 The cloud has dramatically changed the way providers think about delivering database technologies. Not only has cloud first become a mandate for many, if not most, but customers are demanding more capabilities from their technology vendors. Examples include a substantially similar experience for cloud and on-prem workloads, increased automation, and a never-ending quest for more secure platforms. Broadly, there are two prevailing models that have emerged. One is to provide highly specialized database products that focus on optimizing for a specific workload signature. The other end of the spectrum combines technologies in a converged platform to satisfy the needs of a much broader set of use cases. And with me, to get a perspective on these and other issues is Andy Mendelson, is the executive vice president of Oracle, the world's leading database company. Andy leads database server technologies. Hello, Andy, thanks for coming on. Hey, Dave, glad to be here. Okay, so we saw the recent announcements. This is kind of your baby around next generation autonomous data warehouse. Maybe you could take us through the path you took from the original cloud data warehouses to where we are today. Yeah, when we first brought autonomous database out, we were basically a second generation technology at that point. You know, we decided that what customers wanted was to be at the push of a button provision, the really powerful Oracle database technology that they've been using for years. And we did that with autonomous database. And beyond that, we provided a very unique capability that around self-tuning, self-driving of the database, which is something the first generation vendors didn't provide. And this is really important because customers today are developers and data analysts, you know, at the push of a button build out their data warehouses, but, you know, they're not experts in tuning. And so what we thought was really important was that customers get great performance out of the box. And that's one of the really unique things about autonomous data warehouse, autonomous database. And then this latest generation that we just came out with also answers the questions we got from, you know, the data analysts and developers. They said, you know, it's really great that I can press a button and provision this very powerful data warehouse infrastructure or a database infrastructure from Oracle. But, you know, if I'm an analyst, I want data. You know, so it's still hard for me to go and, you know, get data from various data sources, transform them, clean them up and get them to a way, a place where I can start querying the data. No, I still need data engineers to help me do that. And so we've done in the new release, we've said, okay, we want to give data analysts data scientists, developers is a true self-service experience where they can do their job completely without bringing in any engineers from their IT organization. And so that's what this new version is all about. Yeah, awesome. I mean, look, years ago, you guys identified the IT labor problem and you've been focused on R&D and putting it in your R&D to solve that problem for customers. So we're really starting to see that hit now. Now, Gardner recently did some analysis. They ranked and rated them some of the more popular cloud databases and Oracle did very well. I mean, particularly in operational categories. I mean, an operational side and the mission critical stuff smoked everybody. We had Mark Stamer and David Floyer on it. Our big takeaways were that you're, again, dominating in that mission critical workloads that dominance continues, but your approach of converging functionality really differs from some others that we saw. I mean, obviously when you get high ratings from Gardner, you're pretty stoked about that. But what do you think contributed to those rankings and what are you finding specifically in customer interactions? Yeah, so Gardner does a lot of its analysis based on talking to customers, finding out how these products that sound great on paper actually work in practice. And I think that's one of the places where Oracle database technology really shines. It solves real world problems. It's been doing it for a long time. And as we've moved that technology into the cloud, that continues. The differentiation we've built up over the years really stands out. You look at like Amazon's databases, they generally take some open source technology that isn't that new. It could be 30 years old, 25 years old and they put it up on the cloud and they say, oh, it's cloud native. It's great. But in fact, it's the same old technology that doesn't really compete decade behind Oracle database technology. So I think the Gardner analysis really showed that sort of thing quite clearly. Yeah, so let's talk about that a little bit. Because obviously I've learned a lot. One of the things I've learned over the last many years of following this business, there's a lot of ways to skin a cat and cloud database vendors. If you think about, you mentioned AWS, you look at Snowflake kind of right tool for the right job approach. They're going to say that their specialty databases they're focused are better than your converged approach which they make, think of as a Swiss Army knife. What's your take on that? Yeah, well, the converged approach is something of course we've been working on for a long time. So the idea is pretty simple. Think about your smartphone. If you think back over 10 years ago you used to have a camcorder and a camera and a messaging device and also a dumb phone device that all those different devices got converged into what we now call the smartphone. Why did the smartphone win? It's just simply much more productive for you to carry one device around that is actually best to breed in all the different categories instead of lots of separate devices. And that's what we're doing with converged database. Over the years, we've been able to build out technologies that are really good at transaction brass analytics for data