(bright upbeat music) >> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders around the globe, these are Cloud Native Insights. >> Hi, I'm Stu Miniman, the host of Cloud Native Insights. We talk about cloud native, we're talking about how customers can take advantage of the innovation and agility that's out there in the clouds, one of the undercurrents, not so hidden if you've been watching the program so far. We've talked a bit about serverless, say something that's helping remove the friction, allowed developers to take advantage of technology and definitely move really fast. So I'm really happy to welcome to the program, for coming from Fauna. First of all, I have the CTO and Co-founder, who's Evan Weaver. And also joining him is the new CEO Eric Berg. They said, both from Fauna, talking serverless, talking data as an API and talking the modern database. So first of all, thank you both for joining us. >> Thanks for having us Stu. >> Hi, good to be here. >> All right, so Evan, we're going to start with you. I love talking to founders always. If you could take us back a little bit, Fauna as a project first before it was a company, you of course were an early employee at Twitter. So if you could just bring us back a little bit, what created the Fauna project and bring us through a brief history if you would. >> So I was employee 15 and Twitter, I joined in 2008. And I had a database background, I was sort of a performance analyst and worked on Ruby on Rails sites at CNET networks with the team that went on to found GitHub actually. Now I went to Twitter 'cause I wanted Twitter the product to stay alive. And for no greater ambition than that. And I ended up running the back end engineering team there and building out all the distributed storage for the core business objects, tweets, timelines, the social graph, image storage, the cache, that kind of thing. And this was early in the cloud era. API's were new and weird. You couldn't get Amazon EC2 off the shelf easily. We were racking hardware and code ancient center. And there were no databases or platforms for data of any kind. They really let us the Twitter engineering team focus on building the product. And we did a lot of open source work there. Some of which has influenced Fauna, originally, Twitter's open source was hosted on the Fauna GitHub account, which predated Twitter like you mentioned. And I was there for four years build out the team, basically scaled the site, especially scaled the Twitter.com API. And we just never found a platform which was suitable for what we were trying to accomplish. Like a lot of what Twitter did was itself a platform. We had developers all over the world using the Twitter API to interact with tweets. And we're frustrated that we basically had to become specialists in data systems because there wasn't a data API, we can just build the product on. And ultimately, then data API that we wished we had, is now Fauna. >> Well, it's a story we've loved hearing. And it's fascinating one, is that the marketplace wasn't doing what we needed. Often open source is a piece of that, how do we scale that out? How do we build that? Realized that the problem that you have is what others have. And hey, maybe there's a company. So could you give us that transition, Fauna as a product, as a company, where was it understood that, hey, there's a lot of other people that can take advantage from some of the same tools that you needed before. >> I mean, we saw it in the developers working with the Twitter platform. We weren't like, your traditional database experiences, either manage cloud or on-prem, you have to administrate the machine, and you're responsible for its security and its availability and its location and backups and all that kind of thing. People building against Twitter's API weren't doing that. They're just using the web interface that we provided to them. It was our responsibility as a platform provider. We saw lots of successful companies being built on the API, but obviously, it was limited specifically to interacting with tweets. And we also saw peers from Twitter who went on to found companies, other people we knew in the startup scene, struggling to just get something out the door, because they had to do all this undifferentiated heavy lifting, which didn't contribute to their product at all, if they did succeed and they struggled with scalability problems and security problems and that kind of thing. And I think it's been a drag on the market overall, we're essentially, in cloud services. We're more or less built for the enterprise for mature and mid market and enterprise companies that already had resources to put behind these things, then wasn't sort of the cloud equivalent of the web, where individuals, people with fewer resources, people starting new projects, people doing more speculative work, which is what we originally and Jack was doing at Twitter, it just get going and build dynamic web applications. So I think the move to cloud kind of left this gap, which ultimately was starting to be filled with serverless, in particular, that we sort of backtracked from the productivity of the '90s with the lamp era, you can do everything on a single machine, nobody bothered you, you didn't have to pay anyone, just RPM install and you're good to go. To this Kubernetes, containers, cloud, multi site, multi region world where it's just too hard to get a basic product out the door and now serverless is sort of brought that around full circle, we see people building those products again, because the tools have probably matured. >> Well, Evan, I really appreciate you helping set the table. I think you've clearly articulated some of the big challenges we're seeing in the industry right now. Eric, I want to bring you into the conversation. So you relatively recently brought in as CEO, came from Okta a company that is also doing quite well. So give us if you could really the business opportunity here, serverless is not exactly the most mature market, there's a lot of interest excitement, we've been tracking it for years and see some good growth. But what brought you in and what do you see is that big opportunity. >> Yeah, absolutely, so the first thing I'll comment on is what, when I was looking for my next opportunity, what was really important is to, I think you can build some of the most interesting businesses and companies when there are significant technological shifts happening. Okta, which you mentioned, took advantage of the fact of SaaS application, really being adopted by enterprise, which back in 2009, wasn't an exactly a known thing. And similarly, when I look at Fauna, the move that Evan talked about, which is really the maturation of serverless. And therefore, that as an underpinning for a new type of applications is really just starting to take hold. And so then there creates opportunities that for a variety of different people in that stack that to build interesting businesses and obviously, the databases is an incredibly important part of that. And the other thing I've mentioned is that, a lot of people don't know this but there's a very good chunk of Okta's business, which is what they call their customer identity business, which is basically, servicing of identity is a set of API's that people can integrate into their applications. And you see a lot of enterprises using this as a part of their digital transformation effort. And so I was very familiar with that model and how prevalent, how much investment, how much aid was out there for customers, as every company becoming a software company and needing to rethink their business and build applications. And so you put those two trends together and you just see that serverless is going to be able to meet the needs of a lot of those companies. And as Evan mentioned, databases in general and traditionally have come with a lot of complexity from an operational perspective. And so when you look at the technology