(upbeat music) >> The innovation around databases has exploded over the last few years. Not only do organizations continue to rely on database technology to manage their most mission critical business data. But new use cases have emerged that process and analyze unstructured data. They share data at scale, protect data, provide greater heterogeneity. New technologies are being injected into the database equation. Not just cloud which has been a huge force in the space, but also AI to drive better insights and automation, blockchain to protect data and provide better auditability, new file formats to expand the utility of database technology and more. Debates are bound as to who's the best number one, the fastest, the most cloudy, the least expensive, et cetera. But there is no debate, when it comes to leadership and mission critical database technologies. That status goes to Oracle. And with me to talk about the developments of database technology in the market is cube alum Juan Loaiza, who's executive vice president of Mission Critical Database Technology at Oracle. Juan always great to see you, thanks for making some time. >> Thanks, great to see you Dave, always a pleasure to join you. >> Yeah and I hope you have some time because they've got a lot of questions for you. (chuckles) I want to start with- >> All right I love questions. >> Good I want to start and we'll go deep if you're up for it. I want to start with the GoldenGate announcement. We're covering that recent announcement, the service on OCI. GoldenGate it's part of this your super high availability capabilities that Oracle is so well known for. What do we need to know about the new service and what it brings for your customers? >> Yeah, so first of all, GoldenGate is all about creating real time data throughout an enterprise. So it does replication, data integration, moving data into analytic workloads, streaming analytics of data, migrating of databases and making databases highly available. All those are use cases for real-time data movement. And GoldenGate is really the leading product in the market, has been for many years. We have about 80% of the global fortune 500 running GoldenGate today, in addition to thousands and thousands of smaller customers. So it is the premier data integration, replication, high availability, anything involving moving data in real time, GoldenGate is the premier platform. And so we've had that available as a product for many years. And what we just recently done is we've released it as a cloud service, as a fully managed and automated cloud service. So that's kind of the big new thing that's happening right now. >> So is that what's unique about this, is it's now a service, or there are other attributes that are unique to Oracle? >> Yeah, so the service is kind of the most basic part to it. But the big thing about the service is it makes this product dramatically easier to use. So traditionally the data integration, replication products, although very powerful, also are very complex to use. And one of the big benefits of the service is we've made a dramatically simpler. So not just super experts can use it, but anyone can use it. And also as part of releasing it as a cloud service, we've done a number of unique things including making it completely elastically scalable, pay per use and dynamic scalability. So just in time, real time scalability. So as your workload increases we automatically increase the throughput of GoldenGate. So previously you had to figure all this stuff out ahead of time. It was very static. All these products have been very static. Now it's completely dynamic a native cloud product and that's very unique in the market. >> So, I mean, from an availability standpoint, I guess IBM sort of has this with Db2 but it doesn't offer the heterogeneity that GoldenGate has. But at what about like AWS, Microsoft, Google, do they provide services like, like GoldenGate? >> There's really nothing like the GoldenGate service. When you're talking about people like Google and Azure, they really have do it yourself third-party products. So there'll be a third party data integration replication product, and it's kind of available in their marketplace and customers have to do everything. So it's basically a put it together, your own kit. And it's very complicated. I mean these data integration products have always been complicated, and they're even more complicated in the cloud, if you have to do everything yourself. Amazon has a product but it's really focused on basic data migration to their cloud. It doesn't have the same capabilities as Oracle has. It doesn't have the elasticity, it doesn't have pay peruse, so it's really not very clavy at all. >> Well, so I mean the biggest customers have always glommed onto GoldenGate because they need that super ultra high availability. And they're capable of do it yourself. So, tell us how this compares to two DIY. >> Yeah, so you have mentioned the big customers so you're absolutely right. The big customers have been big users of GoldenGate. Smaller customers or users as well, however, it's been challenging because it's complicated. Data integration has been a complicated area of data management. More and most complicated. And so one of the things this does, is that it expands the market. Makes it much dramatically easier for smaller companies that don't have as many it resources to use the product. Also, smaller companies obviously don't have as much data as the really large giants. So they don't have as much data throughput. So traditionally the price has been high for a small customer. But now, with pay per use in the cloud, it eliminates the two big blockers for smaller enterprises. Which are the costs, the high fixed costs and the complexity of the products. So in which, by the way, it's helpful for everyone also. And for big customers they've also struggled with elasticity. So sometimes a huge batch job will kick in, the rate of change increases and suddenly the replication product doesn't keep up. Because on-prem products aren't really very elastic. So it helps large customers as well. Everybody loves these reviews but the elasticity pay per use, on demand nature of it's really helpful for everybody. >> Well, and because it's delivered as a service I would imagine for the large customers that you're giving them more granularity, so they can apply it maybe for a single application, as opposed to trying to have to justify it across a whole suite. And because the cost is higher, but now if you're allowing me to pay by the drink, is that right? I could just sort of apply it in a more granular level. >> Yes, that's exactly right. It's really pay per use. You can use it as much or as little as you want. You just pay for what you use. And as I mentioned, it's not a static payment either. So if you have a lot of data loads going on and right now you pay a little more, at night when you have less going on, you pay a lot less. So you really just paying for what use. It's very easy to set it up for a single application or all your applications. >> How about for things like continuous replication or real-time analytics, is the service designed to support that? >> Yes, so that's the heritage of GoldenGate. GoldenGate has been around for decades and we've worked with some of the most demanding customers in the world on exactly those things. So real time data all over the enterprise is really the goal that everyone wants. Real-time data from OTP and to analytics, from one system to another system, and for availability. That is the key benefit of GoldenGate. And that's the key technology that we've been working on for decades. And now we have it very easy to use in the cloud. >> Well what would be the overheads associated with that? I mean, for instance, you've go it, you need a second copy. You need the other database copies, and where does it make sense to incur that overhead? Obviously the super high availability apps that can exploit real time. Think like fraud detection is the obvious one, but what else can you add there? >> Well, GoldenGate itself doesn't require any extra copies of anything. However, it does enable customers that want to create for example, an analytics system, a data warehouse, to feed data from all their systems in real time into that data warehouse for example. And it also enables the real-time capabilities, enable high availability and you can get high availability within the cloud with it, between on premises in the cloud, between clouds. Also, you can migrate data. Migrate databases without having to take them down. So all these capabilities are available now and they're very easy to use. >> Okay. Thanks for that clarification. What about autonomous? Is that on the roadmap or what you thinking? >> Yeah, the GoldenGate is essentially an autonomous service. And it works with the Oracle Autonomous Database. So you can both use it as a source for data and as a sink for data, as a place you're writing data. So for example, you can have an autonomous OTP database, that's replicating to another autonomous OTP database in real time. And both of them are replicating changes to the autonomous data warehouse. But it doesn't all have to be autonomous. You can have any mix of, autonomous not autonomous, on-prem in cloud, in anybody's cloud. So that's the beauty of GoldenGate, It's extremely flexible. >> Well, you mentioned the plasticity a couple of times. I mean, why is that so important that that GoldenGate on OCI gives you that elastic, whatever billing the auto-scaling talk, talk to me in terms of what that does for the customer. >> Yeah, there's really two big benefits. One benefit is it's very difficult to predict workloads. So normally on an on-prem configuration, you have to say, okay what is the max possible workload that's going to happen here? And then you have to buy the product, configure the product, get hardware, basically size, everything for that. And then if you guess wrong, you're either spending too much because you oversized it or you have a big data real-time problem. The data can't keep up with the real-time because you've undersized the configuration. So that's hard to do. So the beauty of elasticity and the dynamic elasticity, the pay per use, is you don't have to figure all this stuff out. So if you have more workload, we grow it automatically. If you have less workload, we shrink it automatically. And you don't have to guess ahead of time. You don't have to price ahead of time. So you, you just use what, what you use, right? You don't pay for something that you're not using. So it's a very big change in the whole model of how you use these data, replication, integration, high availability technologies. >> Well, I think I'm correct to say GoldenGate primarily has been for big companies. You mentioned that small companies can now take advantage of this service. We talked about the granularity. And I could definitely see, can they afford it? I guess this is part