(upbeat music) >> Okay, welcome back everyone in live coverage here at theCUBE, Boston, Massachusetts, for AWS re:inforce 22 security conference for Amazon Web Services. Obviously reinvent the end of the years' the big celebration, "re:Mars" is the new show that we've covered as well. The res are here with theCUBE. I'm John Furrier, host with a great guest, Ameesh Divatia, co-founder, and CEO of a company called "Baffle." Ameesh, thanks for joining us on theCUBE today, congratulations. >> Thank you. It's good to be here. >> And we got the custom encrypted socks. >> Yup, limited edition >> 64 bitter 128. >> Base 64 encoding. >> Okay.(chuckles) >> Secret message in there. >> Okay.(chuckles) Secret message.(chuckles) We'll have to put a little meme on the internet, figure it out. Well, thanks for comin' on. You guys are goin' hot right now. You guys a hot startup, but you're in an area that's going to explode, we believe. >> Yeah. >> The SuperCloud is here, we've been covering that on theCUBE that people are building on top of the Amazon Hyperscalers. And without the capex, they're building platforms. The application tsunami has come and still coming, it's not stopping. Modern applications are faster, they're better, and they're driving a lot of change under the covers. >> Absolutely. Yeah. >> And you're seeing structural change happening in real time, in ops, the network. You guys got something going on in the encryption area. >> Yes >> Data. Talk about what you guys do. >> Yeah. So we believe very strongly that the next frontier in security is data. We've had multiple waves in security. The next one is data, because data is really where the threats will persist. If the data shows up in the wrong place, you get into a lot of trouble with compliance. So we believe in protecting the data all the way down at the field, or record level. That's what we do. >> And you guys doing all kinds of encryption, or other things? >> Yes. So we do data transformation, which encompasses three different things. It can be tokenization, which is format preserving. We do real encryption with counter mode, or we can do masked views. So tokenization, encryption, and masking, all with the same platform. >> So pretty wide ranging capabilities with respect to having that kind of safety. >> Yes. Because it all depends on how the data is used down the road. Data is created all the time. Data flows through pipelines all the time. You want to make sure that you protect the data, but don't lose the utility of the data. That's where we provide all that flexibility. >> So Kurt was on stage today on one of the keynotes. He's the VP of the platform at AWS. >> Yes. >> He was talking about encrypts, everything. He said it needs, we need to rethink encryption. Okay, okay, good job. We like that. But then he said, "We have encryption at rest." >> Yes. >> That's kind of been there, done that. >> Yes. >> And, in-flight? >> Yeah. That's been there. >> But what about in-use? >> So that's exactly what we plug. What happens right now is that data at rest is protected because of discs that are already self-encrypting, or you have transparent data encryption that comes native with the database. You have data in-flight that is protected because of SSL. But when the data is actually being processed, it's in the memory of the database or datastore, it is exposed. So the threat is, if the credentials of the database are compromised, as happened back then with Starwood, or if the cloud infrastructure is compromised with some sort of an insider threat like a Capital One, that data is exposed. That's precisely what we solve by making sure that the data is protected as soon as it's created. We use standard encryption algorithms, AES, and we either do format preserving, or true encryption with counter mode. And that data, it doesn't really matter where it ends up, >> Yeah. >> because it's always protected. >> Well, that's awesome. And I think this brings up the point that we want been covering on SiliconAngle in theCUBE, is that there's been structural change that's happened, >> Yes. >> called cloud computing, >> Yes. >> and then hybrid. Okay. Scale, role of data, higher level abstraction of services, developers are in charge, value creations, startups, and big companies. That success is causing now, a new structural change happening now. >> Yes. >> This is one of them. What areas do you see that are happening right now that are structurally changing, that's right in front of us? One is, more cloud native. So the success has become now the problem to solve - >> Yes. >> to get to the next level. >> Yeah. >> What are those, some of those? >> What we see is that instead of security being an afterthought, something that you use as a watchdog, you create ways of monitoring where data is being exposed, or data is being exfiltrated, you want to build security into the data pipeline itself. As soon as data is created, you identify what is sensitive data, and you encrypt it, or tokenize it as it flows into the pipeline using things like Kafka plugins, or what we are very clearly differentiating ourselves with is, proxy architectures so that it's completely transparent. You think you're writing to the datastore, but you're actually writing to the proxy, which in turn encrypts the data before its stored. >> Do you think that's an efficient way to do it, or is the only way to do it? >> It is a much more efficient way of doing it because of the fact that you don't need any app-dev resources. There are many other ways of doing it. In fact, the cloud vendors provide development kits where you can just go