>> Narrator: Live from Las Vegas It's theCUBE covering Edge 2016. Brought to you by IBM. Now, here are your hosts Dave Vellante and Stu Miniman. >> Welcome back to Las Vegas, everybody. This is theCUBE the world-wide leader in live tech coverage. Leanne Kemp is here. She's the founder and CEO of Everledger. Leanne, good to see you. >> Hello, hello. What a great place to be. >> Good joke, Las Vegas again. Stu and I spend a lot of time here. Why did you start Everledger? >> Well, you know, some might say it's my mid-life crisis but the reality is I've been in emerging technology for 25 years. In the mid 90s, now I'm giving away my age I was in radio frequency identification so at the chip and inlay level supply chain tracking. A bit boring, really. >> Stu: No, RFID is cool. >> But in the last 10 years I've worked in jewelry and insurance. And that's given me an appreciation of the size of the problems that exist in the market. And couple that with a whole lot of nerd we have the ability to solve the problems that we're solving today. >> And describe that problem. It's a problem of provenance and transparency is that right? >> Provenance, fraud, document tampering. And when you mix all of those together you have a pretty potent formula for black market trade. And sadly, some of that trade is really running into terrorist-funded activities. So, it's a pretty big problem but I think now is a very real issue that's washing the front pages of every paper on a daily event. Diamonds, of course, is one of the vehicles for anti-money laundering. And if we can go and serve to reduce some of those problems then it's worthwhile getting out of bed for. >> Okay, so you're attacking the diamond value chain. Why that? 'Cuz you have a background in jewelry? Okay, how are you solving that problem though? Describe that in a little bit more detail. >> So, attacking's pretty aggressive. I think we're enhancing. So, we're bringing transparency in a once-opaque market. You know, we're enabling, with the use of technology to bring transparency into the market so that we can start to reduce some of the problems around fraud. When you really think about I mean most people look at us as a blockchain company. I liken us to an emerging technology company. We're using the very best of blockchain and smart contracts and machine vision as an enabler to be able to identify fraudulent-related activities and reduce them in marketplaces. And we're just starting with diamonds but it's really anything that is appreciable of value that criminals like to maybe get their grubby mitts on. >> When did you get this idea, like what timeframe? 2010, 2011, 2015? >> To be honest with you I think this has been a cocktail of experience that really has brought it together at the right time. So, you know, as I said my background has been really unfolding like a patchwork quilt. But when you really see the heightened anxiety that's going on in market now particularly around synthetic diamonds that are of gem-quality standards there's no greater time to be able to bring confidence back into the diamond industry and the consumer networks. >> I guess my question is that at what point did you say okay blockchain can be addressed to enhance this problem? Did you look at Bitcoin and say hmm, that's interesting? Not a currency, it's a technology that I can apply to all the problems. >> Yeah, I mean, you know, I'm a technologist so I really am quite bored with Sudoku so I would rather sort of look at what's going on in the tech space. And so when I really saw the emergency of Bitcoin I understood where that application could lie. But because I wasn't from a banking background it was patently obvious to me that I could decouple the currency from the ledger and really use the currency as a vehicle or a tokenization of assets. And the assets is diamonds, a girl's best friend. So why wouldn't you want to protect your assets? (chuckles) >> Fascinating 'cuz I think the first time I heard of, you know, blockchain and Bitcoin it was about being anonymous and therefore there were concerns that some of those unscrupulous people that are trying to benefit off of like diamonds would use, you know, this crypto currency. They don't have to talk to banks. They don't have to talk to governments. So you've almost flipped the usage of the technology to something to help the world a little bit more. >> That's right. I guess when you really think about it, you know the Bitcoin has often been assimilated with the anarchic world. And we're really bringing it to clean and transparency. So, I guess there is a juxtaposition there. But everything's upside down for me. I'm from Australia so it's perfectly normal. >> Go ahead, Stu. >> Yeah, just when you look at Blockchain and kind of the core technology you think we're really in the early days? What kind of usage do you see out beyond the ledgers? Are there other applications be it beyond the diamonds that you guys are looking at? >> Yeah, you know, so it's interesting. In the early 2000s I worked in WAP, you know? And I was so excited. I thought wow, this tech is really going to do something. So, you know, I'm part of Team Asserti in Australia and wrote out an application. And I felt like nearly six months came into the tech. And all of a sudden, I woke up and I went where the bloody hell did WAP go? It just disappeared. There was a very real danger that this technology was likely to face the same ill fate. And we often see in any emerging technology where there are heightened promises. They often end in disappointment. So, actually most of the decisions I've made in a start-up, and we're only 18 months old have really been counterintuitive. You know, when it's the time to put the pedal straight down I've often held back to really wait to see where the maturity of