created the opportunity for us at Reltio to think about the problem at scale for every company out there, every business who needed this kind of capability and for us to provide this capability in the cloud as a software, as a service offering. So that's where, you know, the foundation of Reltio started. And the core problem that we wanted to solve was to bridge the gap that was created by all these data silos, and create a unified view of the core critical information that these companies run on. >> Yeah, the cloud is this giant, you know hyper distributed system, data by its very nature is distributed. It's interesting what you were sort of implying about you know, the days of the monolithic app are gone, but my business partner years ago John Furrier at theCUBE said, data is going to become the new development kit. And we've certainly seen that with the pandemic but tell us more about Reltio and how you help customers deal with that notion of data silos, data fragmentation, how do you solve that problem? >> So data fragmentation is what exists today. And, with the Reltio software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented siloed applications or data sources that they have within their enterprise. At the same time, there's a lot of dependence on the third party data. You know, when you think about different problems that you're trying to solve, you have for B2B type of information that in Bradstreet type of data providers, in life sciences you have IQVIA type of data providers. You know, as you look at other verticals that is a specialized third party data provider for any and every kind of information that most of the enterprise businesses want to combine with their in-house data or first party data to get the best view of who they're dealing with, who are they working with, you know who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. And that's where Reltio fits in as the only platform that can help stitch together this kind of information and create a 360 degree view that spans all the data silos and provides that for real-time use, for BI and analytics to benefit from, for data science to benefit from, and then this emerging notion of data in itself is a, you know, key starting point that is used by us in order to make any decisions. Just like we go, you know, if I they wanted to look at information about you, I would go to places like LinkedIn, look up the information, and then on my next set of decisions with that information. If somebody wanted to look up information on Reltio they would go to, let's say crunchbase as an example and look up, who are the investors? How much money have we raised? All those details that are available. It's not a CRM system by itself but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide as a part of the Reltio platform capabilities. >> Awesome, thank you. And I want to get into the tech, but before we do maybe we just cut to the chase and maybe you can talk about some of the examples of Reltio and action, some of the customers that you can talk about, maybe the industries that are really adopting this. What can you tell us there Manish? >> We work across a few different verticals some of the key verticals that we work in are life sciences and travel and hospitality and financial services, insurance retail, as an example. Those are some of the key verticals for us. But to give you some examples of the type of problems that customers are solving with Reltio as the data unification platform, let's take CarMax as an example,. CarMax is a customer who's in the business of buying used cars, selling used cars servicing those used cars. And then, you know, you as a customer don't just transact with them once, you know, you've had a car for three years you go back and look at what can you trade in that car for? But in order for CarMax to provide a service to you that goes across all the different touch points whether you are visiting them at their store location trying to test drive a car or viewing information about the various vehicles on their website, or just you know, punching in the registration number of your car just to see what is the appraisal from them in terms of how much will they pay for your car. This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points. And the type of information that they use relative for aggregating, unifying, and then making available across all these touch points, is all of the information about the customers, all of the information about the household, you know, the understanding that they are trying to achieve because life events can be buying signals for consumers like you and I, as well as who was the associate who helped you either in the selling of a car, buying of a car, because their business is all about building relationships for the longer term, lifetime value that they want to capture. And in that process, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy yourself, there is a lot of information in order to price it right, that needs to be gathered from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio and then made available through APIs or through other methods and means to the various applications, can be either built on top of that information, or can consume that information in order to better aid and assist the processes, business processes that those applications have to run and to end. >> Well, sounds like we come along, (indistinct). >> I was just going to say that's one example and, you know across other verticals, that are other similar examples of how companies are leveraging, Reltio >> Yeah, so as you say, we've come a long way from simple linear clickstream analysis of a website. I mean, you're talking about really rich information and you know happy to dig into some other examples, but I wonder how does it work? I mean, what's the magic behind it? What's the tech look like? I mean, obviously leveraging AWS, maybe you could talk about how, so, and maybe some of the services