and some of the problems that Fauna has solved, in terms of really removing all of that operational burden when it comes to starting with and scaling a database, not only locally but globally. It's sort of a new, no brainer, everybody would love to have a database that scales, that is reliable and secure that they don't have to manage. >> Yeah, Eric, one follow up question for you. I think back a few years ago, you talked to companies and it's like, okay, database is the center of my business. It's a big expense. I have a team that works on it. There have been dealt so much change in the database market than most customers I talked to, is I have lots of solutions out there. I'm using Mongo, I've got Snowflake, Amazon has flavors of things I'm looking at. Snowflake just filed for their IPO, so we see the growth in the space. So maybe if you could just obviously serverless is a differentiation. There's a couple of solutions out there, like from Amazon or whether Aurora serverless solution but how does Fauna look to differentiate. Could you give us a little bit of kind of compared to the market out there? >> Sure, yeah, so at the high level, just to clarify, at the super high level for databases, there tends to be two types operational databases and then data warehouse which Snowflake is an example of a data warehouse. And as you probably already know, the former CEO of Snowflake is actually a chairman of Fauna. So Bob Muglia. So we have a lot of good insight into that business. But Fauna is very much on the operational database side. So the other half of that market, if you will, so really focused on being the core operational store for your application. And I think Evan mentioned it a little bit, there's been a lot of the transformation that's happened if we rewind all the way back to the early '90s, when it was Oracle, and Microsoft SQL Server were kind of the big players there. And then as those architectures basically hit limits, when it came to applications moving to the web, you had this whole rise in a lot of different no SQL solutions, but those solutions sort of gave up on some of the promises of a relational database in order to achieve some of the ability to scale in the performance required at the web. But we required then a little bit more sophistication, intelligence, in order to be able to basically create logic in your application that could make up for the fact that those databases didn't actually deliver on the promises of traditional relational databases. And so, enter Fauna and it's really sort of a combination of those two things, which is providing the trust, the security and reliability of a traditional relational database, but offering it as serverless, as we talked about, at the scale that you need it for a web application. And so it's a very interesting combination of those capabilities that we think, as Evan was talking about, allows people who don't have large DevOps teams or very sophisticated developers who can code around some of the limitations of these other databases, to really be able to use a database for what they're looking for. What I write to it is what I'm going to read from it and that we maintain that commitment and make that super easy. >> Yeah, it's important to know that the part of the reason that operational database, the database for mission critical business data has remained a cost center is because the conventional wisdom was that something like Fauna was impossible to build. People said, you literally cannot in information science create a global API for data which is transactional and consistent and suitable for relying on, for mission critical, user login, banking payments, user generated content, social graphs, internal IT data, anything that's irreplaceable. People said, there can be no general service that can do this ubiquitously a global internet scale, you have to do it specifically. So it's sort of like, we had no power company. Instead, you could call up Amazon, they drive a truck with a generator to your house and hook you up. And you're like, right on, I didn't have to like, install the generator myself. But like, it's not a good experience. It's still a pain in the neck, it's still specific to the location you're at. It's not getting utility computing from the cloud the way, it's been a dream for many decades that we get all our services through brokers and API's and the web and it's finally real with serverless. I want to emphasize that the Fauna it technology is new and novel. And based on and inspired by our experience at Twitter and also academic research with some of our advisors like Dr. Daniel Abadi. It's one of the things that attracted us, Snowflake chairman to our company that we'd solve groundbreaking problems in information science in the cloud, just the way Snowflakes had. >> Yeah, well and Evan, yeah please go on Eric. >> Yeah, I'm just going to have one thing to that, which is, in addition, I think when you think about Fauna and you mentioned MongoDB, I think they're one of a great examples of database companies over the last decade, who's been able to build a standalone business. And if you look at it from a business model perspective, the thing that was really successful for them is they didn't go into try to necessarily like, rip and replace in big database migrations, they started evolving with a new class of developers and new applications that were being developed and then rode that obviously into sort of a land and expand model into enterprises over time. And so when you think about Fauna from your business value proposition is harnessing the technological innovation that Evan talked about. And then combining this with a product that bottoms up developer first business motion that kind of rides this technological shift into you creating a presence in the database market over time. >> Well, Evan, I just want to go back to that, it's impossible comment that you made, a lot of people they learn about a technology and they feel that that's the way the technology works. Serverless is obviously often misunderstood from the name itself, too. We had a conversation with Andy Jassy, the CEO of AWS a couple years ago, and he said, "If I could rebuild AWS from the ground up today, "it would be using all serverless," that doesn't mean only lambda, but they're rebuilding a lot of their pieces underneath it. So I've looked at the container world and we're only starting the last year or so, talking about people using databases with Kubernetes and containers, so what is it that allows you to be able to have as you said, there's the consistency. So we're talking about acid there, not worry about things like cold starts, which are thing lots of people are concerned about when it comes to serverless and help us understand a little bit that what you do and the underlying technologies that you leverage. >> Yeah, databases are always the last to evolve because they're the riskiest to change and the hardest to build. And basically, through the cloud era, we've done this lift and shift of existing on premises solutions, especially with databases into cloud machines, but it's still the metaphor of the physical computer, which is the overriding unit of granularity mental concept, everything like you mentioned, containers, like we had machines then we had Vms, now we have containers, it's still a computer. And the database goes in that one computer, in one spot and it sits there and you got to talk to it. Wherever that is in the world, no matter how far away it is from you. And people said, well, the relational database is great. You can use locks within a single machine to make sure that you're not conflicting your data when you update it, you going to have transactionality, you can have serialize ability. What do you do, if you want to make that experience highly available at global scale? We went through a series of evolutions as an industry. From initially that the on-prem RDBMS to things