the technology was going to lie. And in any emerging technology and if you're a CEO of a start-up you have to be completely articulate about where the problem is that you're solving. But not only that you need to take the time to really distill the technology to its purest essence and then enable that to be the potent shot that goes out first and foremost. And so this is a nascent technology. And maybe, you know, it has the parentage of a multilingual PhD scientist but the reality is it's only just been born. We're not even nappy feddy. We're not even out of out of our nappies right now. So we need to give it the time to really grow. And we've chosen a niche market. It just so happens that it's a bloody big niche. >> So what took longer to figure out the problem or the solution? >> You know, I think you know, I don't know. That's a really good question, actually. I think the problem for me I understood quite early but I just didn't appreciate the size of the problem globally and the extension of that problem into other areas. And really I think it's taken some time for the technology to be understood. We've taken a view that we'd like to see ourselves as the custodian of the technology. We don't want to go to market too early. We want to be sure that whenever the message is delivered to market that it's something we've already delivered that we have built that the engineering effort has already been afforded. You know, small acorns grow into mighty oaks. And so for us, it's about ensuring that we take the time to really give the right fertilizer to the growth. >> And that's a 50 billion dollar problem you said this morning is that right? Is that there- >> Just in insurance. But we have banks as our clients too so, you know, we're shooting hoops. >> So you're saying it's a multiplier of that 50 billion? >> Leanne: Of course. >> Yeah, big multiplier. >> I mean counterfeit good if you extend it into luxury goods it's 1.7 trillion dollars. >> And you talked about the sort of value chain of rough cut, 15 billion and you maybe triple that when it gets polished almost 50 billion and then another one and a half X at retail. Where are the holes in that value chain, everywhere? I mean are you seeing fraud occur throughout that value chain or- >> Effectively. You know, we don't have you know, visibility of complete provenance through the supply chain. And in fact, it's not just limited to the diamond industry. I mean I guess the diamond industry there's the allure of luxury. You know, there's the backdrop of affluence. And then, of course, there's the atrocity of what goes on in terms of or what used to go on so prolifically in blood diamonds. You know, effectively the industry isn't as burdened with technology as say financial services. It doesn't have the legacy of 50 years of technology that it needs to unwind. So, when you really consider what's going on in the market today to bring emerging technology into this space not limited to blockchain even enabling new technologies like high-definition photographs and machine vision our marketplace has the ability to consume that technology quite rapidly. And when you think about the problems in our market or the restrictions in our market it's really a lightning rod moment for us where we've just been fortunate enough to be able to build out a solid engineering rod to be able to capture that lightning bolt of problem. >> Dave: Mm-hmm. >> We've had a lot of discussions with IBM executives this week and they feel security is one of the things that IBM does really well. Talk a little bit about your relationship with IBM what IBM does well what they're good at partnering with. How is it to work with IBM? >> Dave: What they could do better. >> Yeah. >> Absolutely (chuckles). We, in the very first 12 months of Everledger we managed to onboard, you know, a million diamonds. And most people were applauding the efforts of our engineering team. And we certainly applauded ourselves. But Christmas was a very lonely path for me because I started to become shivered by the thought of what would this mean if I went from a million to 10 million to 15 million and then into rough being able to track 320 million carats of rough diamonds across 80 countries around the world. So, when you're a start-up and you're faced with some of the largest organizations and governments around the world let's face it, the industry's 130 years old. You want to be able to look towards a technology innovator like IBM that has been around and reinvented itself over a trusted 100 years. And that transactional trust is at the very core of this fabric. So, some of the things that you look at in terms of a start-up may be actually too isolated. A lot of technology companies that are in the blockchain space are just looking at the blockchain fabric. But for me, it was patently obvious we needed to stretch further. We needed to realize that we have to deliver this into a cloud solution. We have to deliver this technology in such a form that has to be secured. And the security needs to really be from the ground up at the root source right the way through to the front end. And there's no other partner that's actually doing that. There are other service providers in this space that shall not be mentioned. But they're, of course, taking whatever nascent technology is being built and putting it into the cloud. IBM has really taken the time to sew together the right security fabric. >> And that's about scale for you, right? I mean you wouldn't be able to scale without it. >> I sleep at night knowing that we have IBM. Like as a CEO, I sleep at night. >> My understanding, there's container technology that you're using in here. Most people think of containers as security's one of the holes there so, you know, how do you feel with the security of