there and some of your unique IP. >> Yeah, you know, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And, you know, if you think about the problem itself, the problem has been around as long as you have had more than one system to run your business, but the magnitude of the problem has expanded several fold. You know, for example, I have been in this area was responsible for creating some of the previous generation capabilities and most of the friction in those previous generation MDM or master data management type of solutions as the you know, the technical term that is used to refer to this area, was that those systems could not keep pace with the increasing number of sources or the depth and breadth of the information that customers want to capture, whether it is, you know, about a patient or a product or let's say a supplier that you're working with, there is always additional information that you can capture and you know use to better inform the decisions for the next engagement. And that kind of model where the number of sources we're always going to increase the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use add scale compute capabilities in the cloud, with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information just locking it in a data warehouse has been sort of the problem in the past, and you talked about the clickstream analysis. Analytics has a place, but most of the analytics is a real view mirror picture of the, you know, work that you have to do versus everybody that we talk to as a potential customer wanted to solve the problem of what can we do at the point of engagement? How can we influence decisions? So, you know, I'll give you an example. I think everybody's familiar with Quicken loans as the mortgage lender, and in the mortgage lending business, Quicken loans is the customer who's using Reltio as the customer data unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time vendor, you know anywhere from 10 minutes to about an hour where if somebody expresses an interest in refinancing or getting a mortgage they have to close that business within that hot vendor. The conversion ratios are exponentially better in that hot vendor versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage at? And they've been able to use this notion of real time data where as soon as you come in through the website or if you come in through the rocket mortgage app or you're talking to a broker by calling the 1800 number they are able to triangulate that it's the same person coming from any of these different channels and respond to that person with an offer ASAP so that there is no opportunity for the competition to get in and present you with a better offer. So those are the types of things where the time to conversion or the time to action is being looked at, and everybody's trying to shrink that time down. That ability to respond in real time with the capabilities were sort of the last mile missing out of this equation, which didn't exist with previous generation capabilities, and now customers are able to benefit from that. >> That is an awesome example. I know at firsthand, I'm a customer of Quicken and rocket when you experience that environment, it's totally different, than anything you've ever seen before. So it's helpful to hear you explain like what's behind that because, it's truly disruptive and I'll tell you the other thing that sort of triggered a thought was that we use the word realtime a lot and we try to develop years ago. We said, what does real-time really mean? And the answer we landed on was, before you lose the customer, and that's kind of what you just described. And that is what gives as an example a quick and a real advantage again, having experienced it firsthand. It's pretty, pretty tremendous. So that's a nice reference. So, and the other thing that struck me is, I wanted to ask you how it's different from sort of legacy Master Data Management solutions and you sort of described that they've since to me they've got to take their traditional on-prime stack, rip it out, stick it in the iCloud, it's okay we got our stack in the cloud now. Your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a CTO's perspective, what's your take? >> Yeah, the clean sheet of paper is the luxury that we have. You know, having seen this movie before having, you know looked at solving this problem with previous generation technologies, it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, you know, across all of our customers, we are today managing about 6.5 billion consolidated profiles of people, organizations, product, locations, you know, assets, those kinds of details. And these are the types of crown jewels of the business that every business runs on. You know, for example, if you wanted to let's say you're a large company, like, you know, Ford and you wanted to figure out how much business are you doing, whether, you know another large company, because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. It's been a very difficult to answer to understand what is the total book of business that they have with that other big customer. And, you know, being able to have the right, unified, relevant, ready clean information as the starting point that gives you visibility to that data, and then allows you to run precise analytics on top of that data, or, you know drive any kind of conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run. You have to have that foundation of clean data to work with in order to get to those answers. >> Nice, and then I had questions on just analysis, it's a SAS model I presume, how is it priced? Do you have a freemium? How do I get started? Maybe you could give us some color on that. >> Yeah, we are a SAS provider. We do everything in the cloud, offer it as a SAS offering for customers to leverage and benefit from. Our pricing is based on the volume of consolidated profiles, and I use the word profiles because this is not the traditional