>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is "Breaking Analysis" with Dave Vellante. >> If it weren't for Pat Gelsinger, Intel's future would be a disaster. Even with his clear vision, fantastic leadership, deep technical and business acumen, and amazing positivity, the company's future is in serious jeopardy. It's the same story we've been telling for years. Volume is king in the semiconductor industry, and Intel no longer is the volume leader. Despite Intel's efforts to change that dynamic With several recent moves, including making another go at its Foundry business, the company is years away from reversing its lagging position relative to today's leading foundries and design shops. Intel's best chance to survive as a leader in our view, will come from a combination of a massive market, continued supply constraints, government money, and luck, perhaps in the form of a deal with apple in the midterm. Hello, and welcome to this week's "Wikibon CUBE Insights, Powered by ETR." In this "Breaking Analysis," we'll update you on our latest assessment of Intel's competitive position and unpack nuggets from the company's February investor conference. Let's go back in history a bit and review what we said in the early 2010s. If you've followed this program, you know that our David Floyer sounded the alarm for Intel as far back as 2012, the year after PC volumes peaked. Yes, they've ticked up a bit in the past couple of years but they pale in comparison to the volumes that the ARM ecosystem is producing. The world has changed from people entering data into machines, and now it's machines that are driving all the data. Data volumes in Web 1.0 were largely driven by keystrokes and clicks. Web 3.0 is going to be driven by machines entering data into sensors, cameras. Other edge devices are going to drive enormous data volumes and processing power to boot. Every windmill, every factory device, every consumer device, every car, will require processing at the edge to run AI, facial recognition, inference, and data intensive workloads. And the volume of this space compared to PCs and even the iPhone itself is about to be dwarfed with an explosion of devices. Intel is not well positioned for this new world in our view. Intel has to catch up on the process, Intel has to catch up on architecture, Intel has to play catch up on security, Intel has to play catch up on volume. The ARM ecosystem has cumulatively shipped 200 billion chips to date, and is shipping 10x Intel's wafer volume. Intel has to have an architecture that accommodates much more diversity. And while it's working on that, it's years behind. All that said, Pat Gelsinger is doing everything he can and more to close the gap. Here's a partial list of the moves that Pat is making. A year ago, he announced IDM 2.0, a new integrated device manufacturing strategy that opened up its world to partners for manufacturing and other innovation. Intel has restructured, reorganized, and many executives have boomeranged back in, many previous Intel execs. They understand the business and have a deep passion to help the company regain its prominence. As part of the IDM 2.0 announcement, Intel created, recreated if you will, a Foundry division and recently acquired Tower Semiconductor an Israeli firm, that is going to help it in that mission. It's opening up partnerships with alternative processor manufacturers and designers. And the company has announced major investments in CAPEX to build out Foundry capacity. Intel is going to spin out Mobileye, a company it had acquired for 15 billion in 2017. Or does it try and get a $50 billion valuation? Mobileye is about $1.4 billion in revenue, and is likely going to be worth more around 25 to 30 billion, we'll see. But Intel is going to maybe get $10 billion in cash from that, that spin out that IPO and it can use that to fund more FABS and more equipment. Intel is leveraging its 19,000 software engineers to move up the stack and sell more subscriptions and high margin software. He got to sell what he got. And finally Pat is playing politics beautifully. Announcing for example, FAB investments in Ohio, which he dubbed Silicon Heartland. Brilliant! Again, there's no doubt that Pat is moving fast and doing the right things. Here's Pat at his investor event in a T-shirt that says, "torrid, bringing back the torrid pace and discipline that Intel is used to." And on the right is Pat at the State of the Union address, looking sharp in shirt and tie and suit. And he has said, "a bet on Intel is a hedge against geopolitical instability in the world." That's just so good. To that statement, he showed this chart at his investor meeting. Basically it shows that whereas semiconductor manufacturing capacity has gone from 80% of the world's volume to 20%, he wants to get it back to 50% by 2030, and reset supply chains in a market that has become important as oil. Again, just brilliant positioning and pushing all the right hot buttons. And here's a slide underscoring that commitment, showing manufacturing facilities around the world with new capacity coming online in the next few years in Ohio and the EU. Mentioning the CHIPS Act in his presentation in The US and Europe as part of a public private partnership, no doubt, he's going to need all the help he can get. Now, we couldn't resist the chart on the left here shows wafer starts and transistor capacity growth. For Intel, overtime speaks to its volume aspirations. But we couldn't help notice that the shape of the curve is somewhat misleading because it shows a two-year (mumbles) and then widens the aperture to three years to make the curve look steeper. Fun with numbers. Okay, maybe a little nitpick, but these are some of the telling nuggets we pulled from the investor day, and they're important. Another nitpick is in our view, wafers would be a better measure of volume than transistors. It's like a company saying we shipped 20% more exabytes or MIPS this year than last year. Of course you did, and your revenue shrank. Anyway, Pat went through a detailed analysis of the various Intel businesses and promised mid to high double digit growth by 2026, half of which will come from Intel's traditional PC they center in network edge businesses and the rest from advanced graphics HPC, Mobileye and Foundry. Okay, that sounds pretty good. But it has to be taken into context that the balance of the semiconductor industry, yeah, this would be a pretty competitive growth rate, in our view, especially for a 70 plus billion dollar company. So kudos to Pat for sticking his neck out on this one. But again, the promise is several years away, at least four years away. Now we want to focus on Foundry because that's the only way Intel is going to get back into the volume game and the volume necessary for the company to compete. Pat built this slide showing the baby blue for today's Foundry business just under a billion dollars and adding in another $1.5 billion for Tower Semiconductor, the Israeli firm that it just acquired. So a few billion dollars in the near term future for the Foundry business. And then by 2026, this really fuzzy blue bar. Now remember, TSM is the new volume leader, and is a $50 billion company growing. So there's definitely a market there that it can go after. And adding in ARM processors to the mix, and, you know, opening up and partnering with the ecosystems out there can only help volume if Intel can win that business, which you know, it should be able to, given the likelihood of long term supply constraints. But we remain skeptical. This is another chart Pat showed, which makes the case that Foundry and IDM 2.0 will allow expensive assets to have a longer useful life. Okay, that's cool. It will also solve the cumulative output problem highlighted in the bottom right. We've talked at length about Wright's Law. That is, for every cumulative doubling of units manufactured, cost will fall by a constant percentage. You know, let's say around 15% in semiconductor world, which is vitally important to accommodate next generation chips, which are always more expensive at the start of the cycle. So you need that 15% cost buffer to jump curves and make any money. So let's unpack this a bit. You know, does this chart at the bottom right address our Wright's Law concerns, i.e. that Intel can't take advantage of Wright's Law because it can't double cumulative output fast enough? Now note the decline in wafer starts and then the slight uptick, and then the flattening. It's hard to tell what years we're talking about here. Intel is not going to share the sausage making because it's probably not pretty, But you can see on the bottom left, the flattening of the cumulative output curve in IDM 1.0 otherwise known as the death spiral. Okay, back to the power of Wright's Law. Now, assume for a second that wafer density doesn't grow. It does, but just work with us for a second. Let's say you produce 50 million units per year, just making a number up. That gets you cumulative output to $100 million in, sorry, 100 million units in the second year to take you two years to get to that 100 million. So in other words, it takes two years to lower your manufacturing cost by, let's say, roughly 15%. Now, assuming you can get wafer volumes to be flat, which that chart showed, with good yields, you're at 150 now in year three, 200 in year four, 250 in year five, 300 in year six, now, that's four years before you can take advantage of Wright's Law. You keep going at that flat wafer start, and that simplifying assumption we made at the start and 50 million units a year, and well, you get to the point. You get the point, it's now eight years before you can get the Wright's Law to kick in, and you know, by then you're cooked. But now you can grow the density of transistors on a chip, right? Yes, of course. So let's come back to Moore's Law. The graphic on the left says that all the growth is in the new stuff. Totally agree with that. Huge term that Pat presented. Now he also said that until we exhaust the periodic table of elements, Moore's Law is alive and well, and Intel is the steward of Moore's Law. Okay, that's cool. The chart on the right shows Intel going from 100 billion transistors today to a trillion by 2030. Hold that thought. So Intel is assuming that we'll keep up with Moore's Law, meaning a doubling of transistors every let's say two years, and I believe it. So bring that back to Wright's Law, in the previous chart, it means with IDM 2.0, Intel can get back to enjoying the benefits of Wright's Law every two years, let's say, versus IDM 1.0 where they were failing to keep up. Okay, so Intel is saved, yeah? Well, let's bring into this discussion one of our favorite examples, Apple's M1 ARM-based chip. The M1 Ultra is a new architecture. And you can see the stats here, 114 billion transistors on a five nanometer process and all the other stats. The M1 Ultra has two chips. They're bonded together. And Apple put an interposer between the two chips. An interposer is a pathway that allows electrical signals to pass through it onto another chip. It's a super fast connection. You can see 2.5 terabytes per second. But the brilliance is the two chips act as a single chip. So you don't have to change the software at all. The way Intel's architecture works is it takes two different chips on a substrate, and then each has its own memory. The memory is not shared. Apple shares the memory for the CPU, the NPU, the GPU. All of it is shared, meaning it needs no change in software unlike Intel. Now Intel is working on a new architecture, but Apple and others are way ahead. Now let's make this really straightforward. The original Apple M1 had 16 billion transistors per chip. And you could see in that diagram, the recently launched M1 Ultra has $114 billion per chip. Now if you take into account the size of the chips, which are increasing, and the increase in the number of transistors per chip, that transistor density, that's a factor of around 6x growth in transistor density per chip in 18 months. Remember Intel, assuming the results in the two previous charts that we showed, assuming they were achievable, is running at 2x every two years, versus 6x for the competition. And AMD and Nvidia are close to that as well because they can take advantage of TSM's learning curve. So in the previous chart with Moore's Law, alive and well, Intel gets to a trillion transistors by 2030. The Apple ARM and Nvidia ecosystems will arrive at that point years ahead of Intel. That means lower costs and significantly better competitive advantage. Okay, so where does that leave Intel? The story is really not resonating with investors and hasn't for a while. On February 18th, the day after its investor meeting, the stock was off. It's rebound a little bit but investors are, you know, they're probably prudent to wait unless they have really a long term view. And you can see Intel's performance relative to some of the major competitors. You know, Pat talked about five nodes in for years. He made a big deal out of that, and he shared proof points with Alder Lake and Meteor Lake and other nodes, but Intel just delayed granite rapids last month that pushed it out from 2023 to 2024. And it told investors that we're going to have to boost spending to turn this ship around, which is absolutely the case. And that delay in chips I feel like the first disappointment won't be the last. But as we've said many times, it's very difficult, actually, it's impossible to quickly catch up in semiconductors, and Intel will never catch up without volume. So we'll leave you by iterating our scenario that could save Intel, and that's if its Foundry business can eventually win back Apple to supercharge its volume story. It's going to be tough to wrestle that business away from TSM especially as TSM is setting up shop in Arizona, with US manufacturing that's going to placate The US government. But look, maybe the government cuts a deal with Apple, says, hey, maybe we'll back off with the DOJ and FTC and as part of the CHIPS Act, you'll have to throw some business at Intel. Would that be enough when combined with other Foundry opportunities Intel could theoretically produce? Maybe. But from this vantage point, it's very unlikely Intel will gain back its true number one leadership position. If it were really paranoid back when David Floyer sounded the alarm 10 years ago, yeah, that might have made a pretty big difference. But honestly, the best we can hope for is Intel's strategy and execution allows it to get competitive volumes by the end of the decade, and this national treasure survives to fight for its leadership position in the 2030s. Because it would take a miracle for that to happen in the 2020s. Okay, that's it for today. Thanks to David Floyer for his contributions to this research. Always a pleasure working with David. Stephanie Chan helps me do much of the background research for "Breaking Analysis," and works with our CUBE editorial team. Kristen Martin and Cheryl Knight to get the word out. And thanks to SiliconANGLE's editor in chief Rob Hof, who comes up with a lot of the great titles that we have for "Breaking Analysis" and gets the word out to the SiliconANGLE audience. Thanks, guys. Great teamwork. Remember, these episodes are all available as podcast wherever you listen. Just search "Breaking Analysis Podcast." You'll want to check out ETR's website @etr.ai. We also publish a full report every week on wikibon.com and siliconangle.com. You could always get in touch with me on email, david.vellante@siliconangle.com or DM me @dvellante, and comment on my LinkedIn posts. This is Dave Vellante for "theCUBE Insights, Powered by ETR." Have a great week. Stay safe, be well, and we'll see you next time. (upbeat music)

(upbeat music) >> From around the globe, it's theCUBE with digital coverage of Postgres vision 2021 brought to you by EDB. >> Hello everybody. Welcome back to Postgres Vision 21. My name is Dave Vellante and we're super excited to have Josh Berkus on. He's joining us, he's a leader in the Kubernetes community, extremely well-versed in containerized applications, application development, containerizing databases all things Open-source, CUBE alum, Josh Berkus welcome back to theCUBE. Great to see you again. >> Thank you. I'm glad to be here. >> Just recently, you're coming off KuberCon, we heard some of the themes from that event. There was a lot of focus on inclusion and diversity, which of course, you know, that's the Open-source ethos and a lot of discussion around designing security in, the whole conversation about shift left. That's great to see larger companies giving back, to obviously a lot of the pressure over the years on the big companies that there's a one-way street, they're actually giving back, making some investments. So we love to see that. And just Open-source continues to be the main spring of innovation. I got to say, I got to call-out and a recent Red Hat survey the state of the enterprise Open-source in 2021, 90% of technology leaders said that they're adopting Open-source and made a joke that the other 10% they're doing it they just don't know it. But so what were some of your takeaways from the event and some of the trends you're seeing but specifically as it relates to containers. >> So, I mean, you're right, one thing is this sort of return to security, the security topic again because we've had like a couple of things happen. One was, when we initially got, started doing containers or platform with Docker and with early Kubernetes and that sort of thing we got a lot of container image scan, right? So you have like Clare and Docker has a scanning thing and Amazon and Azure have their own scanning things. And people felt that was kind of good enough for a while but then we both had the solar winds hack. And the thing is like, in the meantime, we've gone from a stage where people were mostly using Kubernetes in dev to people using Kubernetes in production. And there's a lot of extra security issues and vulnerabilities that come up in an actual production environment that people just didn't necessarily think about before. And so now we're looking at adding more pieces to the security stack and making those more standard for everyone who uses Kubernetes. And I've had the chance to work with the StackRox folks since they became part of Red Hat. So it's been very exciting to look at the whole thing and look at things like container supply chain because the solar winds showed us obviously, it's not enough to necessarily just trust the vendor. You need to trust their whole supply chain. And it helps to be able to examine that supply chain. >> Yeah, it's very scary when you look at that you're absolutely right. Multiple components of malware coming into an organization through the supply chain cell forming, different signatures. And so it's great to see the community spending time on that and an emphasis on that. Now I got to cut right to the chase here, in 2018, you wrote a two-part blog series it's called Should I run Postgres in Kubernetes? Obviously it's highly relevant for this community. So I want to talk about your perspective, well, first of all, the thing I love about you is you're tactical and you can go deep, but at the same time, you can speak to a business audience. >> Thanks. >> You're welcome and thank you for writing this and communicating the way you do, but talk about when it makes sense and when it doesn't, I mean, that's kind of... My big three takeaways on the pros were simplify, simplify, simplify, especially if you're running application components and other services on Kubernetes but give us the update three years later, why should you, why shouldn't? >> You know let's actually, why don't we zoom out to an even bigger picture? Which is just honestly like every new platform that we've got, right? So when virtualization and VMware became a thing we had the same sort of decisions about when do I move my database to this, when AWS and the public cloud became a thing. I could have like, like if I had written that 12 years ago I could have written it about AWS and it would have had a lot of the same decision tree 'cause what it really sort of comes down to is the more commodifiable a particular database instance is the better candidate it is to move to an advanced infrastructure platform, and the most advanced, currently being Kubernetes. To the extent that you can describe this particular database, what it does, who needs to use it, what's in it in and a simple one pager then that's probably a really good candidate for hosting on Kubernetes. Whereas if you have a database where it's like, Hey, the entire company uses it and it's so complicated we can't describe it's inputs and outputs. That's possibly the last thing in your company that you're going to migrate to Kubernetes, because both in terms of there's less gain to be made there, because the real advantage of moving stuff to Kubernetes is your ability to automate things. The whole way I got into Kubernetes in the first place was I started out way down the line not using containers at all. I was just looking to solve the problem of how do we automate Postgres high availability. That's what I was looking for. And it started out with something I built using SaltStack called handy rep, that Casey and I built. And mostly that was a problem discovery exercise, we discovered what the hard problems were there. And then we moved from that, and then we moved from that to Docker because containers offered an encapsulation strategy because one of the problems you run into when automating high availability is the database actually down or not. And so the first thing that containers offered us was not packaging, what people usually talk about but instead of encapsulation, right, because it's a lot easier to determine is the container running or not, than is the database down or not? Because an actual Postgres database has multiple components and multiple processes that make it up. And some of those can be down without the others being down which can then make you think a database is down that's not actually shut down. And being able to put that in a container, it gives me more of a binary up or down. And then from there, I got into, okay, well but I need to automate a lot of other components. I need to automate the storage and everything else. And that led to Kubernetes. And so if you look at it in terms of deciding when you're going to migrate the database to Kubernetes you look at, can I take advantage of that automation? Is this something that my application workflow and my team organization allows me to do? And if the answer is yes, particularly, if you're in a company that's doing the full dev ops thing where you have a unified development and infra team that owns the entire stack then those people are going to be a really good candidate for moving that stack to Kubernetes. >> Got it. Okay, so let me ask you, in database especially in critical apps, your recovery's everything, when something goes wrong, you got to recover. So if I understand it correctly, just in reading and listening to you, if you've got Kubernetes expertise and you're building applications in that environment then the application components are in there. And am I inferring correctly that you're going to be able to automate and facilitate high quality recovery with certainty? >> Yeah, there's a bunch of infrastructure involved, and this is why, what enterprises do is they move things like the web front-end to Kubernetes first and is what they should do, right? That is absolutely the right order of things to do because the minute that you're looking at bringing databases in, you're now looking at your whole storage infrastructure. So that direct attack storage that was attached physically to one machine is not going to work once you've moved to a container-based cloud. You suddenly need a way to be able to attach that storage to any of the nodes in your cluster so that you can move the database around and you can have fail-over. But once you build those things up, you can't. I mean, some of the stuff that I've done, I work in the office of the CTO now at Red Hat. So I'm not in production support. So the only Postgres instance I'm supporting are ones for some Open-source projects we support like the Python project. And in those cases, it's not a high criticality database, but I'm not support, I'm not on call on the weekend. I want something where it doesn't require need to be on call in order for it to stay up. And so putting that on open shift with the Patroni fail-over driver was the answer for that. And it has failed over in the Red Hat IT team contacts me and says, "Hey, we need to move those servers. And then we'll just add a node to the cluster and delete the old node and it'll do the right thing." And I don't have to worry about it, which is really what you're going for there. >> The other thing I took away from your writing was that you suggested that a lot of the successes in areas where the Postgres databases were rather small and there were a lots of them. And so to the extent that you can automate that you're going to save yourself a lot of problems. Whereas in the flip side if you're running extremely large databases or there may be performance constraint that might be an area to be a little bit more circumspect. >> Yeah and that's absolutely true because like the other side of this, like I've worked with the dev ops people and the people who are on Heroku and that sort of thing that have one database per application, right. And those people are great candidates for migrating. But then I've also worked with the people who have a one big database for the company, where the database is three terabytes in size, it powers their reporting system and their customer's system and the web portal and everything else in one database. That's the one that's really going to be a hard call and that you might in fact, never physically migrate to Kubernetes because even if it's on Kubernetes you are going to mess with the hardware policy to give it its own dedicated machine. So in that case, what I would honestly tend to do is there's a feature in Kubernetes called service catalog that allows you to expose an external service within Kubernetes as if it were a Kubernetes service. And that's what I tend to do with those kinds of databases because it's, there's not a huge advantage in actually physically moving the database to a container. There's a bunch of steps involved and going via service catalog is a lot easier. >> But essentially you're you're speaking the same language in that example that you just gave. >> Yeah. >> Now, the other thing you pointed out at the time that you wrote this article is there's a lot of pre 1.0 kind of alpha in the Kubernetes stack and it might be prudent to if, not putting your HIPAA compliant, since it evolved. >> Yeah, if I was to update two things in the article I guess that would be one of them the other one I'll get to in a minute. So the first one is that, Kubernetes has progressed along that maturity timeline. Like we recently added the production readiness reviews as part of our feature review process. We've really improved tested adherence, so that we're not releasing with known broken tests, and a bunch of other things to make it more stable. But part of it depends on who I'm talking to because there's still degrees here. So if I'm talking to the context of the world of software then Kubernetes has reached the point of maturity that it is as stable as anything else. And if you use a release, you can assume that any sort of major issues have been worked out. The one difference with it and some other platforms people may have used is it's still young enough that backwards compatibility can be an issue. As in Kubernetes releases now three times a year, we've stepped down from four and within three releases you can find yourself needing to change API calls which means needing to refactor parts of your application. So if you compare that with some other things, like a JVM platform, when's the last time you had a major API change with a JVM platform. But you know the Kubernetes is only six years old, so that's part of that. The other thing is the question is I'm talking to the Postgres community, right? Which is within Postgres, people run the daily Postgres snapshot in production. I would not do that with Kubernetes, I would wait for release. So there's still kind of a difference there if people are coming from the Postgres community, right. Is we're used to this really extreme level of stability that we have with Postgres and Kubernetes as a much younger project isn't quite there yet. >> So that's a process, a change that you would have to be aware of if you want to take the benefits of containers with Postgres, you just have to really understand that and make that process part of your change management. >> The other thing I would say has changed is there are new opportunities in running your data warehouse, your big data databases on Kubernetes. A number of platforms, the one I'm most familiar with is Citus, because I worked with those folks that have taken advantage of Kubernetes as a deployment and management platform for their database, their big data database infrastructure, which makes sense because if you look at a lot of modern data analysis and data mining platforms that are built on top of Postgres part of how they do their work is they actually run a bunch of little Postgres instances that they federate together. And then Kubernetes becomes the tool that allows you to manage all of those little Postgres instances. So that's the sort of exception to the, should I migrate this really big database? That can be a yes, if you are migrating it to a big data platform that supports Kubernetes, then it can be a huge advantage. >> Obviously you've got the practitioner knowledge and you were working in the community. I'm wondering if you can share just thinking about sort of the motivation to move to a container environment if you're one of the Postgres folks in the audience could you share any, either anecdotal or other data on business impact, benchmarks that you've seen, some of the things that you've seen some positives there? >> If you actually look at my history when you talk about performance is one, right? And if you actually look at my history, I actually did, and for that matter of some of the folks from Percona and some of our other folks in the database field did a bunch of benchmarks of running Postgres in MySQL, on Kubernetes versus running it not on Kubernetes. And one of the advantages of containers over VMS is that there isn't any intrinsic, there's not any intrinsic sort of layer gap or virtualization that modifies your performance. In other words, if a container is using storage that's present on the node where the container is running it is using that storage through Linux. And therefore the performance is, with some caveats, performance is going to be identical to if you were running that on the host system. Now, where performance differences creep in is that you might not be able to use the same kind of storage. In that Kubernetes and containers systems in general are organized around the idea that no service is using a majority of the resources on the system, so again, if you're planning on user running a larger Postgres database that really needs all the RAM that a system has you're going to have to do a lot of tinkering with Kubernetes configuration to get the same performance, you would have a running it on a dedicated hardware now. >> Okay, but fundamentally you're saying that overhead is less with caveats, like you said, you just mentioned in the story, right? >> Yeah, well, the overhead is not any different from if you were running under the host system. So a really good example of that was, if you go back to on my lightning talking in, (indistinct) Austin, I think. I showed running a benchmark with Postgres on an AWS instance using EBS storage, both not in Kubernetes and in Kubernetes. And there was no perceptible performance difference between the two of them because it was all metered by how fast was EBS for me. >> Right, and I said less, but I should've been more specific less than say you would expect with virtualization. >> Right, and then it just comes down to a business decision, which is that if you're already on some sort of cloud storage or network storage, and again you have databases that can share hardware systems then you shouldn't really expect substantial performance differences by moving to Kubernetes. That's something that you can eliminate inside of words, but if you're going in the process going to be migrating from direct attached storage to network storage then you are going to see a performance difference but that's caused by the change in storage. Or if you're going to be moving from systems that are not shared to systems that aren't shared again you're going to see a difference from them, but it wouldn't be any different than if you did that without Kubernetes containers being involved. >> If you're using any world-class shared storage device from whatever name of big vendor, you're going to accommodate if you're racking and stacking your own flash drives or worse yet spinning disk drives that's in direct attached, that's maybe a different story, so, okay. That's good. Where would you advise people to get started with Postgres and Kubernetes? >> The nice thing is there are a number of advanced systems now, and advanced systems that are supported by the various Postgres vendors. And that can actually be a great place to get started because the systems are Open-source so you can try them out. This is, as far as I know, they're Open-source you can try them out but then if you decide you like them, you can get support. And so that would include Crunchy data. Enterprise DB has a system, and honestly, I have to admit less familiar with than the ones that Crunchy runs. StackRox is another one out of Europe that has their own system for running cloud native Postgres. And there's one I'm forgetting, and what a lot of these have to do with is taking advantage of the automation. 'Cause you can obviously can put Postgres and container play around, right? But your whole point of moving to Kubernetes in general is going to be take advantage of the automation, so you want to look at the various automation platforms and you can go ahead and do that and the one I'm most familiar with because I develop it as Patroni, is the component for automating Postgres. You do Patroni plus you do operators, it's another word that comes in here. But if you're looking at this as a business you're probably going to want something that supported or that at least there's a potential to buy support and a bunch of the different companies in the Postgres space package up these components for you into a platform. Like I know the Crunchy platform uses Patroni plus some proxy stuff, plus PG back rest plus a couple of other things to give you a sort of full automation platform for running Postgres on Kubernetes. >> Awesome, last question. Where are we in the whole container adoption, we started out kind of you've mentioned this stateless and now you're building stateful applications but still you look at the, we look at spending data with our data partners ETR and containers and container orchestration. It's it's right up there with RPA, with cloud, with AI just in terms of the attention and resource that's going in. So it's exploding. It feels like it's still early days. There's a lot of legs left, what do you see? >> Yeah, well, a lot of it is, I mean you're talking about migrating IT infrastructure, right? So where we are with Kubernetes is we have the early adopters, right? We have all the people who were at the point of building their new infrastructure when Kubernetes came out, right. And people who had major unsolved problems which is a big reason for adopting a new platform was just was no old platform for you. and so we sort of have those people and those people are already on Kubernetes and running their stuff there. And so now we're looking at the really long path of people who are not in one of those camps moving, right. And in a lot of cases, that's a matter of coinciding with other reasons why they have to look at an upgrade because even if, whether it's the gradual replacement of old applications by new ones, where you gradually all the legacy applications get offline and the new applications run in Kubernetes or sometimes it's a, "Hey we're waiting for replacement cycle." We're waiting for, we already had plans to move from on-prem to public cloud, and so we're going to move from on-prem to public cloud on Kubernetes, to make it part of the migration. And that'll be years. I still like, I have fingers into other areas, like I still know a lot of people in the nonprofit space and a lot of nonprofits just got around to adopting virtualization, right? Like they're not even at public cloud yet. I don't even talk to them about Kubernetes. There's this huge long tail in terms of adoption. The nice thing is we don't show any signs of stopping, is that one of the things that we kind of learned from earlier stuff particularly learned from our friends at OpenStack was to really really focus on the APIs, to look at who Kubernetes more as the hub of a system of an infrastructure idea with potentially unbounded growth. If you have a new concept that comes in like service mesh, service mesh is not a successor to Kubernetes. It's not an alternative to Kubernetes. It is a thing you layer on top of Kubernetes because we didn't make it exclusive. >> Right. Great, great example going back to OpenStack and thank you for bringing that in because there's lessons learned. And so Josh, we've got to leave it there. Thanks so much for coming back in theCUBE, great conversation, you're awesome. >> Okay, good to talk to you. >> All right, and thank you for watching everybody, keep it right there for more content from Postgres Vision 21. My name is Dave Vellante, you're watching theCUBE. (upbeat music)

