 Live from Las Vegas, Nevada, it's theCUBE. Covered, AWS re-invent 2016. Brought to you by AWS and its ecosystem partners. Now, here are your hosts, John Furrier. Okay, welcome back everyone. We're here live in Las Vegas for day three of Waltz, Waltz Cover, Silicon Angles theCUBE, our flagship program where we go out to the events and extract all the signal from the noise. I'm John Furrier. My co-host, Stu Miniman, our next guest is entrepreneur and founder and CEO of cask.co. Technical entrepreneur, now CEO, formerly Facebook, HBase guru, just all around, great guy, great entrepreneur. VC backed, cask.co. Welcome to theCUBE. Good to see you again. So I wanted to get you on theCUBE because I wanted to chat, because you get an interesting perspective. You've been on Gen 1 of web scale with Facebook. You've seen a lot of action in open source with Hadoop, HBase, Real Time, all the projects. You're also funded, venture-backed with Ignition. And who else is in there? Battery, Andreessen. Andreessen, a big name, entrepreneurs. You're also developing some really cool technology in the stack to scale up. You also have worked with all the cloud vendors, including AWS. First question. What's going on with all these clouds? Who's got what? Who's the better cloud? Where's the technology going and how is a startup? Are you navigating this landscape as you play out your funded plan? All that and where do you think it's going? Yeah, I mean, I don't even know where to begin with that. I mean, I- Well, first of all, cask. Before we get to that big question, that's what I want to get from you, but take a minute to talk about what you guys are doing at cask.co. Absolutely. So we're a big data company, open source big data company, really focused around big data applications. So not just how do you do ingest or ETL or SQL queries and just BI on lots of data, but how do you actually drive a recommendation engine? Not just understanding what your customers are doing, but what Amazon on their commercial side does, right? I mean, they kind of invented big data in a certain way from the whole collaborative filtering, machine learning angle. And that's basically what we're focused is selling on top of these infrastructure platforms, clouds, Hadoop distributions like Cloudera and Hortonworks and helping people to build these types of applications end to end. So we're in the stack, are you guys playing? Lower in the stack, on top of the stack, where are you? We're the unsexy middleware company, right? So we're a platform company that really, and that's why we're kind of agnostic to the infrastructure people want to use. And so we have customers that have multiple clusters of MapR, Cloudera, and Hortonworks, and they have AWS EMR clusters, and there's a Google data product cluster, and now they're checking out HT Insights on Azure. And so that's the reality for a really major financial services company today. So what problem are you solving specifically? So let's say that's your world of big data. All this ball. You build six different infrastructures, and you're a regulated industry, and you're trying to, let's say you're a bank and you have a mobile app, and you want to upsell a customer, or you want to give them an offer when they log into their mobile app, when you think they're likely to churn. So delivering that recommendation is a massive kind of data lake customer 360 data integration thing where you're pulling mainframe data, CRM data, clickstream data, and this is regulated. So you have governance, fine-grained security. And you need to do it in milliseconds too, right? Yeah, I'm only just getting the data into the cluster at this point, right? And that's kind of almost where the focus of the market is today in a lot of the world of Hadoop. And that's, I think, what's interesting about big data is there's so much opportunity, so much innovation, a lot of value being delivered, but at the same time, a lot of people are still at the starting gate. Jonathan, when you try to kind of parse and figure out this whole cloud marketplace, you know, the landscape out there, you know, I try to start with, you know, where's the data, and you know, what applications are where. And I find there's a lot of difference, you know, they wear Googles going, wear, you know, Microsoft with all their apps, Citrix with them, you know, Amazon, and you know, you mentioned data lakes. I mean, you know, there's lots of infrastructure guys that are, oh, I've got this data lake that's going to live in your environment, where IoT fits. So where do you see the data landscape, the application landscape? It's kind of a big question, but help us kind of squint through the market. So I mean, I'd say really simply, CASC is a five-year-old company. We've been almost a 95% Hadoop on-prem company. Yeah, yeah. 2017, we're not an all-in cloud company in 2017, but that's exactly where we're pointed. We see the cloud coming and really disrupting on-premise Hadoop for these data lake use cases. The exact same kind of magnitude drop and cost from having appliances and filers and things to store your data to Hadoop, you're having that same order of magnitude decrease going to S3 or Azure's data lake service or whatever it is. And now they're announcing more and more stuff to basically turn this flat file storage into a data warehouse. You can do SQL queries in place, all the cloud offerings are now kind of doing that kind of stuff. That's exactly what the on-prem