data model, where you have rows, columns, foreign keys. This is a profile of a customer, regardless of attribution or any other details that you want to capture. And you know, that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles, you know, off these different types of data domains, customer, patient, provider, product, asset, those types of details, but then they grow and some of the customers HPInc, as a customer, is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use, the single source of truth capabilities provided by Reltio. >> And, and your relationship with AWS, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. >> Yeah, AWS has been a key partner for us since the very beginning. We are now on the marketplace. Customers can start with the free version of the product and start to play with the product, understand it better and then move into the paid tier, you know as they bring in more data into Reltio and, you know be also have the partnership with AWS where, you know customers can benefit from the relationship where they are able to use the spend against Reltio to offset the commitment credits that they have for AWS, you know, as a cloud provider. So, you know, we are working closely with AWS on key verticals, like life sciences, travel and hospitality as a starting point. >> Nice, love those credits. Company update, you know, head count, funding, revenue trajectory what kind of metrics are you comfortable sharing? >> So we are currently at about, you know, slightly not at 300 people overall at Reltio. We will grow from 300 to about 400 people this year itself we are, you know, we just put out a press release where we mentioned some of the subscription ARR we finished last year at about $74 million in ARR. And we are looking at crossing the hundred million dollar ARR threshold later this year. So we are on a great growth trajectory and the business is performing really well. And we are looking at working with more customers and helping them solve this, you know, data silo, fragmentation of data problem by having them leverage the Reltio capability at scale across their enterprise. >> That's some impressive growth, congratulations. We're, I'm sure adding hundred people you're hiring all over the place, but where we are some of your priorities? >> So, you know, the, as the business is growing we are spending equally, both on the R and D side of the house investing more there, but at the same time also on our go to market so that we can extend our reach, make sure that more people know about Reltio and can start leveraging the benefit of the technology that we have built on top of AWS. >> Yeah, I mean it sounds like you've obviously nailed product market fit and now you're, you know, scaling the grip, go to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. Why, what was prompted that move? >> Problems of luxury, you know, as I like to call them once you know that you're in a great growth trajectory, and the business is performing well, it's all about figuring out ways of, you know making sure that you can drive harder and faster towards that growth milestones that you want to achieve. And, you know, for us, the story is no different. The team has done a wonderful job of making sure that we can build the right platform, you know work towards this opportunity that we see, which by the way they've just to share with you, MDM or Master Data Management has always been underestimated as a, you know, yes there is a problem that needs to be solved but the market sizing was in a, not as clear but some of the most recent estimates from analysts like Gartner, but the, you know, sort of the new incarnation of data unification and Master Data Management at about a $30 billion, yeah, TAM for this market. So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wide array of customers. And with that, I looked at, you know how could we scale the business faster and have the right team to work help us maximize the opportunity. And that's why, you know, we decided that it was the right point in time for me to bring in somebody who's worked at the stretch of, you know taking a company from just a hundred million dollars in ARR to, you know, half a billion dollars in ARR and doing it at a global scale. So Chris Highland, you know, has had that experience and having him take on the CEO role really puts us on a tremendous path or path to tremendous growth and achieving that with the right team. >> Yeah, and I think I appreciate your comments on the TAM. I love to look at the TAM and to do a lot of TAM analysis. And I think a lot of times when you define the the future TAM based on sort of historical categories, you sometimes under count them. I mean, to me you guys are in the digital business. I mean, the data transformation the company transformation business, I mean that could be order of magnitude even bigger. So I think the future is bright for your company Reltio, Manish and thank you so much for coming on the program. Really appreciate it. >> Well, thanks for having me, really enjoyed it. Thank you. >> Okay, thank you for watching. You're watching theCUBEs Startup Showcase. We'll be right back. (upbeat music)