(upbeat music) >> From around the globe, it's theCUBE! With digital coverage of Postgres Vision 2021, brought to you by EDB. >> Welcome back to Postgres Vision 21, where theCUBE is covering the innovations in open source trends in this new age of application development and how to leverage open source database technologies to create world-class platforms that are cost-effective and also scale. My name is Dave Vellante, and with me is Roberto Giordano, who is the End User Computing, Corporate, and Database Services Manager at Borsa Italiana, the Italian Stock Exchange. Roberto, great to have you. Thanks for coming on. >> Thanks Dave, and thanks to the interview friend for the invitation. >> Okay, and we're going to dig in to the great customer story here. First, Roberto, tell us a little bit more about Borsa Italiana and your role at the organization. >> Absolutely. Well, as you mentioned, Borsa is the Italian Stock Exchange. We used to be part of the London Stock Exchange, but last month we left that group, and we joined another group called Euronext, so we are now part of another group, I would say. And right now within Euronext, Euronext provide the biggest liquidity pool in Europe, just to mention something. And basically we provide the market infrastructure to our customers across Europe and the whole world. So probably if it happens for you to buy a little of, I don't know, Ferrari for instance, probably use our infrastructure. >> So I wonder if you could talk about the key drivers in the exchange business in Italy. I don't know how closely you follow what's going on in the United States, but it's crypto madness, there's the Reddit army driving up stocks that have big short positions, and of course the regulators have to look at that, and there's a big debate going on. Well, I don't know what's it like in Italy, but what are the key drivers that are really informing the priorities for your technology strategy? >> Well, you mentioned, for instance, the stereotypical cases that are a little bit of laterally to the global markets and also to our markets as a it professional running market infrastructure is our first the goal to provide an infrastructure that is reliable and be with the lowest possible latency. So we are very focused on performance and reliability just to mention the two main drivers within our systems. >> Well, and you have end-user computing in your title and we're going to get into the database discussion, but I presumably with with COVID you had to pivot and that that piece of your job was escalated in 2020, I would imagine. And you mentioned latency which is a key factor in obviously in database access but that must've been a big challenge last year. >> Well, it was really a challenge, but basically we move just within a weekend, the wall organization working remotely. And it has been like this since February, 2020. Think about the challenge of moving almost 1000 people that used to come to the office every day to start to work remotely. And as within my team of the end user computing this was really a challenge but it was a good one at the end. We, we, we succeeded and everything work. It's fine from our perspective, no news is is a good news, you know, because normally when something doesn't work, we are on newspapers. So if you didn't heard about us it means that everything worked out just fine. >> Yeah. It's amazing, Roberto. We both in the technology business that you'll be you're a practitioner observer, but I mean if you're in the tech business most companies actually pivoted quite well. You're have always been a digital business, different. I mean, if you're a Ferrari and making cars and you can't get semiconductors, but but most technology companies actually made the transition you know, quite amazingly, let's get into the, the case study a bit of it. I wonder if you could paint a picture of your organization's infrastructure and applications what it looks like and and particularly your database infrastructure what does that look like? >> Well, we are a multi-vendor shop. So we would like to pick the right technology for for the right service. This means that my database services teams currently manage several different technology where possible that plays a big role in, in, in our portfolio. And because we, we, we currently support both the open source, fully open source version of Postgres, but also the EDB distribution in particular we prefer to use EDB distribution where we did specific functionalities that just EDB provide. And we, when we need a first class level of support that EDB in recent year was able to provide to us. >> When you say full functioning, are you talking about things like acid compliance, two phase commits? I mean, all these enterprise capabilities, is that right? Or maybe you could be >> Just too much just to mention one, for instance we recently migrated our wire intrasite availability solution using the ADB fail-over manager. That is an additional component that just it'll be provide. >> Yeah. Okay. So, so par recovery obviously is, is and so that's a solution that you to get from the EDB distro as opposed to having to build it yourself with open source tooling. >> Yeah, correct. Well, basically sterically, we used to rely on OSTP clustering from, from, from that perspective. But over the years we found that even if it's a technology that works fine, it has been around for four decades. And so on. We faced some challenges internally because within my team we don't own also the operative system layers. So we want a solution that was 100% within our control and perimeter. So just few months ago we asked the EDB EDB folks if they can provide something. And after a couple of meetings also with their pre-sales engineers, we found the the right solution for us. So we launched long story short, just a quick proof of concept to a tissue test together, again using the ADB consultancy. And, and then we, beginning of this year, we, we went live with the first mission critical service using this brand new technology, well brand new technology for us. You know, it'd be created a few years ago >> And I do have some follow-up questions but I want to understand what catalyzed the, you know what was the motivation for going with an open source database? I mean, you're, you're a great example because you have your multi-vendor so you have experienced with all of it, the full spectrum. What was it about open source database generally EDB specifically that triggered the, the choice? >> Well thanks for the question. It is, this is one of the, or one of the questions that I always, like. I think what really drove us was the right combination between easy to use, so simplicity and also good value for money. So we like to pick the right database technology for the right kind of service slash budget that the survey says and, and the open source solution for a specific service. It, it, it's, it's our, you know, first, first, first choice. So we are not going to say a company that use just one technology. We like to take the best of breed that the market can offer. In some cases, the open source and Postgres in particular is, is our choice. How involved was >> The line of business in this both the decision and the implementation? Was it kind of invisible to them, or this was really more of a technology decision based on the your interpretation of the requirements I'm interested in who was involved and how you actually got it done? >> Well, I, I think this decision was transplant for, for, for, for the business at the end of the day don't really have that kind of visibility. You know, they just provide requirements in particular in terms of performance and rehabil area, the reliability. And so, so this this is something they are not really involved about. And obviously if they, if we are in opposition to save a little bit of money everybody's at the, even the business >> No. So what did you have to do? So that makes sense to me, I figured that was the case. Who would, who were the stakeholders on your team? I mean, what kind of technical resources did you require an implementation resources? What take us through what the project if you will look like, wh how did you do it? >> Well, it's a combination of database expertise. I got the pleasure to run a team that is paid by very, very senior, very, very skilled database services professional that are able to support more than one more than what the county and also are very open to innovation and changes. Plus obviously we need also the development teams the relevant development teams on board, when you when you run this kind of transformations and it looks like also, they liked the idea to use PostgreSQL for for this specific service I got in mind. So it, it, it was quite, quite easy, not be discussion. You know. >> What was the, what was the elapsed time from from when you said, okay, we're in, you know signed the agreement we're going here you made the decision to actually getting into production. >> Well, as I mentioned, we, we, we were on we're on services and application that are really focused on high availability and performance. So generally speaking, we are not a peak organization. Also we run a business that is highly regulated. So as you know, as you can imagine we are an organization that don't have a lot of appetite for risk, you know, so generally speaking in order to run this kind of transformation is a matter of several months, I will say six nine months to have something delivered in that space. >> Okay. Well, that's, I mean, that's reasonable. I mean, if you could do it inside of a year that's I think quite good especially in the highly regulated industry. And then you mentioned kind of the fail over the high availability Cape Cape capabilities. Were there other specific EDB tools that that you utilize to sort of address the objectives? >> Yeah, absolutely. We were in particular, we used Postgres enterprise, AKA Pam. Okay. And very recently we were involved within ADB about per se specifically developing one functionality that, that that we needed back in the day. I think together with Bart these are the free EDB specific tools that, that we, that that we use right now. >> And, and I'm, I'm interested in, I want to get to the business impact and I know it's early days for you but the real motivation was to save money and simplify. I would actually, I would imagine your developers were happy because they get to use modern tooling and open source. But, but really though if your industry is bottom line, right, I mean that's really what the, the business case was all about. But I wonder if you could add some color there in terms of the business impact that you expect. And then, I mean I don't know how much visibility you have now but anything you can share with us. >> Well, thinking about the EFM implementation that the business impact the, was that in case of a failure or the DBA team that a services team is it is able to provide a solution that is within our 100% within our perimeter. So this means that we are fully accountable for it. So in a nutshell, when you run a service, the less people the less teams you have to involve the more control you can deliver. And in some, again, very critical services that is a great value. >> Okay. So, and, and where do you want to take this? I mean, how do you see w what's your, if you're thinking about your Postgres and, and generally an EDB you know, roadmap, where do you want it to go? >> Well, I stay to, to trends within within the organization, the, the, the, the the first one is about migrating more existing services to open source solution for database is going to be, is going to be prosperous. And other trends that I see within my organization is about designing applications, not really to be, to to use PostgreSQL as the base, as it does a base layer. I think both trends are more or less surroundings at the same state right now. >> Yeah. A lot of the audience members at Postgres vision 21 is just like you they they're managing day-to-day infrastructure. They're there they're expert practitioners. What advice would you give to somebody that is thinking about, you know taking this journey, maybe if you had to do something over again maybe what would you do differently? How can you help your peers here? >> Well, I think in particular, if you are going to say a big organization that runs a highly regulated business in some cases, you are a little bit afraid of open source because there is this, I can say general consideration about the lack of enterprise level support. I would like to say that it is just about the past because they're around bunch of companies like EDB that are we're a hundred percent capable of providing enterprise level of support, even on, on, on even on the open source distribution of Paul's presser. Obviously Dan is you're going to go with their specific distribution. The level of support is going to be even more accurate but as we know, it could be currently is they across say main contributor of the pollsters community. And I think is, is that an insurance for every organization? >> Your advice is don't be afraid. >> Yeah. My advice is done is absolutely, don't be, don't be afraid. And if, if, if I can, if we can mention about also about, you know, the cloud called technologies this is also another, another topic where if possible I would like to suggest to not being afraid EDB as every every I would say organization within the it industry is really pushing for it. And I think for a very, for, for a lot of cases not all of them, but a lot of cases, there is a great value about the design services application to be cloud native or migrating existing application into the cloud. >> Okay. But, but being a highly regulated industry and being a, you know, very much aware of the the narrative around open source, et cetera, you, you must've had just a little piece of your mind saying, okay I have to manage this risk. So there's anything specifically you did with managing the risks that you would advise? Was it, was it or is it really just about good change management? >> I think it was mainly about a good change management when you got, you know the relevant stakeholders that you need on board and we are, everybody's going the same direction. That basically is about executing. >> Excellent. Well, Roberto, I really appreciate your time and your knowledge that you share with the audience. So thanks so much for coming on the cube. >> Thank you, Dave. It was a great pleasure. >> And thank you for watching the cubes continuous coverage of Postgres vision 21. We'll be right back. (upbeat music)

>> For years, the database market was steady, and steadily boring. As virtualization went mainstream, organizations began to rethink their database strategies and ask questions like, "should I run Postgres and VMware?" Now implicit in that question was another drill down question. In other words, can VMware itself handle my critical applications and is PostGres the right solution to optimize my infrastructure estate. Now history has shown that was both a safe and good bet for organizations looking to leverage open source innovation and lower their costs. At the same time, new workloads were emerging that were pushing the boundaries of existing relational database technologies, that were designed primarily for transactional workloads. So-called systems of engagement and systems of analytics we're growing at rates much faster than traditional OLTP workloads. Once again, people ask the question, should I think about running these new workloads on Postgres? Now the answer came from the community response that saw the need to extend the open source platform to handle these emerging workloads. The database market suddenly got really interesting as these new applications emerged. Multiple data sources were combined and analyzed to interpret sentiment from social media and get consumers to buy something before they moved to another website, triangulate data to fight fraud, predict weather patterns, and short drug provenance, and dozens of other use cases. Then when cloud went mainstream, similar questions were asked about Postgres. And once again, the open source community responded to accommodate and extend the platform for the cloud. And now Kubernetes is all the rage. When should I run Postgres and Kubernetes, similar theme right? Open source, community, innovation, lowering license costs, minimizing lock-in, maximizing optionality, avoiding too much database sprawl, confidence to support new workloads. These are the factors that customers tell us they use generally to choose a database, and PostGrest specifically. In reality, it's usually pretty obvious what the right strategic fit is for a platform, but buyers want to make sure they have headroom for innovation. They do want to push the envelope on new data types while at the same time managing their risks. And that's where Postgres and the Postgres community in my view has thrived. It's become the ideal solution for what I call the fat middle of workloads, that are increasingly diverse but require a cost effective and stable approach that can scale. These are some of the themes we heard in the morning keynotes from Suzette Kent, former federal CIO who laid down her knowledge on transformation, leadership, and technology modernization. And then EDB CEO Ed Boyajian gave his annual keynote address and talked about the power of data. Data, as we know is growing at a mind-bending exponential rate. It'll make the 2010s look meager by comparison. My big takeaway from his talk really were around using technology to extract value more quickly. I think this is going to become the new new metric in the industry, which basically is every industry is a data-oriented platform now. Yes, software is eating the world, data is eating software. In other words, the new KPI is how long does it take to go from idea to monetization. That is are going to become critical in my opinion, over this next decade. Ed made what I thought was a critical point, and that is you really can't easily define the future. Industries are transforming right before our eyes. And his premise was that you have to pick a data platform that can evolve in unpredictable times. Now, as I pointed out earlier, the Postgres community has stepped up to changing environments for decades. And that really was a point Boyajian hit on pretty hard. Replatforming is happening and he made a convincing argument that Postgres and EDB will be part of that future, with a significant investment in advancing Postgres with hundreds of engineers on the task. He talked about three growth vectors. First, growth in new workloads. He made the claim that around 50% of new EDB customers are deploying new applications. Second, he talked about legacy migrations as another driver, and third was cloud, both traditional compute in the cloud, but also managed services and DBaaS, database as a service. Of course, he also talked about, and there's been a lot of discussion at Vision 2021 about Kubernetes and developers. Big push there. Let me give you my thoughts on that. First, the Kubernetes community is really focused on security and has made a lot of progress in the past 24 months. I think the second point there is developers, they want simplification, and Kubernetes brings that to a greater degree. And it's maturing with more production-ready capabilities. It just some basic, blocking and tackling, like not releasing with an unstable code, (laughs) but it's still early days and the community has some work to do on things like backwards compatibility, for example. And the release cadence of Kubernetes, it's still pretty frequent, which means you got to update scripts and APIs and the like. Remember, Postgres practitioners, they're used to very high levels of stability. So you got to be a little bit careful there. You got to go experiment because you want to take advantage of containers and benefits within Postgres, but you got to make sure you have the right change management in place and you got the resources to be on top of that. The bottom line is Kubernetes is still a toddler, but it's growing up fast. And I have no doubt it will become a staple of the Postgres stack. I'll end where I started, and that's the market. It's gone from stayed and uninteresting years ago to one that one of the most dynamic sectors of IT infrastructure software. And Ed Boyajian talked about the total available market, the TAM, and the valuations that we're seeing today. The market's enormous. I mean, if you just think about traditional database, it's probably 60 to $70 billion, but when you add in all the data and data clouds and decentralized data architectures and eventually edge computing, the market is potentially hundreds of billions of dollars in value for data platforms. So the last thing I'll say about Vision 21 is there's some great content here that spans both the business discussion and also deep practitioner material. And it's useful, has very useful how to's that both educate and inspire. So sit back and enjoy the show. This is Dave Vellante, and you're watching The Cube's continuous coverage of Postgres Vision 21 brought to you by EDB. Thanks for watching.

