 Live from San Francisco, it's theCUBE, covering Google Cloud Next 19. Brought to you by Google Cloud and its ecosystem partners. Hello everyone, welcome back to theCUBE's live coverage here in San Francisco. This is day two of Google Cloud Next 2019, it's theCUBE's exclusive coverage. We are in the middle of the show floor, all the action, the keynotes are still going on. A little bit over, I'm John Florey, Dave Vellante, Stu Miniman, kicking off, breaking down the keynote analysis, also breaking down post day one, all the action in the evening where all the parties are and all the action on the hallway conversations. Dave Stu, kicking off day two. Day one was setting the table, new CEO on stage. Day two gets into the products, real is about data. It's a data AI machine learning, it's all about the data cloud, data, we're seeing a machine learning, data management, smart analytics, AI and machine learning and collaborations, the four themes of today. Google clearly using data as a key value proposition, big table, big query, machine learning in GA, the support for auto ML and for tables, big announcements, your thoughts? Yeah, so John, I think answering some of the things that we brought up yesterday is when Google put out their vision of why they should be your partner of choice, why customers should choose, we thought that data and AI and ML would be read up front, so they kind of buried the lead a little bit and a question we had coming this week is can they reclaim that really thought leadership that a couple of years ago, you know data, really that geeky technical science stuff is what Google is really good at, so I thought they laid out some really good things. I think everybody was impressed to see there was good diversity of customers as well as all the Google people. There are a lot of the women of Google that you've written about John here showing, they're showing their chops here, so a lot of pieces to go through and everything from the G Suite and the Chromebooks and security and privacy is something I like to talk a little bit about when we get into it here, but quite a lot is used to data and AI at the center of it. And one of the power women dipped to use the big table, you see in the big query, all that stuff, Dave, the big theme and the keynote also was BI with AI, AI with BI. We've been covering the Hadoop space going back about 10 years of doing the Q, the promise of Hadoop, remember those days? Hadoop came from Google, CloudEra co-opted it, they merged with Hortonworks, and Doop is kind of a small little sliver of the ecosystem. Google's now showing what was once the promise of big data, they're giving demos, they're democratizing it, they're bringing it for the masses. We get stories on siliconangle.com, kind of outlining this, but the reality is there now, we're always hitting the road, the promise of big data now with Cloud really changed the game, your thoughts, because you've been covering this from day one. Well, I think that there's no question that this is a data game, and we said early on, John, on theCUBE that the big data war was going to be won in the cloud, the data was going to reside in the cloud, and having now machine intelligence applied to that data is what's giving companies competitive advantage at scale and economics. I was struck by the stats that Google gave at the beginning of the keynote today. Google in the last three years has spent $47 billion on capital expenditures. This year to date alone, they've spent $13 billion in CAPEX and data centers, $13 billion. It would take IBM three and a half years to spend that much in CAPEX. It would take Oracle six years. So from an economic standpoint and a scale standpoint, Google, Microsoft and Amazon are going to win that game. There's no question in my mind. So John, it is a game of scale and data and AI. What do you think? Well, I mean, first of all, Google, they got the Kubernetes stew, the white paper they wrote that they commercialized Kubernetes in a way that I thought was really well executed unlike Hadoop where they left that on the side of the road got picked up by a cloud era, Michael Olsen, Admiral, Jeff, Hammerbocker, we saw what happened with Hadoop. Kubernetes, they didn't screw that up. They basically put it out there in the open source system, the way they get behind CNCF, really positive there. On the data front, Google's got so much in the tool shed. All across Google from day one, their legacy is data, they're data-driven, large scale. They built software and systems to manage data at scale at a whole unprecedented level. I think that they have, they're well ahead of the marketplace on the technologies that are inside Google proper, Google Cloud, Google proper, Alphabet, whatever you want to call it, self-driving cars. The question for Google is, can they bring it together? They need to hire a team of people to just go out and just get it all together, pull the jewels together, and put it into a coherent platform. That's kind of the tea leaves that I see that we're reading here, is that Kurian pointed out in the keynote, we got tons of technology. The question is, can they pull it together in a package and make it consumable, addressable, programmable? Programming APIs, we've seen that movie that's happening right now. The next level of innovation for Google is, can they make data programmable? This is going to be a 10-year opportunity. If they get that right, they will win big, they'll move the ball down the field. You see Amazon going big on SageMaker. It's all about data, data analytics, at scale, auto machine learning. These are the tell signs, stew, data, programmability. They got all the things. Can they bring it to bear? Yeah, well John, one of the things that I saw got a lot of people excited is, if I have, you know, I'm a G Suite customer, we're G Suite customers, and I'm using Spreadsheets. Now I can use BigQuery with that. The power of analytics and big data, be able to plug that right in, make it really easy, and what's interesting is trying to squint through, you know, what was kind of the Google consumer side of the house that many of us know and have used for a lot of years versus the enterprise? G Suite and Chromebooks and mobile? Well, you know, under Diane Green, it was Google Enterprise, and now it's all part of Google Cloud. Just when we talk about Microsoft, it's