warehousing. Now we're working on JSON technologies, graph technologies. The other vendors basically can't do this. I mean, it's much easier to build a specialty database that does one thing than to build out a converged database that does end things really well. And that's what we've been doing for years. And again, it's based on technology that we've invested in for quite a long time. And it's something that I think customers and developers and analysts find to be a much more productive way of doing their jobs. It's very unique and not common at all to see a technology that's been around as long as Oracle database to see that sort of morph into a more modern platform. I mean, you mentioned AWS uses, leverages open source a lot. You know, Snowflake would say, okay, we are born in the cloud and they are. I think Google BigQuery would be another good example. But that notion of, I want to get your take on this born in the cloud. Those folks would say, well, we're superior to Oracle's because they started decades ago, not necessarily native cloud services. How have you been able to address that? I know cloud first is kind of the buzzword, but how have you made that sort of transparent to users or irrelevant to users because you are cloud first. Maybe you could talk about how you've able to achieve that and convince us that you actually really are cloud native now. You know, one of the things we sort of like pointing out is that Oracle very uniquely has had this scale out technology for running all kinds of workloads, not just analytic workloads, which is what you see out in the cloud there. But we can also scale out transaction processing workloads. That was another one of the reasons we do so well in, for example, the Gardner analysis for transact operational workloads. And that technology is really valuable as we went to cloud, it lets us do some really unique things. And the most obvious unique thing we have is something we like to call cloud native, instant elasticity. And so with our technology, if you want to provision a share, some number of amount of compute to run your workloads, you can provision exactly what you need. You know, if you need 17 CPUs to get your job done, you do 17 CPUs when you provision your autonomous database. Our competitors who claim to be born in the cloud like Snowflake and Amazon, they still use this archaic way of provisioning servers based on shapes. You know, Snowflake says, what shape cluster do you want? You want 16, you want 32, you want 64. No, it goes up by a power of two, which means if you compare that to what Oracle does, you have to provision up to like twice as much CPU than you really need. So if you really need 17, they make you provision 32. If you really need 33, they make you provision 64. So this is not a cloud native experience at all. It's an archaic way of doing things. And we like to point out with our instant elasticity, you know, we can go from 17 to 18 to 19, you know, whatever you want, plus we have something called auto scale. So you can set your baseline to be 17, let's say, but we will automatically based on your workloads scale you up to three times that. So in this case, be a 51. And because of that true elasticity we have, we are really the only ones that can deliver true pay as you go kind of, just pay for what you need kind of capability, which is certainly what Amazon was talking about when they first called their cloud elastic, but it turns out for database services, these guys still do this archaic thing with shapes. So that's a really good example where we're quite better than the other guys. And it's much more cloud native than the other guys. I want to follow up on that. Just stay here for a second, because you're basically saying we have better granularity than the so-called cloud native guys. Now you mentioned Snowflake, right? You got the shapes, you got to choose which shape you want. And it sounds like Redshift same. And of course I know the way in which Amazon separates compute from storage is largely a tiering exercise. So it's not as smooth as you might expect, but nonetheless it's good. How is it that you were able to achieve this with a database that was born many decades ago? Is it, I mean, what is it in, from a technical standpoint and R&D standpoint that you were able to do? I mean, did you design that in the 1980s? How'd you get here? Yeah, well, it's a combination of interesting technologies. So Autonomous Database has the Oracle Database software that software is running on a very powerful, optimized infrastructure for database based on the exadata technology that we've had on prem for many years. We brought that to the cloud. And that technology is a scale out infrastructure that supports thousands of CPUs. And then we use our multi-tenant technology, which is a way of sharing large infrastructures amongst separate clients. And we divide it up dynamically on the fly. So if there's thousands of CPUs, this guy wants 20 and this one wants 30, we divide it up and give them exactly what they need. And if they wanna grow, we just take some extra CPUs that are in reserve and we give it to them instantly. And so that's a very different way of doing things. And that's been a shape-based approach where what Snowflake and Amazon do under the covers, they give you a real physical server or a cluster. And that's how they provision. If you wanna grow, they give you another big physical cluster, which takes a long time to get the data populated, to get it working. We just have that one infrastructure that we're sharing among lots of users. And we just give you a little extra capacity. It's done instantly. There's no need for data to be moved to populate the new clusters that Snowflake or Amazon are provisioning for you. So it's a very different way of doing things. And you're able to do that because of the tight integration between, you mentioned dexadata, tight integration between the hardware and software. We got, David Floria calls it the iPhone of enterprise. Sometimes he gets some grief