>> Narrator: From around the globe. It's theCUBE with digital coverage of Postgres vision 2021 brought to you by EDB. >> Welcome back to Postgres Vision 21. My name is Dave Vellante. We're thrilled to welcome Carl Olofsen to theCUBE. Carl is a research vice president at IDC focused on data management. The long-time database analyst is the technologist and market observer. Carl, good to see you again. >> Thanks Dave. Glad to be here. >> All right. Let's let's get into it. Let's talk about, let's go right to the, to the source the open source database space. You know, how, what changes have you seen over the last couple of years in that marketplace? >> Well, this is a dynamic area and it's continuing to evolve. When we first saw the initial open source products like mysQl and PostgreSQL on the early days they were very limited in terms of functionality. They were espoused largely by sort of true believers. You know, people who said everything should be open source. And we saw that mainly they were being used for what I would call rather prosaic database applications. But as time has gone by they both of these products improve. Now there's one key difference, of course, which is a mySQL is company owned open source. So the IP belongs to Oracle corporation. Whereas PostgreSQL is community open source, which means that the IP belongs to the PostgreSQL community. And that can have a big difference in terms of things like licensing and so forth, which really matters now that we're coming into the cloud space because as open-source products moving into the cloud space the revenue model is based on subscriptions. And of course they are always based on subscription to open source cause you don't charge for the license. So what you charge for its support, but in the cloud what you can do is you can set up a database service, excuse me, a database service and then you charge for that service. And if it's open source or it's not open source that actually doesn't matter to the user. If you see what that I mean because they still are paying a subscription fee for a service and they get the service. The main difference between the two types is that if you're a commercial provider of PostgreSQL like enterprise DB, you don't have control over where it goes and you don't have control over the IP and how people use it in different ways. Whereas Oracle owns mySQL so they have a lot more control and they can do things to it on their own. They don't have to consult the community. Now there's also, non-relational open source including MongoDB. And as you may be aware, MongoDB has changed their license. So that it's not possible for third party to offer Mongo DB as a complete managed database service without paying a license fee to MongoDB for that. And that's because they own the IP too. And we're going to see a lot more of this sort of thing. I have conversations with open source all the time and they are getting a little concerned that it has become possible for somebody to simply take their technology, make a lot of money off that. And no money goes back to the community. No money goes back to the IRS. It's a company it's just stays with the supplier. So I think, you know it'll be interesting to see how all this is over time. >> So you're suggesting that the Postgres model then is, is I guess I'll use the word cleaner. And so that feels like it's a it's a benefit or is it a two-edged sword kind of thing? I mean, you were saying before, you know a company controls the IP so they could do things without having to go to the community. So maybe they can do things faster. But at the other hand like you said, you get handcuffed. You think you're going to be able to get a, you know a managed service, but then all of a sudden you're not and the rules change midstream saying it, am I correct? That Postgres, the model is cleaner for the customer? >> Well, you know, I mean, a lot of my friends who are in the open source community don't even consider company owned open source to be true open source because the IP is controlled by a company, not by a community. >> Dave: Right >> So from that perspective certainly Postgres SQL is considered, I don't know if you want to use the word cleaner or more pure or something along those lines, but also because of that the nature of community open source it can be used in many different ways. And so we see Postgres popping up all over the place sometimes partially and sometimes altogether, in other words, a service, a cloud service, we'll take a piece of Postgres and stick it on top of their own technology and offer it. And the reason they do that is they know there are a lot of developers out there who already know how to code for Postgres. So they are immediately first-class users of the service that they're offering. >> So, talk a little bit more about what you're seeing. You just mentioned a lot of different use cases. That's interesting. I didn't realize that was, that was happening. The, what are you seeing in terms of adoption in let's say the last 18, 24 months specific to Postgres? >> Yeah, we're seeing a fair amount of adoption in especially in the middle market. And of course there is rapid adoption in the tech sector. Now, why would that be? Well it's because they have armies of technologists. Who know how to program this stuff. You know, when you, you know, a lot of them will use PostgreSQL without a contract without a support contract, they'll just support themselves. And they can do that because they have the technicians who are capable of doing it. Most regular businesses can't do that. They don't have the staff so they need that support contract. And so that's where a company like enterpriseDB comes. I mentioned them only because they're the leading supplier Postgres to all their other suppliers. >> I was talking to Josh Burgers, red hat and he was, you know, he had just come off a Cubacon and he was explaining kind of what's happening in that community. Big focus of course on security and the whole, you know, so-called shift left. We were having a good discussion about, you know when does it make sense to use, you know Postgres in a container environment should you use Postgres and Kubernetes and he sort of suggested that things have rapidly evolved. There's still, you know, considerations but what are you seeing in terms of the adoption of microservices architectures containers, generally Kubernetes how has that affected the use of things like postsgres? >> So those are all different things or need to be kind of custody. >> Pick your favorite. >> They're related then. So microservices, the microservice concept is that you take an application break it up into little pieces and each one becomes a microservice that's invoked through an API. And then you have this whole structure API system that you use to drive the application and they run. They typically, they run in containers usually Kubernetes govern containers but the reason you do this and this is basically a efficiency because especially in the cloud, you want only to pay for what you use. So when you're running a microservice based application. Applications have lots of little pieces when something needs to be done, microservice fires up it does the thing that needs to be done. It goes away. You only pay for that fraction of a second that the microservice is running. Whereas in a conventional application you load this big heavyweight application. It does stop. It sets some weights with things and does more stuff and sits and waits for things. And you pay for compute for that entire period. So it's much more cost effective to use a microservices application. The thing is that microservice, the concept of microservices is based on the idea that the code is stateless but database code isn't stateless cause it has its attraction to the database which is the ultimate kind of like stateful environment right? So it's a tricky business. Most database technologies that are claimed to be container-based actually run in containers the way they run in servers. In other words, they're not microservice-based they do run in containers. And the reason they're doing that is for portability so that you can deploy them anywhere and you can move them around. But you know deploying a microservice based database is, well, it's it's a big technical project. I mean, that is hard to do. >> Right and so talk about, I mean again we're talking to Josh it was clear that that Kubernetes has evolved, you know quite rapidly at the same time there were cautions. In other words, he would say I think suggested things like, you know, there were known at one point, there were known, you know flaws and known bugs that ship the code that's been been remediated or moderated in terms of that practice but still there's there's considerations just in terms of the frequency of updates. I think he gave the example of when was the last time you know, JVM got, you know, overhauled. And so what kind of considerations should customers think about when considering them, they want the Kubernetes they want the flexibility and the agility but at the same time, if they're going to put it production, they've got to be careful, right? >> Yeah, I think you need to make sure you're using you're using functions that are well-established, you know you wouldn't want to put something into production that's new. They say, oh, here's a new, here's a new operation. Let's try that. And then, you know, you get in trouble. So you want to deal conservative that way you know, Kubernetes is open-source so and the updates and the testing and all that follows a rather slow formal process, you know from the time that the submission comes in to the time that it goes out, whereas you mentioned JVMs JV, but it was owned by Oracle. And so JVMs are managed like products. Now there's a whole sort of legal thing I don't want to get into it as to whether it's legal. They claim it's not libero third parties to build JVMs without paying a licensing. I don't want to talk about that, but it's based on a very state that has a very stable base, you know whereas this area of Kubernetes and govern containers is still rapidly evolving but this is like any technology, right? I mean, when you, if you're going to commit your enterprise to functions that run on an emerging technology then you are accepting some risk. You know, that there's no question about it. >> So we talked about the cloud earlier and the whole trend toward managed services. I mean, how does that specifically apply to Postgres? You can kind of imagine like a sidecar, a little bit of Postgres mixed in with, you know, other services. So what do you see and what do you, what's your telescope say in terms of the the Postgres adoption cloud? How do you see that progressing? >> I think there's a lot of potential. There's a lot of potential there. I think we are nowhere near the option that it should be able to achieve. I say that because for one thing, even though we analyze the future at IDC, that doesn't mean we actually know the future. So I can't say what its adoption will be but I can say that there's a lot of potential there. There's a tremendous number of Postgres developers out there. So there's a huge potential for adoption. And especially in cloud adoption, the main thing that would help that is independent. And I know that enterpriseDB has one independent a managed cloud service. So I think they do. >> Yeah I think so. >> But you know, why do I say that? I say that because alternatives these days there are some small companies that maybe they'll survive and maybe they won't, but that, you know, do you want to get involved with them or the cloud platform providers, but if you use their Postgres you're locked into that cloud platform. You know, if you use Amazon, go press on RDS, right? You're not, you become quickly locked in because you're starting using all the AWS tools that surround it to build and manage your application. And then you can't move. If you see what I mean. >> Dave: Yeah . >> They have have an RDS labor Aurora, and this is actually one of the things that it's really just a thin layer of Postgres interaction code underneath Aurora is their own product. so that's an even deeper level of commitment. >> So what has to happen for, so obviously cloud, you know, big trend. So the Postgres community then adopts the code base for the cloud. Obviously EDB has, you know hundreds of developers contributing to that, but so what does that mean to be able to run in the cloud? Is that making it cloud native? Is that extensions? Is it, you know, what technically has to occur and what has occurred and how mature is it? >> Well, so smaller user organizations are able to migrate fairly quickly cloud because most of their applications are you know, commercially purchased. They're like factories applications. When they move to the cloud, they get the SAS one and often the SAS equivalent runs on Postgres. So that's just fine. Larger enterprises are a real mess. If you've ever been in a large enterprise data center you know what I'm talking about? It's just, there's just servers and storage everywhere. There's, all these applications, databases connections. They are not moving to the cloud anytime soon. But what they are doing is setting up things like private cloud environments and applying in there. And this is a place where if you're thinking about moving to something like a Postgres you know most of these enterprises use the big commercial databases. Oracle SQLserver DB two and so forth. If you're thinking of moving from that to a a PostgreSQL development say, then the smart thing to do would be first to do all your work in the private cloud where you'd have complete control over the environment. It also makes sense still to have a commercial support contract from a vendor that you trust, because I've said this again, unless you are, you know, Cisco or somebody, you know, some super tech company that's got all the technicians you need to do the work. You really don't want to take on that level of risk. If you see that, I mean. Another advantage to working with a supplier, a support supplier, especially if you have a close, intimate relationship is they will speed your security patches on a regular basis which is really important these days, because data security is as you know, a growing concern all over the place. >> So let's stay on the skillsets for a minute. Where do you see the gaps within enterprises? What kind of expertise you mentioned, you know support contracts, what are the types of things that a customer should look for in terms of the the expertise to apply to supporting Postgres databases? >> Well, obviously you want them to do the basics that any software company does, right? You want them to provide you with regular updates and binary form that you can load and, you know test and run. You want to have the you know, 24 hour hotline you know, telephone support, all that kind of thing. I think it's also important to have a solid ability on the part of the vendor that you're working with to provide you with advice and counseling as you, especially, if you're migrating from another technology, help your people convert from what they were using to what they're going to be using. So those are all aspects that I would look for in a vendor for supporting a product like PostgreSQL. >> When you think about the migration to the cloud, you know of course Amazon talks a lot about cloud migration. They have a lot of tooling associated with that. >> Carl: Right. >> But when you step back and look at it it did to a point earlier, I mean a lot of the hardcore mission, critical stuff isn't going to move it, hasn't moved, but a lot of the fat middle, you know, is, are good candidates for it. >> Carl: Right. >> How do you think about that? And how do you look at that? I mean, obviously Oracle is trying to shove everything into OCI and they're, you know, they're all in because they realized that could make a lot of money doing that. But what do you, what are the sort of parameters that we should think about when considering that kind of migration, moving a legacy database into the cloud? >> Well, it has to be done piecemeal. You're not going to be able to do it all at once. You know, if you have hundreds of applications, you're not just you don't even want to, you know, it's a good time to take you into it. And what you've got running, ask yourself are these applications really serving the business interests today and will they in the future or is this a good time to maybe consider something else? Even if you have a packaged application, there might be one that is more aligned with your future goals. So it's important to do that. Look at your data integration, try to simplify it. You know, most data integration that most companies has done piecemeal project by project. They don't reference each other. So you have this chaos of ETL jobs and transformation rules and things like that that are just, you know, even difficult to manage. Now, just forget about any kind of migration or transformation considerations, just trying to run it now is becoming increasingly difficult. You know, maybe you want to change your strategy for doing data integration. Maybe you want to consolidate you want to put more data in one database. I'm not an advocate of the idea that you can put all application data in one database by the way, we know from bitter experience that doesn't work, but we can be rational about the kinds of databases that we use and how they sit together. >> Well, I mean, you've been following this for a long time and you saw the sort of rise and fall of the big data meme. And you know, this idea that you can shove everything into a single place, have a single version of the truth. It's like, it's just never seemed to happen. >> Carl: Right. >> So, you know, Postgres has been around a long time. It's evolved. I mean, I remember when, you know, VMware's ascendancy and people are like, okay, should I, you know should I virtualize my Postgres database is your, you know similar conversations that we were having earlier about Kubernetes. You've seen the move to the cloud. We're going to have this conversation about the edge at some point in time. So what's your outlook for Postgres, the Postgres community and, you know database market overall? >> Well, I really think the future for database growth is in the cloud. That's what all the data we're looking at and the case that's what our recent surveys indicate. As I said before, the rate of change depends on the size of the enterprise. Smaller advices are moving rapidly, large enterprises much more slowly and cautiously for the very simple reason that it's a very complex proposition. And also in some cases, they're wondering if they can move certain data or will they be violating your some sort of regulatory constraint or contractual issue. So they need to deal with those things too. That's why the private cloud is the perfect place to get started and get technology all lined up storing your data center is still under your control no legal issues there, but you can start, you know converting your applications to micro-service architected applications running in containers. You can start replacing your database servers with ones that can run in a container environment and maybe in the future, maybe hope that in the future, some of those will actually also be able to run as microservices. I don't think it's impossible but it just involves programming the database server in a very different way than we've done in the past. But you do those things. You can do those things under your own control over time in your own dataset. And then you reach a point where you want to take the elements of your application environment and say, what pieces of this, can I move to the cloud without creating disruption and issues regarding things like data egress and latency from cloud to data center and that kind of thing. And prepare for that. And then you're doing the step wise and then you start converting in a stepwise manner. I think ultimately it just makes so much sense to be in the cloud that the cloud vendors have economies of scale. They can deploy large numbers of servers and storage systems to satisfy the needs of large numbers of customers and create, you know great considerable savings. Some of which of course becomes their profit which is what's due to them. And some of that comes back to the users. So that's what I expect. We're going to see. And oh gosh, I would say that starting from about three years from now the larger enterprises start making their move and then you'll really start to see changes in the numbers in terms of cloud and cloud revenue. >> Great stuff, Carl, thank you for that. So any cool research you're working on lately, how you're spending your your work time, anything you want to plug? >> Well, working a lot on just as these questions, you know cloud migration is a hot topic, another which is really sort of off the subject. And what we've been talking about is graph database which I've been doing a fair amount of research into. I think that's going to be really important in the coming years and really, you know working with my colleagues in a project called the future of intelligence which looks at all the different related elements not just database, data integration but artificial intelligence, data communications and so on and so forth and how they come together to create a more intelligent enterprise. And that's a major initiative that I see. It's one of the, we call the future of initiatives. >> Great, Carls, thanks so much for coming back to theCUBE. It's great to have you, man. I appreciate it. >> Well, I enjoyed it. Now I have to do it again sometime. >> All right you got it. All right thank you everybody for watching theCUBEs. Continuous coverage of Postgres vision 21. This is Dave Vellante keep it right there. (upbeat music)

(upbeat music) >> From around the globe, it's theCUBE with digital coverage of Postgres Vision 2021 brought to you by EDB. >> Well, hi everybody John Walls here on theCUBE and we're now welcoming Jeremy Wilmot who is the chief product officer at ACI Worldwide part of the Postgres movement, you might say or certainly benefiting from the great value that Postgres is providing a number of enterprises across the globe. Jeremy good to see you today and first off, congratulations you are the first guest I've talked to maybe in a year and a half in their office. So good for you. >> Thanks (chuckles) John that's very kind of you John and great to see you and thanks for having me here. Yeah, it's great to be in the office, it really is. I'm here in Miami in South Florida and getting some sort of normalcy back is great for all of us and I'm certainly enjoying it. So thank you before (indistinct) has been. >> I'm sure you are, yeah, congratulations on that front. First off, let's talk about ACI Worldwide for the folks in our audience who aren't familiar with the payments, your role in terms of that payment ecosystem. Tell us a little bit about ACI Worldwide. >> Sure, well, primarily we're a software company. That's ACI, we started 1975 in Omaha, Nebraska built the first debit card system and ATM system for first National Bank of Omaha and over the last 45 years, we've globalized ourselves, we have, we are delivering mission-critical real-time payment systems across the world to banks to merchants to billers, we help them meet the payment needs of their consumers and their corporates. So we process, manage digital payments, we power omni-commerce and e-commerce payments, we present and process bill payments, we manage fraud, we manage the risk all within that and as I said on a global basis 13 of the G20 countries with a leading DDA account or current account payment processing software in those countries and have been for many years. >> So, as the CPO then quite obviously in the financial space your plate is quite full these days in terms of providing for your client base. How would you characterize maybe the evolution in terms of product development that you've been through in the financial world here over the past say, three to five years, where were you back then to where you are now and what role has Postgres played in that journey? >> Sure, yeah. So, specific to the Postgres part of the ecosystem, previously five-plus years ago our previous database solution was complex, it was expensive, it was hard to change and maintain and we leveraged multiple pieces of software from multiple vendors as a result of that. So at that time we looked for an alternative that was simpler and better and we went through a very comprehensive due diligence process, we explored both open source and license models of database to support our solution and when we looked at all of the options we determined that 2ndQuadrant Postgres was the one that provided the most comprehensive solution we were looking for. It had the right mix of capabilities and performance at the right total cost of ownership that we were looking for. And in the payments world as you can imagine, you've got to to be 24/7 365. And we also required a lower cost of ownership than we had before. But we also wanted a greater flexibility and time to market that we could pass on to our customers. And then the last thing I'd say that we were looking for was a multi-deployment capability. And what I mean by that is that we would be able to use this new platform, Postgres platform in our own data centers in our own private cloud, but we could also deploy it in the public cloud, whether we would run it or whether our customers would run it. We wanted that ability to mix and match between these different deployment options. >> So you've talked about a lot of key elements here attributes in terms of availability, accessibility reliability, security obviously. Walk us through those in terms of why you think 2ndQuadrant was addressing your needs in those particular areas or any others for that matter but what it was that checked the box specifically about what Postgres was offering you as opposed to what these other possible solutions and services were that you were looking at. >> Yeah, I think, we're very focused on being able to identify what our customers need and when they're offering services to consumers and to their corporates what is it that they require that's going to enable them to win and compete. And payments industry has a lot of cost pressures within it. It has regulation, it has consumer convenience and the whole movement of digitalization that puts a lot of downward pressure on the cost space. And those who are going to win in the payment space need to be able to address that. So, that is relevant for our banks, for our merchants, for the billers. They all come under very similar regulatory pressure and market pressure and as a result, the ability to reduce dramatically in a very significant way, the total cost of ownership upon which the payment software was going to be operating that was one of the key elements that was very important to us as we made that decision. The second one I think was to enable us to be able to do what we are good at and what our customers expect us to do. And that in turn enables them to focus on their core competencies. We're a software company, we own our own IP we manage our own software for the needs of the 24/7 365 payment requirements and therefore the merchant or the biller or the bank can really focus in on the digital experience for their customers, focusing on their core competencies and what they need to do to win. That was a second key factor for us. I think the third one for us was as well speed to market. Speed to market for ourselves and being competitive to the alternative to ACI, but also more importantly a speed to market for our customers. And there are, the payment world is highly regulated requires significant certification in order to launch new services that's often the long pole in the tent. So we want to be able to get to that point as quickly as possible. And being able to have a public cloud deployment open systems capabilities that would really allow us to pass on that speed to market to those customers. So for example, an acquirer, a payment acquirer moving into a new geographical country they want to compete in they can (indistinct) on their competitors by launching minimum viable products in six to nine months that is five years ago, that could have been a 24 to 30 months endeavor for them to take on. So I, those were important considerations for us as we were choosing a longterm partner for the Postgres world and the public cloud world. >> Obviously, so you've talked a lot about your relationship with your clients and I know you have a really keen awareness of the need to ensure that trust, to ensure that reliability to ensure the collaboration. How about your relationship on the other side with EDB and in terms of all those elements so how has that evolved over a period of time and what kind of service and what kind of value do you think are you deriving from that relationship now? >> So with EDB, first of all, our journey started with 2ndQuadrant and now EDB. And we were specifically looking at the, one area was at the Bi-Directional Replication BDR that we were wanting to support with our solutions particularly in the public cloud. And that was going to enable us to replace multiple pieces of software from multiple vendors. And so we were to create that solution that was right for ACI, it was right for our customers from a functionality and agility and a cost perspective. So technologically with the non-functional requirements and the reliability, availability, serviceability aspects that we were looking for that was in partnership with 2ndQuadrant and EDB, that was a key element. I think the second piece of it is we worked really well with 2ndQuadrant EDB in terms of partnering to meet the needs of the market. It's great to have the right technology in place but then you need your partners really to be able to work with you tactically real-time in order to win in the market and make it work. And I found that they'd been a great partner for us to be able to do that and to be able to react quickly, do the right thing and really enable us to be a great partner to our customers as we deliver real-time payments, as we deliver the acquiring capabilities, as we deliver a modernization for the big banks that we work with as well. >> Now, before I let you go, I'm going to give you a two-part question here. That's always one way to squeeze a little more info (laughing) to the guest. First off advice. You've been through this transformation obviously you're very happy with all that has transpired, so your advice to others who are considering this journey. And then secondly, what can they and you do you think expect in terms of future challenges, opportunities how we might want to frame that with Postgres? Like, where are we going from here, basically? So, two parts, advice and then where do you think this is headed? >> So advice, I certainly learnings from us versus advice is number one, be very thorough in the due diligence that you do and be very clear on what you want and what are your goals that you're looking for. So from an AGI perspective, we were clear that total cost of ownership in terms of the stack that we were going to be providing to our customers. That was very important, number one number two, nonfunctional requirements. So I've talked about the mission criticality of payments 24/7 365. That was a key second piece. And then the third one, ease of deployment. I talked about that, multi-cloud deployment that we were looking for. So we were clear what we wanted and we we took our time from a due diligence point of view. It's a multi-year decision being made so it's not something specifically I think we want to rush into. In terms of looking forward and where do we go from here? Performance is critical so further up performance enhancements, ability for rapid failover availability, near 100% availability that we're looking for five-nines and above, working together with Postgres in order to make those failovers more seamless because they will happen, particularly in the real-time payments world, where we're now seeing billions of transactions happening in a week and soon that will be in a day, they will need to be able to deal with. And for all of this to happen in a public cloud environment, we, I think all understand a lot of the benefits of public cloud and we need to be able to provide this failover availability capability in the public cloud but also in a hybrid cloud environments we're in a multi-cloud environment, so we need to keep working that and make that happen that will make Postgres a payment-grade infrastructure that could power the world's real-time payments and we would love to be able to do that into the future. >> Well, Jeremy thanks for the insights, we appreciate that and once again, congratulations on getting back in that office. I know it's probably a pretty welcomed addition to your regimen now. >> Yeah, John, thank you very much and thanks to everyone who's dialed in for this and John I look forward to welcoming you in the office soon. >> Very good sir, I look forward to that as well. I'll take you up on that in Miami for sure. John Walls here on theCUBE talking with Jeremy Wilmot is the chief product officer at ACI Worldwide. part of our Postgres Vision 2021 coverage. (upbeat music)