Hadoop vendors are doing. It's a really interesting time. So great points there. We've always seen that intersection of kind of cloud and all the analytics there. Google, of course, talks a lot about it. Amazon, a lot of announcements this week. Yet, as you said today, a lot of Hadoop, it's on-premises, moving data is really tough to do. How long does it take the market to catch up to it? Do those data lakes more and more live in the cloud? I mean, I think it happens super fast because every graph of all the data that's being created, everyone knows it's faster and faster and faster. Well, the data is starting to be created into the cloud and it's starting to stay into the cloud and that creates gravity. And so if half of the data is going to be created in the next two years, isn't 80, 90% of that data going to be generated into the cloud? That makes 50% of the data now cloud-based. So I think the time scale and the acceleration and the growth of data, which is just kind of growing on this rapid, rapid phase, is going to create all the gravity into the cloud. So one of the things Verner Vogel said the CT of Amazon web service on the stage today was a lot of stuff is going to be done on analytics, a lot of value. I think he said 80%, maybe 60, 80, might have been 80%, which I can make a lot of sense. You're doing a lot of this stuff with data, a lot of pressure on latency. You got to have really fast performance going across multiple architectures. That's a real hard software problem. And if you figure it out, solve the middleware boring, rich, lucrative middleware market. You don't get taken out by the big guys first. But as a startup, you have to go out and play with the clouds. Give us a take on the assess the clouds for us. So you got Google, you got Microsoft, you got Amazon, Oracle probably not a fit for you relative to what you're doing. Maybe they are, get IBM with Blue Mix. How do you rate the current clouds? I mean, I think in a lot of ways, what's so interesting is they kind of are who they are and you look at their backgrounds and where they came from and that's who they are. And you see that's their strengths and then that gives them their weaknesses. Microsoft is clearly an enterprise software company. The other two vendors in the space, the other two major vendors in Google, they're not traditional enterprise software companies. And so that's perhaps a weak point for them whereas if you go and talk to Microsoft people, there's a massive field organization over there. While I'm an enterprise software company, I have a field sales organization and so it's really natural to align with a company like Microsoft because we almost have the same business model, enterprise software companies. And so we have the same approach of go-to-market. But at the same time, they're an enterprise software company and so it's slow. And they have long sales cycles and they also have a long, they have this huge back history of products they want to sell, not just your open source stuff. Amazon and Google are really infrastructure companies. Microsoft is at every layer of the stack. But you're going to play second fiddle. We were talking on the intro, you were hearing it, is that as a startup, if there are new rules of engagement, we are. To be a startup? No, with the cloud, I mean Amazon, it might not be a bad thing to be not an enterprise, have a huge enterprise sales force. Agreed, so. That might be right, I just think, but I'm just talking about kind of the strengths and weaknesses of it, but I mean, talk to any venture-backed company, talk to all the VC friends that we're hanging out with this week and they're expecting you to build a field sales organization if you're selling to large enterprise companies. And even AWS is, they have a field sales organization. I mean, they're getting there. They have, they eventually break all the rules, right? Eventually, they allow people to have their own clusters, their own dedicated stuff and all that stuff happens, but. Well, Amazon takes chances and I think one of the things I like about AWS and people kind of give them a bad rap for not having a full sales force, but they don't need one per se. They have account reps, but they don't need to have the army of guys out there, cloud is cloud. Yeah, and I call them upsell reps at Amazon, right? And I mean that not in a bad way. I mean, that's ultimately how Amazon I think is going to drive more and more margin on top of the cloud where if you're just selling hours and bits, you may have a very low margin business and you can make it on volume, but if you're selling analytics, if you're selling applications, if you're doing more and more enriched services, you're going to have a higher cost, you're going to be able to charge your customers more, you're going to be able to have a much higher margin business. And I think that's why that's their focus is, be the easiest person to use, be the capture of all the market and then focus on really, really, I think that's the strength and weakness of Amazon strategy is they're going to have this, and I heard you talking a little bit about it, which is we really want favoritism, we really want you to be all in with us. I think the other two are not like that. Because they can't, they can't be probably. Well, ZDNet misquoted any Jassy, they kind of made it sound like he was being, you know, very, you know, if you're either in or out. That wasn't what he was saying, he was basically