do it yourself. So that is actually something that we completely avoid. And what makes it really, really interesting is that once the data is encrypted in the data store, or database, we can do what is known as "Privacy Enhanced Computation." >> Mm. >> So we can actually process that data without decrypting it. >> Yeah. And so proxies then, with cloud computing, can be very fast, not a bottleneck that could be. >> In fact, the cloud makes it so. It's very hard to - >> You believe that? >> do these things in static infrastructure. In the cloud, there's infinite amount of processing available, and there's containerization. >> And you have good network. >> You have very good network, you have load balancers, you have ways of creating redundancy. >> Mm. So the cloud is actually enabling solutions like this. >> And the old way, proxies were seen as an architectural fail, in the old antiquated static web. >> And this is where startups don't have the baggage, right? We didn't have that baggage. (John laughs) We looked at the problem and said, of course we're going to use a proxy because this is the best way to do this in an efficient way. >> Well, you bring up something that's happening right now that I hear a lot of CSOs and CIOs and executives say, CXOs say all the time, "Our", I won't say the word, "Our stuff has gotten complicated." >> Yes. >> So now I have tool sprawl, >> Yeah. >> I have skill gaps, and on the rise, all these new managed services coming at me from the vendors who have never experienced my problem. And their reaction is, they don't get my problem, and they don't have the right solutions, it's more complexity. They solve the complexity by adding more complexity. >> Yes. I think we, again, the proxy approach is a very simple. >> That you're solving that with that approach. >> Exactly. It's very simple. And again, we don't get in the way. That's really the the biggest differentiator. The forcing function really here is compliance, right? Because compliance is forcing these CSOs to actually adopt these solutions. >> All right, so love the compliance angle, love the proxy as an ease of use, take the heavy lifting away, no operational problems, and deviations. Now let's talk about workloads. >> Yeah. >> 'Cause this is where the use is. So you got, or workloads being run large scale, lot a data moving around, computin' as well. What's the challenge there? >> I think it's the volume of the data. Traditional solutions that we're relying on legacy tokenizations, I think would replicate the entire storage because it would create a token wall, for example. You cannot do that at this scale. You have to do something that's a lot more efficient, which is where you have to do it with a cryptography approach. So the workloads are diverse, lots of large files in the workloads as well as structured workloads. What we have is a solution that actually goes across the board. We can do unstructured data with HTTP proxies, we can do structured data with SQL proxies. And that's how we are able to provide a complete solution for the pipeline. >> So, I mean, show about the on-premise versus the cloud workload dynamic right now. Hybrid is a steady state right now. >> Yeah. >> Multi-cloud is a consequence of having multiple vendors, not true multi-cloud but like, okay, they have Azure there, AWS here, I get that. But hybrid really is the steady state. >> Yes. >> Cloud operations. How are the workloads and the analytics the data being managed on-prem, and in the cloud, what's their relationship? What's the trend? What are you seeing happening there? >> I think the biggest trend we see is pipelining, right? The new ETL is streaming. You have these Kafka and Kinesis capabilities that are coming into the picture where data is being ingested all the time. It is not a one time migration. It's a stream. >> Yeah. >> So plugging into that stream is very important from an ingestion perspective. >> So it's not just a watchdog. >> No. >> It's the pipelining. >> It's built in. It's built-in, it's real time, that's where the streaming gets another diverse access to data. >> Exactly. >> Data lakes. You got data lakes, you have pipeline, you got streaming, you mentioned that. So talk about the old school OLTP, the old BI world. I think Power BI's like a $30 billion product. >> Yeah. >> And you got Tableau built on OLTP building cubes. Aren't we just building cubes in a new way, or, >> Well. >> is there any relevance to the old school? >> I think there, there is some relevance and in fact that's again, another place where the proxy architecture really helps, because it doesn't matter when your application was built. You can use Tableau, which nobody has any control over, and still process encrypted data. And so can with Power BI, any Sequel application can be used. And that's actually exactly what we like to. >> So we were, I was talking to your team, I knew you were coming on, and they gave me a sound bite that I'm going to read to the audience and I want to get your reaction to. >> Sure. >> 'Cause I love this. I fell out of my chair when I first read this. "Data is the new oil." In 2010 that was mentioned here on theCUBE, of course. "Data is the new oil, but we have to ensure that it does not become the next asbestos." Okay. That is really clever. So we all know about asbestos. I add to the Dave Vellante, "Lead paint too." Remember lead paint? (Ameesh laughs) You got to scrape it out and repaint the house. Asbestos obviously causes a lot of cancer. You know, joking aside, the point is, it's problematic. >> It's the asset. >> Explain why that sentence is relevant. >> Sure. It's the assets and liabilities argument, right? You have an asset which is data, but thanks to compliance regulations and Gartner says 75% of the world will be subject to privacy regulations by 2023. It's a liability. So if you don't store your data well, if you don't process your data responsibly, you are going to be liable. So while it might be the oil and you're going to get lots of value out of it, be careful about the, the flip side. >> And the point is, there could be the "Grim Reaper" waiting for you if you don't do it right, the consequences that are quantified would be being out of business. >> Yes. But here's something that we just discovered actually from our survey that we did. While 93% of respondents said that they have had lots of compliance related effects on their budgets. 