>>Hi everyone. And welcome to data citizens. Thank you for making the time to join me and the over 5,000 data citizens like you that are looking to become United by data. My name is Jim Cushman. I serve as the chief product officer at Collibra. I have the benefit of sharing with you, the product, vision, and strategy of Culebra. There's several sections to this presentation, and I can't wait to share them with you. The first is a story of how we're taking a business user and making it possible for him or her data, use data and gain. And if it and insight from that data, without relying on anyone in the organization to write code or do the work for them next I'll share with you how Collibra will make it possible to manage metadata at scales, into the billions of assets. And again, load this into our software without writing any code third, I will demonstrate to you the integration we have already achieved with our newest product release it's data quality that's powered by machine learning. >>Right? Finally, you're going to hear about how Colibra has become the most universally available solution in the market. Now, we all know that data is a critical asset that can make or break an organization. Yet organizations struggle to capture the power of their data and many remain afraid of how their data could be misused and or abused. We also observe that the understanding of and access to data remains in the hands of just a small few, three out of every four companies continue to struggle to use data, to drive meaningful insights, all forward looking companies, looking for an advantage, a differentiator that will set them apart from their peers and competitors. What if you could improve your organization's productivity by just 5%, even a modest 5% productivity improvement compounded over a five-year period will make your organization 28% more productive. This will leave you with an overwhelming advantage over your competition and uniting your data. >>Litter employees with data is the key to your success. And dare I say, sorry to unlock this potential for increased productivity, huge competitive advantage organizations need to enable self-service access to data for everyday to literate knowledge worker. Our ultimate goal at Cleaver has always been to enable this self-service for our customers to empower every knowledge worker to access the data they need when they need it. But with the peace of mind that your data is governed insecure. Just to imagine if you had a single integrated solution that could deliver a seamless governed, no code user experience of delivering the right data to the right person at the right time, just as simply as ordering a pair of shoes online would be quite a magic trick and one that would place you and your organization on the fast track for success. Let me introduce you to our character here. >>Cliff cliff is that business analyst. He doesn't write code. He doesn't know Julian or R or sequel, but is data literate. When cliff has presented with data of high quality and can actually help find that data of high-quality cliff knows what to do with it. Well, we're going to expose cliff to our software and see how he can find the best data to solve his problem of the day, which is customer churn. Cliff is going to go out and find this information is going to bring it back to him. And he's going to analyze it in his favorite BI reporting tool. Tableau, of course, that could be Looker, could be power BI or any other of your favorites, but let's go ahead and get started and see how cliff can do this without any help from anyone in the organization. So cliff is going to log into Cleaver and being a business user. >>The first thing he's going to do is look for a business term. He looks for customer churn rate. Now, when he brings back a churn rate, it shows him the definition of churn rate and various other things that have been attributed to it such as data domains like product and customer in order. Now, cliff says, okay, customer is really important. So let me click on that and see what makes up customer definition. Cliff will scroll through a customer and find out the various data concepts attributes that make up the definition of customer and cliff knows that customer identifier is a really important aspect to this. It helps link all the data together. And so cliff is going to want to make sure that whatever source he brings actually has customer identifier in it. And that it's of high quality cliff is also interested in things such as email address and credit activity and credit card. >>But he's now going to say, okay, what data sets actually have customer as a data domain in, and by the way, why I'm doing it, what else has product and order information? That's again, relevant to the concept of customer churn. Now, as he goes on, he can actually filter down because there's a lot of different results that could potentially come back. And again, customer identifier was very important to cliff. So cliff, further filters on customer identifier any further does it on customer churn rate as well. This results in two different datasets that are available to cliff for selection, which one to use? Well, he's first presented with some data quality information you can see for customer analytics. It has a data quality score of 76. You can see for sales data enrichment dataset. It has a data quality score of 68. Something that he can see right at the front of the box of things that he's looking for, but let's dig in deeper because the contents really matter. >>So we see again the score of 76, but we actually have the chance to find out that this is something that's actually certified. And this is something that has a check mark. And so he knows someone he trusts is actually certified. This is a dataset. You'll see that there's 91 columns that make up this data set. And rather than sifting through all of that information, cliff is going to go ahead and say, well, okay, customer identifier is very important to me. Let me search through and see if I can find what it's data quality scores very quickly. He finds that using a fuzzy search and brings back and sees, wow, that's a really high data quality score of 98. Well, what's the alternative? Well, the data set is only has 68, but how about, uh, the customer identifier and quickly, he discovers that the data quality for that is only 70. >>So all things being equal, customer analytics is the better data set for what cliff needs to achieve. But now he wants to look and say, other people have used this, what have they had to say about it? And you can see there are various reviews for different reviews from peers of his, in the organization that have given it five stars. So this is encourages cliffs, a confidence that this is great data set to use. Now cliff wants to look a little bit more detailed before he finally commits to using this dataset. Cliff has the opportunity to look at it in the broader set. What are the things can I learn about customer analytics, such as what else is it related to? Who else uses it? Where did it come from? Where does it go and what actually happens to it? And so within our graph of information, we're able to show you a diagram. >>You can see the customer analytics actually comes from the CRM cloud system. And from there you can inherit some wonderful information. We know exactly what CRM cloud is about as an overall system. It's related to other logical models. And here you're actually seeing that it's related to a policy policy about PII or personally identifiable information. This gets cliff almost the immediate knowledge that there's going to be some customer information in this PII information that he's not going to be able to see given his user role in the organization. But cliff says, Hey, that's okay. I actually don't need to see somebody's name and social security number to do my work. I can actually work with other information in the data file. That'll actually help me understand why our customers churning in, what can I actually do about it. If we dig in deeper, we can see what is personally identifiable information that actually could cause issues. >>And as we scroll down and take a little bit of a focus on what we call or what you'll see here is customer phone, because we'll show that to you a little bit later, but these show the various information that once cliff actually has it fulfilled and delivered to him, he will see that it's actually massed and or redacted from his use. Now cliff might drive in deeper and see more information. And he says, you know what? Another piece that's important to me in my analysis is something called is churned. This is basically suggesting that has a customer actually churned. It's an important flag, of course, because that's the analysis that he's performing cliff sees that the score is a mere 65. That's not exactly a great data quality score, but cliff has, is kind of in a hurry. His bosses is, has come back and said, we need to have this information so we can take action. >>So he's not going to wait around to see if they can go through some long day to quality project before he pursues, but he is going to come up and use it. The speed of thinking. He's going to create a suggestion, an issue. He's going to submit this as a work queue item that actually informs others that are responsible for the quality of data. That there's an opportunity for improvement to this dataset that is highly reviewed, but it may be, it has room for improvement as cliff is actually typing in his explanation that he'll pass along. We can also see that the data quality is made up of multiple components, such as integrity, duplication, accuracy, consistency, and conformity. Um, we see that we can submit this, uh, issue and pass it through. And this will go to somebody else who can actually work on this. >>And we'll show that to you a little bit later, but back to cliff, cliff says, okay, I'd like to, I'd like to work with this dataset. So he adds it to his data basket. And just like if he's shopping online, cliff wants that kind of ability to just say, I want to just click once and be done with it. Now it is data and there's some sensitivity about it. And again, there's an owner of this data who you need to get permission from. So cliff is going to provide information to the owner to say, here's why I need this data. And how long do I need this data for starting on a certain date and ending on a certain date and ultimately, what purpose am I going to have with this data? Now, there are other things that cliff can choose to run. This one is how do you want this day to deliver to you? >>Now, you'll see down below, there are three options. One is borrow the other's lease and others by what does that mean? Well, borrow is this idea of, I don't want to have the data that's currently in this CRM, uh, cloud database moved somewhere. I don't want it to be persistent anywhere else. I just want to borrow it very short term to use in my Tablo report and then poof be gone. Cause I don't want to create any problems in my organization. Now you also see lease. Lease is a situation where you actually do need to take possession of the data, but only for a time box period of time, you don't need it for an indefinite amount of time. And ultimately buy is your ability to take possession of the data and have it in perpetuity. So we're going to go forward with our bar use case and cliff is going to submit this and all the fun starts there. >>So cliff has actually submitted the order and the owner, Joanna is actually going to receive the request for the order. Joanna, uh, opens up her task, UCS there's work to perform. It says, oh, okay, here's this there's work for me to perform. Now, Joanna has the ability to automate this using incorporated workflow that we have in Colibra. But for this situation, she's going to manually review that. Cliff wants to borrow a specific data set for a certain period of time. And he actually wants to be using in a Tablo context. So she reviews. It makes an approval and submits it this in turn, flips it back to cliff who says, okay, what obligations did I just take on in order to work for this data? And he reviews each of these data sharing agreements that you, as an organization would set up and say, what am I, uh, what are my restrictions for using this data site? >>As cliff accepts his notices, he now has triggered the process of what we would call fulfillment or a service broker. And in this situation we're doing a virtualization, uh, access, uh, for the borrow use case. Cliff suggests Tablo is his preferred BI and reporting tool. And you can see the various options that are available from power BI Looker size on ThoughtSpot. There are others that can be added over time. And from there, cliff now will be alerted the minute this data is available to them. So now we're running out and doing a distributed query to get the information and you see it returns back for raw view. Now what's really interesting is you'll see, the customer phone has a bunch of X's in it. If you remember that's PII. So it's actually being massed. So cliff can't actually see the raw data. Now cliff also wants to look at it in a Tablo report and can see the visualization layer, but you also see an incorporation of something we call Collibra on the go. >>Not only do we bring the data to the report, but then we tell you the reader, how to interpret the report. It could be that there's someone else who wants to use the very same report that cliff helped create, but they don't understand exactly all the things that cliff went through. So now they have the ability to get a full interpretation of what was this data that was used, where did it come from? And how do I actually interpret some of the fields that I see on this report? Really a clever combination of bringing the data to you and showing you how to use it. Cliff can also see this as a registered asset within a Colibra. So the next shopper comes through might actually, instead of shopping for the dataset might actually shop for the report itself. And the report is connected with the data set he used. >>So now they have a full bill of materials to run a customer Shern report and schedule it anytime they want. So now we've turned cliff actually into a creator of data assets, and this is where intelligent, it gets more intelligence and that's really what we call data intelligence. So let's go back through that magic trick that we just did with cliff. So cliff went into the software, not knowing if the source of data that he was looking for for customer product sales was even available to him. He went in very quickly and searched and found his dataset, use facts and facets to filter down to exactly what was available. Compare to contrast the options that were there actually made an observation that there actually wasn't enough data quality around a certain thing was important to him, created an idea, or basically a suggestion for somebody to follow up on was able to put that into his shopping basket checkout and have it delivered to his front door. >>I mean, that's a bit of a magic trick, right? So, uh, cliff was successful in finding data that he wanted and having it, deliver it to him. And then in his preferred model, he was able to look at it into Tableau. All right. So let's talk about how we're going to make this vision a reality. So our first section here is about performance and scale, but it's also about codeless database registration. How did we get all that stuff into the data catalog and available for, uh, cliff to find? So allow us to introduce you to what we call the asset life cycle and some of the largest organizations in the world. They might have upwards of a billion data assets. These are columns and tables, reports, API, APIs, algorithms, et cetera. These are very high volume and quite technical and far more information than a business user like cliff might want to be engaged with those very same really large organizations may have upwards of say, 20 to 25 million that are critical data sources and data assets, things that they do need to highly curate and make available. >>But through that as a bit of a distillation, a lifecycle of different things you might want to do along that. And so we're going to share with you how you can actually automatically register these sources, deal with these very large volumes at speed and at scale, and actually make it available with just a level of information you need to govern and protect, but also make it available for opportunistic use cases, such as the one we presented with cliff. So as you recall, when cliff was actually trying to look for his dataset, he identified that the is churned, uh, data at your was of low quality. So he passed this over to Eliza, who's a data steward and she actually receives this work queue in a collaborative fashion. And she has to review, what is the request? If you recall, this was the request to improve the data quality for his churn. >>Now she needs to familiarize herself with what cliff was observing when he was doing his shopping experience. So she digs in and wants to look at the quality that he was observing and sure enough, as she goes down and it looks at his churn, she sees that it was a low 65% and now understands exactly what cliff was referring to. She says, aha, okay. I need to get help. I need to decide whether I have a data quality project to fix the data, or should I see if there's another data set in the organization that has better, uh, data for this. And so she creates a queue that can go over to one of her colleagues who really focuses on data quality. She submits this request and it goes over to, uh, her colleague, John who's really familiar with data quality. So John actually receives the request from Eliza and you'll see a task showing up in his queue. >>He opens up the request and finds out that Eliza's asking if there's another source out there that actually has good is churned, uh, data available. Now he actually knows quite a bit about the quality of information sturdiness. So he goes into the data quality console and does a quick look for a dataset that he's familiar with called customer product sales. He quickly scrolls down and finds out the one that's actually been published. That's the one he was looking for and he opens it up to find out more information. What data sets are, what columns are actually in there. And he goes down to find his churned is in fact, one of the attributes in there. It actually does have active rules that are associated with it to manage the quality. And so he says, well, let's look in more detail and find out what is the quality of this dataset? >>Oh, it's 86. This is a dramatic improvement over what we've seen before. So we can see again, it's trended quite nicely over time each day, it hasn't actually degraded in performance. So we actually responds back to realize and say, this data set, uh, is actually the data set that you want to bring in. It really will improve. And you'll see that he refers to the refined database within the CRM cloud solution. Once he actually submits this, it goes back to Eliza and she's able to continue her work. Now when Eliza actually brings this back open, she's able to very quickly go into the database registration process for her. She very quickly goes into the CRM cloud, selects the community, to which she wants to register this, uh, data set into the schemas community. And the CRM cloud is the system that she wants to load it in. >>And the refined is the database that John told her that she should bring in. After a quick description, she's able to click register. And this triggers that automatic codeless process of going out to the dataset and bringing back its metadata. Now metadata is great, but it's not the end all be all. There's a lot of other values that she really cares about as she's actually registering this dataset and synchronizing the metadata she's also then asked, would you like to bring in quality information? And so she'll go out and say, yes, of course, I want to enable the quality information from CRM refined. I also want to bring back lineage information to associate with this metadata. And I also want to select profiling and classification information. Now when she actually selects it, she can also say, how often do you want to synchronize this? This is a daily, weekly, monthly kind of update. >>That's part of the change data capture process. Again, all automated without the require of actually writing code. So she's actually run this process. Now, after this loads in, she can then open up this new registered, uh, dataset and actually look and see if it actually has achieved the problem that cliff set her out on, which was improved data quality. So looking into the data quality for the is churn capability shows her that she has fantastic quality. It's at a hundred, it's exactly what she was looking for. So she can with confidence actually, uh, suggest that it's done, but she did notice something and something that she wants to tell John, which is there's a couple of data quality checks that seem to be missing from this dataset. So again, in a collaborative fashion, she can pass that information, uh, for validity and completeness to say, you know what, check for NOLs and MPS and send that back. >>So she submits this onto John to work on. And John now has a work queue in his task force, but remember she's been working in this task forklift and because she actually has actually added a much better source for his churn information, she's going to update that test that was sent to her to notify cliff that the work has actually been done and that she actually has a really good data set in there. In fact, if you recall, it was 100% in terms of its data quality. So this will really make life a lot easier for cliff. Once he receives that data and processes, the churn report analysis next time. So let's talk about these audacious performance goals that we have in mind. Now today, we actually have really strong performance and amazing usability. Our customers continue to tell us how great our usability is, but they keep asking for more well, we've decided to present to you. >>Something you can start to bank on. This is the performance you can expect from us on the highly curated assets that are available for the business users, as well as the technical and lineage assets that are more available for the developer uses and for things that are more warehoused based, you'll see in Q1, uh, our Q2 of this year, we're making available 5 million curated assets. Now you might be out there saying, Hey, I'm already using the software and I've got over 20 million already. That's fair. We do. We have customers that are actually well over 20 million in terms of assets they're managing, but we wanted to present this to you with zero conditions, no limitations we wouldn't talk about, well, it depends, et cetera. This is without any conditions. That's what we can offer you without fail. And yes, it can go higher and higher. We're also talking about the speed with which you can ingest the data right now, we're ingesting somewhere around 50,000 to a hundred thousand records per and of course, yes, you've probably seen it go quite a bit faster, but we are assuring you that that's the case, but what's really impressive is right now, we can also, uh, help you manage 250 million technical assets and we can load it at a speed of 25 million for our, and you can see how over the next 18 months about every two quarters, we show you dramatic improvements, more than doubling of these. >>For most of them leading up to the end of 2022, we're actually handling over a billion technical lineage assets and we're loading at a hundred million per hour. That sets the mark for the industry. Earlier this year, we announced a recent acquisition Al DQ. LDQ brought to us machine learning based data quality. We're now able to introduce to you Collibra data quality, the first integrated approach to Al DQ and Culebra. We've got a demo to follow. I'm really excited to share it with you. Let's get started. So Eliza submitted a task for John to work on, remember to add checks for no and for empty. So John picks up this task very quickly and looks and sees what's what's the request. And from there says, ah, yes, we do have a quality check issue when we look at these churns. So he jumps over to the data quality console and says, I need to create a new data quality test. >>So cliff is able to go in, uh, to the solution and, uh, set up quick rules, automated rules. Uh, he could inherit rules from other things, but it starts with first identifying what is the data source that he needs to connect to, to perform this. And so he chooses the CRM refined data set that was most recently, uh, registered by Lysa. You'll see the same score of 86 was the quality score for the dataset. And you'll also see, there are four rules that are associated underneath this. Now there are various checks that, uh, that John can establish on this, but remember, this is a fairly easy request that he receives from Eliza. So he's going to go in and choose the actual field, uh, is churned. Uh, and from there identify quick rules of, uh, an empty check and that quickly sets up the rules for him. >>And also the null check equally fast. This one's established and analyzes all the data in there. And this sets up the baseline of data quality, uh, for this. Now this data, once it's captured then is periodically brought back to the catalog. So it's available to not only Eliza, but also to cliff next time he, uh, where to shop in the environment. As we look through the rules that were created through that very simple user experience, you can see the one for is empty and is no that we're set up. Now, these are various, uh, styles that can be set up either manually, or you can set them up through machine learning again, or you can inherit them. But the key is to track these, uh, rule creation in the metrics that are generated from these rules so that it can be brought back to the catalog and then used in meaningful context, by someone who's shopping and the confidence that this has neither empty nor no fields, at least most of them don't well now give a confidence as you go forward. >>And as you can see, those checks have now been entered in and you can see that it's a hundred percent quality score for the Knoll check. So with confidence now, John can actually respond back to Eliza and say, I've actually inserted them they're up and running. And, uh, you're in good status. So that was pretty amazing integration, right? And four months after our acquisition, we've already brought that level of integration between, uh, Colibra, uh, data intelligence, cloud, and data quality. Now it doesn't stop there. We have really impressive and high site set early next year. We're getting introduced a fully immersive experience where customers can work within Culebra and actually bring the data quality information all the way in as well as start to manipulate the rules and generate the machine learning rules. On top of it, all of that will be a deeply immersive experience. >>We also have something really clever coming, which we call continuous data profiling, where we bring the power of data quality all the way into the database. So it's continuously running and always making that data available for you. Now, I'd also like to share with you one of the reasons why we are the most universally available software solutions in data intelligence. We've already announced that we're available on AWS and Google cloud prior, but today we can announce to you in Q3, we're going to be, um, available on Microsoft Azure as well. Now it's not just these three cloud providers that were available on we've also become available on each of their marketplaces. So if you are buying our software, you can actually go out and achieve that same purchase from their marketplace and achieve your financial objectives as well. We're very excited about this. These are very important partners for, uh, for our, for us. >>Now, I'd also like to introduce you our system integrators, without them. There's no way we could actually achieve our objectives of growing so rapidly and dealing with the demand that you customers have had Accenture, Deloitte emphasis, and even others have been instrumental in making sure that we can serve your needs when you need them. Uh, and so it's been a big part of our growth and will be a continued part of our growth as well. And finally, I'd like to actually introduce you to our product showcases where we can go into absolute detail on many of the topics I talked about today, such as data governance with Arco or data privacy with Sergio or data quality with Brian and finally catalog with Peter. Again, I'd like to thank you all for joining us. Uh, and we really look forward to hearing your feedback. Thank you..