saying, hey, we're going to put our priorities where people are all in on it. Every part is like, everyone's like that, right? You know, even the Hadoop distributions are like that. We have a very special relationship with Cladera. We also do stuff with MapR and Hortonworks. They don't necessarily mutually exclusive, but when you create special relationship with vendors, that's good. I think they've been, Amazon has been, for how big and how many partners and how much attention everyone wants from them, easy to do business with, they've been accessible. And I think that's a really hard thing to do. That's something that somebody like Microsoft can always struggle with. I'd say Google has been a very, very accessible company. Really strong on the technical aspects of everything. Really, you know, strong there. I mean, they're- They're not known for their, they have no feels organization. No, oh, they have no enterprise software. No customer support. It's very product oriented, it's very engineering oriented. But at the same time, you know, here's my reality to 50% of our customer base. They're paying millions of dollars to Netiza, Teradata, for fairly simple reporting workloads. And Cladera is trying to sell them in Paula and other people are selling Presto or these other things that are four to five times slower for a lot of their workloads. If you can, and Redshift is good, but it's still several, you know, two, three, four X, whatever it is slower for a lot of different queries. If you solve that problem, if you do, that's a technical problem, really a performance problem. That's a huge market opportunity. And so I think that's areas where somebody like Google could actually, if all you're doing is, you have bits going somewhere and you're running queries against your Tableau or whatever your UI is, you ultimately don't necessarily care what the commodity underneath is. And so if Google's opportunity to me is, you can create a commodity which is actually better and cheaper, then you have a real opportunity in the cloud. And I think that's- Yeah, I agree. And I think one of the things that the technical aspect is a really critical one. And you can always jury rig sales forces and create incentives. I mean, entrepreneurs want to make money. They want to get their product in front of customers. But if it compromises the product, that's a whole nother issue. So there might be some soft dollars incentives to work with a cloud. But in the day, if the product sucks, that doesn't matter. I mean, Azure has been getting a lot of ground. So how is Azure and these other guys clouds as they cobble together their approach versus Amazon's approach of pure services, straight up, is Microsoft cloud getting there? What's your take on Microsoft's maturity level? Yeah, I think there's these pockets of just excellence within their clouds and then pockets that are not so much, but it's maturing very rapidly. I think one of the things that's great about Microsoft is they've tried to embrace a dual approach of we'll do open source and partners and all that other stuff and we'll have our own solutions for it, that's always going to be hard. And you're talking about salespeople, that's where it's going to be hardest because which is the salesperson want to sell? I heard a hallway conversation. Someone pulled me aside and said, look at Amazon is light years ahead of the competition in terms of cloud and their platform. You agree? So I mean, experience matters. They've been doing it the longest for sure at massive, massive scale. But I think that's also one of the Google advantages which is they created essentially a lot of these architectures that born the big data ecosystem, this ecosystem, all of these things came from web scale, came from Google's papers and not changed my life, the big table paper, you know, actually, like those formative papers in the early 2000s and stuff changed this and led to a lot of this. So I think they both have distinct technical opportunities there, Amazon just, if you've been doing it, you're going to have this advantage and they've built a platform within their platform to continue to rapidly scale and innovate new products. So scale and speed is huge for them, they're doing it. The culture's working clearly, you know, it seems to be working for them and so the center of gravity, you know, it just... What's next for you guys? Cloud, cloud for us, you know, and it's really figuring out, I think the topic in VCs is how do you create large long-term companies that are relevant in the cloud era that Amazon isn't going to be able to eat your lunch? And I don't mean that negatively to Amazon. Amazon's right to go after the different opportunities. You know, Oracle bought all kinds of companies. They're a database company that bought everything else around them and why shouldn't Amazon do that too? Yeah, it was nice to see work day on stage, kind of putting a dig at Larry Ellison and a hostile takeover with PeopleSofts. But, you know, in the open source, the hostile takeover really isn't available, it's really more get the mind share of developers and make money for entrepreneurs through an ecosystem, right? So, you know, that's Amazon's play, obviously. Yeah. All right, Jonathan, thanks so much for coming on. Jonathan Gray, entrepreneur, founder and CEO of cask.co, not cask.com, cask.co, check them out. Middleware for the cloud, multiple clouds. We're back with more coverage after this short break.