75% actually thought that it makes them better. They can use the security postures as a competitive differentiator. That's very heartening to us. We don't like to sell the fear aspect of this. >> Yeah. We like to sell the fact that you look better compared to your neighbor, if you have better data hygiene, back to the. >> There's the fear of missing out, or as they say, "Keeping up with the Joneses", making sure that your yard looks better than the next one. I get the vanity of that, but you're solving real problems. And this is interesting. And I want to get your thoughts on this. I found, I read that you guys protect more than a 100 billion records across highly regulated industries. Financial services, healthcare, industrial IOT, retail, and government. Is that true? >> Absolutely. Because what we are doing is enabling SaaS vendors to actually allow their customers to control their data. So we've had the SaaS vendor who has been working with us for over three years now. They store confidential data from 30 different banks in the country. >> That's a lot of records. >> That's where the record, and. >> How many customers do you have? >> Well, I think. >> The next round of funding's (Ameesh laughs) probably they're linin' up to put money into you guys. >> Well, again, this is a very important problem, and there are, people's businesses are dependent on this. We're just happy to provide the best tool out there that can do this. >> Okay, so what's your business model behind? I love the success, by the way, I wanted to quote that stat to one verify it. What's the business model service, software? >> The business model is software. We don't want anybody to send us their confidential data. We embed our software into our customers environments. In case of SaaS, we are not even visible, we are completely embedded. We are doing other relationships like that right now. >> And they pay you how? >> They pay us based on the volume of the data that they're protecting. >> Got it. >> That in that case which is a large customers, large enterprise customers. >> Pay as you go. >> It is pay as you go, everything is annual licenses. Although, multi-year licenses are very common because once you adopt the solution, it is very sticky. And then for smaller customers, we do base our pricing also just on databases. >> Got it. >> The number of databases. >> And the technology just reviewed low-code, no-code implementation kind of thing, right? >> It is by definition, no code when it comes to proxy. >> Yeah. >> When it comes to API integration, it could be low code. Yeah, it's all cloud-friendly, cloud-native. >> No disruption to operations. >> Exactly. >> That's the culprit. >> Well, yeah. >> Well somethin' like non-disruptive operations.(laughs) >> No, actually I'll give an example of a migration, right? We can do live migrations. So while the databases are still alive, as you write your. >> Live secure migrations. >> Exactly. You're securing - >> That's the one that manifests. >> your data as it migrates. >> Awright, so how much funding have you guys raised so far? >> We raised 36 and a half, series A, and B now. We raised that late last year. >> Congratulations. >> Thank you. >> Who's the venture funders? >> True Ventures is our largest investor, followed by Celesta Capital, National Grid Partners is an investor, and so is Engineering Capital and Clear Vision Ventures. >> And the seed and it was from Engineering? >> Seed was from Engineering. >> Engineering Capital. >> And then True came in very early on. >> Okay. >> Greenspring is also an investor in us, so is Industrial Ventures. >> Well, privacy has a big concern, big application for you guys. Privacy, secure migrations. >> Very much so. So what we are believe very strongly in the security's personal, security is yours and my data. Privacy is what the data collector is responsible for. (John laughs) So the enterprise better be making sure that they've complied with privacy regulations because they don't tell you how to protect the data. They just fine you. >> Well, you're not, you're technically long, six year old start company. Six, seven years old. >> Yeah. >> Roughly. So yeah, startups can go on long like this, still startup, privately held, you're growing, got big records under management there, congratulations. What's next? >> I think scaling the business. We are seeing lots of applications for this particular solution. It's going beyond just regulated industries. Like I said, it's a differentiating factor now. >> Yeah >> So retail, and a lot of other IOT related industrial customers - >> Yeah. >> are also coming. >> Ameesh, talk about the show here. We're at re:inforce, actually we're live here on the ground, the show floor buzzing. What's your takeaway? What's the vibe this year? What if you had to