(upbeat music) >> From around the globe, it's theCUBE with digital coverage of Postgres Vision 2021 brought to you by EDB. >> Well, hi everybody John Walls here on theCUBE and we're now welcoming Jeremy Wilmot who is the chief product officer at ACI Worldwide part of the Postgres movement, you might say or certainly benefiting from the great value that Postgres is providing a number of enterprises across the globe. Jeremy good to see you today and first off, congratulations you are the first guest I've talked to maybe in a year and a half in their office. So good for you. >> Thanks (chuckles) John that's very kind of you John and great to see you and thanks for having me here. Yeah, it's great to be in the office, it really is. I'm here in Miami in South Florida and getting some sort of normalcy back is great for all of us and I'm certainly enjoying it. So thank you before (indistinct) has been. >> I'm sure you are, yeah, congratulations on that front. First off, let's talk about ACI Worldwide for the folks in our audience who aren't familiar with the payments, your role in terms of that payment ecosystem. Tell us a little bit about ACI Worldwide. >> Sure, well, primarily we're a software company. That's ACI, we started 1975 in Omaha, Nebraska built the first debit card system and ATM system for first National Bank of Omaha and over the last 45 years, we've globalized ourselves, we have, we are delivering mission-critical real-time payment systems across the world to banks to merchants to billers, we help them meet the payment needs of their consumers and their corporates. So we process, manage digital payments, we power omni-commerce and e-commerce payments, we present and process bill payments, we manage fraud, we manage the risk all within that and as I said on a global basis 13 of the G20 countries with a leading DDA account or current account payment processing software in those countries and have been for many years. >> So, as the CPO then quite obviously in the financial space your plate is quite full these days in terms of providing for your client base. How would you characterize maybe the evolution in terms of product development that you've been through in the financial world here over the past say, three to five years, where were you back then to where you are now and what role has Postgres played in that journey? >> Sure, yeah. So, specific to the Postgres part of the ecosystem, previously five-plus years ago our previous database solution was complex, it was expensive, it was hard to change and maintain and we leveraged multiple pieces of software from multiple vendors as a result of that. So at that time we looked for an alternative that was simpler and better and we went through a very comprehensive due diligence process, we explored both open source and license models of database to support our solution and when we looked at all of the options we determined that 2ndQuadrant Postgres was the one that provided the most comprehensive solution we were looking for. It had the right mix of capabilities and performance at the right total cost of ownership that we were looking for. And in the payments world as you can imagine, you've got to to be 24/7 365. And we also required a lower cost of ownership than we had before. But we also wanted a greater flexibility and time to market that we could pass on to our customers. And then the last thing I'd say that we were looking for was a multi-deployment capability. And what I mean by that is that we would be able to use this new platform, Postgres platform in our own data centers in our own private cloud, but we could also deploy it in the public cloud, whether we would run it or whether our customers would run it. We wanted that ability to mix and match between these different deployment options. >> So you've talked about a lot of key elements here attributes in terms of availability, accessibility reliability, security obviously. Walk us through those in terms of why you think 2ndQuadrant was addressing your needs in those particular areas or any others for that matter but what it was that checked the box specifically about what Postgres was offering you as opposed to what these other possible solutions and services were that you were looking at. >> Yeah, I think, we're very focused on being able to identify what our customers need and when they're offering services to consumers and to their corporates what is it that they require that's going to enable them to win and compete. And payments industry has a lot of cost pressures within it. It has regulation, it has consumer convenience and the whole movement of digitalization that puts a lot of downward pressure on the cost space. And those who are going to win in the payment space need to be able to address that. So, that is relevant for our banks, for our merchants, for the billers. They all come under very similar regulatory pressure and market pressure and as a result, the ability to reduce dramatically in a very significant way, the total cost of ownership upon which the payment software was going to be operating that was one of the key elements that was very important to us as we made that decision. The second one I think was to enable us to be able to do what we are good at and what our customers expect us to do. And that in turn enables them to focus on their core competencies. We're a software company, we own our own IP we manage our own software for the needs of the 24/7 365 payment requirements and therefore the merchant or the biller or the bank can really focus in on the digital experience for their customers, focusing on their core competencies and what they need to do to win. That was a second key factor for us. I think the third one for us was as well speed to market. Speed to market for ourselves and being competitive to the alternative to ACI, but also more importantly a speed to market for our customers. And there are, the payment world is highly regulated requires significant certification in order to launch new services that's often the long pole in the tent. So we want to be able to get to that point as quickly as possible. And being able to have a public cloud deployment open systems capabilities that would really allow us to pass on that speed to market to those customers. So for example, an acquirer, a payment acquirer moving into a new geographical country they want to compete in they can (indistinct) on their competitors by launching minimum viable products in six to nine months that is five years ago, that could have been a 24 to 30 months endeavor for them to take on. So I, those were important considerations for us as we were choosing a longterm partner for the Postgres world and the public cloud world. >> Obviously, so you've talked a lot about your relationship with your clients and I know you have a really keen awareness of the need to ensure that trust, to ensure that reliability to ensure the collaboration. How about your relationship on the other side with EDB and in terms of all those elements so how has that evolved over a period of time and what kind of service and what kind of value do you think are you deriving from that relationship now? >> So with EDB, first of all, our journey started with 2ndQuadrant and now EDB. And we were specifically looking at the, one area was at the Bi-Directional Replication BDR that we were wanting to support with our solutions particularly in the public cloud. And that was going to enable us to replace multiple pieces of software from multiple vendors. And so we were to create that solution that was right for ACI, it was right for our customers from a functionality and agility and a cost perspective. So technologically with the non-functional requirements and the reliability, availability, serviceability aspects that we were looking for that was in partnership with 2ndQuadrant and EDB, that was a key element. I think the second piece of it is we worked really well with 2ndQuadrant EDB in terms of partnering to meet the needs of the market. It's great to have the right technology in place but then you need your partners really to be able to work with you tactically real-time in order to win in the market and make it work. And I found that they'd been a great partner for us to be able to do that and to be able to react quickly, do the right thing and really enable us to be a great partner to our customers as we deliver real-time payments, as we deliver the acquiring capabilities, as we deliver a modernization for the big banks that we work with as well. >> Now, before I let you go, I'm going to give you a two-part question here. That's always one way to squeeze a little more info (laughing) to the guest. First off advice. You've been through this transformation obviously you're very happy with all that has transpired, so your advice to others who are considering this journey. And then secondly, what can they and you do you think expect in terms of future challenges, opportunities how we might want to frame that with Postgres? Like, where are we going from here, basically? So, two parts, advice and then where do you think this is headed? >> So advice, I certainly learnings from us versus advice is number one, be very thorough in the due diligence that you do and be very clear on what you want and what are your goals that you're looking for. So from an AGI perspective, we were clear that total cost of ownership in terms of the stack that we were going to be providing to our customers. That was very important, number one number two, nonfunctional requirements. So I've talked about the mission criticality of payments 24/7 365. That was a key second piece. And then the third one, ease of deployment. I talked about that, multi-cloud deployment that we were looking for. So we were clear what we wanted and we we took our time from a due diligence point of view. It's a multi-year decision being made so it's not something specifically I think we want to rush into. In terms of looking forward and where do we go from here? Performance is critical so further up performance enhancements, ability for rapid failover availability, near 100% availability that we're looking for five-nines and above, working together with Postgres in order to make those failovers more seamless because they will happen, particularly in the real-time payments world, where we're now seeing billions of transactions happening in a week and soon that will be in a day, they will need to be able to deal with. And for all of this to happen in a public cloud environment, we, I think all understand a lot of the benefits of public cloud and we need to be able to provide this failover availability capability in the public cloud but also in a hybrid cloud environments we're in a multi-cloud environment, so we need to keep working that and make that happen that will make Postgres a payment-grade infrastructure that could power the world's real-time payments and we would love to be able to do that into the future. >> Well, Jeremy thanks for the insights, we appreciate that and once again, congratulations on getting back in that office. I know it's probably a pretty welcomed addition to your regimen now. >> Yeah, John, thank you very much and thanks to everyone who's dialed in for this and John I look forward to welcoming you in the office soon. >> Very good sir, I look forward to that as well. I'll take you up on that in Miami for sure. John Walls here on theCUBE talking with Jeremy Wilmot is the chief product officer at ACI Worldwide. part of our Postgres Vision 2021 coverage. (upbeat music)

(upbeat music) >> Narrator: From around the globe, it's theCUBE, with digital coverage of Postgres Vision 2021, brought to you by EDB. >> Well, good day, everybody. John Walls here on theCUBE, and continuing our CUBE conversation as part of Postgres Vision 2021, sponsored by EDB, with EDB Chief Technology Officer, Mr. Mark Linster. Mark, good morning to you. How are you doing today? >> I'm doing very fine, very good, sir. >> Excellent. Excellent. Glad you could join us. And we appreciate the time, chance, to look at what's going on in this world of data, which, as you know, continues to evolve quite rapidly. So let's just take that 30,000-foot perspective here to begin with here, and let's talk about data, and management, and what Postgres is doing in terms of accelerating all these innovative techniques, and solutions, and services that we're seeing these days. >> Yeah, so I think it's really... It's a fantastic confluence of factors that we've seen in Postgres, or are seeing in Postgres today, where Postgres has really, really matured over the last couple of years, where things like high availability, parallel processing, use of very high core counts, et cetera, have come together with the drive towards digital transformation, the enormous amounts of data that businesses are dealing with today, so, and then the third factor's really the embracing of open source, right? I mean, Linux has shown the way, and has shown that this is really, really possible. And now we're seeing Postgres as, I think, the next big open source innovation, after Linux, achieving the same type of transformation. So it's really, it's a maturing, it's an acceptance, and the big drive towards dealing with a lot more data as part of digital transformation. >> You know, part of that acceptance that you talk about is about kind of accepting the fact that you have a legacy system that maybe, if you're not going to completely overhaul, you still have to integrate, right? You've got to compliment and start this kind of migration. So in your perspective, or from your perspective, what kind of progress is Postgres allowing in the mindset of CTOs among your client base, or whatever, that their legacy systems can function in this new environment, that all is not lost, and while there is some, perhaps, catching up to do, or some patching you have to do here and there, that it's not as arduous, or not as complex, as might appear to be on the face. >> Well, I think there's, the maturing of Postgres that has really really opened this up, right? Where we're seeing that Postgres can handle these workloads, right? And at the same time, there's a growing number of success cases where companies across all industries, financial services, insurance, manufacturing, retail are using Postgres. So, so you're no longer, you're no longer the first leader who's taken a higher risk, right? Like, five or 10 years ago, Postgres knowledge was not readily available. So if you want Postgres, it was really hard to find somebody who could support you, right? Or find an employee that you could hire who would be the Postgres expert. That's no longer the case. There's plenty of books about Postgres. There's lots of conferences about Postgres. It's a big meetup topic. So, getting know how and getting acceptance amongst your team to use Postgres has become a lot easier, right? At the same time, over 90% of all enterprises today use open source in one way or the other. Which basically means they have open source policies. They have ways to bring open source into the development stream. So that makes it possible, right? Whereas before it was really hard, you had to have an individual who would be evangelized to go, get open source, et cetera, now open source is something that almost everybody is using. You know, from government to financing services, open sources use all over the place, right? So, so now you have something that really matured, right? There's a lot of references out there and then you have the policies that make it possible, right? You have the success stories and now all the pieces have come together to deal with this onslaught of data, right? And then maybe the last thing that that really plays a big role is the cloud. Postgres runs everywhere, right? I mean, it runs from an Arduino to Amazon. Everywhere. And so, which basically means if you want to drive agile business transformation, you call Postgres because you don't have to decide today where it's going to run. You're not locking into a vendor. You're not locking into a limited support system. You can run this thing anywhere. It'll run on your laptop. It'll run on every cloud in the world. You can have it managed, you can have it hosted. You can add have every flavor you want and there's lots of good Postgres support companies out there. So all of these factors together is really what makes us so interesting, right? >> Kubernetes and this marriage, this complimentary, you know relationship right now with Kubernetes, what has that done? You think in terms of providing additional services or at least providing perhaps a new approach or new philosophies, new concepts in terms of database management? >> Well, it's maybe the most the most surprising thing or surprising from the outside. Probably not from the inside, but you think that that Postgres this now 25 year old, database twenty-five year old open source project would be kind of like completely, you know, incompatible with Kubernetes, with containers. But what really happens is Postgres in containers today is the number one database, after Engine X. It is the number two software that is being deployed in containers. So it's really become the workhorse of the whole microservices transformation, right? A 25 year old software, well, it has a very small footprint. It has a lot of interesting features like GIS, document processing, now graph capabilities, common table expressions all those things that are really like cool for developers. And that's probably what leads it to be the number one database in containers. So it's absolutely compatible with Kubernetes. And the whole transformation towards microservices is is like, you know, there's nothing better out there. It runs everywhere and has the most innovative technologies in it. And that's what we're seeing. Also, you go to the annual stack overflow survey of developers, right? It's been consistently number one or number two most loved and most used database, right? So, so what's amazing is that it's this relatively old technology that is, you know, beating everybody else in this digital transformation and then the adoption by developers. >> Just like old dog new tricks, right? It's still winning, right? >> Yeah, yeah, and, and, you know, the elephant is the symbol and this elephant does dance. >> Still dancing that's right. You know, and this is kind of a loaded question but there are a lot of databases out there, a lot of options, obviously from your perspective, you know, Postgres is winning, right? And, and, and from the size of the marketplace it is certainly leading RA leader. In your opinion, you know, what, what is this confluence of factors that have influenced this, this market position if you will, of Postgres or market acceptance of Postgres? >> It's, I mean, it's the, it's a maturing of the core. As I said before, that the transaction rates et cetera, Postgres can handle, are growing every year and are growing dramatic, right? So that's one thing. And then you have it, that Postgres is really, I think, the most reliable and relational database out there as what is my opinion, I'm biased, I guess. And, and it's, it's super quality code but then you add to that the innovation drive. I mean, it was the first one out there with good JSONB support, right? And now it's brought in JSON Path as as part of the new SQL standard. So now you can address JSON data inside your database and the same way you do it inside your browser. And that's pretty cool for developers. Then you combine that with PostGIS, right, which is, I think the most advanced GIS system out there in database. Now, now you got relations, asset compliant, GIS and document. You may say what's so cool about that. Well, what's cool about it is I can do absolutely reliable asset compliant transactions. I can have a fantastic personalization engine through JSONB, and then all my applications need to know where is the transaction? Where is the next store? How far away I'm a form of the parking spot? Right? So now I got a really really nice recipe to put the applications of the future together. You add onto that movements toward supporting graph and supporting other capabilities inside the database. So now you got, you got capability, you've got reliability and you got fantastic innovation. I mean, there's nothing better out there. >> Let's hit the security angle here, 'cause you talked about the asset test, and certainly, you know, those, that criteria is being met. No question about that, whether it's isolation, durability, consistency, whatever, but, but security, I don't have to tell you what a growing concern this is. It's already paramount, but we're seeing every day write stories about, about intrusions and and invasions, if you will. So in terms of providing that layer of security that everybody's looking for right now, you know, this this ultra impenetrable force, if you will, what in your mind, what's Postgres allowing for, in that respect in terms of security, peace of mind, and maybe a little additional comfort that everybody in your space is looking for these? >> So, so look at, look at security with a database like, like multiple layers, right? There's not just, you don't do security only one place. It's like when you go into a bank branch, right? I mean, they do lock the door, they have a camera, there is a gate in front of the safe, there's a safe door. And inside the safe, there is still, again safety deposit boxes with individual locks. The same applies to Postgres, right? Where let's say we start at the heart of it where we can secure and protect tables and data. We're using access control lists and groups and usernames, et cetera. Right? So that's, that's at the heart of it. But then outside of that, we can encrypt the data when on disk or when it's in transit on disk. Most people use the Linux disc encryption systems but there's also good partners out there, like like more metric or others that we work with, that that provide security on disk. And then you go out from there and then you have the securing of the database itself again through the log-ins and the groups. You go out from there and now you have the securing of the hosts that the database is sitting on. Then you'll look at securing the data on the networks through SSL and certificates, et cetera. So that basically there's a multi-layer security model layer that positions Postgres extremely well. And then maybe the last thing is to say it certainly integrates very well with ELDAP, active directory, Kerberos, all the usual suspects that you would use to secure technology inside the enterprise or in an open network, like where people work from home, et cetera. >> You talked about the history about this 25 year old technology, you know, founded back at Cal Berkeley, you know, probably almost some 30 years ago and certainly has evolved. And, and as you have pointed out now as a very mature technology, what do you see though in terms of growth from here? Like, where does it go from here in the next 18 months, 24 months, what what do you think is that next barrier, that challenge that that you think the technology and this open source community wants to take on? >> Well, I think there's there's the continuous effort of making it faster, right? That always happens, right? Every database wants to be faster do more transactions per second, et cetera. And there's a lot of work that has been done there. I mean, just in the last couple of years, Postgres performance has increased by over 50%. Right? So, so transactions per second and that kind of scalability that is going to continue to be, to be a focus, right? And then the other one is leading the implementation of the SQL standards, right? So there'd be the most advanced database, the most innovative database, because, remember for many years now, Postgres has come up with a new release on an annual basis. Other database vendors are now catching up to that, but Postgres has done that for years. So innovation has always been at the heart of it. So we started with JSONB, Key value pair came even before that, PostGis has been around for a long time, graph extensions are going to be the next thing, ingestion of time series data is going to, is going to happen. So there's going to be an ongoing stream of innovations happening. But one thing that I can say is because Postgres is a pure open source project. There's not a hard roadmap, like where it's going to go but where it's going to go is always driven by what people want to have, right? There is no product management department. There's no, there's no great visionary that says, "Oh, this is where we're going to go." No, no. What's going to happen is what people want to have, right? If companies or contributors want to have a certain feature because they need it, well, that's how it's going to happen. And that's really been at the heart of this since Mike Stonebraker, who's an advisor to EDB today, invented it. And then, you know, the open source project got created. This has always been the movement to only focus on things that people actually want to have because if nobody wants to have it, we're just not going to build it because nobody wants it. Right? So when you asked me for the roadmap I believe it's going to be, you know, faster, obviously, always faster, right? Everybody wants faster. And then there's going to be innovation features like making the document stored even better, graph ingestion of large time series, et cetera. That's really what I believe is going to drive it forward. >> Wow. Yeah, the market has spoken and as you point out the market will continue to speak and, and drive that bus. So Mark, thank you for the time today. We certainly appreciate that. And wish EDB continued success at Postgres vision 2021. And thanks for the time. >> Thanks John, it was a pleasure. >> You bet. Mark Linster, joining us, the CTO at EDB. I'm John Walls, you've been watching theCUBE. (upbeat music)

(upbeat music) >> From around the globe, it's theCUBE. With digital coverage of Postgres Vision 2021 brought to you by EDB. >> Well, good day, everybody. John Walls here on theCUBE. We continue our coverage here at Postgres Vision in 2021. Talking today with Andy Harris, who is the Chief Technology Officer at Osirium, a leader in the Privileged Access Management Space, and Andy, good day to you. Thanks for joining us here on theCUBE. >> Good morning to you and good afternoon, yes. >> That's right. Joining us from overseas over in England, we're on this side of the big pond, but nonetheless, we're joined by the power of Zoom. So again, thanks for the time. Andy, for those who aren't familiar who are watching about Osirium, share a little bit about your various service levels of what you provide, the kind of solutions you provide, and how you've achieved a great success in this space. >> Okay. I know these things, mine will be boring. So I'll just put a little slide up now, which is the minimum I think I can get away with which is that we're all about managing privilege. So that's privileged at the endpoint, Privileged Access Management, and Privileged Process Automation. So wherever a CIS admin has to do something on a machine that needs privilege, we like to be involved. Obviously, we like to be able to delegate all the way down to the business functions with Privileged Process Automation and with the EDB or the BDR part of that functionality in EDB that really fits in to our Privileged Access Management. So what I'll do just to take you away from our product. So I'll just quickly show you a slide of the architecture, which is as simple as we have these nodes. If you like the running ADB BDR and they can perform log-ins to a target device using privileged credentials, which we control when we might be really long up to about 128 characters. >> So Andy, if you would, I think you had put together a little show and tell you a demonstration for how when these systems are perhaps under siege if you will. That there are ways in which obviously you've developed to counter this and to be able to continue secure communications, which in the privilege assets world as you know is paramount. >> Yes, indeed. So I'll show you another slide, which gives you a kind of a overview of everything that's going on and you're going to see a little demonstration of two nodes here that has the BDL technology on and they can make these logins, and we have these characters, Bob and Allison. I've just noticed how it marks in department turn Alice to Allison. they should really be Alice because you get Bob, Alice, Carol, Dave, which are the standard encryption users. And what we're going to do is we're going to demonstrate that you can have breaks in the network. So I'm just sharing the network breaks slide. I'm showing the second network break slide. And then we have this function that we've built which we're going to demonstrate for you today, which is called evil beatings. And what it does is whilst there is a politician in the network, we are going to refresh many thousands of times the credentials on the target device. And then we're going to heal the break in the network and then prove that everything is still working. So right now, I'm going to zoom over to my live connection, terminal connections to the machine. And I'm going to run this command here, which is Python EV3. And I'm going to put a hundred cycles in it which is going to do around about 10,000 password refreshes. Okay. And I'm then going to go over to Chrome, and I should have a system here waiting for me. And in this system, you'll see that I've got the device demo and I've got this come online, SSH. And if I click on this I've got a live connection to this machine. Even whilst I have a huge number of queued up and I'll just show you the queued out connections through the admin interface. The system is working extremely hard at the moment. And in fact, if I show you this slide here, you can see that I have all of these queued credential resets and that is giving our system an awful lot of grief. Yeah. I can go back to the device connection and it is all here still top. Why not? And as you can see, it is all working perfectly. And if I was a user of EDB, I think this has to be one of the demonstrations I'd be interested in because it's one of the first things that we did when we dropped that functionality into our products. We wanted to know how well it would work under extreme conditions because you don't think of extreme conditions as normal working, but whenever you have 10 nodes in different countries, there will always be a network break somewhere and someone will always need to be refreshing passwords a ridiculous rates of knots. So Andy let's talk about this kind of the notion that you're providing here, this about accountability and visibility, audit-ability, all these insights that you're providing through this kind of demonstration you've given us how critical is that today, especially when we know there are so many possible intrusions and so many opportunities with legacy systems and new apps and all of this. I mean talking about those three pillars, if you will, the importance of that and what we just saw in terms of providing that peace of mind that everybody wants in their system. >> That's a cracking question. I'm going to enjoy that question. Legacy systems, that's a really good question. If you, we have NHS, which is our national health service and we have hospitals and you have hospitals every country has hospitals. And the equipment that they use like the MRI scanners, the electro-microscope, some of the blood analysis machines, the systems in those costs multiple Gillions of dollars or should use dollars euros, dollars, pounds and the operating systems running those systems, the lifetime of that piece of equipment is much much longer than the lifetime of an operating system. So we glibly throw around this idea of legacy systems and to a hospital that's a system that's a mere five years old and has got to be delivering for another 15 years. But in reality, all of this stuff gets, acquires vulnerabilities because our adversaries the people that want to do organizations bad things ransomware and all the rest of it they are spending all that time learning about the vulnerabilities of old systems. So the beauty of what we do is being able to take those old legacy systems and put a zero trust safety shell around them, and then use extremely long credentials which can't be cracked. And then we make sure that those credentials don't go anywhere near any workstations. But what they do do, is they're inside that ADB database encrypted with a master encryption key, and they make that jump just inside the zero trust boundary so that Bob and Alice outside can get administration connections inside for them to work. So what we're doing is providing safety for those legacy systems. We are also providing an environment for old apps to run in as well. So we have something called a map server which I didn't think you'd asked us that question. I'd have to find you some slides or presentations, which we want to do. We have a map server, which is effectively a very protected window server, and you can put your old applications on them and you can let them age gracefully and carry on running. Dot net 3.5 and all of those old things. And we can map your connection into the older application and then map those connections out. But in terms of the other aspects of it is the hospital stay open 24 hours a day banks run 24 hours a day and they need to be managed from anywhere. We're in a global pandemic, people are working from home. That means that people are working from laptops and all sorts of things that haven't been provisioned by centrality and could all have all sorts of threats and problems to them. And being able to access any time is really important. And because we are changing the credentials on these machines on a regular basis, you cannot lose one. It's absolutely critical. You cannot go around losing Windows active directory domain credentials it just can't be done. And if you have a situation where you've just updated a password and you've had a failure one of those 10 nodes has the correct set of credentials. And when the system heals, you have to work out which one of the 10 it is and the one that did it last must be the one that updates all the other 10 nodes. And I think the important thing is as Osirium we have the responsibility for doing the updates and we have the responsibility for tracking all those things. But we hand the responsibility of making sure that all the other 10 nodes are up to date which just drop it into bi-directional replication and it just happens. And you've seen it happen. I mean, might be just for the fun of it, We'll go back to that demonstration Chrome, and you can see we're still connected to that machine. That's all still running fine but we could go off to our management thing, refresh it and you see that everything there is successful. I can go to a second machine and I can make a second connection to that device. Yet, in the meantime that password has been changed, Oh, I mean, I wouldn't like to tell you how many times it's been changed. I need to be on a slightly different device. I was going to do a reveal password for you, I'll make another connection but the passwords will be typically, do a top on that just to create some more load. But the passwords will typically be... I'll come back to me. They'll typically be 128 characters long. >> Andy, if I could, I mean, 'cause I think you're really showing this very complex set of challenges that you have these days, right? In terms of providing access to multiple devices across, in multiple networking challenges, when you talk to your prospective clients about the kind of how this security perimeters changed, it's very different now than it was four or five years ago. What are the key points that you want them to take away from your discussion about how they have to think about security and access especially in this day and age when we've even seen here in the States. Some very serious intrusions that I think certainly get everybody's attention. >> That's a great question again. They're all... The way that I would answer that question would definitely depend on the continent that I was talking to. But my favorite answer will be a European answer, so I'll give you a European answer. One of the things that you're doing when you come along and provide Privileged Access Management to a traditional IT team, is your taking away the sysadmins right now, before privilege access, they will know the passwords. They will be keeping the passwords in a password vault or something like this. So they own the passwords, they own the credentials. And when you come along with a product like privilege access management you're taking over management of those credentials and you're protecting those systems from a whole wide range of threats. And one of those threats is from the system administrators themselves. And they understand that. So what I would say, it's an interesting question. 'Cause I'm like, I'm thinking I've got two ways of answering I can answer as if I'm talking to management or as if I'm talking to the people who are actually going to use the products and I feel more aligned with the, I feel more aligned with the actual users. >> Yeah, I think let's just, we'll focus on that and I'll let you know, we just have a moment or two left. So if you could maybe boil it down for me a little bit. >> Boiling it down, I would say now look here CIS admins. It's really important that you get your job done but you need to understand that those privileged accounts that you're using on those systems are absolute gold dust if they get into the hands of your adversaries and you need protections income away from those adversaries, but we trust you and we are going to get you the access to your machines as fast as possible. So we're a little bit like a nightclub bouncer but we're like the Heineken of nightclub bounces. When you arrive, we know it's you and we're going to get you to your favorite machine logged on as domain admin, as fast as possible. And while you're there, we're going to cut that session recording of you. And just keep you safe and on the right side. >> All right, I'm going to enjoy my night in the nightclub. Now I can sleep easy tonight knowing that Andy Harris and Osirium are on the case. Thanks, Andy. Andy Harris speaking with us. So the Chief Technology Officer from Osirium as part of our Postgres vision, 2021, coverage here on theCUBE. (upbeat music) >> From theCUBE studios in Palo Alto, in Boston connecting with thought leaders all around the world. This is theCUBE conversation.