like Google's percolator scheme, which essentially scales that up to data center scale and puts different parts of the traditional database on different physical machines on low latency links, but otherwise doesn't change the consistency properties, then to things like Google Spanner, which rely on synchronized atomic clocks to guarantee consistency. Well, not everyone has synchronized atomic clocks just lying around. And they're also, their issues with noisy neighbors and tenancy and things because you have to make sure that you can always read the clock in a consistent amount of time, not just have the time accurate in the first place. And Fauna is based on and inspired and evolved from an algorithm called Calvin, which came out of a buddy's lab at Yale. And what Calvin does is invert the traditional database relationship and say, instead of doing a bunch of work on the disk and then figuring out which transactions won by seeing what time it is, we will create a global pre determined order of transactions which is arbitrary by journaling them and replicating them. And then we will use that to essentially derive the time from the transactions which have already been committed to disk. And then once we know the order, we can say which one's won and didn't win and which happened before, happen after and present the appearance of consistency to all possible observers. And when this paper came out, it came out about a decade ago now I think, it was very opaque. There's a lot of kind of hand waving exercises left to the reader. Some scary statements about how wasn't suitable for things that in particular SQL requires. We met, my co-founder and I met as Fauna chief architect, he worked on my team at Twitter, at one of the database groups. We were building Fauna we were doing our market discovery or prototyping and we knew we needed to be a global API. We knew we needed low latency, high performance at global scale. We looked at Spanner and Spanner couldn't do it. But we found that this paper proposed a way that could and we can see based on our experience at Twitter that you could overcome all these obstacles which had made the paper overall being neglected by industry and it took us quite a while to implement it at industrial quality and scale, to qualify it with analysts and others, prove to the world that it was real. And Eric mentioned Mongo, we did a lot of work with Cassandra as well at Twitter, we're early in the Cassandra community. Like I wrote, the first tutorial for Cassandra where data stacks was founded. These vendors were telling people that you could not have transactionality and scale at the same time, and it was literally impossible. Then we had this incrementalism like things with Spanner. And it wasn't till Fauna that anyone had proved to the world that that just wasn't true. There was more marketing around their failure to solve the information science problem, than something fundamental. >> Eric, I'm wondering if you're able to share just order of magnitude, how many customers you have out there from a partnership standpoint, we'd like to understand a little bit how you work or fit into the public cloud ecosystems out there. I noticed that Alphabets General Venture Fund was one of the contributors to the last raise. And obviously, there's some underlying Google technology there. So if you could just customers and ecosystem. >> Yeah, so as I mentioned, we've had a very aggressive product lead developer go to market. And so we have 10s of thousands of people now on the service, using Fauna at different levels. And now we're focused on, how do we continue to build that momentum, again, going back to the model of focus on a developer lead model, really what we're focused on there is taking everything that Evan just talked about, which is real and very differentiated in terms of the real core tech in the back end and then combining that with a developer experience that makes it extremely easy to use and really, we think that's the magic in terms of what Fauna is bringing, so we got 10s of thousands of users and we got more signing up every day, coming to the service, we have an aggressive free plan there and then they can migrate up to higher paying plans as they consume over time. And the ecosystem, we're aggressively playing in the broader serverless ecosystem. So what we're looking at is as Evan mentioned, sometimes the databases is the last thing to change, it's also not necessarily the first thing that a developer starts from when they think about building their application or their website. And so we're plugging into the larger serverless ecosystem where people are making their choices about potentially their compute platform or maybe a development platform like I know you've talked to the folks over at JAMstack, sorry at Netlify and Purcell, who are big in the JAMstack community and providing really great workflows for new web and application developers on these platforms. And then at the compute layer, obviously, our Amazon, Google, Microsoft all have a serverless compute solution. CloudFlare is doing some really interesting things out at the edge. And so there's a variety of people up and down that stack, if you will, when people are thinking about this new generation of applications that we're plugging into to make sure that the Fauna is that the default database of choice. >> Wonderful, last question, Evan if I could, I love what I got somebody with your background. Talk about just so many different technologies maturing, give us a little bit as to some of the challenges you see serverless ecosystem, what's being attacked, what do we still need to work on? >> I mean, serverless is in the same place that Lamp was in the in the early '90s. We have the old conservatives ecosystem with the JAMstack players that Eric mentioned. We have closed proprietary ecosystems like the AWS stack or the Google Firebase stack. As to your point, Google has also invested in us so they're placing their bets widely. But it's seeing the same kind of criticism. That Lamp, the Linux, Apache, MySQL, PHP, Perl, it's not mature, it's a toy, no one will ever use this for real business. We can't switch from like DV2 or mumps to MySQL, like no one is doing that. The movement and the momentum in serverless is real. And the challenge now is for all the vendors in collaboration with the community of developers to mature the tools as those the products and applications being built on the new more productive stack also mature, so we have to keep ahead of our audience and make sure we start delivering and this is partly why Eric is here. Those those mid market and ultimately enterprise requirements so that business is built on top of Fauna today, can grow like Twitter did from small to giant. >> Yeah, I'd add on to that, this is reminiscent for me, back in 2009 at Okta, we were one of the early ISVs that built on in relied 100% on AWS. At that time there was still, it was very commonplace for people racking and stacking their own boxes and using Colo and we used to have conversations about I wonder how long it's going to be before we exceed the cost of this AWS thing and we go and run our own data centers. And that would be laughable to even consider today, right, no one would ever even think about that. And I think serverless is in a similar situation where the consumption model is very attractive to get started, some people sitting there, is it going to be too expensive as I scale. And as Evan mentioned, when we think about if you fast forward to kind of what the innovation that we can anticipate both technologically and economically it's just going to be the default model that people are going to wonder why they used to spend all these time managing these machines, if they don't have to. >> Evan and Eric, thank you so much, is great to hear the progress that you've made and big supporters, the serverless ecosystem, so excited to watch the progress there. Thanks so much. >> Thanks Stu. >> Thanks for having us Stu. >> All right and I'm Stu Miniman. Stay tuned. Every week we are putting out the Cloud Native Insights. Appreciate. Thank you for watching. (bright upbeat music)