for that, but it's not a bad metaphor. But is that really the sort of secret? Well, the big secret under the covers is this exadata technology, our real application cluster scale out technologies, our multi-tenant technology. So these are things we've been working on for a long time. And they're very mature, very powerful technologies. And they really provide very unique benefits in a cloud world where people want things to happen instantly. And they want it to work well for any kind of workload. That's why we talk about being converted. We can do mixed workloads. You can do transactions and analytics all in the same data. The other guys can't do that. They're really good at, like you said, a narrow workload. Like I can do analytics or I can do graph, I can do JSON, but they can't really do the combination, which is what real world applications are like. They're not pure one thing versus enough. Right, thank you for that. So one of the questions people want to know is can Oracle attract new customers that aren't existing Oracle customers? So maybe you could talk about that. And why should somebody who's not an existing Oracle customer think about using autonomous database? Yeah, that's a really good question. Oracle, if you look at our customer base, has a lot of really large enterprises, the biggest banks and the biggest telcos. They run Oracle, they run their businesses on Oracle. And these guys are sort of the most conservative of the bunch out there. And they are moving to cloud at a somewhat slower rate than the smaller companies. And so if you look at who's using autonomous database now, it's actually the smaller companies. The same type of people that first decided Amazon was an interesting cloud 10 years ago, they're also using our technologies. And it's for the same reason. They're finding, they don't have large IT organizations, they don't have large numbers of engineers to engineer their infrastructure. And that's why cloud is so attractive to them. And autonomous database on top of cloud is really attractive as well, because information is the lifeblood of every organization. And if they can empower their analysts to get their job done without lots of help from IT organizations, they're going to do it. And that's really what's made autonomous database really interesting. The whole self-driving nature is very attractive to the smaller shops that don't have a lot of sophisticated IT expertise. Let's talk about developers. You guys are the stewards of the Java community. So obviously, the biggest most popular programming language out there. But when I think of developers, I think of guys in hoodies pounded away, but when I think of Oracle developers, I might think of maybe an app dev team inside of maybe some of those large customers that you talked about. But why would developers or analysts be interested in using Oracle as opposed to some of those more focused narrow use databases that we were talking about earlier? Yeah, so if you're a developer, you want to get your job done as fast as possible. And so having a database that gives you the most productive application development experience is important to you. And so, you know, I was talking, we've been talking about converged database off and on. So if I'm a developer, I have a given job to do a converged database that lets me do a combination of analytics and transactions and do a little JSON and little graph all in one is a much more productive place to go. Because if I don't have something like that, then I'm stuck taking my application and breaking it up into pieces. You know, this piece I'm going to run on, say, Aurora on Amazon. And this piece I have to run on the graph database. And here's some JSON. I got to run that on some document database. And then I have to move the data around, the data gets sort of fragmented between these databases. And I have to do all this data integration and whatever. With a converged database, I have a much simpler world where I can just use one technology stack. I can get my job done. And then I'm future proof against change. You know, requirements change all the time. So you build the initial version of the application and you use your say, you know, this is not what I want. I want something else. And it turns out that something else often is why I want analytics. And you use something like a, you know, document store technology that has really poor analytic capabilities. And then so you have to take that data and you have to move it to another, you know, database. And so with our converged approach, you don't have to do that. You know, you're already in a place where everything works, everything that you need, you can possibly need in the future is going to be there as well. And so for developers, I think, you know, converged is the right way to go. Plus for people who are what we call citizen developers, you know, like the data analysts that they cut, they write a little code occasionally, but they're really after getting value out of the data, we have this really fabulous no-code, low-code tool called Apex. And Apex is again, a very mature technology that's been around for years and it lets somebody who's just a data analyst, he knows a little sequel, but he doesn't want to write code, get their job done really fast. And we've published some benchmark on our website, showing, you know, basically you can get the job done 20 to 40 times faster using a no-code, low-code tool like Apex versus something like, you know, just writing, cutting lots of traditional code. I'm glad you brought up Apex. We recently interviewed one of your former colleagues and it's Avery. And all you would talk about is low-code, no-code. And in the Apex announcement, you said something to the effect of coding should be the exception, not the rule. Did you mean that? What do you mean by that? Yeah, so Apex is a tool that people use with our database technology for building what we call data-driven applications. So if you got a bunch of data and you want to get some value out of it, you want