containers today? And maybe you can share a little bit about you know, what IBM's doing specifically for that. >> Yeah, I mean the container services team that we've been working with and today I had the absolute privilege it was a diary note moment for me to present on stage with Donna. You know, her background in security has afforded us the ability to really deliver this quite quickly. The work that they have been doing is recognized not only and I touched on the surface of the three markets that of real concern or focus for us is fraud and theft and cyber. And when you consider the container services and the security team that's wrapped this around I really think that actually one of the silent winners in this is the reduction in cyber crime. And maybe that hasn't been focused on too largely. And the 50 billion dollars that I was talking about was really around document tampering and, you know, the over-inflation of insurance claims. When you really think about it it's actually cyber crime that I think we could actually truly solve as part of the solution itself. >> So explain again, Leanne, how does it work? So each diamond has a unique identifies it's got a fingerprint on there. How does it get on there? >> So there are existing processes in industry. There are two parts to the market first is rough diamonds and the second is polished diamonds. And as diamonds are crossing borders as a part of international trade they're often inspected by gemologists. Those that, of course, have received licenses in the skill of identifying diamonds. But that's all- >> Dave: But that's a spot inspection, is that right or- >> Correct. >> Dave: Yeah. >> But there's also actual machinery. So there are certain types of science that have been applied and have been applied for a number of years. And one of the challenges that we faced with ourselves is to IoT-enable the diamond pipeline. So, some of these machines have been in existence. They're highly calibrated and they have precision but that data is often blackboxed. It's not, indeed, ledgered or stored for public view or even inter-office view. And so one of the tricks that we've enabled is the ability to take all of those data points 40 meta data points as well as the reputation or the expert opinion and lay that data into the blockchain. So we're layering really a reputation score not only of the person, the machine but also the diamond and the validity of that diamond. And that can only come over time with large aggregated data sets. >> Okay, and that is your providence. You said the world's provenance is locked in paper. So now you're locking it into- >> Leanne: You're listening >> The blockchain. Of course (chuckles). I knew we had to talk to you. We better listen. Okay, so all right. And then can you explain the banking crisis the liquidity crisis in the diamond business? >> Leanne: Yeah, absolutely. >> What's that stem from? I didn't quite understand. >> It's really affecting the middle part of the pipeline. We have very large mining companies and of course quite substantial retailers but it's the middle part of the pipeline that's really being caused in terms of a squeeze. And so they are the diamond cutters and polishers really generational businesses that have perfected the art and the skill of cutting diamonds. It's the middle part of the pipeline that's really being affected at the moment. And as I mentioned there are two brave Western banks that remain supporting industry. The largest, which has been really in industry for quite some time is ABN AMRO. And proudly, they still remain. And Barclay's Bank. But we've seen an announcement more recently with Standard pulling back out of the industry for a lack of transparency and a burden on their balance sheet. This, of course, has come from Basel III and some of the regulations that's been pushed down from them. And if we're able to take certification and extend transparency but also bring certification to the next level to enable a collateral management system to be built so banks can take the security on the underlying asset rather than just take a balance sheet position it will lift the burden on their balance sheet. It will give them security of the diamond. And let's face it, diamonds are worth something. And as I said when you start to understand the true effect of rough to polished to track the diamond through its lifecycle and give security is something that banks are open-minded about. >> Yes, okay. So it's not a chicken and egg problem it's a transparency begets liquidity is that right? That's the premise anyway >> Yeah >> Dave: That you're testing basically making that bet with your company. We don't have much time but I just wanted to ask you about your company. You're an entrepreneur. You started the company, you said 18 months ago. Funding, VC, you know, give us the lowdown. >> Sure, sure, sure. I mean I came into London in October of 2014. And I was desperate to talk to insurers. And so one of the largest insurers in the London market is Aviva. And they had a hackathon at Google so I thought hey, this would be all right. I'm just going to Trojan Horse the event and see if I can have a talk to the CFO and COO. So I went there. They opened up some APIs. And because I, of course, had a technical background I thought those APIs are hopeless there's not much I can do with that. But if you want to solve some of the problems here this is what you can do. You can take diamonds, take certification and put it on the blockchain as a way to reduce fraud. And at that hackathon I was awarded the innovation prize. But the managing director of Barclay's Techstars was one of the judges and came to me and invited me to join them as part of their accelerator in London which began in March 2015. And, of course, I thought this is crazy. Why