one and then, and then the other part of the question is, I can see GoldenGate really satisfying your on-prem customers and them taking advantage of it, but do you think this will attract new customers beyond your core? So two part question there. >> Yeah, absolutely. So small customers have been challenged by the complexity of data integration. And that's one of the great things about the cloud services is it's dramatically simpler. So Oracle manages everything. Oracle does the patching, the upgrades. Oracle does the monitoring. It takes care of the high availability of the product. So all that management, complexity, all the configuration set up, everything like that, that's all automated, that's owned by Oracle. So small customers were always challenged by the complexity of product, along with everything else that they had to do. And then the other of course benefit is small customers were challenged by the large fixed price. So now with pay per use, they pay only for what they use. It's really usable by easily by small customers also. So it really expands the market and makes it more broadly applicable. >> So kind of same answer for beyond your existing customer base, beyond the on-prem that that's kind of... You answered >> Right. >> my two part question with one answer, so that was pretty efficient, (chuckles) pun intended. So the bottom line for me and squinting through this announcement is you've got the heterogeneity piece with GoldenGate OCI and as such it's going to give you the capability to create what I'll call an architecturally coherent decentralized data mesh. Big on this data mesh these days, could have decentralized data. With the proviso then I going to be able to connect to OCI, which of course you can do with Azure or I guess you could bring cloud to a customer on prem, first of all, is this correct? And can we expect you over time to do this with AWS or other cloud providers? >> It can move data from Amazon or to Amazon. It can actually handle, any data wherever it lives. So, yeah, it's very flexible and it's really just the automation of all the management, that we're running in our public cloud But the data can be from anywhere to anywhere. >> Cool, all right, let's switch topics here a little bit. Just talk about some of the things that you've been working on, some of the innovation. I sat through your blockchain announcement, it was very cool. Of course I love anything blockchain and crypto, NFTs are exploding, so that Coinbase IPO. It's just really an exciting time out there. I think a lot of people don't really appreciate the innovation that's occurring. So you've been making a lot of big announcements last several months. You've been taking your R and D bringing it into product, So that's great, we love to always see that because that's where really the rubber meets the road. Just for the database side of the house, you announced 21c the next generation of the self-driving data warehouse, ADW, blockchain tables, now you got GoldenGate running on OCI. Take us inside the development organizations. What are the underlying drivers other than your boss. >> When we talk about our autonomous database, it is the mission critical Oracle database, but it's dramatically easier to do. So Oracle does all the management all on automation, but also we use machine learning to tune, and to make it highly available, and to make it highly secure. So that that's been one of our biggest products we've been working on for many years. And recently we enhanced our autonomous data warehouse taking it beyond being a data warehouse to complete a data analytics platform. So it includes things like ETL. So we built ETL into the autonomous data warehouse. We're building our GoldenGate replication into autonomous data warehousing. We built machine learning directly natively into the database. So now, if someone wants to run some machine learning they just run a machine learning queries. They no longer have to stand up a separate system. So a big move that we've been making is, taking it beyond just a database to a full analytic platform. And this goes beyond what anyone else in the industry is doing, because we have a lot more technology. So for example, the ML machine learning directly in the database, the ETL directly in the database. The data replication is directly in the database. All these things are very unique to Oracle. And they dramatically simplify for customers how they manage data. In addition to that, we've also been working in our database product. We've enhanced it tremendously. So our big goal there is to provide what we call it converged database. So everything you need, all the data types. Whether it's JSON, relational, spatial, graph, all that different kinds of data types, all the different kinds of workloads. Analytics, OTP, things like blockchain, microservices events, all built into the Oracle database, making it dramatically easier to both develop and deploy new applications. So those are some of our big, big goals. Make it simple, make it integrated. Take the complexity, we'll take on the complexity. So developers and customers find it easy to develop an easy to use. And we've made huge strides in all these areas in the last couple of years. >> That's awesome. I wonder if we could land on blockchain again for now it's kind of jogging, but sort of on crypto. Though you're not about crypto but you are about applying blockchain. Maybe you can help our audience understand what are some of the real use cases where blockchain tech can be used with Oracle database. >> Yeah, so that's a very interesting topic. As you mentioned, blockchain is very currently, we see a lot of cryptocurrencies. I distributed applications for blockchain. So in general, in the past, we've had two worlds. We've had the enterprise data management world and we've had the blockchain world. And these are very distinct, right? And on the blockchain side the applications have mostly centered around, distributed multi-party applications, right? So where you have multiple parties that all want to reach consensus and then that consensus is stored in a blockchain. So that's kind of been the focus of blockchain. And what we've done is very innovative. We're the first company to ever do this. Is we've taken the core architecture, ideas. And really a lot of it has to do with the cryptography of blockchain. And we've built, we've engineered that natively into the mainstream Oracle database. So now in mainstream Oracle database, we have blockchain technology built in. And it's very dramatically simpler to use. And the use cases, you asked about the use case, that's what we've done. And it's taken us about five years to do this. Now it's been released into the market in our mainstream 19c Oracle database. So the use case is different from the conventional blockchain use case. Which I mentioned was really multi-party consensus based apps. We're trying to make blockchain useful for mainstream, enterprise and government applications. So any kind of mainstream government application, or enterprise application. And that idea of blockchain, the core concept of blockchain, is it addresses a different kind of security problem. So when you look at conventional security, it's really trying to keep people out. So we have things like firewalls, passwords, networking cryption, data encryption. It's all about keeping bad people out of the data. And there's really two big problems that it doesn't address well. One problem is that there's always new security exploits being published. So you have hackers out there that are working overtime. Sometimes they're nation States that are trying to attack data providers. And every week, every month there's a new security exploit that's discovered and this happens all the time. So that's one big problem. So we're building up these elaborate walls of protection around our core data assets. And in the meantime, we have basically barbarians attacking on every side.(chuckles) And every once in a while, they get over the walls and this is just what's happening. So that's one big problem. And the second big problem is elicit changes made by people with credentials. So sometimes you have an insider in your, in your company. Whether it's an administrator or a sales person, a support person, that has valid credentials, but then uses those valid credentials in some illicit way. They go out and change somebody's data for their own gain. And even more common than that cause there's not that many bad guys inside the company to they exist, is stolen credentials. So what's happened in many cases is hackers or nation States will steal for example, administrative credentials and then use those administrative credentials to come into a system and steal data. So that's the kind of problem that is not well addressed by security mechanism. So if you have privileges security mechanism says, yeah you're fine. If somebody steals your privileges, again you get the pass through the gate. And so what we've done with blockchain is we've taken the cryptography elements of blockchain. We call it crypto secure data management. And we've built those into the Oracle database. So think of it this way. If someone actually makes it through over the walls that we built, and in into the core data, what we've done with that cryptographic technology of blockchain, is we've made that immutable. So you can't change it. So even if you make it over the gate you can't get into the core data assets and change those assets. And that's not built into Oracle databases is super easy to adopt. And I think it's going to really enhance and expand the community of people that can actually use that blockchain technology. >> I mean, that's awesome. I could talk all day about blockchain. And I mean, when you think about hackers, it's all there. They're all about ROI, value over cost. And if you can increase the denominator they're going to go somewhere else, right? Because the value will will decline. And this is really the intersection of software engineering cryptography. And I guess even when you bring crypto currency into it, it's like sort of the game theory. That's really kind of not what you're all about, but the first two pieces are really critical in terms of just next generation of raising that security hurdle. Love it. Now, go ahead. >> Yeah it's a different approach. I was just going to say, it's a different approach. Because think about trying to keep people out with things like passwords and firewalls, you can have basically bugs in that software that allow people to exploit and get in. When you're talking about cryptography, that's math, it's very difficult. I mean, you really can't fight pass math. Once the data is cryptographically protected on a blockchain, a hacker can't really do anything with that. It's just, math is math. There's nothing you can do to break it, right. It's very different from trying to get through some algorithm. That's really trying to keep you