share what your opinion the top story here at the show, what would be the two top things, or three things? >> I think it's two things. First of all, it feels like we are back. (both laugh) It's amazing to see people on the show floor. >> Yeah. >> People coming in and asking questions and getting to see the product. The second thing that I think is very gratifying is, people come in and say, "Oh, I've heard of you guys." So thanks to digital media, and digital marketing. >> They weren't baffled. They want baffled. >> Exactly. >> They use baffled. >> Looks like, our outreach has helped, >> Yeah. >> and has kept the continuity, which is a big deal. >> Yeah, and now you're a CUBE alumni, welcome to the fold. >> Thank you. >> Appreciate you coming on. And we're looking forward to profiling you some day in our startup showcase, and certainly, we'll see you in the Palo Alto studios. Love to have you come in for a deeper dive. >> Sounds great. Looking forward to it. >> Congratulations on all your success, and thanks for coming on theCUBE, here at re:inforce. >> Thank you, John. >> Okay, we're here in, on the ground live coverage, Boston, Massachusetts for AWS re:inforce 22. I'm John Furrier, your host of theCUBE with Dave Vellante, who's in an analyst session, right? He'll be right back with us on the next interview, coming up shortly. Thanks for watching. (gentle music)

(bright music) >> Hello, everyone, and welcome to this CUBE video exclusive. This is Dave Vellante, and as I've said many times what people sometimes forget is Oracle's chairman is also its CTO, and he understands and appreciates the importance of engineering. It's the lifeblood of tech innovation, and Oracle continues to spend money on R and D. Over the past decade, the company has evolved its Exadata platform by investing in core infrastructure technology. For example, Oracle initially used InfiniBand, which in and of itself was a technical challenge to exploit for higher performance. That was an engineering innovation, and now it's moving to RoCE to try and deliver best of breed performance by today's standards. We've seen Oracle invest in machine intelligence for analytics. It's converged OLTB and mixed workloads. It's driving automation functions into its Exadata platform for things like indexing. The point is we've seen a consistent cadence of improvements with each generation of Exadata, and it's no secret that Oracle likes to brag about the results of its investments. At its heart, Oracle develops database software and databases have to run fast and be rock solid. So Oracle loves to throw around impressive numbers, like 27 million AKI ops, more than a terabyte per second for analytics scans, running it more than a terabyte per second. Look, Oracle's objective is to build the best database platform and convince its customers to run on Oracle, instead of doing it themselves or in some other cloud. And because the company owns the full stack, Oracle has a high degree of control over how to optimize the stack for its database. So this is how Oracle intends to compete with Exadata, Exadata Cloud@Customer and other products, like ZDLRA against AWS Outposts, Azure Arc and do it yourself solutions. And with me, to talk about Oracle's latest innovation with its Exadata X9M announcement is Juan Loaiza, who's the Executive Vice President of Mission Critical Database Technologies at Oracle. Juan, thanks for coming on theCUBE, always good to see you, man. >> Thanks for having me, Dave. It's great to be here. >> All right, let's get right into it and start with the news. Can you give us a quick overview of the X9M announcement today? >> Yeah, glad to. So, we've had Exadata on the market for a little over a dozen years, and every year, as you mentioned, we make it better and better. And so this year we're introducing our X9M family of products, and as usual, we're making it better. We're making it better across all the different dimensions for OLTP, for analytics, lower costs, higher IOPs, higher throughputs, more capacity, so it's better all around, and we're introducing a lot of new software features as well that make it easier to use, more manageable, more highly available, more options for customers, more isolation, more workload consolidation, so it's our usual better and better every year. We're already way ahead of the competition in pretty much every metric you can name, but we're not sitting back. We have the pedal to the metal and we're keeping it there. >> Okay, so as always, you announced some big numbers. You're referencing them. I did in my upfront narrative. You've claimed double to triple digit performance improvements. Tell us, what's the secret sauce that allows you to achieve that magnitude of performance gain? >> Yeah, there's a lot of secret sauce in Exadata. First of all, we have custom designed hardware, so we design the systems from the top down, so it's not a generic system. It's designed to run database with a specific and sole focus of running database, and so we have a lot of technologies in there. Persistent memory is a really big one that we've introduced that enables super low response times for OLTP. The RoCE, the remote RDMA over convergency ethernet with a hundred gigabit network is a big thing, offload to storage servers is a big thing. The columnar processing of the storage is a huge thing, so there's a lot of secret sauce, most of it is software and hardware related and interesting about it, it's very unique. So we've been introducing more and more technologies and actually advancing our lead by introducing very unique, very effective