>> Announcer: Live from San Francisco, it's theCUBE. Covering Red Hat Summit 2018. Brought to you by Red Hat. >> Hello everyone, welcome to theCUBE's special coverage here at Red Hat Summit. This is exclusive three days of wall-to-wall coverage of theCUBE. I've been covering Red Hat for years. Excited to be back here at Moscone West. I'm John Furrier, the co-host of theCUBE, with my co-host analyst this week, John Troyer. He's the CEO of TechReckoning, an advisory firm in the technology industry as well as an influencer, and he advises on influencer and influencer of communities. I would say it's community focused. John, great to see you. Welcome to the Red Hat Summit. We're going to kick it off! >> Great to be here. Thanks for having me. >> So you know I am pretty bullish on open source. I have been from day one. At my age who have lived through the wars of when it was second class citizen. Now it's first class citizen. Software power in the world. Again, on and on, this is not a new story. What is the new story is the cloud impact to the world of open source and business. We're seeing the results of Amazon just continue to be skyrocketing. You see Microsoft as you're having their developer conference of Microsoft Build this week. Google I/O is also this week. There is a variety of events happening. It's all pointing to cloud economics, cloud scale, and the role of software and data, and Red Hat has been a big time winner in taking advantage of these trends by making some good bets. >> Absolutely. I think one of the words were going to hear a lot this week is OpenShift. They are a container and cloud platform. Hybrid cloud is a super big emphasis here. Hybrid cloud, multi cloud already on stage at the first key note. They had a big stack of machines and they were going out to a multi cloud deployment right there on stage. Open source, also huge this week, right? The key note, the tagline, of the whole conference, if you are interested in open source, you should be here. I think you nailed it. It's going to be about multi cloud. >> It's exciting for me, I got to say. The disruption that's happening obviously with IT, with cloud, is pretty much out there. We pretty much recognize IT as transforming into a whole other look in terms of how it's operating, but the interesting thing that's just happening recently is the overwhelming takeover of Kubernetes and the conversation and in the stack you're seeing a rallying point and a rallying cry and establishing a de facto standard of Kubernetes. The big news of 2018 is, to me, the de facto standard of Kubernetes across a multi cloud, hybrid cloud architecture to allow developers and also infrastructure providers the ability to move workloads around, managing workloads across clouds. This is kind of the holy grail outcome everyone's looking for is how do I get to a true multi cloud world? And I think Kubernetes this year has the stake in the ground to say we're going to make that the interoperable capability. And Red Hat made a bet a couple years ago, three, four years ago. Everyone was scratching their head. What the hell are they doing with Kubernetes? What's Red Hat-- They're looking like geniuses now because of the results. >> Absolutely. In fact, I think by the end my joke is going to be this is the OpenShift Summit. I'll be very interested, John in your observations. You were at KubeCon last week. So that's the open source project and the ecosystem around Kubernetes. Red Hat owns a lot of Kubernetes. Red Hat employs many of the Kubernetes' leaders. They have really taken over from Google in a lot of ways about the implementation and go-forward path for Kubernetes. So this is the show that takes that open source project and packages it into something that an IT buyer can understand and take. >> I got to say one of the things that is interesting, and this is not well-reported in the news. It's a nuanced point but it's kind of an interesting thing, I think an inflection point for Red Hat. By them buying CoreOS has been a really good outcome for both companies. CoreOS, pure open source DNA in that business. Those guys were doing some amazing technology development, and again, all pure open source. Total pure. There is nothing wrong with being a pure open source. My point is, when you have that kind of religious point of view and then the pressure to monetize it Docker has had. We know what happened there. So CoreOS was doing amazing things but it kind of took a lot of pressure from the market. How are you going to make money? You know I always say it's hard to make money when you're trying to do it too early. So CoreOS lands at Red Hat who has generations of commercialization. Those two together is really going to give Red Hat the capability to go to the next level when you talk about applications. It's going to increase their total addressable market. It's going to give them more range. And with Kubernetes becoming the de facto standard, OpenShift now can become a key platform as a service that really enables new applications, new management capabilities. This should expand the RHEL opportunity from a market standpoint in a significant, meaningful way. I think if you're like a financial analyst or you're out there looking at this going, hmm, where's the dots connecting? It's connecting up the stack, software to service, with DevOps, with cloud native, Red Hat is positioned well. So that's my takeaway from KubeCon. >> Interesting. Yeah, before we move away from CoreOS, a lot of announcements today about how Red Hat will be incorporating CoreOS technologies into their platform. They talked about the operator framework. I think one of the bigger pieces of news is that CoreOS' OS, called Container Linux changes its name back to CoreOS and will now be the standard container operating system for Red Hat. That's kind of big news because Red Hat had its own atomic host, its own kind of micro, mini Linux distribution and so now they're switching over to that. They also talked about Tectonic, which actually is a really good automated operations stack, some of those technologies. In the future they will be incorporated into OpenShift. So they were talking a little bit about futures but it at least they've given a roadmap. No one was quite sure what the super-smart rocket scientists at CoreOS were doing here and so now we know a little more. >> And also at KubeCon they announced the open source of the operator framework. It's an open source toolkit for managing Kubernetes clusters. Again, and first of all, I love the CoreOS name. This is all about what Red Hat is doing. Now let's not forget the ecosystem that Red Hat has. So you're talking about a company that's been successful in open source for multiple generations now. Looking forward to this next generation modern infrastructure, you're seeing the stack look completely different with the cloud. If you look at all the presentations from Amazon, Google, Microsoft, the stack is not the old stack. It's a new concept. New things are happening so you've got to swap some pieces out. You get CoreOS, you bring that in, new puzzle piece. But look at the deals they're doing. They did a relationship with IBM, so IBM's back into the fold with Red Hat joining forces. >> Containerizing some of their biggest components like WebLogic and Dv2 and MQ. >> I think the containerization will create a nice compatibility mode, bring these old legacy apps into a modern cloud native architecture and gives that an opportunity to kind of get into the game, but also bring cloud native to the table. >> Absolutely. >> You've got IoT Edge, all these new applications. You just can't go anywhere without hearing about Internet of Things, machine learning, AI, cameras, whatnot. All this is happening. >> Absolutely. So we're going to break it down all week for the next three days. Red Hat Summit. It's all about containers, it's all about the Linux moment, kind of going to the next level. Cloud native, big time data action. All the great stuff happening. All done with open source with projects with new products being commercialized from these projects. This is the open source ethos. This is of course theCUBE coverage. We'll be back with more live coverage here in San Francisco at Moscone West after this short break.