out. >> Awesome. I said, I could talk forever on this topic. But let me, let me go into some competitive dynamics. You recently announced Autonomous Data Warehouse. You've got service capabilities that are really trying to appeal to the line of business. I want to get your take on that announcement and specifically how you think it compares name names. I'm going to name names you don't have to. But Snowflake, obviously a lot of momentum in the marketplace. AWS with Redshift is doing very, very well. Obviously there are others. But those are two prominent ones that we've tracked in our data shows that have momentum. How do you compare? >> Yeah, so there's a number of different ways to look at the comparison. So the most simplest and straightforward is there's a lot more functionality in Oracle data warehousing. Oracle has been doing this for decades. We have a lot of built-in functionality. For example, machine learning natively built into the database makes it super easy to use. We have mixed workloads, we have spatial capabilities. We have graph capabilities. We have JSON capabilities. We have a microservice capabilities. We have-- So there's a lot more capabilities. So that's number one. Number two, our cloud service is dramatically more elastic. So with our cloud service all you really do, is you basically move the slide. You say hey, I want more resources, I want less resources. In fact, we'll do that automatically, that's called auto-scaling. In contrast when you look at people like Snowflake or Redshift they want you to stand up a new cluster. Hey you have some more workload on Monday, stand up another cluster and then we'll have two sets of clusters or maybe you'd want a third cluster, maybe you want a fourth cluster. So you end up with all these different systems which is how they scale. They say, hey, I can have multiple sets of servers access the same data. With Oracle you don't have to even think about those things. We auto scale, you get more workload. We just give it more resources. You don't even have to think about that. And then the other thing is we're looking at the whole data management end to end problem. So starting with capturing the data, moving the data in real time, transforming the data, loading the data, running machine learning and analytics on the data. Putting all kinds of data in a single place that you can do analytics on all of it together. And then having very rich screen capabilities for viewing the data, graphing the data, modeling the data, all those things. So it's all integrated. It makes it super easy to use. So a much easier, much more functionality and much more elastic than any of our competitors in the market. >> Interesting, thank you for those comments. I mean, it's a different world, right? I mean, you guys got all the market share, they got all the growth, those things over time, you've been around, you see it, they come together and you fight it out and may the best approach wins. >> So we'll be watching >> Yeah also I forgot to mention the obvious thing, which is Oracle runs everywhere. So you can run Oracle on premises. You can run Oracle on the public cloud. You can run what we call cloud at customer. Our competitors really are just public cloud only. So you customers don't get the choice of where they want to run their data warehouse. >> Now Juan a while ago I sat down with David foyer and Mark steamer. We reviewed how Gartner looks at the marketplace and it wasn't surprise that when it came to operational workloads, Oracle stood out. I mean, that's kind of an understatement relative to the major competitors. Most of our viewers, I don't think expected for instance Microsoft or AWS to be that far away from you. But at the same time, the database magic quadrant maybe didn't reflect that gap as widely. So there's some dissonance there with the detailed workload drill downs were dramatic. And I wonder what your take on the results. I mean, obviously you're happy with them. You came out leading in virtually every category or you will one and two, and some of that sort of not even non-mission critical operational stuff. But what can you add to my narrative there? >> Yeah, so Gartner, first of all, we're talking about cloud databases. >> Right. >> Right, so this is not on premises databases this is pure cloud databases. And what they did is they did two things. One is, the main thing was a technical rating of the databases, of the cloud databases. And, there's other vendors that have been had database in the cloud for longer than we have. But in the most recent Gartner analysis report, as you mentioned, Oracle came out on top for cloud database technology, in almost every single operational use case including things like Internet of Things, things like JSON data, variable data, analytics as well as a traditional OTP and mixed workloads. So Oracle was rated the highest technology which isn't a big surprise. We've been doing this for decades. Over 90% of the global fortune 500 run Oracle. And there's a reason, because this is what we're good at. This our core strength. Our availability, our security, our scalability, our functionality, both for OTP and analytics. All the capabilities, built-in machine learning, graph analytics, everything. So even when we compare narrowly things like Internet of Things or variable data against niche competitors that that's what all they do. We came up dramatically ahead. But what surprised a lot of people is how far ahead of some of the other cloud vendors like Amazon, like Azure, like Google, Oracle came out ahead in the cloud database category. So a lot of people think, well, some of these other pure cloud vendors must be ahead of Oracle in cloud database. But actually not. I mean, if you look at the Gartner analyst report, it was very clear. It was Oracle was dramatically ahead of their cloud database technologies with our cloud database. >> So I'm pretty much out of time but last question. I've had some interesting discussions lately and we've pointed out for years in our research that of course you're delivering the entire stack, the database, part of the infrastructure the applications, you have the whole engineered system strategy. And for the most part you're kind of unique in this regard. I mean, Dell just announced that it's spinning off VMware and it could have gone the other direction. And become more integrated hardware and software player, for the data center. But look, it's working for Dell based on the reaction, from the street post announcement. Cisco they got a hardware and software model that's sort of integrated but the company's value that peaked back in the .com boom, it's been very slow to bounce back. But my point is for these companies the street doesn't value, the integrated model. Oracle is kind of the exception. You know, it's at trading at all time highs, I know you're not going to comment on the stock price, but I guess in SAP until it missed it guided conservatively, was kind of on the good trajectory. But so I'm wondering, why do you think Oracle strategy resonates with investors, but not so much those companies? Is it, because you have the applications piece? I mean, maybe that's kind of my premise for, for SAP but what's your take? Why is it working for you? >> Well, okay. I think it's pretty simple, which is some of our competitors, for example, they might have a software product and a hardware product. But mostly those are acquired in their separate products that just happen to be in a portfolio. They are not a single company with a single vision and joint engineering going on. It's really, hey, I got the software on over here. I got the hardware over there, but they don't really talk to each other, they don't really work together. They're not trying to develop something where the stack is actually not just integrated but engineered together. And that is really the key. Oracle focuses on data management top to bottom. So we have everything from our ERP, CRM applications talking to our database, talking to our engineered systems, running in our cloud. And it's all completely engineered together. So Oracle doesn't just acquire these things and kind of glue them together. We actually engineer them and that's fundamentally the difference. You can buy two things and have them as two separate divisions in your company but it doesn't really get you a whole lot. >> Juan it's always a pleasure, I love these conversations and hope we can do more in the future. Really appreciate your time. Thanks for coming to the CUBE >> Pleasure, Dave nice to talk to you. >> All right keep it right there, everybody. This is Dave Vellante for theCUBE, we'll see you next time. (upbeat musiC)

(bright upbeat music) >> Hi well, this is Dave Vellante. We're digging deeper into the world of database. You know, there are a lot of ways to skin a cat and different vendors take different approaches and we're reaching out to the technologists to get their perspective on the major trends that they're seeing in the market, 'cause we want to understand the different ways in which you can solve problems. So look, if you have thoughts and the technical chops on this topic, I'd love to interview you. Just ping me at at DVellante, on Twitter, a lot of ways to get ahold of me. Anyway, we recently spoke with Andrew Mendelsohn, who is Oracle's EVP and he's responsible for database server technologies. And we talked a lot about Oracle's ADW, Autonomous Data Warehouse. And we looked at the cloud database strategy that Oracle is taking and the company's plans and how they're different maybe from other solutions in the marketplace, but I wanted to dig deeper. And so today we have two members of Mendelsohn's team on The Cube, and we're going to probe a little bit. George Lumpkin, is the Vice President of Autonomous Data Warehouse. And Neil Mendelson is the VP of Modern Data Warehouse, that business for Oracle. They're both 20-year veterans of Oracle. When I reached out to Steve Savannah, who's a colleague of mine for many years, he's always telling me how great Oracle is relative to the competition. So I said, okay, come on The Cube and talk about this, give me your best people. And he said, whatever these two don't know about cloud data warehouse, it isn't worth knowing anyway. So with that said gentlemen, welcome to The Cube. Thanks so much for coming on. >> Thank you. >> Hey, glad to be here. >> So George, let's start with you. And maybe we could recap for some of the viewers who might not be familiar with the interview that I did with Andy. In your words, what exactly is an Autonomous Data Warehouse? Is this cloud native? Is it an Oracle buzzword? What is it? >> Well, I mean, Autonomous Data Warehouse is Oracle's cloud data warehouse. It's a service that built to allow business users to get more value from their data. That's what the cloud data warehouse market is. Autonomous Data Warehouse is absolutely cloud native. This is a huge misconception that people might have