technologies, like the ones I mentioned, and we're continuing that with our X9 generation. >> So that persistent memory allows you to do a right directly, atomic right directly to memory, and then what, you update asynchronously to the backend at some point? Can you double click on that a little bit? >> Yeah, so we use persistent memory as kind of the first tier of storage. And the thing about persistent memory is persistent. Unlike normal memory, it doesn't lose its contents when you lose power, so it's just as good as flash or traditional spinning disks in terms of storing data. And the integration that we do is we do what's called remote direct memory access, that means the hardware sends the new data directly into persistent memory and storage with no software, getting rid of all the software layers in between, and that's what enables us to achieve this extremely low latency. Once it's in persistent memory, it's stored. It's as good as being in flash or disc. So there's nothing else that we need to do. We do age things out of persistent memory to keep only hot data in there. That's one of the tricks that we do to make sure, because persistent memory is more expensive than flash or disc, so we tier it. So we age data in and out as it becomes hot, age it out as it becomes cold, but once it's in persistent memory, it's as good as being stored. It is stored. >> I love it. Flash is a slow tier now. So, (laughs) let's talk about what this-- >> Right, I mean persistent memory is about an order of magnitude faster. Flash is more than an order of magnitude faster than disk drive, so it is a new technology that provides big benefits, particularly for latency on OLTP. >> Great, thank you for that, okay, we'll get out of the plumbing. Let's talk about what this announcement means to customers. How does all this performance, and you got a lot of scale here, how does it translate into tangible results say, for a bank? >> Yeah, so there's a lot of ways. So, I mentioned performance is a big thing, always with Exadata. We're increasing the performance significantly for OLTP, analytics, so OLTP, 50, 60% performance improvements, analytics, 80% performance improvements in terms of costs, effectiveness, 30 to 60% improvement, so all of these things are big benefits. You know, one of the differences between a server product like Exadata and a consumer product is performance translates in the cost also. If I get a new smartphone that's faster, it doesn't actually reduce my costs, it just makes my experience a little better. But with a server product like Exadata, if I have 50% faster, I can translate that into I can serve 50% more users, 50% more workload, 50% more data, or I can buy a 50% smaller system to run the same workload. So, when we talk about performance, it also means lower costs, so if big customers of ours, like banks, telecoms, retailers, et cetera, they can take that performance and turn it into better response times. They can also take that performance and turn it into lower costs, and everybody loves both of those things, so both of those are big benefits for our customers. >> Got it, thank you. Now in a move that was maybe a little bit controversial, you stated flat out that you're not going to bother to compare Exadata cloud and customer performance against AWS Outposts and Azure Stack, rather you chose to compare to RDS, Redshift, Azure SQL. Why, why was that? >> Yeah, so our Exadata runs in the public cloud. We have Exadata that runs in Cloud@Customer, and we have Exadata that runs on Prem. And Azure and Azure Stack, they have something a little more similar to Cloud@Customer. They have where they take their cloud solutions and put them in the customer data center. So when we came out with our new X8, 9M Cloud@Customer, we looked at those technologies and honestly, we couldn't even come up with a good comparison with their equivalent, for example, AWS Outpost, because those products really just don't really run. For example, the two database products that Outposts promote or that Amazon promotes is Aurora for OLTP and Redshift for analytics. Well, those two can't even run at all on their Outposts product. So, it's kind of like beating up on a child or something. (laughs) It doesn't make sense. They're out of our weight class, so we're not even going to compare against them. So we compared what we run, both in public cloud and Cloud@Customer against their best product, which is the Redshifts and the Auroras in their public cloud, which is their most scalable available products. With their equivalent Cloud@Customer, not only does it not perform, it doesn't run at all. Their Premiere products don't run at all on those platforms. >> Okay, but RDS does, right? I think, and Redshift and Azure SQL, right, will run a their version, so you compare it against those. What were the results of the benchmarks when you did made those comparisons? >> Yeah, so compared against their public cloud or Cloud@Customer, we generally get results that are something like 50 times lower latency and close to a hundred times higher analytic throughput, so it's orders of magnitude. We're not talking 50%, we're talking 50 times, so compared to those products, there really is kind of, we're in a different league. It's kind of like they're the middle school little league and we're the professional team, so it's really dramatically different. It's not even in the same league. >> All right, now you also chose to compare the X9M performance against on-premises storage systems. Why and what were those results? >> Yeah, so with the on-premises, traditionally customers bought