(upbeat music) >> From around the globe, it's theCUBE! With digital coverage of Postgres Vision 2021, brought to you by EDB. >> Welcome back to Postgres Vision 21, where theCUBE is covering the innovations in open source trends in this new age of application development and how to leverage open source database technologies to create world-class platforms that are cost-effective and also scale. My name is Dave Vellante, and with me is Roberto Giordano, who is the End User Computing, Corporate, and Database Services Manager at Borsa Italiana, the Italian Stock Exchange. Roberto, great to have you. Thanks for coming on. >> Thanks Dave, and thanks to the interview friend for the invitation. >> Okay, and we're going to dig in to the great customer story here. First, Roberto, tell us a little bit more about Borsa Italiana and your role at the organization. >> Absolutely. Well, as you mentioned, Borsa is the Italian Stock Exchange. We used to be part of the London Stock Exchange, but last month we left that group, and we joined another group called Euronext, so we are now part of another group, I would say. And right now within Euronext, Euronext provide the biggest liquidity pool in Europe, just to mention something. And basically we provide the market infrastructure to our customers across Europe and the whole world. So probably if it happens for you to buy a little of, I don't know, Ferrari for instance, probably use our infrastructure. >> So I wonder if you could talk about the key drivers in the exchange business in Italy. I don't know how closely you follow what's going on in the United States, but it's crypto madness, there's the Reddit army driving up stocks that have big short positions, and of course the regulators have to look at that, and there's a big debate going on. Well, I don't know what's it like in Italy, but what are the key drivers that are really informing the priorities for your technology strategy? >> Well, you mentioned, for instance, the stereotypical cases that are a little bit of laterally to the global markets and also to our markets as a it professional running market infrastructure is our first the goal to provide an infrastructure that is reliable and be with the lowest possible latency. So we are very focused on performance and reliability just to mention the two main drivers within our systems. >> Well, and you have end-user computing in your title and we're going to get into the database discussion, but I presumably with with COVID you had to pivot and that that piece of your job was escalated in 2020, I would imagine. And you mentioned latency which is a key factor in obviously in database access but that must've been a big challenge last year. >> Well, it was really a challenge, but basically we move just within a weekend, the wall organization working remotely. And it has been like this since February, 2020. Think about the challenge of moving almost 1000 people that used to come to the office every day to start to work remotely. And as within my team of the end user computing this was really a challenge but it was a good one at the end. We, we, we succeeded and everything work. It's fine from our perspective, no news is is a good news, you know, because normally when something doesn't work, we are on newspapers. So if you didn't heard about us it means that everything worked out just fine. >> Yeah. It's amazing, Roberto. We both in the technology business that you'll be you're a practitioner observer, but I mean if you're in the tech business most companies actually pivoted quite well. You're have always been a digital business, different. I mean, if you're a Ferrari and making cars and you can't get semiconductors, but but most technology companies actually made the transition you know, quite amazingly, let's get into the, the case study a bit of it. I wonder if you could paint a picture of your organization's infrastructure and applications what it looks like and and particularly your database infrastructure what does that look like? >> Well, we are a multi-vendor shop. So we would like to pick the right technology for for the right service. This means that my database services teams currently manage several different technology where possible that plays a big role in, in, in our portfolio. And because we, we, we currently support both the open source, fully open source version of PostgreSQL, but also the EDB distribution in particular we prefer to use DDB distribution where we did specific functionalities that just EDB provide. And we, when we need a first class level of support that ADB in in recent year was able to provide to us. >> When you say full functioning, are you talking about things like acid compliance, two phase commits? I mean, all these enterprise capabilities, is that right? Or maybe you could be >> Just too much just to mention one, for instance we recently migrated our wire intrasite availability solution using the ADB fail-over manager. That is an additional component that just it'll be provide. >> Yeah. Okay. So, so par recovery obviously is, is and so that's a solution that you to get from the EDB distro as opposed to having to build it yourself with open source tooling. >> Yeah, correct. Well, basically sterically, we used to rely on OSTP clustering from, from, from that perspective. But over the years we found that even if it's a technology that works fine, it has been around for four decades. And so on. We faced some challenges internally because within my team we don't own also the operative system layers. So we want a solution that was 100% within our control and perimeter. So just few months ago we asked the EDB EDB folks if they can provide something. And after a couple of meetings also with their pre-sales engineers, we found the the right solution for us. So we launched long story short, just a quick proof of concept to a tissue test together, again using the ADB consultancy. And, and then we, beginning of this year, we, we went live with the first mission critical service using this brand new technology, well brand new technology for us. You know, it'd be created a few years ago >> And I do have some follow-up questions but I want to understand what catalyzed the, you know what was the motivation for going with an open source database? I mean, you're, you're a great example because you have your multi-vendor so you have experienced with all of it, the full spectrum. What was it about open source database generally EDB specifically that triggered the, the choice? >> Well thanks for the question. It is, this is one of the, or one of the questions that I always, like. I think what really drove us was the right combination between easy to use, so simplicity and also good value for money. So we like to pick the right database technology for the right kind of service slash budget that the survey says and, and the open source solution for a specific service. It, it, it's, it's our, you know, first, first, first choice. So we are not going to say a company that use just one technology. We like to take the best of breed that the market can offer. In some cases, the open source and Pasquesi in particular is, is our choice. How involved was >> The line of business in this both the decision and the implementation? Was it kind of invisible to them, or this was really more of a technology decision based on the your interpretation of the requirements I'm interested in who was involved and how you actually got it done? >> Well, I, I think this decision was transplant for, for, for, for the business at the end of the day don't really have that kind of visibility. You know, they just provide requirements in particular in terms of performance and rehabil area, the reliability. And so, so this this is something they are not really involved about. And obviously if they, if we are in opposition to save a little bit of money everybody's at the, even the business >> No. So what did you have to do? So that makes sense to me, I figured that was the case. Who would, who were the stakeholders on your team? I mean, what kind of technical resources did you require an implementation resources? What take us through what the project if you will look like, wh how did you do it? >> Well, it's a combination of database expertise. I got the pleasure to run a team that is paid by very, very senior, very, very skilled database services professional that are able to support more than one more than what the county and also are very open to innovation and changes. Plus obviously we need also the development teams the relevant development teams on board, when you when you run this kind of transformations and it looks like also, they liked the idea to use PostgreSQL for for this specific service I got in mind. So it, it, it was quite, quite easy, not be discussion. You know. >> What was the, what was the elapsed time from from when you said, okay, we're in, you know signed the agreement we're going here you made the decision to actually getting into production. >> Well, as I mentioned, we, we, we were on we're on services and application that are really focused on high availability and performance. So generally speaking, we are not a peak organization. Also we run a business that is highly regulated. So as you know, as you can imagine we are an organization that don't have a lot of appetite for risk, you know, so generally speaking in order to run this kind of transformation is a matter of several months, I will say six nine months to have something delivered in that space. >> Okay. Well, that's, I mean, that's reasonable. I mean, if you could do it inside of a year that's I think quite good especially in the highly regulated industry. And then you mentioned kind of the fail over the high availability Cape Cape capabilities. Were there other specific EDB tools that that you utilize to sort of address the objectives? >> Yeah, absolutely. We were in particular, we used Postgres enterprise, AKA Pam. Okay. And very recently we were involved within ADB about per se specifically developing one functionality that, that that we needed back in the day. I think together with Bart these are the free EDB specific tools that, that we, that that we use right now. >> And, and I'm, I'm interested in, I want to get to the business impact and I know it's early days for you but the real motivation was to save money and simplify. I would actually, I would imagine your developers were happy because they get to use modern tooling and open source. But, but really though if your industry is bottom line, right, I mean that's really what the, the business case was all about. But I wonder if you could add some color there in terms of the business impact that you expect. And then, I mean I don't know how much visibility you have now but anything you can share with us. >> Well, thinking about the EFM implementation that the business impact the, was that in case of a failure or the DBA team that a services team is it is able to provide a solution that is within our 100% within our perimeter. So this means that we are fully accountable for it. So in a nutshell, when you run a service, the less people the less teams you have to involve the more control you can deliver. And in some, again, very critical services that is a great value. >> Okay. So, and, and where do you want to take this? I mean, how do you see w what's your, if you're thinking about your Postgres and, and generally an EDB you know, roadmap, where do you want it to go? >> Well, I stay to, to trends within within the organization, the, the, the, the the first one is about migrating more existing services to open source solution for database is going to be, is going to be prosperous. And other trends that I see within my organization is about designing applications, not really to be, to to use PostgreSQL as the base, as it does a base layer. I think both trends are more or less surroundings at the same state right now. >> Yeah. A lot of the audience members at Postgres vision 21 is just like you they they're managing day-to-day infrastructure. They're there they're expert practitioners. What advice would you give to somebody that is thinking about, you know taking this journey, maybe if you had to do something over again maybe what would you do differently? How can you help your peers here? >> Well, I think in particular, if you are going to say a big organization that runs a highly regulated business in some cases, you are a little bit afraid of open source because there is this, I can say general consideration about the lack of enterprise level support. I would like to say that it is just about the past because they're around bunch of companies like EDB that are we're a hundred percent capable of providing enterprise level of support, even on, on, on even on the open source distribution of Paul's presser. Obviously Dan is you're going to go with their specific distribution. The level of support is going to be even more accurate but as we know, it could be currently is they across say main contributor of the pollsters community. And I think is, is that an insurance for every organization? >> Your advice is don't be afraid. >> Yeah. My advice is done is absolutely, don't be, don't be afraid. And if, if, if I can, if we can mention about also about, you know, the cloud called technologies this is also another, another topic where if possible I would like to suggest to not being afraid EDB as every every I would say organization within the it industry is really pushing for it. And I think for a very, for, for a lot of cases not all of them, but a lot of cases, there is a great value about the design services application to be cloud native or migrating existing application into the cloud. >> Okay. But, but being a highly regulated industry and being a, you know, very much aware of the the narrative around open source, et cetera, you, you must've had just a little piece of your mind saying, okay I have to manage this risk. So there's anything specifically you did with managing the risks that you would advise? Was it, was it or is it really just about good change management? >> I think it was mainly about a good change management when you got, you know the relevant stakeholders that you need on board and we are, everybody's going the same direction. That basically is about executing. >> Excellent. Well, Roberto, I really appreciate your time and your knowledge that you share with the audience. So thanks so much for coming on the cube. >> Thank you, Dave. It was a great pleasure. >> And thank you for watching the cubes continuous coverage of Postgres vision 21. We'll be right back. (upbeat music)

>> Ed Boyajian, the CEO of Enterprise DB. Ed, what are some of the more exciting things that people can expect from Postgres Vision 2021. Who should attend and why? >> Yeah, so really key things that we're going to be covering. Because of our focus on the enterprise, we're going to to talk a lot about how Postgres is used and deployed at scale in the enterprise. As we've seen, developers are playing such a prominent role now in the decision-making for technologies, especially database. So we're going to talk a lot about application development with Postgres. We're going to spend time. Of course, it's a technology conference. There's a lot coming on the horizon with Postgres and work that EDB is doing. So we're going to talk about emerging technologies and what's ahead. And then, you know, a lot of outsiders don't understand the nature and power of the Postgres community. And so we're going to put some cycles into sharing a little more depth and insight about what happens in the community and why that is powerful and what makes it great. >> Postgres Vision '21 is June 22nd and 23rd. Go to Enterprise DB.com and register. The Cube's going to be there. We hope you will be too. Ed, thanks for coming on the Cube and previewing the event. >> Thanks, Dave. >> And thank you, we'll see you at Vision '21.

(upbeat music) >> From around the globe, it's the CUBE with digital coverage of Postgres Vision 2021. Brought to you by EDB. >> Hello everyone, this is Dave Vellante for the CUBE. We're covering Postgres Vision 2021, the Virtual CUBE edition. Welcome to our conversation with the CEO, Ed Boyajian, the CEO of Enterprise DB. And we're going to talk about what's happening in open source and database and the future of tech. Ed, Welcome. >> Hi Dave, good to be here. >> Hey, several years ago at Postgres Vision event you put forth the premise that the industry was approaching a threshold moment, and digital transformation was the linchpin of that shift. Now, Ed, while you were correct, and I have no doubt the audience agreed, most people went back to their offices after that event and they returned to their hyper-focus of their day-to-day jobs. Yeah, maybe a few accelerated their digital initiatives but generally, pre COVID, we moved at a pretty incremental pace and then the big bang hit. And if you weren't digital business, you were out of business. So, that single event created the most rapid change that we've ever seen in the tech industry by far, nothing really compares. So, the question is, why is Postgres specifically and EDB generally the right fit for this new world? >> Yeah, I think, look a couple of things are happening Dave. You know, right along the bigger picture of digital transformation, we are seeing the database market in transformation. And, and I think the things that are driving that shift are the things that are resulting the success of Postgres and the success of EDB. I think first and foremost, we're seeing a dramatic re-platforming. And just like we saw in the world of Linux where I was at, Red Hat during that shift where people were moving from Unix-based systems to X86 systems, we're seeing that similar re-platforming happening whether that's from traditional infrastructures to cloud-based infrastructures or container-based infrastructures, it's a great opportunity for databases to be changed out. Postgres wins in that context because it's so easily deployed anywhere. I think the second thing that's changing is we're seeing a broad expansion of developers across the enterprise. They don't just live in IT anymore. And I think as developers take on more power and control, they're just defining the agenda. And it's another place where Postgres shines. It's been a priority of EDB's to make Postgres easier and that's coming to life. And I think the last stack overflow developer survey suggested that, I think they survey 65,000 developers, the second most loved and the second most used database by developers is Postgres. And so I think there again, Postgres shines in a moment of change. And then I think the third is kind of obvious. It's always an elephant in the room, no pun intended, but it's this relentless nagging burden of the expenses of the incumbent proprietary databases and the need. And we especially saw this in COVID. To start to change that, more dramatically change that economic equation, here again, Postgres shines. >> You know, I want to ask you, I'm going to jump ahead to the future for a second, because you're talking about the re-platforming and with your Red Hat shops I kind of want to pick your brain on this because you're right. You saw that with Red Hat and you're kind of seeing it again when you think about open shift and where it's going, my question is related to re-platforming around new types of workloads, new processing models at the edge, I mean, you've seen an explosion of processing power GPU's, NPUs, accelerators, DSPs and it appears that there this is happening at a very low cost. I'm inferring that you're saying Postgres can take advantage of that trend as well, that that broader re-platforming trend to the edge, is that correct? >> It is. And, and I think, you know this is the this has been one of the I think the most interesting things with Postgres. Now I've been here almost 13 years. So if you put that in some perspective, I've watched and participated in leading transformation in the category. You know, we've been squarely focused on Postgres so we've got 300 engineers who worry about making Postgres better. And as you look across that landscape a time, not only as Postgres gotten more performance and more scalable, it's also proven to be the right database choice in the world of not just legacy migrations but new application development. And I think that stack overflow developer survey is a good indicator of how developers feel about Postgres, but, you know over that timeframe, I think if you went back to 2008 when I joined EDB, Postgres was was considered a really good general purpose database. And today I think Postgres is a great general purpose database. General purpose isn't sexy in the market, broadly speaking but Postgres capabilities across workloads in every area is really robust. And let me just spend a second on it. We look at our customer base as deploying and what we think of as systems of record, which are the traditional ERP type apps, you know where there's a single source of truth. You might think of ERP apps there. We look at our customers deploying and systems of engagement, and those are apps that you might think of in the context of social media style apps or websites that are backed by a database. And the third area is systems of analytics where you would typically think of data warehouse style applications, interestingly, Postgres performs well. And our customers report using us across that whole landscape of application areas. And I think that is one of Postgres' hidden superpowers, is that ability to reach into each area of requirement on the workload side. >> Yeah. And as I was alluding to before. That, that itself is evolving as you now inject AI into the equation AI inferencing. And it's just a very exciting times ahead. There's no, there's no database, you know 20 years ago it was kind of boring. Now it's just exploding. I want to come back to that, the notion of of Postgres that maybe talk about other database models. I mean, you've mentioned that you've evolved from this, you know, system of record. You can take a system engagement on structured data, et cetera, Jason it's-. So how should we think about Postgres in relation to other databases and specifically other business models of companies that provide database services? Why is Postgres attractive? Where is it winning? >> Yeah, I think a couple of places. So, I mean, for first and foremost, Postgres, you know at its core, Postgres is a SQL relational database a trend in asset compliance, equal relational database. And that is inherently a strength of Postgres but it's also a multi-model database. Which means we handle a lot of other, you know database requirements, whether that's geospatial or, or JSON for documents or, or time series, things like that. And, so Postgres extensibility is one of its inherent strengths. And that's kind of been built in from the beginning of Postgres. So not surprisingly people use Postgres across a number of workloads because at the end of the day, there's still value in having a database that's able to do more. There are a lot of important specialty databases and I think they will remain important specialty databases, but Postgres thrives in its ability to crossover in that way. And I think that is, you know one of the different key differentiators in in how we've seen the market and the business develop. And, and that's the breadth of of workloads that Postgres succeeds in. But, but our growth if you kind of ventured it across vectors we see growth happening, you know, in a few dimensions. First, we see growth happening in new applications. About half of our customers have come to us today for new, new Postgres users are deploying us on new applications. The others are our second area migrating away from some existing legacy incumbent. Often Oracle, not always. The third area of growth we see is in cloud where we're Postgres is deployed very prolifically both in the traditional cloud platforms like EC2, but then again also in the database as a service environment and then the fourth area growth we're seeing now is around container deployment, Kubernetes deployment. >> Well, you mean Oracle's prominent because it's just, it's, it's, it's a big install base and it's expensive and people, you know they got to look at that. I mean, It's funny. I do a lot of TCO work and mostly, you know usually TCO is about labor costs when it comes to Oracle it's about license costs and maintenance costs. And so to the extent that you can reduce that at least for a portion of your state, you're going to, you're going to drop right to the bottom line. But, but, I want to ask you about the kind of that spectrum that you think about the prevailing models for database you've got on the one hand, you've got the right tool for the right job approach. You know, it might be 10 or 12 data stores in the cloud. On the other hand, you've got kind of a converged approach. You know, Oracle is going that direction, clearly Postgres, with its open source innovation, is going that direction. And it seems to me yet that at scale that's a more, the latter is the more cost-effective model. How do you think about that? >> Well, you know, I think at the end of the day you kind of have to look at it. I mean, the, the business side of my brain looks at that as an addressable market question, right? And you heard me talk about three broad categories of workloads and, you know, people define workloads in different buckets, but that's how we do it. But if you look at just a system of record in the system of engagement market I think that's what would be traditionally viewed as the database market. And there that's, you know, let's just say for the sake of arguments, a 45 to $50 billion market. The third, the systems of analysis that market's an $18 billion market. And, and, you know, as we talk about that so all in it's still between 60 and $70 billion market. And I think what happens, there's so much heat and light poured on the valuation multiples of some of the specialty players that the market gets confused. But the reality is our customers don't get confused. I mean, if you look at those specialty players take that $48 billion market. I mean, add up Mongo, Reds, Cockroach, Neo, all of those. I mean, hugely valued companies all unicorn companies, but combined they add up to a billion bucks. Don't get me wrong, that's important revenue and meaningful in the workloads they support, but it's not, it doesn't define the full transformation of this category. Look at the systems of analysis again, another great, great market example. I mean, if you add up the consolidation of the Hadoop vendors, add in there, snowflake you're still talking to, you know $1.5 billion in revenue in an $18 billion market. So while those are all important technologies the question is in this transformation move did the database market fully transformed yet. And my view is, no, it didn't, we're in the first maybe second inning of a $65 billion transformation. And I think this is where Postgres will ultimately shine. I think this is how Postgres wins, because at the end of the day, the, the nature of the workloads fits with Postgres and the future tech that we're building in Postgres will serve that broader set of needs. I think more effectively. >> Well, and I love these tam expansion discussions because I think you're right on. And I think it comes back to the data and we all we all talk about the data growth, the data exposure and we see the IDC numbers. Well, you ain't seen nothing yet. And so at data by its very nature is distributed. That's why I get so excited about these new platform models. And I want to tie it back to developers and open source because to me, that is the linchpin of innovation in the next decade. It has been, I would even say for the last decade we've seen it, but it's gaining momentum. So, so in thinking about innovation and specifically Postgres in open source, you know, what can you share with us in terms of how we should think about your advantage and again where people are glomming, leaning in to that advantage? >> Yeah. So, I mean, I think, I think you bring up a really important topic for us as a company, Postgres, we think is an incredibly powerful community and, and when you step away from it, again, I, now you remember, I told you, I'd been at, I was at Red Hat before now here at EDB. And there's a common thread that runs through those two experiences. In, in both experiences the companies are attached and prominent alongside a strong, independent open-source community. And I think the notion of an independent community is really important to understand around Postgres. There are hundreds and thousands of people contributing to Postgres. Now EDB plays a big role in that about, you know approaching a third of the contributions in the last release, released 13 of Postgres came from EDB. Now you might look at that and say, gee, that sounds like a lot, but if you step away from it, you know at about 30% of those contributions, most of the contributions come from a universe around EDB and that's inherently healthy for the community's ability to innovate and accelerate. And I think that while we play a strong role there you can imagine that having, and there are other great companies that are contributing to Postgres. I think having those companies participating and contributing gets the best the best ideas to the front in innovation. So I think the inherent nature Postgres community makes it strong and healthy. I mean, and then contrast that to some of the other prominent high value open-source companies. Companies and the communities are intimately intertwined. They're one in the same. They're actually not independent open source communities. And I think that they're therein lies one of, one of the inherent weaknesses in those. But, Postgres thrives because, you know we bring all those ideas from EDB. We bring a commercial contingent with us and all the things we hope, we emphasize and focus on, in growth and Postgres. Whether that's in the areas of scalability, manageability, all hot topics, of course security, all of those areas. And then, you know, performance as always. All of those areas are informed to us by enterprise customers deploying Postgres at scale. And I think that's the heart of what makes a successful independent project. >> Common editorial powers of, of that ecosystem. They, they they're they're multiplicative as opposed to the, the resources of one. I want to talk about Postgres Vision 2021 sort of set up that a little bit. The theme this year is 'The Future is You'. What do you mean by that? >> So, if you think about what we just said, posts, the category is in Tran-, the database categories in transformation. And we know that many of our people are interested in Postgres are early in their journey. They're early in their experience. And so we want to focus this year's Postgres Vision on them. That we understand, as a company who's been committed to Postgres, as long as we have. And with the understanding we have of the technology and best practices, we want to share that view, those insights with, with those who are coming to Postgres. Some for the first time, some who are experienced. >> Postgres Vision 21 is June 22nd and 23rd go to enterprisedb.com and register. The CUBE's going to be there. We hope you will be too. Ed, thanks for coming to the CUBE and previewing the event. >> Thanks, Dave. >> And thank you. We'll see you at Vision 21. (upbeat music)