when they first sort of hear about something, this service because they think this is a Oracle database, right? Oracle makes databases. This is the same old database I knew from 10 years ago. And that's absolutely not true. We built a cloud native service or data warehousing built it with cloud features. You know, if your understanding of the cloud data warehouse market is based upon how you thought things look 10 years ago, like Snowflake wouldn't have even existed, right? You can't base your understanding of Oracle based upon that. We have a modern service that's highly elastic, provides cloud capabilities like online patching and it's fully autonomous. It's really built the business users so they don't need to worry about administering their database. >> So I want to come back and actually ask you some questions about that, but let me follow up and talk about some of the evolution of the ADW. And where did you start? I think it was 2018, maybe where you came from, where you are today, maybe you can take us through the technological progression and maybe the path you took to get here. >> And so 2018, was when we released the service and made generally available, but of course, you know we started much earlier than that. And this was started within my product management team, and other organization. So we really sat down with a blank sheet of paper and we said, what should the data warehouse in the cloud look like? You know, let's put aside everything that Oracle does for its on-prem customers and think about how the cloud should be different. And the first thing that we said was, well, you know, if Oracle writes the database software, and Oracle builds its own hardware, and Oracle has created its own cloud, why do we need customers to manage a database? And that's where the idea of autonomous database came from. That Oracle is managing the entire ecosystem. And therefore we built a database that we believe it's far and away the simplest to use simplest data warehouse in the market. And that's been our focus since we started with 2018. And that continues to be our focus, looking at more ways that we can make an Autonomous Data Warehouse as simpler and easier for business users to get more value out of their data. >> Awesome, one more question. And actually Neil, you might want to chime in on this as well. So just from a technical perspective, you know forget the marketing claims and all the BS. How do you compare ADW to the so-called born in the cloud data warehouses? You mentioned Snowflake, you know Redshift, is Redshift born in the cloud. Well, it was par XL but Amazon's done some good work around Redshift. I think big query is maybe probably a better example 'cause it was, you know, like Snowflake started in the cloud but how do you compare ADW to some of these other so-called born in the cloud data warehouses? >> I think part of this, you mentioned Redshift wasn't important in the cloud. It was, you know, a code base taken from a prior company that was on-premise company. So they adapted it to the cloud, right? And you know, we have done, as George said, much of the same, which is, you know, our starting point was not you know another company's code base, but our starting point was our own code base. But as George said, it's less about the starting point and it's more about where you envision the end point, right? Which is that, you know, whatever your starting point is, I think we have a fundamental different view of the endpoint. Amazon talks about how they're literally built for you know, a cloud built for developers, right? You know, builders, right? And you know Oracle wasn't first in the infrastructure business, we entered through applications business. And all of a sudden, you know we began taking on 100s of 1000s and 100s of even more customers that were SAS customers. Underneath was the database and all the infrastructure. One of the things that we took away from that was that we couldn't possibly hire enough people DBA, to manage all the infrastructure below our applications customers. So one of the things that influenced this is that, you know customers expect SAS applications to just take care of themselves, right? So we had to essentially modify the infrastructure to allow it to do so as well, right? And we're bringing that capability to those people who, you know, may or may not have an application, but their interest is, you know more of this self-service agility type of aspect. >> So it seems to me and Georgia was sort of alluding to this before. I mean, when you mentioned Snowflake a couple of times, and then Neil, something you just said, I'm going to pick up on is you've been around for a long time. And you know, when I talked to the Snowflake people, they know Oracle, a lot of them came from Oracle. They understand I think how you can't just build Oracle overnight and build in the capabilities that Oracle has and the recovery. And you talk to customers and you know you are the gold standard of, you know especially mission critical databases, so I get that. But now you just sort of hit on it, is it takes a lot of people and skill to run the database. So that's the problem that you're saying you were attacking, is that, am I getting that right? >> Right, right, so the people that you talked about who originally built Snowflake came from Oracle, but they came from Oracle more than a decade ago. So their context is over a decade old, right? In the meantime, we've been busy, you know building a economies and many other capabilities, right? Their view of Oracle is that view that was back more than 10 years ago, right? They're still adding capability. So a really good example of this illustration is Oracle as you said, it's the most capable system that's out there and has been for many years. We've been focusing on how do we simplify that and how do we use machine learning embedded within the system itself? Because core to the concept of autonomous is that inside, is this machine learning system that's continually improving, right? That's the whole notion. Where in Snowflakes case, they're still adding functionality. Last year, they added masking which you know functionality they didn't have, but when they added the capability, they added it without, you know, the ability for a business user to actually take advantage of it. There's no capability for a business user to actually find the information that needs to be masked. And then after the information is found, you require a technical person to actually implement the mask. In Oracle's case, we've had masking and those capabilities for a long time, our focus was to be able to provide a simple tool that a business user can use that doesn't need technical or security experience. Find the data that needs to be masked PII data, and then hit a button and have it masked for you. So, you know, they're still, you know, without this notion of a strategy to move toward the system to heal itself and to manage itself, they're just going to continue. As they continue to add more capability, they will in turn add more complexity. What we're trying to do is take complexity out while others are adding it in, its an ironic twist. >> It is an ironic twist. It is interesting to look at it. And I don't want to make this about Snowflake. But I mean, Hey, I like what they're doing. I like them. I know the management, they're growing like crazy and you know and the customers tell me, hey, this is really simple. And it's simple by design. I mean, to your point over time it's going to get, you know, more and more complex. I was talking to Andy, I think it was Andy. He was saying, you know, they've got the different sizes you've got to shape some, you know, they call it t-shirt sizes. And I was like, okay, I got a small, I got a medium and a large, maybe that's okay. But you guys would say, we give more granular you know, a scaling, I guess is the point there, right? I mean George, I don't know if you can comment on that. It just a different strategy. You've got a company that was founded well, I guess, 2015 versus one that was founded in 1977. So you would think the latter has, you know way more function than the former, but George, anything you'd add to this conversation? >> Yeah, I mean, I'm always amazed that there are these database systems that are perceived as cloud native and they do things like sell you database sizes by t-shirt sizes, as you described. I mean, if you look at Snowflake, it's small, medium, large extra large too extra large, but they're all factors of two. You're getting a size of your database of two, four, eight, six, 32, et cetera. Or if you look at AWS Redshift, you're buying your database by the nodes. You say, how many nodes do you want? And in both those cases, this is a cloud native. This is saying we have some hardware underneath our database and we need you, Mr. Customer, to tell us how many servers you want. That's not the way the clouds should work, right? And I think this is one of the things that we did with Autonomous Data Warehouse. We said, no, that's not how the rules should work. We still run our database on hardware, we still have nodes and servers. We should tell the customer, how many CPU's you would like for your data warehouse? You want 16? Sounds good. You want 18? Yeah, we can give you 18. We're not, you know, we're not selling these to you in bundles of eight or bundles of six or powers of two. We'll sell you what you need. That's what cloud elasticity should be. Not this idea that oh, we are a database that should be managed by IT. IT already knows about servers and nodes. Therefore it's okay if we tell people your cloud data warehouse runs on nodes. Within Oracle as Neil said, we wouldn't. The data warehouse should be used by the people who want to actually analyze their data, should be used by the business users. >> Well, and so the other piece of cloud native that has become popular, is this idea of separating compute from storage and being able to scale those two independent of each other which is pretty important, right? Because you don't want to have to pay for a chunk of compute if you don't need the storage and vice versa. Maybe you could talk about that, how you solve that problem, to the extent that you solve that problem. >> Absolutely, we do separate compute print storage with Autonomous Data Warehouse. When you come in and you say, I need 10 CPU's for my data warehouse and I need two terabytes of storage. Those are two dependent decisions that you make. So they're not tied together in any way. And, you are exactly right, Dave, this is how things should work in the cloud. You should pay for what you need, pay for what you use, not be constrained by having big sets of storage you have to use for a given amount CPU or vice versa. >> Okay, go ahead Neil, please. >> Oh, just to add on to that, you know, the other aspect that comes into play is that, you know, so your starting point is X, whatever that happens to be. Over time that