conventional storage and that kind of stuff, and those products have advanced quite a bit. And again, those aren't optimized. Those aren't designed to run database, but some customers have traditionally deployed those, you know, there's less and less these days, but we do get many times faster both on OLTP and analytic performance there, I mean, with analytics that can be up to 80 times faster, so again, dramatically better, but yeah, there's still a lot of on-premise systems, so we didn't want to ignore that fact and compare only to cloud products. >> So these are like to like in the sense that they're running the same level of database. You're not playing games in terms of the versioning, obviously, right? >> Actually, we're giving them a lot of the benefit. So we're taking their published numbers that aren't even running a database, and they use these low-level benchmarking tools to generate these numbers. So, we're comparing our full end-to-end database to storage numbers against their low-level IO tool that they've published in their data sheets, so again, we're trying to give them the benefit of the doubt, but we're still orders of magnitude better. >> Okay, now another claim that caught our attention was you said that 87% of the Fortune 100 organizations run Exadata, and you're claiming many thousands of other organizations globally. Can you paint a picture of the ICP, the Ideal Customer Profile for Exadata? What's a typical customer look like, and why do they use Exadata, Juan? >> Yeah, so the ideal customer is pretty straightforward, customers that care about data. That's pretty much it. (Dave laughs) If you care about data, if you care about performance of data, if you care about availability of data, if you care about manageability, if you care about security, those are the customers that should be looking strongly at Exadata, and those are the customers that are adopting Exadata. That's why you mentioned 87% of the global Fortune 100 have already adopted Exadata. If you look at a lot of industries, for example, pretty much every major bank almost in the entire world is running Exadata, and they're running it for their mission critical workloads, things like financial trading, regulatory compliance, user interfaces, the stuff that really matters. But in addition to the biggest companies, we also have thousands of smaller companies that run it for the same reason, because their data matters to them, and it's frankly the best platform, which is why we get chosen by these very, very sophisticated customers over and over again, and why this product has grown to encompass most of the major corporations in the world and governments also. >> Now, I know Deutsche bank is a customer, and I guess now an engineering partner from the announcement that I saw earlier this summer. They're using Cloud@Customer, and they're collaborating on things like security, blockchain, machine intelligence, and my inference is Deutsch Bank is looking to build new products and services that are powered by your platforms. What can you tell us about that? Can you share any insights? Are they going to be using X9M, for example? >> Yes, Deutsche Bank is a partnership that we announced a few months ago. It's a major partnership. Deutsche Bank is one of the biggest banks in the world. They traditionally are an on-premises customer, and what they've announced is they're going to move almost the entire database estate to our Exadata Cloud@Customer platform, so they want to go with a cloud platform, but they're big enough that they want to run it in their own data center for certain regulatory reasons. And so, the announcement that we made with them is they're moving the vast bulk of their data estate to this platform, including their core banking, regulatory applications, so their most critical applications. So, obviously they've done a lot of testing. They've done a lot of trials and they have the confidence to make this major transition to a cloud model with the Exadata Cloud@Customer solution, and we're also working with them to enhance that product and to work in various other fields, like you mentioned, machine learning, blockchain, that kind of project also. So it's a big deal when one of the biggest, most conservative, best respected financial institution in the world says, "We're going all in on this product," that's a big deal. >> Now outside of banking, I know a number of years ago, I stumbled upon an installation or a series of installations that Samsung found out about them as a customer. I believe it's now public, but they've something like 300 Exadatas. So help us understand, is it common that customers are building these kinds of Exadata farms? Is this an outlier? >> Yeah, so we have many large customers that have dozens to hundreds of Exadatas, and it's pretty simple, they start with one or two, and then they see the benefits, themselves, and then it grows. And Samsung is probably the biggest, most successful and most respected electronics company in the world. They are a giant company. They have a lot of different sub units. They do their own manufacturing, so manufacturing's one of their most critical applications, but they have lots of other things they run their Exadata for. So we're very happy to have them as one of our major customers that run Exadata, and by the way, Exadata again, very huge in electronics, in manufacturing. It's not just banking and that kind of stuff. I mean, manufacturing is incredibly critical. If you're a company like Samsung, that's your bread and butter. If your factory stops working, you have huge problems. You