>>Ash it's, you know, what will that mean to my investment? And the announcement fusion IO is that, you know, we're 25 times faster on read intensive HBase applications. The combination. So as organizations are deploying Hadoop, and they're looking at technology changes coming down the pike, they can rest assured that they'll be able to take advantage of those in a much more aggressive fashion with map R than, than other distribution. >>Jack, how I got to ask you, we were talking last night at the Hadoop summit, kind of the kickoff party and, you know, everyone was there. All the top execs were there and all the developers, you know, we were in the queue. I think, I think that either Dave or myself coined the term, the big three of big data, you guys ROMs cloud Cloudera map R and Hortonworks, really at the, at the beginning of the key players early on and Charles from Cloudera was just recently on. And, and he's like, oh no, this, this enterprise grade stuff has been kicked around. It's been there from the beginning. You guys have been there from the beginning and Matt BARR has never, ever waffled on your, on your messaging. You've always been very clear. Hey, we're going to take a dupe open source a dupe and turn it into an enterprise grade product. Right. So that's clear, right? That's, that's, that's a great, that's a great, so what's your take on this because now enterprise grade is kind of there, I guess, the buzz around getting the, like the folks that have crossed the chasm implemented. So what can you comment on that about one enterprise grade, the reality of it, certainly from your perspective, you haven't been any but others. And then those folks that are now rolling it out for the first time, what can you share with them around? What does it mean to be enterprise grade? >>So enterprise grade is more about the customer experience than, than a marketing claim. And, you know, by enterprise grade, what we're talking about are some of the capabilities and features that they've grown to expect in their, their other enterprise applications. So, you know, the ability to meet full S SLA is full ha recovery from multiple failures, rolling upgrades, data protection was consistent snapshots business continuity with mirroring the ability to share a cluster across multiple groups and have, you know, volumes. I mean, there's a, there's a host of features that fall under the umbrella enterprise grade. And when you move from no support for any of those features to support to a few of them, I don't think that's going to, to ha it's more like moving to low availability. And, and there's just a lot of differences in terms of when we say enterprise grade with those features mean versus w what we view as kind of an incomplete story. So >>What do you, what do you mean by low availability? Well, I mean, it's tongue in cheek. It's nice. It's a good term. It's really saying, you know, just available when you sometimes is that what you mean? Is this not true availability? I mean, availability is 99.9%. Right? >>Right. So if you've got a, an ha solution that can't recover from multiple failures, that's downtime. If you've got an HBase application that's running online and you have data that goes down and it takes 10 to 30 minutes to have the region servers recover it from another place in the distribution, that's downtime. If you have snapshots that aren't consistent across the cluster, that doesn't provide data protection, there's no point in time recovery for, for a cluster. So, you know, there's a lot of details underneath that, but what it, what it amounts to is, do you have interruptions? Do you have downtime? Do you have the potential for losing data? And our answer is you need a series of features that are hardened and proven to deliver that. >>What about recoverability? You mentioned that you guys have done a lot of work in that area with snapshotting, that's kind of being kicked around, are our folks addressing, what are the comp what's your competition doing in those areas of recoverability just mentioned availability. Okay, got that. Recoverability security, compliance, and usability. Those are the areas that seem to be the hot focus areas what's going on in the energy. How would you give them the grade, the letter grade, if you will, candidly, compared to what you guys offer? Well, the, >>The first of all, it's take recoverability. You know, one of the tenants is you have a point in time recovery, the ability to restore to a previous point that's consistent across the cluster. And right now there's, there's no point in time recovery for, for HDFS, for the files. And there's no point in time recovery for HBase tables. So there's snapshot support. It's being talked about in the open source community with respect to snapshots, but it's being referred to in the JIRAs as fuzzy snapshots and really compared to copy table. >>So, Jack, I want to turn the conversation to the, kind of the topic we've talked about before kind of the open versus a proprietary that, that whole debate we've, we've, we've heard about that. We talked about that before here on the cube. So just kind of reiterate for us your take. I mean, we, we hear perhaps because of the show we're at, there's a lot of talk about the open source nature of Hadoop and some of the purists, as you might call them are saying, it's gotta be open a hundred percent Patrick compatible, et cetera. And then there's others that are taking a different approach, explain your approach and why you think that's the key way to make, to really spur adoption of a dupe and make it >>W w we're we're a part of the community we're, we've got, you know, commitment going on. We've, you know, pioneered and pushed a patchy drill, but we have done innovations as well. And I think that those innovations are really required to support and extend the, the whole ecosystem. So canonical distributes RN, three D distribution. We've got, you know, all our, our packages are, are available on get hub and, and open source. So it's not, it's not a binary debate. And I think the, the point being that there's companies that have jumped ahead and now that Peloton is, is, you know, pedaling faster and, and we'll, we'll catch up. We'll streamline. I think the difference is we rearchitected. So we're basically in a race car and, you know, are, are racing ahead with, with enterprise grade features that are required. And there's a lot of work that still needs to be done, needs to be accomplished before that full rearchitecture is, is in place. >>Well, I mean, I think for me, the proof is really in the pudding when you, when it comes to talk about customers that are doing real things and real production, grade mission, critical applications that they're running. And to me that shows the