like, well, is it Azure or is it O365? Well, is it G Suite or is it Google? And the one that I want to get your guys' comment on is they talked about privacy. We know Google as a whole, Alphabet, is 95% plus ad revenue, and they were very strong out here and said, we do not own your data. We will not sell it to a third party. Privacy, privacy, privacy. And it's great to hear them say that, but we all interact and work with Google. We know all the cloud providers, the data is an important thing. When I do AI and ML type activities, I need to be able to anonymize it and leverage it and train on it. So that data privacy issue is still something that I heard what they said, but there's got to be some concerns there. There's another angle here that I'd like to talk about, and that's the database. Google, Amazon, Microsoft, Oracle, IBM, Micotension, Alibaba, all the big cloud guys, they want your data. That's why Amazon's spending so much effort on the database market. That's why, you know, see Oracle having such a dominant position in database. If you look at Google's announcements yesterday, they were basically doing a backhand slap at Amazon saying, we're more open. They did a deal with Mongo. There's a lot of discussion in the community, the software community about how Amazon, obviously Bogart's open source. But if you look, that's true. If you look at Amazon, they've basically taken a lot of open source products and built their own databases. But if you look at Google, Google's got relational databases, they got non-relational databases, they got operational databases. And so, I wonder out loud, is this a Trojan Horse strategy because they need to own your data? That database is so important. Now the other thing I'll add is I talked to Juan Loiza yesterday who's an executive VP at Oracle. And he said to me that the cloud providers basically look at the database as another application to run on top of servers and virtual machines. He said, we're at Oracle, we integrate, they do all the exadata stuff, et cetera. So my point is database is the war to be won. That's where it starts. And if you're going to do AI, you want to have the data proximate to the application. Well, I mean, there's two ways to look at that data. I would say that my take on the database war or position in the stack is you look at it from the old way or the new way. The old way would be an Oracle, well, we got to preserve the database, we license it, we have all these license agreements. The new way is to change the game automation like what Google's showing where all this stuff is going to be done on behalf of the customer. So the business model of how databases and the impact of data is being used will dictate, in my opinion, the monetization. And that's the question that everyone that I've talked to on the show floor, offline on email and direct messages, how are we going to make money with containers? How are we going to make money with Kubernetes? How am I going to make money with data? This is the fundamental question. Now, if you look at the success pattern of the partner ecosystem, the money making is about new economics, new price points and new services. So if you're Deloitte or you're Accenture, you're saying, wow, if Google can automate all the stuff that used to be really hard to do, like data migration, moving application workloads around, that was once a high profit yield activity for the system integrators or selling databases like Oracle, that's the old way. The smart partners are essentially saying, okay, I'll take the new economics where all that cost is extracted away by the automation and I'll lower my price point, but still capture the margin. The margin opportunity for cloud is significant and this is where the smart money is going. The smart monetization schemes are around leveraging what Google and Amazon are doing at scale and shifting their business model, take advantage of the lower cost but then lowering the price not as much. So they still capture the margin. So this is the integration. These are things that were like months and months project. You go to data migrations too. Now those projects could be months. So smart money is saying, okay, how do I make money on this? It's not the old way. So this classic, which side is treating you on? Old way or new way? That's going to define who wins and who loses in my opinion. Well, what do you mean by old way? I mean, it's who owns the license, right? Selling database license, for instance, is an old way. Well, essentially what Amazon does, database is a service. Well, I mean, it's a license. Buy as you go, but you don't have, Oracle sells it as a buy as you go too. I mean, they could play that same game. To me, it's more about when it comes to database, it's more about workloads. How much of the world needs acid property databases because that's Oracle's game versus how much of the world needs, you know, a database data store for less structured data. And that's really I think what Google and to a certain extent Amazon are betting on. Although both companies, especially Amazon is making a bet on both transactional databases and non-relational. I mean, in the ideal world, database would be free and the margin gets shifted to another spot. That's not clear yet, but still it can make money on database but it's a lower price. So Google makes money at scale. So with cloud scale, they can lower the price of the database license, whether it's a service or some fee, but it's the people implementing, like the integrators and the people that are building applications. As they build that agility in, how are they going to monetize? How does a company out on this floor make money? I just remember data stacks in probably like 2012, I was talking to Billy Bosworth, the CEO, about the merits of being in the AWS marketplace. And he said, you know, I'm a little nervous about that. What do you think, Dave? Do you think they're going to like own me at some point in time and compete with me? So, and that's what Google's announcement yesterday said is, you know, you're our friends, we're not going to, they didn't really come out and say we're not going to compete with you. They just basically said, we are more open than AWS without mentioning AWS. Yeah, so it's interesting, you know, I've only had a little bit of a chance to walk around but it's a different