can't produce products, and you will want to improve the quality. You want to improve the tracking. You want to improve the customer service, all that requires a huge amount of data. Customers like Samsung are generating terabytes and terabytes of data per day from their manufacturing system. They track every single piece, everything that happens, so again, big deal, they care about data. They care deeply about data. They're a huge Exadata customer. That's kind of the way it works. And they've used it for many years, and their use is growing and growing and growing, and now they're moving to the cloud model as well. >> All right, so we talked about some big customers and Juan, as you know, we've covered Exadata since its inception. We were there at the announcement. We've always stressed the fit in our research with mission critical workloads, which especially resonates with these big customers. My question is how does Exadata resonate with the smaller customer base? >> Yeah, so we talk a lot about the biggest customers, because honestly they have the most critical requirements. But, at some level they have worldwide requirements, so if one of the major financial institutions goes down, it's not just them that's affected, that reverberates through the entire world. There's many other customers that use Exadata. Maybe their application doesn't stop the world, but it stops them, so it's very important to them. And so one of the things that we've introduced in our Cloud@Customer and public cloud Exadata platforms is the ability for Oracle to manage all the infrastructure, which enables smaller customers that don't have as much IT sophistication to adopt these very mission critical technology, so that's one of the big advancements. Now, we've always had smaller customers, but now we're getting more and more. We're getting universities, governments, smaller businesses adopting Exadata, because the cloud model for adopting is dramatically simpler. Oracle does all the administration, all the low-level stuff. They don't have to get involved in it at all. They can just use the data. And, on top of that comes our autonomous database, which makes it even easier for smaller customers to adapt. So Exadata, which some people think of as a very high-end platform in this cloud model, and particularly with autonomous databases is very accessible and very useful for any size customer really. >> Yeah, by all accounts, I wouldn't debate Exadata has been a tremendous success. But you know, a lot of customers, they still prefer to roll their own, do it themselves, and when I talk to them and ask them, "Okay, why is that?" They feel it limits their reliance on a single vendor, and it gives them better ability to build what I call a horizontal infrastructure that can support say non-Oracle workloads, so what do you tell those customers? Why should those customers run Oracle database on Exadata instead of a DIY infrastructure? >> Yeah, so that debate has gone on for a lot of years. And actually, what I see, there's less and less of that debate these days. You know, initially customers, many customers, they were used to building their own. That's kind of what they did. They were pretty good at it. What we have shown customers, and when we talk about these major banks, those are the kinds of people that are really good at it. They have giant IT departments. If you look at a major bank in the world, they have tens of thousands of people in their IT departments. These are gigantic multi-billion dollar organizations, so they were pretty good at this kind of stuff. And what we've shown them is you can't build this yourself. There's so much software that we've written to integrate with the database that you just can't build yourself, it's not possible. It's kind of like trying to build your own smartphone. You really can't do it, the scale, the complexity of the problem. And now as the cloud model comes in, customers are realizing, hey, all this attention to building my own infrastructure, it's kind of last decade, last century. We need to move on to more of an as a service model, so we can focus on our business. Let enterprises that are specialized in infrastructure, like Oracle that are really, really good at it, take care of the low-level details, and let me focus on things that differentiate me as a business. It's not going to differentiate them to establish their own storage for database. That's not a differentiator, and they can't do it nearly as well as we can, and a lot of that is because we write a lot of special technology and software that they just can't do themselves, it's not possible. It's just like you can't build your own smartphone. It's just really not possible. >> Now, another area that we've covered extensively, we were there at the unveiling, as well is ZDLRA, Zero Data Loss Recovery Appliance. We've always liked this product, especially for mission critical workloads, we're near zero data loss, where you can justify that. But while we always saw it as somewhat of a niche market, first of all, is that fair, and what's new with ZDLRA? >> Yeah ZDLRA has been in the market for a number of years. We have some of the biggest corporations in the world running on that, and one of the big benefits has been zero data loss, so again, if you care about data, you can't lose data. You can't restore to last night's backup if something happens. So if you're a bank, you can't restore everybody's data to last night. Suppose you made a deposit during the day. They're like, "Hey, sorry, Mr. Customer, your deposit, "well, we don't have any record of it