would I want to do that? Why would I want to be in London with a bank? It doesn't really make too much sense. And let's face it, I mean Australia is a much nicer country to spend your holidays in rather than London. But in any event, I returned and participated as part of the Barclay's accelerator and I've been supported through the process of the acceleration. But Barclay's is both a bank and an insurance company in Africa so the penny dropped and we put our head down. We wore some letters off the keyboard and Everledger was born. And away we go. >> And so Barclay's funded, in part the company or- >> Barclay's and the Techstars accelerator program have a seed funding event which is a part of the acceleration program for start-ups if you're chosen. And we were fortunate enough to be chosen. And since that time we've been we haven't disclosed who one of our backers are. >> Dave: Okay. >> But we will, in time. And so we've been funded by a selected name in industry. And we're actually just about to go into our Series A so we're looking towards that in the next number of months. >> Dave: You're not even in Series A yet? So you've gotten this far without even getting to your Series A? >> Leanne: Yeah. >> 980 thousand? >> Well, we have revenue, so- >> Dave: Yeah. >> This is my last start-up. I had to go through an intervention with my family to enable me to be here. >> Dave: This is my last So this is it. >> Dave: We've heard that before. >> I promise. I know, it's true, it's true. >> Opportunities beyond diamonds or is that getting too ahead of our speech here? >> Diamonds, watches, art, fine wine you know, and I'm completely empowered by how do we bring what the diamond industry did so well in the reduction of blood diamonds and bring ethical trade really to the forefront of the mind of the consumer and also the mind of the financial services market. So, you know, for me it's really around that part of the world. If that nexus point comes together then I'll keep getting out of bed for it. >> Awesome. Great story. Impressive entrepreneur. Thanks for coming on theCUBE. >> Leanne: Yes, thank you. >> London's not so bad (chuckles). Comment? >> London's probably watching. (Dave and Leanne laugh) >> All right, thanks again. Keep it right there, buddy. Stu and I will be back with our next guest. We're live from IBM Edge in Las Vegas. We'll be right back. (low tempo music)

>>Live from Las Vegas, Nevada. Extracting the signal from the noise. It's the queue covering IBM edge 2015 brought to you by IBM. >>Hello everyone. Welcome to the cube. I'm John furrier. We are here in Las Vegas for a special presentation inside the cube. A special announcement. We have mayor AC Borden, mayor of Memphis and Jen Crozer who's the vice president at IBM alliances and Alliance. Welcome to the cube. So mayor Memphis, I'll see renounced city, great culture. Um, smarter cities is a big thing right now. So talk about why Memphis, why IBM, why are you here? What's the big announcement? What's happening in Memphis? >>Well, it's a great day for Memphis in addition to the Grizzlies had slipped that in there, but uh, one, uh, of, of, of just the handful of cities that are receiving what are known as IBM smart cities challenge grants, we pick a challenge. We have, uh, they help us come up with a solution to it. And it's not some abstract idea. In our case, it's how do we weed out the non-emergency calls from the true emergency calls and our EMS service? 120,000, over 120,000 calls a year, about 25,000 of them are not truly emergency calls. So what that does is it takes valuable time and resources away from those true emergency, a true emergency calls. It should be attended to on a priority basis. >>So I know that you have a Twitter handle and you've got a lot of followers. Is the tech culture in Memphis emerging describes the folks that they, what's it like in Memphis from a tech perspective? Are there people who have moved over or there's rabbit. I know there's a lot of folks in town really talk about the tech community. >>Even in my generation, I'm on there just to do a little quality checking. Also on a double analysis. I'm still in this from Zinn. Uh, we're one of the three cities that will received the, uh, Twitter grants, which will allow us to access us and get that data there and use it as we make decisions. So that's really going to be unique for Memphis. So yes, Memphis is a up to date. >>Jen, I gotta ask you because one of the things that's near and dear to our heart in the cube is technology for the advancement of better signal, not noise, whether that's society, education, the Twitter data, and we've talked to in heat you saw about this is that it's the signal of the humans. Um, and this notion of smarter cities is bringing technology to impact the human lives, not just making people get an iWatch or what are, there's some real benefits. Talk about the grants, talk about what IBM is doing because this is real important stuff. I mean, smarter planets to marketing slogan, but the end of the day technology can help people and talk about how that's part of the grant and, and why Memphis and what are these guys doing that's unique. That could be a great case study for others. We started building a smarter planet at one of the things we had to think about was what was the acupressure >>points that would have the biggest ripple effects. And it's cities, right? More than half of the world's population lives in cities. And that's growing by a multiplier every day. And so that's where we wanted to start and we've been really gratified when we started smarter cities challenge, which is a pro bono program. Give us your toughest problem. We will send you a team of six IBM executives for three weeks to help you solve it for free. We've had over 600 mayors apply and