(upbeat techno music) >> From around the globe, it's theCUBE. With digital coverage of Postgres Vision 2021. Brought to you by EBD. >> Hello everyone, this is David Vellante, for the CUBE. And we're here covering Postgres Vision 2021. The virtual version, thCUBE virtual, if you will. And welcome to our power-panel. Now in this session, we'll dig into database modernization. We want to better understand how and why customers are tapping open source to drive innovation. But at the same time, they've got to deliver the resiliency and enterprise capabilities that they're used to that are now necessary to support today's digital business requirements. And with me are three experts on these matters. Abdul Sheik, is Global CTO and President of Cintra. Young Il Cho, aka Charlie, is High Availability Cluster Sales Manager, at Daone CNS. And Alan Villalobos, is the Director of Development Partnerships, at IBM. Gentlemen, welcome to theCUBE. >> Thank you, Dave, nice to be here. >> Thank you, Dave. >> All right, let's talk trends and frame the problem. Abdul, I want to start with you? Cintra you're all about this topic. Accelerating innovation using EDB Postgres helping customers move to modern platforms. And doing so, you got to do it cost-effectively but what's driving these moves? What are the problems that you're seeing at the organizations that you serve? >> Oh, so let me quickly introduce, Abdul Sheik, CTO. I'll quickly introduce Cintra. So we are a multicloud and database architecture MSP. And we've been around for 25 plus years. Headquartered in New York and the UK. But as a global organization, we're serving our SMB customers as well as large enterprise customers. And the trends we're seeing certainly in this day and age is transformation and modernization. And what that means is, customers looking to get out of the legacy platforms, get out of the legacy data centers and really move towards a modern strategy with a lower cost base, while still retaining resiliency and freedom. Ultimately, in terms of where they're going. The key words that really I see driving this, number one is choice. They've been historically locked into vendors. With limited choice with a high cost base. So choice, freedom to choose in terms of what database technologies they apply to which workloads and certainly EDB and the work that has been done to closely marry what enterprise RD platforms offer with EDBs in a work that they've done in terms of filling those gaps and addressing where the resiliency monitoring performance and security requirements are, are certainly are required from an enterprise customer perspective. Choice is driving the move that we see and choice towards a lower cost platform that can be deployed anywhere. Both on-prem modernization customers are looking to retain on premise platforms or moving into any multi clouds whether it's an infrastructure cloud play or a platform cloud play. And certainly with EDBs offering in terms of, you know the latest cloud native offerings also very interesting. And lastly, aside from just cost and the freedom to choose where they deploy those platforms the SLA, the service level model where is the resiliency requirement where the which system is going to bronze, silver, gold? Which ones are the tier one revenue platform revenue generating platforms which are the lower, lower utility platforms. So a combination of choice, a combination of freedom to deploy anywhere and while still maintaining the resiliency and the service levels that the customers need to deliver to their businesses >> Abdul that was a beautiful setup. And, and we've got so much to talk about here because customers want to move from point A to point B but getting there and they, they need help. It's sometimes not trivial. So Charlie Daone is a consultancy. You've got a strong technical capabilities. What are you seeing in this space? You know, what are the major trends? Why are organizations considering that move? And what are some of the considerations there? >> Well, like in other country in South Korea or so our a lot of customers, banking's a manufacturing distributor. They are 90, over 90%. They are all are using Oracle DB and a rack system. But as the previous presenters pointed out, a lot of customers that are sick of the Oracle and they have to undergo the huge cost of a maintenance costs. They want to move away from this cost stress. And secondly, they can think about they're providing service to customer on their cloud base which is a private or the public. So we cannot imagine running on database, Oracle database running on the cloud the system that's not matches on this cloud. And first and second, and finally the customer what they want is the cost and they want to move away from the Oracle locking. They cannot be just a slave at Oracle for a long time and the premium for the new cloud the service for the customer. >> Great. Thank you for that. Oh, go ahead. Yeah. Did you have something else to add Charlie go ahead and please. >> No that's all. >> Okay, great. Yeah, Allen, welcome to theCUBE. You know, it's very interesting to us. IBM, you, you, of course, you're a big player in database. You have a lot of expertise here. And you partner with EDB, you're offering Postgres to customers, you know, what are you seeing? Charlie was talking about Oracle and RAC. I mean, the, the, the thing there is obviously, we talked about the maintenance costs but there's also a lot of high availability capabilities. That's something that IBM really understands well. Do you see this as largely a cloud migration trend? Is it more modernization? Interested in what's IBM's perspective on this? >> I think modernization is the right word. The points that the previous panelists brought up or are on point, right? You know, lower TCO or lower costs in general but that of agility and then availability for developers and data scientists as well. And then of course, you know, hybrid cloud, right? You know, you want to be able to deploy on prem or in the cloud, or both in a mixture of all of that. And I think, I think what ties it together is the customers are looking for insights, right? And, you know, especially in larger organizations there's a myriad of data sources that they're already working with. And, you know, we, you know we want to be able to play in that space. We want to give an offering that is based on Postgres and open source and be able to further what they're strong at at and kind of, you know on top of that, you know, a layer of, of of need that we see is, is seamless data governance across all of those different stores. >> All right, I'm going to go right to the heart of the hard problem here. So if, I mean, I want to, it's just that I want to get from point A to point B, I want to save money. I want to modernize, but if I'm the canary in the coal mine at the customer, I'm saying guys, migration scares me. How do I do that? What are the considerations? And what do I need to know that I don't know. So Abdul, maybe you could walk us through what are some of the concerns that customers have? How do you help mitigate those? Whether it's other application dependencies, you know freezing code, you know, getting, again from that point A to point B without risking my existing business processes how do you handle that? >> Yeah, certainly I think a customer needs to understand what the journey looks like to begin with. So we've actually developed our own methodology that we call Rocket Cloud, which is also part of our cloud modernization strategy that builds in and database modernization strategy built into it starts with an assessment in terms of current state discovery. Not all customers totally understand where they are today. So understanding where the database state is, you know where the risks lie what are the criticality of the various databases? What technologies are used, where we have RAC or we don't have RAC but we have data God, where we have encryption. And so on. That gives the customer a very good insight in terms of the current state, both commercially and technically that's a key point to understand how they're licensed today and what costs could be freed up to free the journey to effectively fund the journey. It's a big, big topic, but once we do that, we get an idea and we've actually developed a tool called rapid discovery. That's able to discover a largest stake without knowing the database list. We just put the scripts at the database servers themselves and it tells us exactly which databases are suited to be you know, effectively migrated to Postgres with in terms of the feature function usage in terms of how heavy they are, would store procedures in the database amount of business logic use of technologies like RAC data guard and how they convert over to to Postgres specifically. That ultimately gives us the ability to give that customer an assessment and that assessment in a short sharp few weeks and get the customer view of all of my hundreds of databases. Here are the subset of candidates for Postgres and specifically than we do the schemer advisor tool the actual assessment tool from EDB, which gives us a sense of how well the schema gets converted and how best to then also look at the stored procedure conversion as well. That gives the customer a full view of their architecture mapping their specific candidate databases and then a cost analysis in terms of what that migration looks like and how we migrate. We also run and maintain those platforms once we're on EDB. >> Thank you for that again, very clear but so you're not replacing, doing an organ transplant. You may, you're you're, you know, this is not I don't mean this as a pejorative, but you're kind of cherry picking those workloads that are appropriate for EDB and then moving those and then maybe, maybe through attrition or, you know over time, sun-setting those other, those other core pieces. >> Exactly. >> Charlie, let me ask you, so we talked about RAC, real application clusters, data guard. These are, you know kind of high profile Oracle capabilities. Can you, can you really replicate the kind of resiliency at lower costs with open source, with EDB Postgres and how do you do that? >> It's my turn? >> yes, please. >> Quite technically, again, I go on in depths and technically the RAC, RAC system is so-called is the best you know, best the tool to protect data and especially in the Unix system, but apart from the RAC by the some nice data replication solution we just stream the application and log shipping and something and then monitor Pam and, and EFM solution which is enterprise failover manager. So even though it be compared to Apple the Apple RAC versus with EDB solution, we can definitely say that RAC is more stable one, but after migration, whatever, we can overcome the, you know, drawbacks of the HA cluster system by providing the EDB tools. So whatever the customer feel that after a successful migration, utilizing the EDB high availability failable solution they can make of themselves at home. So that's, that's how we approach it with the customers. >> So, Alan, again, to me, IBM is fascinating here with your level of involvement because you're the, you guys are sort of historically the master of proprietary the mainframes, VCM, CICF, EB2, all that stuff. And then, you know IBM was the first I remember Steve Mills actually announced we're going to invest a billion dollars in open source with Linux. And that was a major industry milestone. And of course, the, the acquisition of red hat. So you've got now this open source mindset this open source culture. So we, you know, as it's all about recovery in, in database and enterprise database and all the acid properties in two phase commits, and we're talking about, you know the things that Charlie just talked about. So what's your perspective here? IBM knows a lot about this. How do you help customers get there? >> Yeah, well, I mean the main, the main thrust right now IBM has a offering called IBM cloud Pak for data which from here, which runs EDB, right? EDB, Postgres runs on top of cloud Pak for Data But the, you know I think going back to Abdul's points about, you know migrating whatever's needed and whatever can be migrated to Postgres and maybe migrating other things other places, we have data virtualization and autoSQL, right? So once you have migrated those parts of your database or those schemes that can be, having, you know a single point where you can query across them and by the way, being able to query across them you know, before, during and after migration as well. Right? So we're kind of have that seamless experience of layer of SQL. And now with autoSQL of spark SQL as well, as you're, as you're migrating and after is, I'd say, you know, key to this. >> What, what's the typical migration look like? I know I'm sorry, but it's a consultant question but thinking about the, you know, the average, in terms of timeframe, what are the teams look like? You know who are the stakeholders that I need to get involved? If I'm a customer to really make this a success? maybe Abdul, you could talk about that and Charlie and Alan can chime in. >> Well, I think, well, number one you knew the exact sponsors bought into it in terms of the business case, supporting the business case an architect has got a big picture understanding not only database technology but also infrastructure that they're coming from as well as the target cloud platforms and how you ensure that the infrastructure can deliver the performance. So the architect role is important, of course the core DBA that lives within the scope of the database understands the schema of the data model the business logic itself, and the application on it. That's key specifically around the application certification testing connectivity and the migration of the code. And specifically in terms of timeline just to touch on that quickly. I mean, in our experience so far and we're seeing the momentum really really take off the last 18 months, a small project with limited business logic within the database itself can we migrate it in a couple of months but typically with all the testing and rigor around that you typically say three months timeline a medium-sized complexity projects, a six month timeline and a large complex project could be anything from nine months and beyond, but it really comes down to how heavy the database is with business logic and the database and how much effort it will take to re-engineer effectively migrate that PLC code, business logic into EDB given the compatibility level between Oracle and EDB it's relatively certainly an easier path than any other target platform in terms of options. Yeah. Not perspective. That's certainly looks like the composition of a team and timeline >> Charlie or Alan, anything you guys would add. >> Yeah. So, so I think all those personas make sense. I think you might, on the consumer side of the consumer the consumer of the data side the data scientists often we see, you know during migrations and then obviously the dev ops, I think or any operations, right, have to be heavily involved. And then lastly, you know, you see more and more data steward role or data steward type persona, CDO office type type person coming in there make sure that, you know, whatever data governance that is already in place or wants to be in place after the migration is also part of the conversation. >> Why EDB? You know, there's a lot of databases out there you know, it's funny, I always say like, you know, 10, 15 years ago databases were kind of sort of a boring market, right? It was like, okay, you're going to work or whatever. And now it's exploded. You got open source databases, you got, you know not only sequel databases, you got graph databases you know, you get cloud databases, it's going crazy. Why EDB? You wonder if you guys could address that? >> Allan why don't you go first this time? I'll compliment your answers. >> Yeah. I mean, again, I think it goes back to, to the, the I guess varying needs and, and enterprises. Right. And I think that's, what's driven this explosion in databases, whether it's a document store like you're saying, or, or new types of RDBMS, the needs that we talked about at the beginning, like lower TCO, and the push to open source. But you know, the fact of the matter is that that yes, there is a myriad, an ecosystem of databases, pretty much any organization. And so, yeah, we want to tap into that. And why EDB? EDB has done a great job of taking Postgres and making it enterprise ready, you know, that's what they're, they're good at and that, you know fits very nicely with the IBM story obviously. And, and so, you know, and they've they've worked with us as well. They have an operator on, on the runs on red hat OpenShift. So that makes it portable as well but also part of the IBM cloud Pak for data story. And, and yeah, you know, we want to break down those silos. We realized that that need is there for all of these, you know, there's this ecosystem of databases. And so, you know, we're, we see our role as being that platform, whether it's red hat OpenShift, or IBM cloud Pak for data that, that unifies, and kind of gives you that single pane of glass across all of those sources. >> And Charlie, you're obviously all in, you've got EDB in your background. Why EDB for you? >> Before talking about EDB you asked about the previous question about how the migration was different from Oracle to EDB. We had a couple of success story in Korea telecom and some banking area, and it was easier. So EDB provide MTK tool as a people know but it was an appropriate, like a 90%. So we are the channel partner of the EDB for four years. So what we have done was to hire the Oracle expert. So we train Oracle export as as EDB expert at the same time so that they can approach customer and make it easy. So you have no worry about that. Just migrating EDB, Oracle to EDB. There is a no issue. Those telltales include all the tasks, you know Stratus test and trainee, and a POC that we there. So by investing that Oracle expert that we could overcome and persuade the customer to adopt EDB. So, why EDB? Simply I can say there, is there any database they can finally replaced Oracle in the world? Why is the, it's the interoperability between Oracle to EDB as the many experts pointed out there is no other DBE. They can, you know, 90, 90% in compatibility and intercooperability with EDB. That's why, of course, there's the somewhat, you know budget issues or maintenance issue cost the issue escape from Oracle lock-in. But I think the the number one reason was the interoperability and the compatibility with database itself, Oracle database. That was a reason, I guess >> Great Abdul we've talked about, we all know the, as is, you've got a high maintenance costs. You got a lot of tuning, and it's just a lot of complexity. What about the 2B maybe you could share with us sort of the outcome some of the outcomes you've seen what the business impact has been of some of these migrations? >> Sure. I mean, I'll give you a very simple example then just the idea of running Oracle on prem a lot of customer systems teams, for example will drive a virtualization VMware strategy. We know some of the challenges of running Oracle MBM where from a license perspective. So giving the business the ability where I want to go customer in the financial services market in New York, heavy virtualization strategy the ability for them to move away from Oracle on, you know expensive hardware on to Postgres EDB on virtualization just leverage existing skillsets, leveraging existing investment in terms of infrastructure, and also give them portability in AWS. The other clouds, you know, in terms of a migration. More from a business perspective as well, I would say about some of the Allan's points in terms of just freeing up the ability for data scientists and data consumers, to, you know, to consume some of that data from an Postgres perspective more accessibility spinning up environments quicker less latency in terms of the agility is another key word in terms of the tangible differences, the business, lower cost agility, and the freedom to deploy anywhere at the end of the day. Choices, I think the key word that we could come back to and knowing that we can do that to Charlie's point specifically around maintaining service levels. And as architects, we support some of the big, big names out there in terms of airlines, online, cosmetic retailers, financial services, trading applications, hedge funds, and they all want one thing as architect: for us to deliver that resiliency and stand behind them. And as the MSP we're accountable to ensure those systems are up and running and performing. So knowing that the EDB is provided the compatibility but also plugged the specific requirements around performance management, security availability that's fundamentally been key. >> [Dave I mean, having done a lot of TCO studies in this area, it's, it's it Oracle's different. You know, normally the biggest component of TCO is labor with Oracle. The biggest component of TCO is licensed and maintenance costs. So if you can virtualize and reduce those costs and of course, of course the Oracle will fight you and say we won't support it in a VMware environment. Of course, you know, they will, but, but you got to really, you got to battle. But, so here's my last question. So if I'm a customer in that state that you described you know, a lot of sort of Oracle sprawl a lot of databases out there, high maintenance costs, the whole lock-in thing. I got to choices. I, you know, a lot of choices out there. One is EDB. You guys have convinced me that you've got the expertise If I can partner with firms like yours, it's safer route. Okay, cool. My other choice is Oracle is going to, The Oracle sales reps is going to get me in a headlock and talk about exit data and how their Oracle cloud, and how it's, they've invested a lot there. And they have, and, I can pay by the drink all this sort of modern sort of discussion, you know, Oracle act like they invented it late to the game. And then here we are. So, so help me. What's the pitch as to, well, that's kind of compelling. It's maybe the safe bet they're there. They're working with my CIO, whatever. Why should I go with the open source route versus that route? It sounds kind of attractive to me, help me understand that each of you maybe take me through that. Abdul, why don't you start. >> Yeah. I'd say, you know, Oracle's being the defacto for so many years that people have just assumed and defaulted saying, high availability, RAC, DR. Data guard, you know, and I'll apply to any database need that I have. And at the end of the day customers have a three tier database requirement: the lowest, less critical, bronze level databases that really don't need RAC or a high availability, silver tier that are departmental solutions. That means some level of resiliency. And then you've got your gold revenue producing brand impact databases that are they're down. And certainly they won. You see no reason why the bronze and silver databases can be targeted towards EDB. Admittedly, we have some of our largest customers are running platforms, are running $5 million an hour e-commerce platform or airlines running large e-commerce platforms. And exit data certainly has a place. RAC has a place in those, in those scenarios. Were not saying that the EDB is a solution for everything in all scenarios, but apply the technology where it's appropriate where it's required and, you know, generally wherever Oracle has being the defacto and it's being applied across the estate, that's fundamentally what's changed. It doesn't have to be the only answer you have multiple choices now. EDB provides us with the ability to probably address, you know more than 50% of the databases' state, and comfortably cope with that and just apply that more expensive kind of gold tier one cost-based but also capability, you know from the highest requirements of performance and availability where it's appropriate. >> Yeah. Very pragmatic approach. Abdul, thank you for that. And Charlie. Charlie, what's your perspective? Give us your closing thoughts. >> Well, it has been, Oracle has been dominating in Asia in South Korea has market or over many years. So customers got tired of this, continuous spending money for the maintenance costs and there is no discount. There is no negotiation. So they want to move away from expensive stuff. And they were looking for a flexible platform with the easygoing and the high speed and performance open source database like a possibly as career. And now the EDB cannot replace a hundred percent of existing legacy worker, but 10%, 20% 50% as time goes on the trend that will continue. And it will be reaching some high point or replacing the existing Oracle system. And it can, it can also leading to good business chance to a channel partner and EDB steps and other related business in open source. >> Great. Thank you, Charlie and Allen, bring us home here. Give us your follow up >> I think my, co- panelists hit the nail on the head, right? It's a menu, right? That's as things become more diverse and as people make more choices and as everybody wants more agility, you have to provide, I mean, and so that, that's where that's coming in and I liked the way that Andul I kind of split it into gold silver and bronze. Yeah. And I think that that's where, we're going, right? I mean you should ask your developers right? Are your developers like pining to start up a new instance of Oracle every time you're starting a new project? Probably not reach for their Postgres right? And so, because of that, that's where this is coming from and that's not going to change. And, and yeah, that that ecosystem is going to continue to, to thrive. And there'll be lots of different flavors in the growing open source ecosystem. >> Yeah. I mean, open source absolutely is the underpinning you know, the, the bedrock of innovation, these days. Gentlemen, great power panel. Thanks so much for bringing your perspectives and best of luck in the future. >> Thank you, next time we'll try and match our backgrounds >> Next time. Well, we'll up our game. Okay. And thank you for watching everybody. This is Dave Volante for theCUBE. Stay tuned for more great coverage. Postgres vision, 21. Be right back. (upbeat techno music)

>>Ed. Biology in the ceo of enterprise DB ed. What are some of the more exciting things that people can expect from postgres Vision 2021 who should attend and why? >>Yeah. So really um key things that we're going to be covering were because of our focus on the enterprise. We're gonna we're gonna talk a lot about how Postgres is used and deployed at scale in the enterprise. As we've seen, developers are playing such a prominent role now in the decision making for technologies, especially database. So we're going to talk a lot about application development with Postgres. We're going to spend time, of course, it's a technology conference, there's a lot coming on the horizon with Postgres and work that Ebs doing. So we're going to talk about emerging technologies and what's ahead and then, you know, a lot of outsiders don't understand the nature and power of the postgres community. And so we're gonna put some cycles into sharing a little more depth than insight about what happens in the community and why that is powerful and what makes it great. >>Postgres Vision 21 is june 22nd and 23rd go to Enterprise db dot com and register the cube is gonna be there. We hope you will be too. Ed, thanks for coming on the Cuban previewing the event. >>Thanks Dave. >>Thank you. We'll see you at Vision 21.