changes. And we all know that workloads vary right throughout the day throughout the month, throughout the year by various events that occur maybe the close of the year, close of business at the end of the quarter, it maybe you know, holiday season for retailers and so forth. So, you know, it's not only the starting point, but how do you actually manage the growth, right? scaling up and scaling down, right? In our case, we tried, as George said, we abstracted that completely for the customer basically said check a box, which has auto scale. So, if the system is required more resources, will apply more resources. And we do so instantaneously without any downtime whatsoever, right? Because you know, again, you know, people think in terms of these systems have now become business critical. So if the business critical, you can't just shut down to expand. Imagine during the holiday season is your business is ramping up. And then all of a sudden you have to scale, right? And your system either shuts down, reboots itself, right? Or it slows down to the point that it's a crawl and all your customers get frustrated. We don't do that. You click a button, auto scale and we take care of it for you smoothing out those lumps, right? Without any technical assistance. And again, if you look at Redshift, you look at all these various systems, they require technical assistance to be able to figure out not only your initial data, but how you scale out over time. >> Interesting, okay. So all is said, you know, a lot of companies are using Azure, AWS Google for infrastructure, why would these customers not just use their database? Why would they switch to Oracle or ADW? >> Well, I think Neil will probably add something. I want to start by saying a huge number of our existing Autonomous Data Warehouse customers today are customers of AWS and Azure. They are pulling data from AWS and Azure and bringing it into an Oracle Autonomous Data Warehouse. And we built feature Joe, I focused on product managers. We feel featured for that. And so it's perfectly viable and it it's almost commonplace, that the very largest enterprises to be doing that. But then coming to the question of why would they want to do it? I don't know, Neil, you want to take that? >> Yeah, yeah, so one of the things that we've really see emerge here is you know, a data warehouse doesn't generate the transactions on itself, right? So the data has to come from somewhere, right? And you ask yourself, well, where does the data come from? Well, in a lot of cases, that data is coming from applications and increasingly SAS applications that the company has deployed. And those are, you know, HR applications, you know, CRM applications, you know ERP applications and many vertical applications. In Oracle's case, what we've done is we say, okay, well, we have the application, this transactional thing, we have the infrastructure from the economist data warehouse, why don't we just make it really, really easy? And if you're an Oracle applications customer, that's already running on the Oracle cloud, we will essentially provide you the ability to create a data warehouse from that information, right? With a clicker, with largely either with a product and service or quick start kit. You don't start from scratch, you start from where you are. And there are many cases that where you are has data, very much as George mentioned before telcos, banks, insurance companies, governments, all of the data that they want to analyze, a lot of that data guess where it's coming from, it's coming from Oracle applications. So it makes sense to be able to have both the data that's generated and the data that's being analyzed close to the same place. Because at the end of the day, the payoff pitch for any form of analysis is not coming up with an insight, oh, I realized X, Y, Z, but it's rather putting the insight directly into production. And that's where, when you have this stuff spread all over God's greener trying to go from insight into action can take months, if not years. The reason that a lot of customers are now turning to us is that they need to be much more agile and they need to be able to turn that insight into action immediately without it being a science project. >> Okay, thank you for that. So let's tick them off. Like what are the top things that customers can get from Oracle Autonomous Data Warehouse, that they couldn't get from say a Snowflake or Redshift or Big query or SQL server or something yet. I appreciate you guys' willingness to talk about the competition. Let's tick them off. What are the most important things that we should know about that they can't get elsewhere? >> So first, I mean, we already talked about a couple of what we think are really the major themes of Autonomous Data Warehouse. The services is autonomous. You don't need to worry about managing it, anyone can manage the data warehouse. The service is elastic. You can buy and pay for what you use. You know, those are just what we think of as being the general characteristics of Autonomous Data Warehouse. But you know, when you come to your question of, hey, what do we give that other vendors don't provide? And I think the one angle that Autonomous Data Warehouse does a really good job is and Neil was just discussing this, it focuses on the business problems, right? We have years and years of experience with not just database security, but data security, right? You know, every cloud vendor can say, oh we encrypt all your data, we have these compliance certifications, all of these things. And what they're saying is, we are securing your database, we are securing your database infrastructure. At Oracle of course has to do those as well. But where we go further, is we say, hey, no, no, no, no, no, we know what business users want. They want to secure their data. What kind of data am I storing? Do I have PII data? Could you detect whether there's PII data and tell me about it in case some user loaded something that I wasn't aware of? What kind of privileges did I give my users? Can you make sure that those privileges are right? And can you tell me if users were given privileges that they're not using maybe I need to take them away. These are the problems that Oracle's tackled in security over the last 20 years. It's really more about the business problem. Yeah, some other, oh, go ahead. >> Oh, I'm sorry, I got so many questions for you guys. We'll get back to that 'cause it sounds like there's a long list. (laughs) >> We have nowhere to go.(laughs) I want to pick up with George on something you said about elasticity. Is it true pay by the drink? Do you have a consumption pricing? I mean, can I dial it up and dial it down whenever I want? How does that work? >> Yes, I mean not to be too many technical details, but you say, I want 14 CPU's that's what your database runs at. You can change that default number anytime you want online, right? You can say, okay, I'm coming up on my quarter end, I'm going to raise my database 20 CPU. We just do it on the ply. We just adjust the size--- >> What about the other way? What about coming down? Can I go down to one? >> You go down, you can go down to one--- >> And you're not going to charge me for 14 if I go down to one? >> No, if you set it down to one, you get charged for one, right? >> Okay, that's good, that's good. >> In the background, you know we are also allowing levels of auto scaling. You say, if you say hey, I want to charged for 14 and Oracle, can you take care of all those scaling for me? So if a bunch of people jump on at 5:00 PM, to run some queries, 'cause the executive said, hey, I need a report by tomorrow morning. We'll take care of that for you. We'll let you go beyond 14 and only charge you for exactly what you use for those extra CPU's beyond 14. >> Okay, thank you. Go ahead, Neil. >> And maybe, if we add, you know, Andy talked about this when he was on that show with you last week, right? And you know, he talked about this concept of a converged database, but let me talk about it in the way that we see it from a business point of view, right? You know, business users are looking to, you know ask a variety of questions, right? And those questions need to be able to relate to both you know, the customer themselves, the relationship that the customer might have with others. You know, today we talk about like the social network and who are influencers within that, and then where they actually conduct business. Which is really, you know, in every case, it's on some form of increasingly on a mobile device. So in that case, you want to be able to ask questions, which is not only, you know, who should I focus on, but who are the key influencers within this community, right? That could influence others? And does that happen in a particular place in time? Meaning, you know, let's say pre COVID, it might happen at a coffee shop or somewhere else. We can answer all of those questions and more inside of the autonomous system without having to replicate the data out to one system that does graph and another system that does spatial, a third system that does this. It's like a business user. It's like, wait a minute, come on, you're trying to tell me that I need a separate system and replicate the data just be able to understand location? The answer in many cases is yes, you have to have separate, which a business person says, well, that's absurd. Can't I just do this all in one system? You can with Oracle. >> So look, I'm not trying to be the snarky journalist or analyst here but I want to keep pushing on this issue. So here we are, it's 2021. It's April. We're like a third of the way through the year. And so far, nobody has come out and said, okay, we're going to deliver Autonomous Data Warehouse just like Oracle. So I asked myself, well, why is Oracle doing this? You guys answered, you know, to reduce the labor cost. But I asked myself, is this how they're solving the problem of keeping relevant a database that spans five decades? And you guys said, no, no, this is cloud native born in the cloud, you know started essentially with a new mindset. But is this a trend that others are going to follow? You know, and if so, why haven't we seen it this idea of a self-driving databases? Why is it right now unique to Oracle? What's really going on here? >> So I think there's a really interesting thing that's happening, it's not visible outside of Oracle. It's very visible for those of us who work inside of the development organization. You know, if you look at Oracle, I can tell you bad. I mean, I think it's safe to presume Oracle has the largest database development organization on the planet, right? I mean, it was kind of the largest database or large most used database for the past two decades. And what's happened is we pivoted to building a cloud platform. We're not just building a database, we're taking all of these resources that we have with all these expertise of building database software. We were