anymore, "'cause we had to restore to last night's backup," you know, that doesn't work. It doesn't work for airlines. It doesn't work for manufacturing. That whole model is obsolete, so you need zero data loss, and that's why we introduced Zero Data Loss Recovery Appliance, and it's been very successful in the market. In addition to zero data loss, it actually provides much faster restore, much more reliable restores. It's more scalable, so it has a lot of advantages. With our X9M generation, we're introducing several new capabilities. First of all, it has higher capacity, so we can store more backups, keep data for longer. Another thing is we're actually dropping the price of the entry-level configuration of ZDLRA, so it makes it more affordable and more usable by smaller businesses, so that's a big deal. And then the other thing that we're hearing a lot about, and if you read the news at all, you hear a lot about ransomware. This is a major problem for the world, cyber criminals breaking into your network and taking the data ransom. And so we've introduced some, we call cyber vault capabilities in ZDLRA. They help address this ransomware issue that's kind of rampant throughout the world, so everybody's worried about that. There's now regulatory compliance for ransomware that particularly financial institutions have to conform to, and so we're introducing new capabilities in that area as well, which is a big deal. In addition, we now have the ability to have multiple ZDLRAs in a large enterprise, and if something happens to one, we automatically fail over backups to another. We can replicate across them, so it makes it, again, much more resilient with replication across different recovery appliances, so a lot of new improvements there as well. >> Now, is an air gap part of that solution for ransomware? >> No, air gap, you really can't have your back, if you're continuously streaming changes to it, you really can't have an air gap there, but you can protect the data. There's a number of technologies to protect the data. For example, one of the things that a cyber criminal wants to do is they want to take control of your data and then get rid of your backup, so you can't restore them. So as a simple example of one thing we're doing is we're saying, "Hey, once we have the data, "you can't delete it for a certain amount of days." So you might say, "For the 30 days, "I don't care who you are. "I don't care what privileges you have. "I don't care anything, I'm holding onto that data "for at least 30 days," so for example, a cyber criminal can't come in and say, "Hey, I'm going to get into the system "and delete that stuff or encrypt it," or something like that. So that's a simple example of one of the things that the cyber vault does. >> So, even as an administrator, I can't change that policy? >> That's right, that's one of the goals is doesn't matter what privileges you have, you can't change that policy. >> Does that eliminate the need for an air gap or would you not necessarily recommend, would you just have another layer of protection? What's your recommendation on that to customers? >> We always recommend multiple layers of protection, so for example, in our ZDLRA, we support, we offload tape backups directly from the appliance, so a great way to protect the data from any kind of thing is you put it on a tape, and guess what, once that tape drive is filed away, I don't care what cyber criminal you are, if you're remote, you can't access that data. So, we always promote multiple layers, multiple technologies to protect the data, and tape is a great way to do that. We can also now archive. In addition to tape, we can now archive to the public cloud, to our object storage servers. We can archive to what we call our ZFS appliance, which is a very low cost storage appliance, so there's a number of secondary archive copies that we offload and implement for customers. We make it very easy to do that. So, yeah, you want multiple layers of protection. >> Got it, okay, your tape is your ultimate air gap. ZDLRA is your low RPO device. You've got cloud kind of in the middle, maybe that's your cheap and deep solution, so you have some options. >> Juan: Yes. >> Okay, last question. Summarize the announcement, if you had to mention two or three takeaways from the X9M announcement for our audience today, what would you choose to share? >> I mean, it's pretty straightforward. It's the new generation. It's significantly faster for OLTP, for analytics, significantly better consolidation, more cost-effective. That's the big picture. Also there's a lot of software enhancements to make it better, improve the management, make it more usable, make it better disaster recovery. I talked about some of these cyber vault capabilities, so it's improved across all the dimensions and not in small ways, in big ways. We're talking 50% improvement, 80% improvements. That's a big change, and also we're keeping the price the same, so when you get a 50 or 80% improvement, we're not increasing the price to match that, so you're getting much better value as well. And that's pretty much what it is. It's the same product, even better. >> Well, I love this cadence that we're on. We love having you on these video exclusives. We have a lot of Oracle customers in our community, so we appreciate you giving us the inside scope on these announcements. Always a pleasure having you on theCUBE. >> Thanks for having me. It's always fun to be with you, Dave. >> All right, and thank you for watching. This is Dave Vellante for theCUBE, and 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)