>> From theCUBE Studios in Palo Alto, and Boston bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Microsoft CEO, Satya Nadella sees a different future for cloud computing over the coming decade. And as Microsoft Ignite keynote, he laid out the five attributes that will define the cloud in the next 10 years. His vision is a cloud platform that is decentralized, ubiquitous, intelligent, sensing, and trusted. One that actually tickles the senses and levels the playing field between consumers and creators by placing tools in the hands of more people around the world. Welcome to this week's wiki buns cube insights, powered by ETR. In this Breaking Analysis we'll review the highlights of Nadella's Ignite keynote share our thoughts on what it means for the future of cloud specifically, and the tech industry generally. We'll also give you a more tactical view of Microsoft and compare its performance within the ETR's dataset to its peers. Satya Nadella's forward-looking cloud attributes comprised five key vectors that he talked about. The first was ubiquitous and decentralized computing, Nadella made the statement that we've reached peak centralization today that we're witnessing radical changes in computing architecture from the materials used to semiconductors software, and that is going to serve a new frontier that's forming at the edge. Nadella envisions a world where there will be more sovereignty and decentralized control. We couldn't agree more. The cloud universe is expanding and the lines are blurring between what's being done on-prem, across public clouds and the cloud experience which is going to extend everywhere, including the edge. And of course, data is going to be flowing through this hyper decentralized system. Next was sovereign data and ambient intelligence. To us data sovereignty means that whatever the local laws are the system is going to have the intelligence to govern privacy, ensure data provenance, and adhere to corporate edicts. Ambient intelligence is a field of research that leverages pervasive sensor networks and AI to respond to and anticipate humans and machines. Nadella sees the future where a business logic will move from being code that is written to code that is actually learned from data, pretty interesting. He sees this autodidactic system if you will, as fundamental to tackling big problems like personalized medicine or even climate change. Third, he talked about empowered creators and communities everywhere. Nadella said, there'll be increasingly a balance between consumption and creation. His talking about an economic balance essentially he's predicting that creation will be democratized and his vision is to put tools in the hands of people to allow them to tip the scales toward knowledge workers, frontline employees, students, everyone, essentially creating content, applications, code, et cetera power to the people if you will. And underneath this vision is a new form of or emerging new forms of Silicon operating systems and entirely transformative digital experiences. Next was economic opportunity for the global workforce. So picking up on the accelerated themes of remote work that were catalyzed by COVID, Nadella emphasize that the future has to accommodate flexibility in how, when and where people work. He sees a new model of productivity emerging, not necessarily defined by corporate revenue per employee for example, but by the economic advantages that become accessible to everyone through better access to technology, collaboration tools, education, and healthy lifestyles, all enabled by this ubiquitous cloud. Finally, trust by design, Nadella said that ethical principles must govern the design, development and deployment of AI. The system he said must be secure by design with zero trust built in to protect business assets and personal privacy. So this was a big vision that Nadella put forth it, connects the dots between bits and atoms and sets up Microsoft to extend its reach well beyond office productivity tools and cloud infrastructure. He cited the Microsoft cloud as the underpinning of its future and specifically called out Teams, he mentioned 365, HoloLens 2 and the announcement of Microsoft Mesh, a new mixed reality platform. Nadella said Mesh will do for virtual reality what X-Box live did for gaming. Take the experience from single person to multi-person imagine holographic images with no screens, empowering advances in medicine, science, technology, and very importantly social interactions. Now, one of the things that we took away from his talk was this notion of Microsoft as a technology arm's dealer. No, we're not, Nadella avoided slamming the competition directly by name one statement that he made, stood out. He said, " No customer wants to be dependent on a provider that sells them technology on one end and competes with them on the other" And to us this was a direct shot at Amazon, Google and Apple. How so you ask? And what does it tell us? In his book "Seeing Digital" author David Moschella said, "that Silicon Valley broadly defined as a duel disruption agenda." What does that mean? Not only are large tech companies disrupting horizontal layers of the tech stack like compute, storage, networking, database, security, applications, and so forth. But they're also disrupting industries Amazon and media, grocery, logistics, for example. Google and Amazon on healthcare, Google and Apple on automobiles, all three in FinTech. And it's likely this is just the beginning but Nadella's posture suggests that Microsoft for now anyway, is content being mostly a horizontal technology provider, aka arms dealer. Now, there are some examples where you could argue that Microsoft sort of crosses the line maybe as a games developer or as a SAS competitor. Do you really want to, if you're a SAS player do you want to run your system on Azure and compete with Microsoft? Well, it depends if you're vertically oriented or maybe horizontal in their swim lanes, but anyway, these are more natural cohorts to technology than say for example, Amazon's retail business. So I thought that was something that was worth taking a look at. All right, let's take a quick look at how Microsoft compares to a couple of the great tech giants of the past several decades. Here's a financial snapshot of Microsoft compared to Oracle a highly profitable software company and IBM an industry legend. The first two things that jumped right out of Microsoft, size and it's growth rate. Microsoft is twice the revenue of IBM and nearly four extent of Oracle. And yet Microsoft is growing in the mid-teens compared to low single digits for Oracle and IBM continues to shrink so extensible you can grow. Microsoft's gross margin model has been pulled down by its hardware business but its operating margins are unbelievable. Meanwhile, the cash on its balance sheet is immense much larger than Oracles, which is very impressive. It's certainly dwarfs that of IBM, a company that had to take on a lot of debt to acquire Red Hat and has a balance sheet, that increasingly looks more like Dell's than it's historical self. And then on the last two rows Oracle and IBM, both owners of their own cloud have been lapped by Microsoft in terms of CapEx and research & development investment. Ironically, as we pointed out, IBM's R & D spend in 2007 the year after AWS launched the modern era of cloud was comparable to that of Microsoft. Let's now pivot it to some of the ETR survey data and see how Microsoft fares. We'll start by sharing a fundamental basis of the ETR methodology, that is the calculation of net score. Net score is a measure of spending momentum and here's how it's derived. This chart shows the components of Microsoft's net score. It comprises five parts and represents the percentage of customers within the ETR survey with specific spending profiles. The lime green is new adoptions, the forest green is increased spend of 6% or more for 2021 relative to 2020, the gray is flat spend, the pinkish slice is spend declining by more than 6% or 6% or more relative to last year and the bright red is replacing the platform. You subtract the reds from the greens and you get net score. As you can see, Microsoft's net score is 53% which is very high for $150 billion Company. Now let's put that in context and expand the scope here a little bit. This chart shows how Microsoft fares relative to its peers, the vertical axis shows net score against spending velocity and the horizontal axis shows market share. Market share measures pervasiveness in the survey. In the table insert, you can see the vendors they're sorted by net score and the shared end column is there as well, which represents the number of shared accounts in the dataset. On both accounts bigger is better. Now note the red dotted line, that's the 40% watermark which is my personal indicator of an elevated net score anything above that in our view is really solid. Microsoft is as usual off the charts strong well to the right with it's market presence and then an overall net score of 53% as we showed earlier. And then there's Azure, separate from Microsoft overall. We wanted to plot that specifically which of course it doesn't have the presence of Microsoft overall, no surprise, but it's still prominent on the x-axis and it has a net score approaching 70%, which is quite amazing. AWS not surprisingly is highly elevated with a presence that's even larger than Azure. And you can see Zoom, Salesforce and Google Cloud all above the 40% line. Google as we've reported is well off the pace in the horizontal axis and even though its net score is elevated, we would like to see it even higher, given its smaller size relative to AWS and Azure. You know, SAP always stands out because it's a large company and it's got a net score that's hovering just under 30%. It's not above that 40% line, but it's solid. And you can see IBM and Oracle now we're showing here IBM and Oracle overall so it's the whole kitchen sink comparable to Microsoft that turquoise dot, if you will. So you can see why those two are valued much lower Microsoft. The large base of its business that's declining is much, much larger than the pieces of their business that are growing. Now Oracle has some momentum, the Back Aaron's article on February 19th, which declared Oracle a cloud giant and it declared its stock a buy combined with some earnings upgrades including one today from Ramo Lyncho of Barclays has catapulted the stock to all time highs and a valuation over $200 billion. IBM is a different story as we've discussed frequently Arvind has a lot of work to do to get this national treasure back to what's prominent itself. Okay, let now unpack Microsoft's vast portfolio a bit and see where it's doing well and where it's making moves and maybe where it's struggling, some. This graphic shows Microsoft's net score across its entire product portfolio within the ETR taxonomy. And you can see it's pretty much killing it across the board. Microsoft plays in almost every sector in the ETR taxonomy and you can see the 40% red line and how many of its offerings are above that line. The yellow bar being the most recent survey and while there's quite a bit of gray, i.e. flat spend relative to 2020, we're talking about some very tough compares from last year. And yet there's still a huge chunk of the portfolio in the green meaning spending momentum is actually up from last year and some of Microsoft's most important sectors like Cloud and Teams and Analytics. Look only Skype and Microsoft Dynamics are lagging, so really nice story there in our view. Now let's come back and take a look at Microsoft's cloud business specifically as compared to its peers. So Satya basically said that Microsoft's future will build on top of its cloud and looking at this picture it's pretty encouraging for the company. This chart, again, shows net score or spending momentum inside specifically Fortune 500 customers and it's a key bellwether in the ETR dataset, and you can see Azure and Azure functions well above the 40% red line and extremely well positioned relative to AWS and GCP. Importantly, the yellow bar tells us that compared to previous surveys Microsoft's cloud business is actually gaining momentum in this very important sector. Now, other notable call-outs on this chart VMware Cloud, which, it's on-prem hybrid cloud and VMware Cloud on AWS, which is reportedly doing well but off from the momentum of its highs last spring. You can see Oracle jumped up indicating cloud momentum, but still well below the performance of the largest cloud players. The IBM Cloud appears to be a non-factor in the survey and as we previously stated, we'd like to see IBM recalibrate the financials for its cloud business and come up with a reporting framework that better represents the prevailing mental model of cloud computing. We think a cleaner number would allow IBM to build on the Red Hat momentum. I'm not sure what to make of the HPE boost, it looks significant, but in digging into the data it's only 17 data points, but look 17 within the Fortune 500 companies is not terrible. And HPE net score in that sector is more than double its overall cloud net score so that's positive we think. Okay, let's wrap by looking at how customers are thinking about multi-cloud adoption and really this data that we're about to show you simply asking customers about clouds they're using versus any type of long-term vision. So it's a good representation of what's happening today and what CIO is are thinking about in the near future particularly over the next 12 months. The survey asks customers to describe their cloud provider usage and strategy. You can see that only 14% of the survey respondents have exclusively a mono-cloud strategy, but now add in another 22% who were predominantly single cloud and you now have more than a third of the customer base gravitating toward mono-cloud. Another 14% say they're concentrating cloud providers more narrowly. Now on the flip side, you've got a big group, 29% that are moving toward multi-cloud and if you add in the additional 16% who say they are and will continue to be evenly spread, 45% of the survey is solidly headed in that direction so it's a mixed picture. What's the takeaway? Well, we think Andy Jassy is right when he says that while many customers use more than one cloud, they tend to have a primary provider and have something like a 70,30 or even 80,20 split between primary and secondary clouds. Now we think, however that this will change, but only to the extent that the vendor community is adding value on top of the existing hyperscale clouds. What we're saying and have been saying is that there is a real opportunity to create value on top of the cloud infrastructure that's being built out by AWS, Google and Microsoft. Instead of fearing cloud, the vendor community should be embracing it creating a layer on top, abstracting away the underlying complexities associated with cloud native, exploiting cloud native, and then building on top of that. Snowflake's data cloud vision is right on in my view, we can envision virtually every layer of the stack following suit. Even within database there are opportunities to identify more granular segments across clouds. For example, despite Snowflakes early multi-cloud lead you're seeing competitive firms like Teradata begin to architect a system across clouds that can query data warehouses from distributed locations, including on-prem as part of what they refer to as a data fabric, sounds kind of like Snowflakes global data mesh, or maybe better Zhamak Dehghani's data mesh. Yeah, sure but Teradata has capabilities that Snowflake doesn't for example, the ability to do complex joins and we can see plenty of market for both companies to differentiate. And why shouldn't similar vision extend from on-prem, across clouds to the edge for data protection, security, governance, hybrid compute ,analytics, federated applications, its a huge market that the hyperscale providers are likely too busy worrying about their own walled gardens to start building across on top of their competitors clouds. So Dell, HPE, VMware, Cisco, Palo Alto Fortunate, Zscaler or Cohesity, Veeam and hundreds of other tech companies, including by the way IBM and Oracle should be saying thank you to AWS, Google and Microsoft for spending all that money to build out great infrastructure on which they can build value, tap for future growth. And many of you will say, Hey, we're already doing this. Okay, I'll be watching to see the ratio of real versus slideware because generally today, in my opinion the denominator is much larger than the numerator. So when that ratio hits 1X we'll know it started to become real. Okay, that's it for today remember, all these episodes are available as podcasts wherever you listen so please subscribe. I publish weekly on wikibun.com and siliconangle.com. Please comment on my LinkedIn post or you can tweet me @DVellante or feel free to email me at David.Vellante@siliconangle.com. And don't forget to check out etr.plus for all the survey and data science action. This is Dave Vellante for the Cube Insights powered by ETR. Be well, thanks for watching and we'll see you next time. (relaxing music)

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(upbeat music) >> Announcer: From San Francisco, it's theCUBE. Covering Accenture Tech Vision 2020. Brought to you by Accenture. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're at the Accenture San Francisco Innovation Hub on the 33rd floor of the Sales Force Tower in downtown San Francisco. It's 2020, the year we know everything with the benefit of hindsight. And what better way to kick off the year than to have the Accenture Tech Vision reveal, which is happening later tonight, so we're really happy to have one of the authors who's really driving the whole thing. He's Michael Blitz, the managing director of the Accenture Tech Vision 2020, a very special edition. Michael, great to see you. >> Hey, thanks for having me. >> Absolutely, so you've been doing this for a while. I think we heard earlier, this thing's been going on for 20 years? >> It is. >> You've been involved for at least the last eight. >> Michael: I think a little bit more than that. >> More than that, so what's kind of the big theme before we get into some of the individual items? >> Yeah, so I mean, I think right now, what we're really talking about is that our real big theme is this: We the digital people. And it's that recognition that says that we've fundamentally changed. When you start looking at yourself and your lives, it's that you've gotten to a point where you're letting your cell phone track you. Your car knows where you are probably better than your spouse does. You're handing your key to Amazon and Walmart so they can deliver packages in your house. And more than that is that actually, we're trying to start to revolve our lives around this technology. I look at my own life, and we just sold our second car, specifically because we know that Uber and Lyft exist to fill that void. >> Right, well you don't have to look much further than phone numbers. How many people remember anybody's phone number anymore, right, 'cause you don't really have to. I think it's the 15th anniversary of Google Maps. >> Michael: Yep. >> This year, and to think of a world without Google Maps, without that kind of instant access to knowledge, is really hard to even fathom. But as you said, we're making trade-offs when we use all these services, and now, some of the costs of those things are being maybe more exposed? Maybe more cute or in your face? I don't know, what would you say? >> Yeah, I mean, I think what's happening now is that what we're realizing is that it's changed our relationship with companies. Is that suddenly we've actually brought them into our lives. And, on one hand, they're offering and have the ability to offer services that you could never really do before. But on the other hand is that, if I'm going to let somebody in my life, suddenly they don't have to just provide me value and this is useful, is that they actually, people are expecting them to retain their values, too. So, how they protect your data, what they're good for the community, for the environment, for society, whether it's sustainable or not. Is that suddenly, whereas people used to only care about what the product you're getting, now how it's built and how your company's being run is starting, it's just starting to become important, too. >> Right, well it's funny, 'cause you used to talk about kind of triple bottom line, shareholders, customers and your employees. And you talked about, really, this kind of fourth line, which is community and really being involved in the community. People care, suddenly you go to conferences where we spend a lot of time all the utensils are now compostable and the forks are compostable. And a lot of the individual packaging stuff is going away. So people do care. >> They do, and there's a fourth and a fifth. It says that your community cares, but your partners do, too. Is that you can't, I'm going to say, downgrade the idea that your B2B folks care is that suddenly, we're finding ourselves tied to these other companies, and not just in a supply chain, but from everything. And so, you're not in this alone in terms of how you're delivering these things. But now it's becoming a matter that says, Well, man, if my partners are going to get pummeled because they're not doing the right thing or they don't have that broad scope, that's going to reflect on me, too. And so, now you're suddenly in this interesting position where all of the things that we suspected were going to happen around digital connecting everybody is just starting to, and I think that's going to have a lot of positive effects. >> Yeah, so one of the things you talked about earlier today, in an earlier presentation was kind of the shift from kind of buyer and seller, seller and consumer, to provider and collaborator. Really kind of reflecting a very different kind of a relationship between the parties as opposed to this one-shot transactional relationship. >> No, and that's right, and it doesn't matter who you're talking about, is that, if you're hiring folks for skills that you're assuming that they're going to learn, that's going to be different in three years, in five years, you're essentially partnering with them in order to take all of you on a journey. When you start talking about governments, is that you're now partnering with regulators. You look at companies like Tesla, who are working on regulations for electric cars, they're working on regulations around battery technology. And you see that this go-it-alone approach isn't what you're doing. Rather, it's becoming much more holistic. >> Right, so we're in the innovation hub, and I think number five of the five is really about innovation today. >> Michael: It is. >> And you guys are driving innovation. And, rest in peace, Clayton Christensen passed away, Innovator's Dilemma, my all-time favorite book. But the thing I love about that book is that smart people making sound decisions based on business logic and taking care of existing customers will always miss discontinuous change. But you guys are really trying to help big companies be innovative. What are some of the things that they should be thinking about, besides, obviously, engaging with Mary and the team here at Innovation Hub? >> Yeah, no, and that's the really interesting thing is that when we talked about innovation, you know, five or even 10 years ago, you were talking about, just: How do I find a new product or a new service to bring to market? And now, that's the minimum stakes. Like, that's what everybody's doing. And I think what we're realizing as we're seeing tech become such a big part is that we all see how it's affecting the world. And a lot of times that things are good is that there's no reason why you wouldn't look at somebody like a Lyft or Uber and say that it's had a lot of positive effects. But from the same standpoint is that, you ask questions of: Is it good for public transit? It is good for city infrastructure? And those are hard questions to ask. And I think where we're really pushing now is that question that says: We've got an entire generation of not-tech companies, but every company that's about to get into this innovation game, and what we want them to do is to look at this not the way that the tech folks did, that says, here's one service or one technology, but rather, look at it holistically that says: How am I actually going to implement this, and what is the real effects that it's going to have on all of these different aspects? >> Right, Law of Unintended Consequences is always a good one. >> Michael: It is. >> And I remember hearing years ago of this concept of curb management. I'm like, Curb management, who ever thought of that? Well, drive up and down in Manhattan when they're delivering groceries or delivering Amazon packages and FedEx packages and UberEats and delivery dog food now. Where is that stuff being staged now that the warehouse has kind of shifted out into the public space? So, you never kind of really know where these things are going to end up. >> No, and I'm not saying that we're going to be able to predict all of it. I think, rather, it's that starting point that says that we're starting to see a big push that says that these things need to be factored and considered. And then, similarly, it's the, if you're working with them up-front, it becomes less of a fault, on a fight of whose fault it is at the end, and it becomes more of a collaboration that says, How much more can we do if we're working with our cities, if we're working with our employees, if we're working with our customers? >> Right, now another follow up, you guys've been talking about this for years, is every company is a tech company or a digital company, depending on how you want to spin that. But as you were talking about it earlier today, in doing so and in converting from products to service, and converting from an ongoing relationship to a one-time transaction, it's not only at that point of touch with a customer, but you've got to make a bunch of fundamental changes back in your own systems to support kind of this changing business model. >> Now, and that's right, and I think this is going to become the big challenge of the generation, is that we've gotten to a point where just using their existing models for how you interact with your customers or how you protect their data or who owns the data, all of these types of things, is that they were designed back when we were doing single applications, and they were loading up on your Windows PC. And where we're at now is that we're starting to ask questions that says, All right, in this new world, what do I have to fundamentally do differently? And sometimes that can be as simple as asking a question that says, you know, there's a consortium of pharma folks who have created a joint way for them to develop all of their search algorithms for new drugs. But they're using block chain, and so they're not actually sharing the data. So they do all the good things, but they're pushing that up. But fundamentally, that's a different way to think about it. You're now creating an entirely new infrastructure because what you're used to is just handing somebody the data, and what they do with the data afterwards is kind of their issue and not yours. And so now we're asking big, new questions to do it. >> Right, another big thing that keeps coming up over and over is trust. And again, we talked a little earlier. But I find this really ironic situation where people don't necessarily trust the companies in terms of the people running the companies and what they're going to do with their data, but they fundamentally trust the technology coming out of the gate and this expectation of: Of course it works, everything works on my mobile phone. But the two are related, but not equal. >> Michael: No, I mean, they're not, I mean, and it's really pushing this idea that says we've been looking at all these, I'm going to say scary headlines, of people not trusting companies for the last number of years, while at the same time, the adoption for the technology has been huge. So there's this dichotomy that's going on in people, where at one point, they like the tech. You know, I think the last stat I saw is that everybody spends up to six-and-a-half hours a day involved on the internet, in their technology. But from the same standpoint is that they worry about who's using it and how and what is going to be done. And I think where we're at is that interesting piece that says we're not worried about a tech lash. We don't think that people are going to stop using technology. Rather, we think it's really this tech clash that says they're not getting the value that they thought out of it, or they're seeing companies that may be using this technologies that don't share the same values that they do, and really, what we think this becomes, is the next opportunity for the next generations of service providers in order to fill that gap. >> Right, yeah, don't forget there was a Friendster and a MySpace before there was a Facebook. >> Yeah, there was. >> So, nothing lasts forever. So, last question before I let you go, it's a busy night. The first one was the I in experience, and I think kind of the user experience doesn't get enough light as to such a defining thing that does move the market if, again, I love to pick on Uber, but the Uber experience compared to walking outside on a rainy day in Manhattan and hoping to hail down a cab is fundamentally different, and I would argue, that it's that technology put together in this user experience that defined this kind of game-changing event, as opposed to it's a bunch of APIs stitching stuff together in the back. >> No, that's right, and I think where we're at right now is that we're about to see the next leap beyond that. Is that, most of the time when we look at the experiences that we're doing today, they're one way. Is that people assume that, Yeah, I have your data, I'm trying to customize. And whether it's an ad or a buying experience or whatever, but they're pushing it as this one-way street, and when we talk about putting the I back in experience, it's that question of the next step to really get people both more engaged as well as to, I'm going to say improve the experience itself, means that it's going to become a partnership. So you're actually going to start looking for input back and forth, and it's sometimes going to be as simple as saying that that ad that they're pushing out is for a product that I've already bought. Or, you know, maybe even just tell me how you knew that that's what I was looking for. But it's sometimes that little things, the back and forth, is how you take something from, what can be a mediocre experience, even potentially a negative one, and really turn it into something that people like. >> Yeah, well, Michael, I'll let you go. I know you got a busy night, we're going to present this. And really thankful to you and the team, and congratulations for coming up with something that's a little bit more provocative than, Cloud's going to be big, or Mobile's going to be big, or Edge is going to be big. So this is great material, and thanks for having us back. Look forward to tonight. >> No, happy to do it, and next year we'll probably do it again. >> [Jeff\ I don't know, we already know everything, it's 2020, what else is unknown? >> Everything's going to change. >> All right, thanks again. (upbeat music)