>> Announcer: Live from San Jose, California, it's theCUBE, covering Big Data Silicon Valley 2017. (upbeat percussion music) >> Okay, welcome back everyone. Live here in Silicon Valley, San Jose, is the Big Data SV, Big Data Silicon Valley in conjunction with Strata Hadoop, this is theCUBE's exclusive coverage. Over the next two days, we've got wall-to-wall interviews with thought leaders, experts breaking down the future of big data, future of analytics, future of the cloud. I'm John Furrier with my co-host George Gilbert with Wikibon. Our next guest is Yuanhao Sun, who's the co-founder and CTO of Transwarp Technologies. Welcome to theCUBE. You were on, during the, 166 days ago, I noticed, on theCUBE, previously. But now you've got some news. So let's get the news out of the way. What are you guys announcing here, this week? >> Yes, so we are announcing 5.0, the latest version of Transwarp Hub. So in this version, we will call it probably revolutionary product, because the first one is we embedded communities in our product, so we will allow people to isolate different kind of workloads, using dock and containers, and we also provide a scheduler to better support mixed workloads. And the second is, we are building a set of tools allow people to build their warehouse. And then migrate from existing or traditional data warehouse to Hadoop. And we are also providing people capability to build a data mart, actually. It allow you to interactively query data. So we build a column store in memory and on SSD. And we totally write the whole SQL engine. That is a very tiny SQL engine, allow people to query data very quickly. And so today that tiny SQL engine is like about five to ten times faster than Spark 2.0. And we also allow people to build cubes on top of Hadoop. And then, once the cube is built, the SQL performance, like the TBCH performance, is about 100 times faster than existing database, or existing Spark 2.0. So it's super-fast. And in, actually we found a Paralect customer, so they replace their data with software, to build a data mart. And we already migrate, say 100 reports, from their data to our product. So the promise is very good. And the first one is we are providing tool for people to build the machine learning pipelines and we are leveraging TensorFlow, MXNet, and also Spark for people to visualize the pipeline and to build the data mining workflows. So this is kind of like Datasense tools, it's very easy for people to use. >> John: Okay, so take a minute to explain, 'cus that was great, you got the performance there, that's the news out of the way. Take a minute to explain Transwarp, your value proposition, and when people engage you as a customer. >> Yuanhao: Yeah so, people choose our product and the major reason is our compatibility to Oracle, DV2, and teradata SQL syntax, because you know, they have built a lot of applications onto those databases, so when they migrate to Hadoop, they don't want to rewrote whole program, so our compatibility, SQL compatibility is big advantage to them, so this is the first one. And we also support full ANCIT and distribute transactions onto Hadoop. So that a lot of applications can be migrate to our product, with few modification or without any changes. So this is the first our advantage. The second is because we are providing, even the best streaming engine, that is actually derived from Spark. So we apply this technology to IOT applications. You know the IOT pretty soon, they need a very low latency but they also need very complicated models on top of streams. So that's why we are providing full SQL support and machine learning support on top of streaming events. And we are also using event-driven technology to reduce the latency, to five to ten milliseconds. So this is second reason people choose our product. And then today we are announcing 5.0, and I think people will find more reason to choose our product. >> So you have the compatibility SQL, you have the tooling, and now you have the performance. So kind of the triple threat there. So what's the customer saying, when you go out and talk with your customers, what's the view of the current landscape for customers? What are they solving right now, what are the key challenges and pain points that customers have today? >> We have customers in more than 12 vertical segments, and in different verticals they have different pain points, actually so. Take one example: in financial services, the main pain point for them is to migrate existing legacy applications to Hadoop, you know they have accumulated a lot of data, and the performance is very bad using legacy database, so they need high performance Hadoop and Spark to speed up the performance, like reports. But in another vertical, like in logistic and transportation and IOT, the pain point is to find a very low latency streaming engine. At the same time, they need very complicated programming model to write their applications. And that example, like in public sector, they actually need very complicated and large scale search engine. They need to build analytical capability on top of search engine. They can search the results and analyze the result in the same time. >> George: Yuanhao, as always, whenever we get to interview you on theCube, you toss out these gems, sort of like you know diamonds, like big rocks that under millions of years, and incredible pressure, have been squeezed down into these incredibly valuable, kind of, you know, valuable, sort of minerals with lots of goodness in them, so I need you to unpack that diamond back into something that we can make sense out of, or I should say, that's more accessible. You've done something that none of the Hadoop Distro guys have managed to do, which is to build databases that are not just decision support, but can handle OLTP, can handle operational applications. You've done the streaming, you've done what even Databricks can't do without even trying any of the other stuff, which is getting the streaming down to event at a time. Let's step back from all these amazing things, and tell us what was the secret sauce that let you build a platform this advanced? >> So actually, we are driven by our customers, and we do see the trends people are looking for, better solutions, you know there are a lot of pain to set up a habitable class to use the Hadoop technology. So that's why we found it's very meaningful and also very necessary for us to build a SQL database on top of Hadoop. Quite a lot of customers in FS side, they ask us to provide asset until the transaction can be put on top of Hadoop, because they have to guarantee the consistency of their data. Otherwise they cannot use the technology. >> At the risk of interrupting, maybe you can tell us why others have built the analytic databases on top of Hadoop, to give the familiar SQL access, and obviously have a desire also to have transactions next to it, so you can inform a transaction decision with the analytics. One of the questions is, how did you combine the two capabilities? I mean it only took Oracle like 40 years. >> Right, so. Actually our transaction capability is only for analytics, you know, so this OLTP capability it is not for short term transactional applications, it's for data warehouse kind of workloads. >> George: Okay, so when you're ingesting. >> Yes, when you're ingesting, when you modify your data, in batch, you have to guarantee the consistency. So that's