successor or relative success of a given approach. So I know you guys are working with companies like ancestry.com, live nation and Quicken loans. Maybe you could, could you walk us through a couple of those scenarios? Let's take ancestry.com. Obviously they've got a huge amount of data based on the kind of geological information, where do you guys do >>With them? Yeah, so they've got, I mean, they've got the world's largest family genealogy services available on the web. So there's a massive amount of data that they make accessible and, and, you know, ability for, for analysis. And then they've rolled out new features and new applications. One of which is to ship a kit out, have people spit in a tube, returned back and they do DNA matching and reveal additional details. So really some really fabulous leading edge things that are being done with, with the use of, of Hadoop. >>Interesting. So talk about when you went to, to work with them, what were some of their key requirements? Was it around, it was more around the enterprise enterprise, grade security and uptime kind of equation, or was it more around some of the analytics? What, what, what's the kind of the killer use case for them? >>It's kind of, you know, it's, it's hard with a specific company or even, you know, to generalize across companies. Cause they're really three main areas in terms of ease of use and administration dependability, which includes the full ha and then, and then performance. And in some cases, it's, it's just one of those that kind of drives it. And it's used to justify, in other cases, it's kind of a collection. The ease of use is being able to use a cluster, not only as Hadoop, but to access it and treat it like enterprise storage. So it's a complete POSIX compliance file system underneath that allows the, the mounting and access and updates and using it in dynamic read-write. So what that means from an application level, it's, it's faster, it's much easier to administer and it's much easier and reliable for developers to, to utilize. >>I got to ask you about the marketing question cause I see, you know, map our, you guys have done a good job of marketing. Certainly we want to be thankful to you guys is supporting the cube in the past and you guys have been great supporters of our mission, but now the ecosystem's evolving a lot more competition. Claudia mentioned those eight companies they're tracking in quote Hadoop, and certainly Jeff and I, and, and SiliconANGLE by look at there's a lot more because Hadoop washing has been going on now for the term Hadoop watching me and jumping in and doing Hadoop, slapping that onto an existing solution. It's not been happening full, full, full bore for a year. At least what's the next for you guys to break above the noise? Obviously the communities are very active projects are coming online. You guys have your mission in the enterprise. What's the strategy for you guys going forward is more of the same and anything new even share. >>Yeah, I, I, I think as far as breaking above the noise, it will be our customers, their success and their use cases that really put the spotlight on what the differences are in terms of, of, you know, using a big data platform. And I think what, what companies will start to realize is I'd rather analogy between supply chain and the big, the big revolution in supply chain was focusing on inventory at each stage in the supply chain. And how do you reduce that inventory level and how do you speed the, the flow of goods and the agility of a company for competitive advantage. And I think we're going to view data the same way. So companies instead of raw data that they're copying and moving across different silos, if they're able to process data in place and send small results sets, they're going to be faster, more agile and more competitive. >>And that puts the spotlight on what data platform is out there that can support a broad set of applications and it can have the broadest set of functionality. So, you know, what we're delivering is a mission grade, you know, enterprise grade mission, critical support platform that supports MapReduce and does that high performance provides NFS POSIX access. So you can use it like a file system integrates, you know, enterprise grade, no SQL applications. So now you can do, you know, high-speed consistent performance, real time operations in addition to batch streaming, integrated search, et cetera. So it's, it's really exciting to provide that platform and have organizations transform what they're doing. >>How's the feedback on with Ted Dunning? I haven't seen a lot of buzz on the Twittersphere is getting positive feedback here. He's a, a tech athlete. He's a guru, he's an expert. He's got his hands in all the pies. He's a scientist type. What's he up to? What's his, what's his role within Mapa and he's obviously playing in the open-source community. What's he up to these days, >>Chief application architect, he's on the leading edge of my house. So machine learning, so, you know, sharing insights there, he was speaking at the storm meetup two nights ago and sharing how you can integrate long running batch, predictive analytics with real-time streaming and how the use of snapshots really that, that easy and possible. He travels the world and is helping organizations understand how they can take some very complex, long running processes and really simplify and shorten those >>Chance to meet him in New York city had last had duke world at a, at a, a party and great guy, fantastic geek, and certainly is doing a great work and shout out to Ted. Congratulations, continue up that support. How's everyone else doing? How's John and Treevis doing how's the team at map are we're pedaling as best as you can growing >>Really quickly. No, we're just shifting gears. Would it be on pedaling >>Engine? >>Yeah. Give us an update on the company in terms of how the growth and kind of where you guys are moving that. >>Yeah. We're, we're expanding