we've delivered more than 115 teens >>and in Memphis. I got to ask the question about how you look at the, the governing process now with mobile computing, you can hear everything. They're talking back in real time and it might not be as organized. Certainly tweeting all over the place and kind of getting that data is really key. What's your vision >>that that's the key. We know Memphis, we know what information we have with that. We have what in the world do you do with it? So what better partner than IBM? We know Memphis, but IBM knows the world. We're not the only one who's faced this challenge. So with this team of experts, the IBM professionals who will be owned the ground there, they will then say, here's what you have. Here's the best way to use it. Here's what they did in Rome. Here's what they did in Berlin, London, New York or wherever. So the key is not how much information do you have but what in the world can you do with it in real day to day solutions to those everyday problems. And let me point this out. This is much more than just technology with the process we're going to employ in Memphis using nurses perhaps as dispatchers so that they can ask a few more questions when the call comes in are perhaps helping us set up a system in which nurses will go to the homes of the individuals who we call frequent flyers who often call when, it's not true any emergency but this is because life is on the line here and you really have to have the ability to analyze in real time and apply the right solution. >>And this is why IBM's expertise on a worldwide basis is so critical. >>We always talk about, we always talk about two aspects of real time near real time, which is people get today it's close enough, but when you're in a self driving car maybe or an emergency situation, you want real time. So that's really the key here. Yeah, >>that's the gay real time information being employed in a real real life situation. And that's what any emergency call that's. >>So I've got to get under the hood a little bit cause we like to go a little bit into the engine of, of the, of the local environment. I mean it, people who know life today, they got their cell phones, they think it's easy to call nine one one. It's not that easy. You have these old systems and the cell towers are connected to the municipal networks and you've got a lot of volume of calls coming in. That's a challenge for the local, the technology team and with this new system that's going to clear it up. So, so talk how you guys go from this clogged, you know, traffic calls to really segmenting the emergencies from the nonverbal. >>Again, that's another critical point. We're confident this is going to work and it will somewhat declaw if that's a word unclog because I experienced just without the grant shows us that we could weed out so many of the other calls. They will not be coming in to your nine one one. So that's, that's a big, big help right there is to make sure if we could weed out 25,000 calls, which is what we had last year. We're not truly emergency calls, you wouldn't speak in terms of a Claude nine one one system. >>I was talking to a friend, they're like, give me an example of some of this clog networks that I go, well imagine your phone going off a million times a night. The notifications, cause we're in a notification economy that you have to kind of weed through that. So how are you guys using the data? What's the technology? Can you give some specifics to what's being implemented, the team and how the local resources inter interact with IBM? >>Well I think, you know, the mayor's called out this one source of data that he's getting and mayors we know are getting multiple strings. So we have our intelligent operations center that IBM uses to create dashboards for mayors to see real time data about several different industries or sources or areas that are important to them. But I think that your point about the humans talking is a really critical one. And I want to come back to that because it's easy for us to fixate on the technology. And I think one of the things we've seen in this program is the technology enabling city leaders to hear their constituents in new ways, what they're saying and what they're not saying. And also for them to communicate back with them and close the loop on feedback as policies and programs are inactive. And the thing about the presence of IBM is kind of like a good housekeeping. It will open up Memphis to resources from other national groups. As a matter of fact, we're already using funds from another entity to set up our dashboards for performance in all areas, including of the nine one one calls. So IBM is like this huge magnet. But once folks see, Hey, IBM is in there, others who come in and say, we're going to help Memphis as it develops this system. So >>may I have to ask you a question. If as automation and technology helps abstract away a lot of the manual clogged data and understanding the signal from the noise, what's relevant, what's real time, you have a lot more contextual visibility into your environment and the people. How would you envision the future organization of the government and education and, and uh, police, fire, et cetera, working together? What's the preferred future in your mind's eye? As technology rolls out? The preferred future will be >>the, that when we come up with an innovation like this will be a non event. It would just be, it ought to be the order of the day. Uh, government sometimes kind of lags behind. No, we want to get to the point where we're leading. Uh, quite frankly, my vision is that this soon will become a non event. It will become the order of the day. Uh, humans are citizens will not be afraid of, Oh, I bet not call. I'm going to get a computer on the end of the line or they