the OLTP capability. But we are also building another distributed storage, and distributed database, and that are providing that with OLTP capability. That means you can do concurrent transactions, on that database, but we are still developing that software right now. Today our product providing the digital transaction capability for people to actually build their warehouse. You know quite a lot of people believe data warehouse do not need transaction capability, but we found a lot of people modify their data in data warehouse, you know, they are loading their data continuously to data warehouse, like the CRM tables, customer information, they can be changed over time. So every day people need to update or change the data, that's why we have to provide transaction capability in data warehouse. >> George: Okay, and then so then well tell us also, 'cus the streaming problem is, you know, we're told that roughly two thirds of Spark deployments use streaming as a workload. And the biggest knock on Spark is that it can't process one event at a time, you got to do a little batch. Tell us some of the use cases that can take advantage of doing one event at a time, and how you solved that problem? >> Yuanhao: Yeah so the first use case we encounter is the anti-fraud, or fraud detection application in FSI, so whenever you swipe your credit card, the bank needs to tell you if the transaction is a fraud or not in a few milliseconds. But if you are using Spark streaming, it will usually take 500 milliseconds, so the latency is too high for such kind of application. And that's why we have to provide event per time, like means event-driven processing to detect the fraud, so that we can interrupt the transaction in a few milliseconds, so that's one kind of application. The other can come from IOT applications, so we already put our streaming framework in large manufacture factory. So they have to detect the main function of their equipments in a very short time, otherwise it may explode. So if you... So if you are using Spark streaming, probably when you submit your application, it will take you hundreds of milliseconds, and when you finish your detection, it usually takes a few seconds, so that will be too long for such kind of application. And that's why we need a low latency streaming engine, but you can see it is okay to use Storm or Flink, right? And problem is, we found it is: They need a very complicated programming model, that they are going to solve equation on the streaming events, they need to do the FFT transformation. And they are also asking to run some linear regression or some neural network on top of events, so that's why we have to provide a SQL interface and we are also embedding the CEP capability into our streaming engine, so that you can use pattern to match the events and to send alerts. >> George: So, SQL to get a set of events and maybe join some in the complex event processing, CEP, to say, does this fit a pattern I'm looking for? >> Yuanhao: Yes. >> Okay, and so, and then with the lightweight OLTP, that and any other new projects you're looking at, tell us perhaps the new use cases you'd be appropriated for. >> Yuanhao: Yeah so that's our official product actually, so we are going to solve the problem of large scale OLTP transaction problems like, so you know, a lot of... You know, in China, there is so many population, like in public sector or in banks, they need build a highly scalable transaction systems so that they can support a very high concurrent transactions at the same time, so that's why we are building such kind of technology. You know, in the past, people just divide transaction into multiple databases, like multiple Oracle instances or multiple mySQL instances. But the problem is: if the application is simple, you can very easily divide a transaction over the multiple instances of databases. But if the application is very complicated, especially when the ISV already wrote the applications based on Oracle or traditional database, they already depends on the transaction systems so that's why we have to build a same kind of transaction systems, so that we can support their legacy applications, but they can scale to hundreds of nodes, and they can scale to millions of transactions per second. >> George: On the transactional stuff? >> Yuanhao: Yes. >> Just correct me if I'm wrong, I know we're running out of time but I thought Oracle only scales out when you're doing decision support work, not when you're doing OLTP, not that it, that it can only, that it can maybe stretch to ten nodes or something like that, am I mistaken? >> Yuanhao: Yes, they can scale to 16 to all 32 nodes. >> George: For transactional work? >> For transaction works, but so that's the theoretical limit, but you know, like Google F1 and Google Spanner, they can scale to hundreds of nodes. But you know, the latency is higher than Oracle because you have to use distributed particle to communicate with multiple nodes, so the latency is higher. >> On Google? >> Yes. >> On Google. The latency is higher on the Google? >> 'Cus it has to go like all the way to Europe and back. >> Oracle or Google latency, you said? >> Google, because if you are using two phase commit protocol you have to talk to multiple nodes to broadcast your request to multiple nodes, and then wait for the feedback, so that mean you have a much higher latency, but it's necessary to maintain the consistency. So in a distributed OLTP databases, the latency is usually higher, but the concurrency is also much higher, and scalability is much better. >> George: So that's a problem you've stretched beyond what Oracle's done. >> Yuanhao: Yes, so because customer can tolerant the higher latency, but they need to scale to millions of transactions per second, so that's why we have to build a distributed database. >> George: Okay, for this reason we're going to have to have you back for like maybe five or ten consecutive segments, you know, maybe starting tomorrow. >> We're going to have to get you back for sure. Final question for you: What are you excited about, from a technology, in the landscape, as you look at open source, you're working with Spark, you mentioned Kubernetes, you have micro services, all the cloud. What are you most excited about right now in terms of new technology that's going to help simplify and scale, with low latency, the databases, the software. 'Cus you got IOT, you got autonomous vehicles, you have all this data, what are you excited about? >> So actually, so this technology we already solve these problems actually, but I think the most exciting thing is we found... There's two trends, the first trend is: We found it's very exciting to find more competition framework coming out, like the AI framework, like TensorFlow and MXNet, Torch, and tons of such machine learning frameworks are coming out, so they are solving different kinds of problems, like facial recognition from video and images, like human computer interactions using voice, using audio. So it's very exciting I think, but for... And also it's very, we found it's very exciting we are embedding these, we are combining these technologies together, so that's why we are using competitors you know. We didn't use YARN, because it cannot support TensorFlow or other framework, but you know, if you are using containers and if you have good scheduler, you can schedule any kind of competition frameworks. So we found it's very interesting to, to have these new frameworks, and we can combine together to solve different kinds of problems. >> John: Thanks so much for coming onto theCube, it's an operating system world we're living in now, it's a great time to be a technologist. Certainly the opportunities are out there, and we're breaking it down here inside theCube, live in Silicon Valley, with the best tech executives, best thought leaders and experts here inside theCube. I'm John Furrier with George Gilbert. We'll be right back with more after this short break. (upbeat percussive music)