saying, we now have to build the platform to run and manage the database software in the cloud, right? And it's a little bit like, you know I think to make people relate to it a little better, there was a really good quote from Elon Musk couple of years ago, talking about Tesla. Like everyone looks at the car, right? Tesla, the car is really great. The hard part of this, is building the factory, and that's analogy holds for Oracle. What we're building is the cloud battery. And what we have transitioned is our database development organization is now building as robust a cloud as possible. So that you know, when we increase the number of databases by 10 X, we don't add 10 X, more cloud ops people to manage it. We are ramping up developer building features to automate the management of our cloud infrastructure. And with that automation, we get better ability, less errors, more security. We give benefits to our cloud data warehouse customers with it. And I think this something really important to realize, right? We build database software. We build, you know, an engineered system built for databases called exit data, and we build a cloud platform. And these are really equal tiers in what we are building and developing today in 2021 from Oracle database development organization. >> Well, you mentioned exit data, I want to shift gears here a little bit and talk about we're seeing this hybrid cloud on-premises clouds, they're finally gaining some traction. I got to give props Oracle's cloud of customers really the early to that game. I think it was the first in my view anyway, true same same vision, took you guys a little while to get there but it was the right vision. And the thing I always say about Oracle people don't understand is Oracle invest in R and D, your chairman is also the CTO. You guys are serious about technical investment so you know, that's where innovation comes from. But, and we heard during your recent earnings call, we heard some positive comments on this. So what's your take on delivering autonomous data warehouse on-prem and how do you compare with say Snowflake and AWS in that area? Snowflake, Frank Slootman, I've had him on record saying we're not going to do that halfway house. Forget it, we are always going to be in the cloud. We're never going to do an on-prem installation. AWS, we'll see to date. Yeah, I don't think you can get a Redshift for instance in outposts, but maybe that'll come. But, how do you see that emerging? What's your difference there? Maybe Neil, you could talk about that. >> Yeah, so, you know, I think, you know, customers had a lot of regulated industries, right? Still have concerns about the public cloud. And I think that when you hear statements like, you know, we're never going to do, you know, on-prem. Well, economist cloud at customer, it's not a classic on-prem solution. What it is, it's a piece of our cloud delivered in your data center. It's still the cloud software. Oracle manages it, Oracle, you know, the system itself manages itself and we take care of that responsibility so you don't have to. The differences is that we can make that available in a public cloud as well as in a private cloud, right? And there are so many use cases, you know, that you can imagine from a regulatory point of view, or just from a comfort point of view, where customers are choosing, they want the ability to decide for themselves where to place this stuff as compared to only having one option, right? And you know, you look at a lot of what's happening in the emerging world where, you know, there are a lot of places in the world that may not have, you know, really really high-speed internet connections to make, you know a public cloud feasible. Well, in that case, whether you're talking about, you know an oil rig or you're talking about something else, right? We can put that capability where it needs to be close to the operation that you're talking about, irrespective of the deployment option. >> Well, let me just follow up on that because I think it's interesting that, you know Frank Slootman said that to me, I oftentimes around AWS I say, never say never 'cause they'll surprise you, right? And I've learned that with Andy Jassy, but one of the things that seems difficult for on-prem, would be to separate that compute from storage because you have to actually physically move in resources. I think about Vertica Xeon mode. It's not quite the same, same. So, I mean, in that regard, maybe you're not the same same. And maybe that dogma makes sense for some companies. For Oracle, obviously you've got a huge on-prem state, thoughts on that. >> So, you know, clearly, you know, so typically what we'll do is that we'll provide additional hardware beyond what the customer might expect and that allows them to use the capabilities of expansion, right? We also have the ability to allow the customer to expand from their cloud of customer into the public cloud as well, of which we have a lot of those situations. So we can provide a level of elasticity, even on-premises by over provisioning the systems, well not charging the customer until they use only based on what they consume, right? Combined together with the ability for us to augment their usage in the public cloud as well, right? Where others, again are constraint, right? Because they only have a single option. >> Right, well, you've got the capital resources to do that as well which is not to be overlooked. Okay, I mean, I've blown our time here but you guys are so awesome. (laughs) I appreciate the candor. So last question and George, if you want to throw in a couple of those other tick boxes, you know the differentiators, please feel free, but for both of you, if you can leave customers with the one key point or the top key points on how Oracle Autonomous Data Warehouse can really help them improve their business in the near term, what would they be? Maybe George, you could start and then Neil you bring us home. >> Yeah, I mean, I think that, as I said before, our starting point with Autonomous Data Warehouse, is how can we build a better customer experience in the cloud? And I think, and this continues throughout 2021, and I think that the big theme here is the business users should be able to get value directly from their data warehouses. We talked a few times about how a line of business user should be able to manage their own data, should be able to load their own data warehouse, should be able to start to work with their own data, should be able to run machine learning, model of build machine learning, models against that data and all of that built in, and delivered in Autonomous Data Warehouse. And we think that this is, you know we see our customer organizations large and small, the light bulbs starting to go on how easy the services to use to and how completed it is for helping business users get value from their data. And just adding onto what George said, you know, the development organization has done a tremendous job of really simplifying this cooperation. What we also tried to do that on the business side. You know, when a customer has an on-prem situation, they're looking at moving to the cloud, whether lift and shift or modernized, they're looking at costs, they're looking at risk and they're looking at time. So one of the things we look at is how do we mitigate that? How do we mitigate the cost, the risk and the time? Well, this week, I think we announced our new cloud lift program and the cloud lift program is what Oracle will provide to its cloud engineering resources around the world is that we will do, we will take the cost, the risk and the time out of the equation and Oracle will work directly with the customer or the customer's partner of choice, maybe an Accenture or Deloitte, and we will move them, right? You know, at little or no cost, most cases there's no cost whatsoever, right? We mitigate the risk because we're taking the risk on. And we've built a lot of automated tools to make that go very quickly, right? And securely, and then finally, we do it in a very very short amount of time as compared to what you would need to do with, you know 'cause there is no Redshift on-premises. There is no Snowflake on-premises. You have to convert from what you already have to that, right? And, but the company beyond the technological barriers that George talked about were also trying to smooth the operation so that a business itself can make a decision that not only did they not need the technical people to operate it, they won't need an entire consulting contract with millions of dollars in order to actually do the movement to the cloud. >> Well, guys, I really appreciate you coming on the program and again, your candor to speak openly about you know, your approach, the competitors. And so it's great having you, really really thank you for, for your time. >> Appreciate it. >> And thank you for watching everybody. Look, if you guys want to come back, go toe to toe with these guys, say the word you're always welcome to come on The Cube. One thing for sure, Oracle are serious, when it comes to database. Thank you for watching. This is Dave Vellante. We'll see you next time. (bright music)

(upbeat music) >> On February 19th of this year, Barron's dropped an article declaring Oracle, a cloud giant and the article explained why the stock was a buy. Investors took notice and the stock ran up 18% over the next nine trading days and it peaked on March 9th, the day before Oracle announced its latest earnings. The company beat consensus earnings on both top-line and EPS last quarter, but investors, they did not like Oracle's tepid guidance and the stock pulled back. But it's still, as you can see, well above its pre-Barron's article price. What does all this mean? Is Oracle a cloud giant? What are its growth prospects? Now many parts of Oracle's business are growing including Fusion ERP, Fusion HCM, NetSuite, we're talking deep into the double digits, 20 plus percent growth. It's OnPrem legacy licensed business however, continues to decline and that moderates, the overall company growth because that OnPrem business is so large. So the overall Oracle's growing in the low single digits. Now what stands out about Oracle is it's recurring revenue model. That figure, the company says now it represents 73% of its revenue and that's going to continue to grow. Now two other things stood out on the earnings call to us. First, Oracle plans on increasing its CapEX by 50% in the coming quarter, that's a lot. Now it's still far less than AWS Google or Microsoft Spend on capital but it's a meaningful data point. Second Oracle's consumption revenue for Autonomous Database and Cloud Infrastructure, OCI or Oracle Cloud Infrastructure grew at 64% and 139% respectively and these two factors combined with the CapEX Spend suggest that the company has real momentum. I mean look, it's possible that the CapEx announcements maybe just optics in they're front loading, some spend to