worldwide, you know, just this, you know, last few months we've opened up offices and in London and Munich and Paris, we're expanding in Asia, Japan and Korea. So w our, our sales and services and engineering, and basically across the whole company continues to expand rapidly. Some really great, interesting partnerships and, and a lot of growth Natalie's we add customers, but it's, it's nice to see customers that continue to really grow their use of map are within their organization, both in terms of amount of data that they're analyzing and the number of applications that they're bringing to bear on the platform. >>Well, that a little bit, because I think, you know, one of the, one of the trends we do see is when a company brings in big data, big data platform, and they might start experiment experimenting with it, build an application. And then maybe in the, maybe in the marketing department, then the sales guys see it and they say, well, maybe we can do something with that. How is that typically the kind of the experience you're seeing and how do you support companies that want to start expanding beyond those initial use cases to support other departments, potentially even other physical locations around the world? How do you, how do you kind of, >>That's been the beauty of that is if you have a platform that can support those new applications. So if you know, mission critical workloads are not an issue, if you support volumes so that you can logically separate makes it much easier, which we have. So one of our customers Zions bank, they brought in Matt BARR to do fraud detection. And pretty soon the fact that they were able to collect all of that data, they had other departments coming to them and saying, Hey, we'd like to use that to do analysis on because we're not getting that data from our existing system. >>Yeah. They come in and you're sitting on a goldmine, there are use cases. And you also mentioned kind of, as you're expanding internationally, what's your take on the international market for big data to do specifically is, is the U S kind of a leaps and bounds ahead of the rest of the world in terms of adoption of the technology. What are you seeing out there in terms of where, where the rest of the, >>I wouldn't say leaps and bounds, and I think internationally, they're able to maybe skip some of the experimental steps. So we're seeing, we're seeing deployment of class financial services and telecom, and it's, it's fairly broad recruit technologies there. The largest provider of recruiting services, indeed.com is one of their subsidiaries they're doing a lot with, with Hadoop and map are specifically, so it's, it's, it's been, it's been expanding rapidly. Fantastic. >>I also, you know, when you think about Europe, what's going on with Google and some of the, the privacy concerns even here, or I should say, is there, are there different regulatory environments you've got to navigate when you're talking about data and how you use data when you're starting to expand to other, other locales? >>Yeah. There's typically by vertical, there's different, different requirements, HIPAA and healthcare, and basal to, and financial services. And so all of those, and it, it, it basically, it's the same theme of when you're bringing Hadoop into an organization and into a data center, the same sorts of concerns and requirements and privacy that you're applying in other areas will be applied on Hindu. >>I'm now kind of turning back to the technology. You mentioned Apache drill. I'd love to get an update on kind of where, where that stands. You know, it's put, then put that into context for people. We hear a lot about the SQL and Hadoop question here, where does drill fit into that, into that equation? >>Well, the, the, you know, there's a lot of different approaches to provide SQL access. A lot of that is driven by how do you, how do you leverage some of the talent and organization that, you know, speak SQL? So there's developments with respect to hive, you know, there's other projects out there. Apache drill is an open source project, getting a lot of community involvement. And the design center there is pretty interesting. It started from the beginning as an open source project. And two main differences. One was in looking at supporting SQL it's, let's do full ANSI SQL. So it's full 2003 ANSI, sequel, not a SQL like, and that'll support the greatest number of applications and, you know, avoid a lot of support and, and issues. And the second design center is let's support a broad set of data sources. So nested sources like Jason scheme on discovery, and basically fitting it into an enterprise environment, which sometimes is kinda messy and can get messy as acquisitions happen, et cetera. So it's complimentary, it's about, you know, enabling interactive, low latency queries. >>Jack, I want to give you the final word. We are out of time. Thanks for coming on the cube. Really preached. Great to see you again, keep alumni, but final word. And we'll end the segment here on the cube is your quick thoughts on what's happening here at Hadoop world. What is this show about? Share with the audience? What's the vibe, the summary quick soundbite on Hadoop. >>I think I'll go back to how we started. It's not, if you used to do putz, how you use to do and, you know, look at not only the first application, but what it's going to look like in multiple applications and pay attention to what enterprise grade means. >>Okay. They were secure. We got a more coverage coming, Jack Norris with map R I'll say one of the big three original, big three, still on the, on the list in our mind, and the market's mind with a unique approach to Hadoop and the mid-June great. This is the cube I'm Jennifer with Jeff Kelly. We'll be right back after this short break, >>Let's settle the PR program out there and fighting gap tech news right there. Plenty of the attack was that providing a new gadget. Let's talk about the latest game name, but just the.