>> Voiceover: Live from San Francisco, it's theCUBE! Covering Oracle OpenWorld 2016, brought to you by Oracle. Now here's your hosts, John Furrier and Peter Burris. >> Welcome back everyone, we're here live in San Francisco for Oracle OpenWorld 2016. This is SiliconANGLE Media's theCUBE, our flagship program We go out to events and extract the signal noise. Three days of coverage, wall to wall, ending up day one right now. Wrapping up amazing day. I'm John Furrier with my co-host Peter Burris. Our next guest is Senior Vice President of Oracle Cloud, Steve Daheb. CUBE alumni, great to see you again! >> I have four times, four time alum. >> (Mumbles) the MVP award for most times on theCUBE. You've been there almost for a couple years now. >> Yeah. >> Peter: Yeah, you and Alec Baldwin. (laughter) >> Yeah, less than two years, it's exciting. >> So you are working hard. Last time I saw you like, you have to be running harder. You're running harder. >> Yeah, we were in DC together. >> You've been running really hard, so congratulations. Saw the numbers, 70% growth percentage. Not numbers, I don't remember the eh, four billion. >> Numbers are getting bigger, percentages are still going up, so it's good. >> Percentages are double digits, but the real big thing is that you guys now are putting a dent into the awareness of Oracle being a viable and competing opportunity against Amazon Web Service. Larry Ellison said "Amazon, your lead is no more." Which was a headline in SiliconANGLE. So question, how are you guys continuing to differentiate yourself against AWS and Microsoft? >> I think there's three things. One is we differentiate when we look holistically in cloud. 'Cause you know you talk about cloud, and people define it in multiple different ways. Some say oh, Salesforce is cloud, or Amazon is cloud. And we define it as really requiring all three layers of the stack. So Software as a Service, which we can talk about. Platform as a Service, which is that core database middleware application development. And then the Infrastructure as a Service. And we're seeing at some points all these things are interrelated. When does past-op and IS begin? What's a discrete IaaS motion and how does that move to sort of production databases and different things? And so we first and foremost differentiate by looking holistically at what we're offering, and then sharing that we have a complete portfolio that's also open and provides choice to customers in terms of how to deploy it. >> Holistic, end to end holistic or holistic breadth? >> I think it's both. So we look at where we go deep into all layers of the cloud, and then we'll look holistically around a hybrid solution that allows people to deploy in cloud and on prem. And that's where we can differentiate with Amazon. So you know, at a technology perspective, Larry announced some incredible things in terms of we have the benefit of coming in and re-defining what an IaaS architecture looks like and provide scale and performance as well as cost. We provide choice in terms of, look, if I deploy something on Amazon, I can't actually move that back to what's on prem. You can't actually have isolated orphaned sort of instances on public cloud without tying that back to what's on prem. And then you just look at some of the database examples. It's a fork of an old code. I mean, it's not compatible with anything so I can run Oracle database on Amazon, I can run Oracle database on Oracle, I can run Oracle database in Microsoft. I can run Amazon on Amazon. I can't inter-operate with DV2, with SQL, with Oracle, with Teradata, so I think we're just sort of trying to demystify a little bit of what's going on out there. >> But one of the ways was talk about work loads moving between on prem, that's going to get that right 100% across the board. >> Absolutely. >> It's interesting, but I got to ask you. Larry Ellison said on the earnings call last Thursday after Safra and then Mark Hurd made their announcements and man, sounded like things were going amazing. The earnings call was like woohoo, oh my God, the Kool-Aid injection! Then Larry got on, but he said a really cool thing I wanted to just drill down on. He said we're not even getting started yet. We are playing the long game is what he's obviously saying. But he made a comment about Microsoft. He said Microsoft is already well into moving their install base and apps onto Azure. >> Yeah. >> And Oracle hasn't even begun getting started. Now, I'm sure you started, but implying significantly that a lot of the database customers and customers haven't really moved there yet. Is that true? How would you (mumbles). >> It's actually interesting, 415 Research just actually published a study and they said only 6% of workloads are actually running in public cloud infrastructure today. And IDC just actually put out a note that said only 6% around database and analytics. So I think we're actually showing up with the right solution at the right time. And we have 4,000 database customers, we're in a great position to move them to cloud. >> So is Larry right, that a large portion haven't moved yet, and Microsoft, larger have moved? >> Yeah, I think that the majority hasn't. I think that the analogy he was drawing is think about Microsoft that can move their office suite. Take 365 and move that to cloud, or things like SharePoint and move that to cloud. I think what he's saying is look at that analogy in terms of who's in the best position to migrate these database customers to cloud, and we believe Oracle is. And again, it is early days overall. There's a lot of noise about what the cool kids are out there doing, but when you think about it, 90% of these. >> The cool kids are making money. >> The cool kids are making money, Oracle is making money too. >> Of course, that's what I brought a (mumbles). You had a question, sorry to interrupt. >> Well yeah, no, really quickly. So in many respects, it sounds like what you're saying is that you can do what Amazon can do, but Amazon still can't do what you can do. >> Yeah, I think that's right. I mean, I think we're coming out and saying look, if you look at it, the application layer, they don't have anything. And so again, we have core ERP, HCM, supply, sales, service, all these things that we've shipped it to cloud. We actually do 45 billion transactions a day and support 30 million unique users weekly on our cloud. We're a viable cloud. These are core financial systems that companies use to run their business. We've been running in cloud for a while. We have the PaaS layer, our database, our middleware, the analytics, the security, things like IOT, that's core to Oracle's DNA. And then yeah, you have this commodity compute infrastructure. If you look at Amazon, 86% of their business is still about commodity compute. So we can offer that for customers as part of the overall solution. And I know they've been talking about getting it to the database so I would say stay tuned to what Larry has to say tomorrow on that. But we believe holistically when you look at all the pieces, we provide that solution that those 95% of workloads that haven't moved to cloud yet actually really need. >> So that brings up a good point. Cloud world, you mentioned DC where we had your special event, theCUBE was broadcasting live in DC. There all up on youtube.com/siliconangle. >> Shameless plug, shameless plug. >> Of course, get that last minute in there. But I want to ask you (mumbles) you announced the Cloud at Customer >> Yeah. >> So what's the status of that, 'cause we get lost in the slew of announcements here at Oracle OpenWorld. What's the update? Doing well? Reaction from customers? >> It's doing really well. It actually solves a big, again, that problem we talked about. I want to consume public cloud services, but I might have regulatory data sovereignty sort of industry or it might just be my own internal governance