to build maybe dashboards or more sophisticated reports, Apex is an incredible tool for doing that. And it's modern, you know, it builds applications that look great on your smartphone and it automatically, you know, renders that same user interface on a bigger device like a laptop desktop device as well. And it's very, it's one of these things that the people that use it just go bonkers with. It's a viral technology. They get really excited about how productive they've been using it and they tell all their friends. And I think we decided, I guess about a year ago when we came up with this Apex service that, you know, we really want to start going bigger on the marketing around it because it's very unique. Nobody else has anything quite like it and it again, it just adds value to the whole developer productivity story around an Oracle database. So that's why we have the Apex service now and we also have Apex available with every Oracle database on the cloud. Got it. I want to ask you about some of the features around 21C. There are a lot of them you announced early this year. Maybe you could tease out some of the top things that we should be paying attention to in 21C. Yeah, sure. So one of the ways to look at 21C is we're continuing down this path of a converged database. And so one of the marquee features in 21C is something we call blockchain tables. So what is blockchain? Well, blockchain was this technology that's under the covers behind Bitcoin. You know, it's a way of creating a tamper-proof data store that was used by the original Bitcoin algorithms. Well, developers actually like having tamper-proof data objects and databases too. And so what we decide to do is say, well, if I create a SQL table in an Oracle database, what if there's a new option that just says, I want that table implemented using blockchain technology to make the table tamper-proof and fully audited, et cetera. And so we just did that. And so in 21C, you can now get basically another feature of the converged database that says, give me a SQL table. I can do everything. I can query it. I can insert rows into it. But it's tamper-proof. I can't ever update it. I can't delete rows from it. Amazon did their usual thing. They took, again, some open source technology. And they said, hey, we got this great thing called quantum ledger database. And it does blockchain tables. But if you want to do blockchain tables in any of their other databases, you're out of luck. They don't have it. You have to go move the data into this new thing. And it's, again, showing sort of the problem with their proprietary approach of having specialty databases versus just having one converged that does it all. So that's the blockchain table feature. We did a bunch of other things. The one I think is worth mentioning the most is support for persistent memory. So a lot of people out there haven't noticed this very interesting technology that Intel shipped a couple of years ago called Optane Data Center Memory. And what it is, it's basically a hybrid of flash memory, which is persistent memory, and standard DRAM, which is not persistent. It means you can't store a database in DRAM. And so with this persistent memory, you can basically have a database stored persistently in memory all the time. And so it's a very innovative new technology from a database standpoint. It's a very disruptive technology to the database market because now you can have an in-memory database basically, period, all the time, 24-7. And so 21-C is the first database out there that has native support for this new kind of persistent memory technology. And we think it's really important. So we're actually making it available to our 19 C customers as well. And that's another technology I'd call out that we think is very unique. We're way ahead of the game there. And we're going to continue investing, moving forward in that space as well. Yeah, so that layer in between DRAM and persistent flash, that's a great innovation, and a game changing from a performance. And actually the way you write applications. But I got to ask Andy. I and all the analysts were on with Juan recently, Juan and to listen to that introduction of blockchain. And everybody wants to know, is SAFRA going to start putting Bitcoin on the Oracle balance sheet? Some of us have to take that leap. Yeah, that's a good question. Who knows? Again, come in on specialization. That would be interesting. OK, last question, then we got to go. Look, Oracle, the narrative on Oracle is you're expensive and you're mean. It's hard to do business with. Do you care? Are you doing things to maybe change that perception in the cloud? Yeah, I think we've made a very conscious decision that as we move to the cloud, we're offering a totally new business model on the cloud. That is a cloud data model. You pay for what you use. You have everyday low prices. You don't have to negotiate with some salesman for months to get a good price. So yeah, we really like the message to get out there that those of you who think you know what Oracle is all about and how it might be to work with Oracle and from your on-premises days, you should really check out how Oracle is now on the cloud. We have this autonomous database technology. Really easy to use, really simple. Any analyst can now get value out of the data without any help from any other engineers. It's very unique. It's the same technology you're used to, but now it's delivered in a way that's much easier to consume and much lower cost. And so yeah, you should definitely take a look at what we've got out there on the cloud. And it's all free to try out. We got this free tier. You can provision free VMs, free databases, free Apex, whatever you want, and try it out and see what you think. Well, thanks for that. I'm just kidding about me. I got a lot of friends at Oracle, some relatives as well. And thanks, Andy, for coming on theCUBE today. It's really great to talk to you. Yeah, it's my pleasure. And thanks for watching. This is Dave Vellante. We'll see you next time.