show the street that it's a player in cloud but I don't think so. Oracle's Safra Catz's usually pretty disciplined when it comes to it's spending. Now today on March 17th, Oracle announced updates towards Autonomous Data Warehouse and with me is David Floyer who has extensively researched Oracle over the years and today we're going to unpack the Oracle Autonomous Data Warehouse, ADW announcement. What it means to customers but we also want to dig into Oracle's strategy. We want to compare it to some other prominent database vendors specifically, AWS and Snowflake. David Floyer, Welcome back to The Cube, thanks for making some time for me. >> Thank you Vellante, great pleasure to be here. >> All right, I want to get into the news but I want to start with this idea of the autonomous database which Oracle's announcement today is building on. Oracle uses the analogy of a self-driving car. It's obviously powerful metaphor as they call it the self-driving database and my takeaway is that, this means that the system automatically provisions, it upgrades, it does all the patching for you, it tunes itself. Oracle claims that all reduces labor costs or admin costs by 90%. So I ask you, is this the right interpretation of what Oracle means by autonomous database? And is it real? >> Is that the right interpretation? It's a nice analogy. It's a test to that analogy, isn't it? I would put it as the first stage of the Autonomous Data Warehouse was to do the things that you talked about, which was the tuning, the provisioning, all of that sort of thing. The second stage is actually, I think more interesting in that what they're focusing on is making it easy to use for the end user. Eliminating the requirement for IT, staff to be there to help in the actual using of it and that is a very big step for them but an absolutely vital step because all of the competition focusing on ease of use, ease of use, ease of use and cheapness of being able to manage and deploy. But, so I think that is the really important area that Oracle has focused on and it seemed to have done so very well. >> So in your view, is this, I mean you don't really hear a lot of other companies talking about this analogy of the self-driving database, is this unique? Is it differentiable for Oracle? If so, why, or maybe you could help us understand that a little bit better. >> Well, the whole strategy is unique in its breadth. It has really brought together a whole number of things together and made it of its type the best. So it has a single, whole number of data sources and database types. So it's got a very broad range of different ways that you can look at the data and the second thing that is also excellent is it's a platform. It is fully self provisioned and its functionality is very, very broad indeed. The quality of the original SQL and the query languages, etc, is very, very good indeed and it's a better agent to do joints for example, is excellent. So all of the building blocks are there and together with it's sharing of the same data with OLTP and inference and in memory data paces as well. All together the breadth of what they have is unique and very, very powerful. >> I want to come back to this but let's get into the news a little bit and the announcement. I mean, it seems like what's new in the autonomous data warehouse piece for Oracle's new tooling around four areas that so Andy Mendelsohn, the head of this group instead of the guy who releases his baby, he talked about four things. My takeaway, faster simpler loads, simplified transforms, autonomous machine learning models which are facilitating, What do you call it? Citizen data science and then faster time to insights. So tooling to make those four things happen. What's your take and takeaways on the news? >> I think those are all correct. I would add the ease of use in terms of being able to drag and drop, the user interface has been dramatically improved. Again, I think those, strategically are actually more important that the others are all useful and good components of it but strategically, I think is more important. There's ease of use, the use of apex for example, are more important. And, >> Why are they more important strategically? >> Because they focus on the end users capability. For example, one of other things that they've started to introduce is Python together with their spatial databases, for example. That is really important that you reach out to the developer as they are and what tools they want to use. So those type of ease of use things, those types of things are respecting what the end users use. For example, they haven't come out with anything like click or Tableau. They've left that there for that marketplace for the end user to use what they like best. >> Do you mean, they're not trying to compete with those two tools. They indeed had a laundry list of stuff that they supported, Talend, Tableau, Looker, click, Informatica, IBM, I had IBM there. So their claim was, hey, we're open. But so that's smart. That's just, hey, they realized that people use these tools. >> I'm trying to exclude other people, be a platform and be an ecosystem for the end users. >> Okay, so Mendelsohn who made the announcement said that Oracle's the smartphone of databases and I think, I actually think Alison kind of used that or maybe that was us planing to have, I thought he did like the iPhone of when he announced the exit data way back when the integrated hardware and software but is that how you see it, is Oracle, the smartphone of databases? >> It is, I mean, they are trying to own the complete stack, the hardware with the exit data all the way up to the databases at the data warehouses and the OLTP databases, the inference databases. They're trying to own the complete stack from top to bottom and that's what makes autonomy process possible. You can make it autonomous when you control all of that. Take away all of the requirements for IT in the business itself. So it's democratizing the use of data warehouses. It is pushing it out to the lines of business and it's simplifying it and making it possible to push out so that they can own their own data. They can manage their own data and they do not need an IT person from headquarters to help them. >> Let's stay in this a little bit more and then I want to go into some of the competitive stuff because Mendelsohn mentioned AWS several times. One of the things that struck me, he said, hey, we're basically one API 'cause we're doing analytics in the cloud, we're doing data in the cloud, we're doing integration in the cloud and that's sort of a big part of the value proposition. He made some comparisons to Redshift. Of course, I would say, if you can't find a workload where you beat your big competitor then you shouldn't be in this business. So I take those things with a grain of salt but one of the other things that caught me is that migrating from OnPrem to Oracle, Oracle Cloud was very simple and I think he might've made some comparisons to other platforms. And this to me is important because he also brought in that Gartner data. We looked at that Gardner data when they came out with it in the operational database class, Oracle smoked everybody. They were like way ahead and the reason why I think that's important is because let's face it, the Mission Critical Workloads, when you look at what's moving into AWS, the Mission Critical Workloads, the high performance, high criticality OLTP stuff. That's not moving in droves and you've made the point often that companies with their own cloud particularly, Oracle you've mentioned this about IBM for certain, DB2 for instance, customers are going to, there should be a lower risk environment moving from OnPrem to their cloud, because you could do, I don't think you could get Oracle RAC on AWS. For example, I don't think EXIF data is running in AWS data centers and so that like component is going to facilitate migration. What's your take on all that spiel? >> I think that's absolutely right. You all crown Jewels, the most expensive and the most valuable applications, the mission-critical applications. The ones that have got to take a beating, keep on taking. So those types of applications are where Oracle really shines. They own a very large high percentage of those Mission Critical Workloads and you have the choice if you're going to AWS, for example of either migrating to Oracle on AWS and that is frankly not a good fit at all. There're a lot of constraints to running large systems on AWS, large mission critical systems. So that's not an option and then the option, of course, that AWS will push is move to a Roller, change your way of writing applications, make them tiny little pieces and stitch them all together with microservices and that's okay if you're a small organization but that has got a lot of problems in its own, right? Because then you, the user have to stitch all those pieces together and you're responsible for testing it and you're responsible for looking after it. And that as you grow becomes a bigger and bigger overhead. So AWS, in my opinion needs to have a move towards a tier-one database of it's own and it's not in that position at the moment. >> Interesting, okay. So, let's talk about the competitive landscape and the choices that customers have. As I said, Mendelssohn mentioned AWS many times, Larry on the calls often take shy, it's a compliment to me. When Larry Ellison calls you out, that means you've made it, you're doing well. We've seen it over the years, whether it's IBM or Workday or Salesforce, even though Salesforce's big Oracle customer 'cause AWS, as we know are Oracle customer as well, even though AWS tells us they've off called when you peel the onion >> Five years should be great, some of the workers >> Well, as I said, I believe they're still using Oracle in certain workloads. Way, way, we digress. So AWS though, they take a different approach and I want to push on this a little bit with database. It's got more than a dozen, I think purpose-built databases. They take this kind of right tool for the right job approach was Oracle there converging all this function into a single database. SQL JSON graph databases, machine learning, blockchain. I'd love to talk about more about blockchain if we have time but seems to me that the right tool for the right job purpose-built, very granular down to the primitives and APIs. That seems to me to be a pretty viable approach versus kind of a Swiss Army approach. How do you compare the two? >> Yes, and it is to many initial programmers who are very interested for example, in graph databases or in time series databases. They are looking for a cheap database that will do the job for a particular project and that makes, for the program or for that individual piece of work is making a very sensible way of doing it and they pay for ads on it's clear cloud dynamics. The challenge as you have more and more data and as you're building up your data warehouse in your