that's not going to allow me to deploy that, consume public cloud services on somebody else's cloud, but I can consume it with Cloud at Customer. >> Is it a transition point, because they feel good about this, they get some stability with the Cloud on Customer? Is it a transition point, is it a fixture, is it a blanky? Is it their binky? >> I think it could be both. I think it could be a transition point. I think for some customers again, depending on where they are, where they live, what type of industry, what type of data we're talking about, that might be the way they're going to consume it. Whereas I have data sovereignty laws, I can't actually move anything to cloud unless those change, but it still allows me to consume cloud in a cloud-like fashion subscription basis. Same identical services that we have in our public cloud, but just have it behind their firewall. >> So today's announcements featured partners pretty strong, and Oracle's always had a pretty big ecosystem. It's one of the key reasons for your success. And a lot of the partners out there would like themselves to start getting into the cloud, by offering services to their customers using a lot of what you're doing from a standpoint of moving your enterprise customers forward. As Oracle looks out at the landscape, you see Oracle, AWS, you're going to compete aggressively for that. But also your partners are going to step up, and they're going to offer their own cloud services. What about your customers? Do you anticipate seeing branded cloud services from your customers as they engage their customers differently through digital means? >> Yeah, that's actually a great question. I do think, yeah, a lot of our customers actually have their own services that they provide to end users. And I would say first, to back up, I think again it's about providing choice to our customers so they can engage within Oracle. They can engage with our partners on not only our technology, but maybe how do I migrate to cloud? How do I consume it in different ways? Also take a more solutions-based approach. (intercom blares) So if I'm looking at. Aw, we just got hit with that. Are they shutting this thing down in a few minutes? >> No no, we're good. >> A 16 ton thing's going to drop on the table. >> What is happening here? >> The Monty Python foot is going to come down on us. >> That's right. >> I thought that was a CUBE announcement sort of coming up. >> CUBE, Steve Daheb is on theCUBE! >> We should be announcing that. So I think that again, enabling the ecosystem to provide solutions. And I think as customers provide their own branded solutions, hopefully that's based on Oracle Cloud services and it's something that they can just re-brand, maybe augment, customize, and deploy for their own customers. >> They're giving us the bell here, but I want to get one last word in, we've got a little noise factor going on here. >> This is alright, man. >> The Infrastructure as a Service really is the third leg of the stool here for you guys. Big push here, you have the SaaS business on the press release. Second year in a row, Oracle has sold more SaaS and PaaS than any other cloud service provider. I think Larry used the word combined. Not sure I agree with that, but I haven't looked up the numbers, so I haven't fact-checked that. But then the next one comes down here as the second generation infrastructure that does twice the compute, twice the memory, four times the storage, 10 times more IO, 20% in price lower than Amazon Web Services. It's a new opportunity for Oracle to layer on top of our rapidly growing SaaS and PaaS. How are you going to layer infrastructures on top of PaaS and Saas? Isn't it the other way around? >> Yeah, I think it, yeah, sort of how do you look at it. They're tightly integrated. There's different sorts of entry points for IaaS. There could be discrete compute, but we think ultimately we see a lot of pull through from PaaS. So I might be deploying Oracle database but I'm doing it on a non-Oracle sort of application here. So I move the database to cloud and I pull compute to support that. And then from a software perspective, as Mark would say and Larry would say, we actually when we sell SaaS, you know, Software as a Service, we're selling that full stack to go along with it. >> Well, put it this way, that a database buyer looks at IaaS and sees infrastructure. An applications seller looks at the database and sees infrastructure. And so as you said, it's really what your perspective is. Containers is going to make it even more complex. >> Yeah, I agree. But it's interesting, 'cause I think ultimately that's the more strategic way that this is going to be consumed. I don't think you walk into somewhere, you say hey, you want some compute? We got some compute. Maybe more on the storage archive position, but when you look at the application development, when you look at applications, when you look at migrating databases, I think that's where you're going to pull through the infrastructure, and so that's why we're focused on offering all three layers of the cloud. >> There's definitely a trend towards enterprise-grade cloud, I was seeing that here at Oracle and at VMworld. We were just at theCUBE there. You're seeing this shift, they're getting out of the cloud game, so they're a different strategy. But Pat Gelsinger when I asked, pressed him on Amazon Web Service, saying did Amazon Web Service kind of force your hand? He kind of called it the developer cloud. That's how he called the Amazon Web Services. But they have developers. So my question to you is what's the strategy for developers? 'Cause at the end of the day we're seeing, talking to the VC certainly that was just on, there's going to be a mobile explosion of enterprise developers for mobile, cloud, lot of white space. You guys have an ecosystem, you have PaaS that's developer friendly. >> It is very developer friendly. >> What do you do with developers? Give us the update. What specifically are you guys doing in market. >> We have a big focus you're going to see with respect to developers. We've had Java developers that have been an incredible community for years and we've been serving them for years. I think Judy, before Larry took the stage, announced Oracle Code, which is going to be a multi-city road show where can get together. We're going to provide them access to Oracle Cloud, allow them to develop in multiple type tools, which I think was an important part of the announcement as well. Larry's saying look, it's not just about Java. It's about Ruby, it's about Python, it's about Node.js, it's about having an open platform that supports all developers. Tools like application containers and some of the other things. >> How would you grade you guys now? Not well suited for developers? Certainly Java you have developer community. But in market when you bring it to customers, is there a developer program that you guys have in motion? What's in the market? >> We do have things in motion. There's a developer program today and we continue to expand in that community. So we move away from just maybe traditionally Oracle developers to a broader set of developers. I think giving them a robust enterprise-grade platform, that gives them choice. So you're going to see a lot, hopefully we'll see you guys on the road at some of these events. But we're going to go out. >> There's a huge demand for developers to create opportunity in the ecosystem. I know you got to go, better wrap up. Thanks for spending the time. >> No thanks, a great way to wrap up the day. >> Congratulations, I know you're running hard. You look great, nice watch again. Yeah, flash the watch. >> I just miss the pocket square that you guys had in DC, I got to get that right next time. >> Best dressed man at Oracle. We are here live at theCUBE in San Francisco. I'm John Furrier, Peter Burris. Day one of coverage, three days wall-to-wall here live. TheCUBE, Thanks for watching.