ecosystem than Amazon. I remember six years ago when we first went to Amazon, it was like game developers and all these weird startups that I couldn't understand what they do. And now it's like, you know, like VMworld but bigger with just the broad ecosystem here. You know, there's a big section on collaboration. I went to Enterprise Connect a couple of weeks ago talking about contact centers. I see a lot of the same companies here. I heard Five Nines mentioned on stage, Zoom's here, you know, how do they plug into Google Cloud? I heard Salesforce talking about the modern contact center. So it's a diverse ecosystem but it's different than Amazon. And there's not, at Amazon, there's always that underlying, you know, thing. Oh, is Amazon going to take over this business here? You know, I haven't heard that concern at this show. Well, I mean, look, the bottom line is that there's a shift in the economics and business model technology. Back to the database question. The fact that MongoDB was once forecast to go out of business, oh, Amazon's going to kill MongoDB. They had a DynamoDB. Google's got databases. The fact of the matter is there's no one database anymore. Every application at some level has a database. So if you think about that, then you're going to have a new model where everything has a database. And the database is going to be characteristic on the workload and application. So I do agree with that point. The question is, it's not mutually exclusive. One database licensed for all versus databases everywhere. So if databases are everywhere, then the connective tissue becomes the opportunity. That's where I think you see some of these data plane technologies with cloud very compelling because I can move data very quickly around and that's where the machine learning really shines. That's going to be a latency question. That's going to be a data integrity question. This is the new model. This is what horizontal scalability means in the cloud. Not bi-oracle database and we're good. It's kind of, that game is slowly moving into the Bolivian. Well, I think Amazon would say, hey, if you're a database vendor, you got to innovate or because we're not going to stop innovating. Whereas I think Google's message to the database vendors is somewhat different. We want to partner with you and maybe that's because they're not coming from a position of enterprise strength. I'm sensing two apparently different strategies. I just don't know what the end game is and I believe the end game is to own the data in the cloud. The tell sign on the database is the developer, right? If I want to run a document store because that's the best for my JSON or my feeds if I'm using, say, a lot of JavaScript, I'll use document store. If I want to use a relational database, I'll use a relational database. So the ideal world is not to have the developer forced into a tooling and database decision that they don't want. Yeah, but Mongo changed its licensing policy as a direct result of what Amazon was doing. So they made their community addition, license terms, more restrictive. I don't know if you follow that. So what they said is anybody, any cloud service provider that distributes our community addition has to open source their entire software stack associated with distributing that or they got to pay us. So basically saying you have to pay an open source tax or you got to pay us. Well, I mean, look at the part. Very interesting change in their database. One of the announcements here on the day two was the data fusion thing, which essentially to me is a tell sign as well, that fusion data, moving data, integrating data is a critical thing for AI. AI and machine learning in AI is only as good as the data that it's working with. So if the data, if there's missing data, say on a retail transaction, you potentially are missing out on an opportunity to create a better user experience. So addressability of data, having that accessible is a critical feature for machine learning and AI. And again, it's garbage in, garbage out relative to the data equation, high quality data gets high quality machine learning, high quality machine learning gets high quality AI. So Stu, that's kind of what cloud offers with large compute, large horizontal scalability. Well, and I said yesterday, I was kind of disappointed there wasn't enough talk about AI. Well, Google certainly made up for that today, didn't they, Stu? Yeah, absolutely. Yeah. Sorry, was there a question, John? What was your favorite keynote moment today? Look, it was good when they actually let a couple of the customers go up there and talk. It was a little bit disappointed that, you know, some of the sessions feel a little bit too scripted for my take, but they laid out a lot of pieces there. It takes a little while to, you know, squint through all of the adjustments, you know, and all the changes that they have there. I'm still digging through, like on the Anthos, we talked about it quite a bit yesterday, but, you know, had some good conversations afterwards. They've got the cloud run announcement that's coming out this afternoon. But, you know, digging into that open source discussion that you were just talking about from a database is something that I have a lot of interest in. I'm glad we actually have Red Hat on today. We'll get their opinion as to, you know, they know a thing or two about open source and Kubernetes and how does something like OpenShift fit with Anthos. They can work together, but it's not a, oh, and everything works back and forth. If I'm PKS, if I'm OpenShift, or if I'm, you know, the GKE-based Anthos, it's not seamless and it sure ain't free. You pointed out customers, you were hearing from UPS, Scotia Bank, Baker Hughes, McCastin heard from Kohl's yesterday, so it's pretty high level senior people from the customer side speaking on stage, which is progress. Yeah, the CIO of UPS, I thought was great. He really laid out, you know, the scale of their business and how they grow. All right, guys, we got Day 2, we're kicking off here, we're on the show floor here in San Francisco for Google Cloud next 2019. Taking off, we got all day interviews. Day 2 of three days of live coverage. Stay with us as we kick off full day of great interviews, executives, entrepreneurs, and ecosystem parties here at Google next. Stay with us for more after this short break.