data lakes is that you do not want to have to move data from one place to another place. So for example, if you've got a Roller,, you have to move the database and it's a pretty complicated thing to do it, to move it to Redshift. It's a five or six steps to do that and each of those costs money and each of those take time. More importantly, they take time. The Oracle approach is a single database in terms of all the pieces that obviously you have multiple databases you have different OLTP databases and data warehouse databases but as a single architecture and a single design which means that all of the work in terms of moving stuff from one place to another place is within Oracle itself. It's Oracle that's doing that work for you and as you grow, that becomes very, very important. To me, very, very important, cost saving. The overhead of all those different ones and the databases themselves originate with all as open source and they've done very well with it and then there's a large revenue stream behind the, >> The AWS, you mean? >> Yes, the original database is in AWS and they've done a lot of work in terms of making it set with the panels, etc. But if a larger organization, especially very large ones and certainly if they want to combine, for example data warehouse with the OLTP and the inference which is in my opinion, a very good thing that they should be trying to do then that is incredibly difficult to do with AWS and in my opinion, AWS has to invest enormously in to make the whole ecosystem much better. >> Okay, so innovation required there maybe is part of the TAM expansion strategy but just to sort of digress for a second. So it seems like, and by the way, there are others that are doing, they're taking this converged approach. It seems like that is a trend. I mean, you certainly see it with single store. I mean, the name sort of implies that formerly MemSQL I think Monte Zweben of splice machine is probably headed in a similar direction, embedding AI in Microsoft's, kind of interesting. It seems like Microsoft is willing to build this abstraction layer that hides that complexity of the different tooling. AWS thus far has not taken that approach and then sort of looking at Snowflake, Snowflake's got a completely different, I think Snowflake's trying to do something completely different. I don't think they're necessarily trying to take Oracle head-on. I mean, they're certainly trying to just, I guess, let's talk about this. Snowflake simplified EDW, that's clear. Zero to snowflake in 90 minutes. It's got this data cloud vision. So you sign on to this Snowflake, speaking of layers they're abstracting the complexity of the underlying cloud. That's what the data cloud vision is all about. They, talk about this Global Mesh but they've not done a good job of explaining what the heck it is. We've been pushing them on that, but we got, >> Aspiration of moment >> Well, I guess, yeah, it seems that way. And so, but conceptually, it's I think very powerful but in reality, what snowflake is doing with data sharing, a lot of reading it's probably mostly read-only and I say, mostly read-only, oh, there you go. You'll get better but it's mostly read and so you're able to share the data, it's governed. I mean, it's exactly, quite genius how they've implemented this with its simplicity. It is a caching architecture. We've talked about that, we can geek out about that. There's good, there's bad, there's ugly but generally speaking, I guess my premise here I would love your thoughts. Is snowflakes trying to do something different? It's trying to be not just another data warehouse. It's not just trying to compete with data lakes. It's trying to create this data cloud to facilitate data sharing, put data in the hands of business owners in terms of a product build, data product builders. That's a different vision than anything I've seen thus far, your thoughts. >> I agree and even more going further, being a place where people can sell data. Put it up and make it available to whoever needs it and making it so simple that it can be shared across the country and across the world. I think it's a very powerful vision indeed. The challenge they have is that the pieces at the moment are very, very easy to use but the quality in terms of the, for example, joints, I mentioned, the joints were very powerful in Oracle. They don't try and do joints. They, they say >> They being Snowflake, snowflake. Yeah, they don't even write it. They would say use another Postgres >> Yeah. >> Database to do that. >> Yeah, so then they have a long way to go. >> Complex joints anyway, maybe simple joints, yeah. >> Complex joints, so they have a long way to go in terms of the functionality of their product and also in my opinion, they sure be going to have more types of databases inside it, including OLTP and they can do that. They have obviously got a great market gap and they can do that by acquisition as well as they can >> They've started. I think, I think they support JSON, right. >> Do they support JSON? And graph, I think there's a graph database that's either coming or it's there, I can't keep all that stuff in my head but there's no reason they can't go in that direction. I mean, in speaking to the founders in Snowflake they were like, look, we're kind of new. We would focus on simple. A lot of them came from Oracle so they know all database and they know how hard it is to do things like facilitate complex joints and do complex workload management and so they said, let's just simplify, we'll put it in the cloud and it will spin up a separate data warehouse. It's a virtual data warehouse every time you want one to. So that's how they handle those things. So different philosophy but again, coming back to some of the mission critical work and some of the larger Oracle customers, they said they have a thousand autonomous database customers. I think it was autonomous database, not ADW but anyway, a few stood out AON, lift, I think Deloitte stood out and as obviously, hundreds more. So we have people who misunderstand Oracle, I think. They got a big install base. They invest in R and D and they talk about lock-in sure but the CIO that I talked to and you talked to David, they're looking for business value. I would say that 75 to 80% of them will gravitate toward business value over the fear of lock-in and I think at the end of the day, they feel like, you know what? If our business is performing, it's a better business decision, it's a better business case. >> I fully agree, they've been very difficult to do business with in the past. Everybody's in dread of the >> The audit. >> The knock on the door from the auditor. >> Right. >> And that from a purchasing point of view has been really bad experience for many, many customers. The users of the database itself are very happy indeed. I mean, you talk to them and they understand why, what they're paying for. They understand the value and in terms of availability and all of the tools for complex multi-dimensional types of applications. It's pretty well, the only game in town. It's only DB2 and SQL that had any hope of doing >> Doing Microsoft, Microsoft SQL, right. >> Okay, SQL >> Which, okay, yeah, definitely competitive for sure. DB2, no IBM look, IBM lost its dominant position in database. They kind of seeded that. Oracle had to fight hard to win it. It wasn't obvious in the 80s who was going to be the database King and all had to fight. And to me, I always tell people the difference is that the chairman of Oracle is also the CTO. They spend money on R and D and they throw off a ton of cash. I want to say something about, >> I was just going to make one extra point. The simplicity and the capability of their cloud versions of all of this is incredibly good. They are better in terms of spending what you need or what you use much better than AWS, for example or anybody else. So they have really come full circle in terms of attractiveness in a cloud environment. >> You mean charging you for what you consume. Yeah, Mendelsohn talked about that. He made a big point about the granularity, you pay for only what you need. If you need 33 CPUs or the other databases you've got to shape, if you need 33, you've got to go to 64. I know that's true for everyone. I'm not sure if that's true too for snowflake. It may be, I got to dig into that a little bit, but maybe >> Yes, Snowflake has got a front end to hiding behind. >> Right, but I didn't want to push it that a little bit because I want to go look at their pricing strategies because I still think they make you buy, I may be wrong. I thought they make you still do a one-year or two-year or three-year term. I don't know if you can just turn it off at any time. They might allow, I should hold off. I'll do some more research on that but I wanted to make a point about the audits, you mentioned audits before. A big mistake that a lot of Oracle customers have made many times and we've written about this, negotiating with Oracle, you've got to bring your best and your brightest when you negotiate with Oracle. Some of the things that people didn't pay attention to and I think they've sort of caught onto this is that Oracle's SOW is adjudicate over the MSA, a lot of legal departments and procurement department. Oh, do we have an MSA? With all, Yes, you do, okay, great and because they think the MSA, they then can run. If they have an MSA, they can rubber stamp it but the SOW really dictateS and Oracle's gotcha there and they're really smart about that. So you got to bring your best and the brightest and you've got to really negotiate hard with Oracle, you get trouble. >> Sure. >> So it is what it is but coming back to Oracle, let's sort of wrap on this. Dominant position in mission critical, we saw that from the Gartner research, especially for operational, giant customer base, there's cloud-first notion, there's investing in R and D, open, we'll put a question Mark around that but hey, they're doing some cool stuff with Michael stuff. >> Ecosystem, I put that, ecosystem they're promoting their ecosystem. >> Yeah, and look, I mean, for a lot of their customers, we've talked to many, they say, look, there's actually, a tail at the tail way, this saves us money and we don't have to migrate. >> Yeah. So interesting, so I'll give you the last word. We started sort of focusing on the announcement. So what do you want to leave us with? >> My last word is that there are platforms with a certain key application or key parts of the infrastructure, which I think can differentiate themselves from the Azures or the AWS. and Oracle owns one of those, SAP might be another one but there are certain platforms which are big enough and important enough that they will, in my opinion will succeed in that cloud strategy for this. >> Great, David, thanks so much, appreciate your insights. >> Good to be here. Thank you for watching everybody, this is Dave Vellante for The Cube. We'll see you next time. (upbeat music)