got a gadget down. They're just going to try to innovate me and see if I'm going to say it would be the order of the day. That's, that's what we're working forward and what we are emphasizing here is not what we are taking away but what we are bringing in. Additionally for this technology, we will actually be able to have a good diagnosis, a good case record built on what we call the frequent flyers. We know the people who call every two weeks, but they will feel so much better when two days before they usually call. A nurse will show up and say, came to check on you and that's what's coming out of this will be customers. This will be the new norm >>because is work. This is already that they're happy people, happy customers, happy voters. Hey, you nailed it. Barack Obama had put in for the first time a data scientist on the white house, DJ Patel, a former entrepreneur, former venture capitalist. Data science is a big deal. Now. Um, are you guys seeing that role coming into the local presence as well? Yes, >>and it's so critical to government and the private sector. If you come up with an item that's not reducing the profit margin, you just shut it down. We can't do that in government that week. Every service we provide, we're locked into that. I cannot say, well the police department where we are, we're not breaking even on that. Let's just shut that down. We won't run three shifts. We'll cut out that third shift. So we have a mandate. It's an imperative. What we're doing here is not an option. This is an absolutely essential. >>So you're excited for the grant. What's next after the announcement? What do you guys be doing together? We've got 16 cities around the world who will be getting these teams. So it's time to schedule them and get started and have the grant now, how many mayors applied and what was the numbers again? Over the life of the program, over 600 mayors have applied for this. This year it was just over a hundred and we are sending teams to 16 cities this year. Well, you guys can get that technology go and get some more music pumping through the world. That's a great place and I'll see the technology, help them. This is a citizen. Thanks for, for sharing the great story. Congratulations, mr mayor. Thanks for joining us on the cube. We right back here in Las Vegas. You watching the cube? I'm John. We'll be right back.

>>Yeah, >>from the Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Welcome back, everybody. This is Dave Vellante of the Cube, and you're watching our continuous coverage of the IBM think Digital 2020 experience. And we're really pleased to have Rob High here. He's not only an IBM fellow bodies. He runs the vice president CTO of the IBM Edge Computing Initiative. Rob, thanks so much for coming on the Cube. Good to see you. Which we're face to face, but yeah, that time to be safe and healthy, I guess. And did so edge obviously hot topic. Everybody has this sort of point of view would be interested in how IBM looks at edge. You define it and what your thoughts are on. It's evolution. >>Yeah, well, you know, there's ah really kind of two fairly distinct ways of thinking about the edge of the telcos. Our, ah, you know, they're creating edge capabilities in their own network facilities. We call that the network edge on the other side of the edge they that I think matters a lot to our enterprise businesses is there's remote on premise locations where they actually perform the work that they do, where the majority of people are, where the data that actually gets created is first formed and where the actions that they need to operate on are being taken. That is a lot of interest, because if we can move work workloads, Iot workloads to where that data is being created, where those actions are being taken Uh, not only can we dramatically reduce the late and see to those decisions, uh, but we can also ensure continuous operations and the failed in the presence of perhaps network failures. We can manage the growth of increasing demand for network bandwidth as Maura born data gets created and we can optimize the efficiency of both the business operations as well as the I t operations before that. So for us edge computing at the end of the day is about movie work where the data and the actions are being taken >>well, so this work from home, you know, gives a result of this pandemic is kind of creating a new stresses on networks and people are putting, you know, pouring money actually into beefing up that infrastructure is sort of an extension of what we used to think about edge. But I wonder if you could talk about some of the industries and the use cases that you guys we are seeing and notwithstanding, though assay that >>work from home pivot. Yeah, absolutely. So I mean, look, we have seen ah, the need for placing workloads close to where it is being created and where actions have been picking in virtually every industry, the ones that are probably easier for us to think about and more common in terms of our mindset. Our is manufacturing. If you think about all the things that go on in a factory floor that need to be able to perform analytic in, uh, in the equipment and the processes that are performing in the affection for, If you think, for example, production quality. Uh, you know, if you've got a machine that's putting out parts and maybe it's welding seams on metal boxes, uh, you know, you want to be able to look at the quality of that seem at the moment that is being performed, so that if there are any problems, you can remediate that immediately rather than having that box move on down the line and find that you know the quality issues they were created earlier on now have exacerbated in other ways. Um, you know, so quality, productive quality. Ah, inspection production optimization in our world of Covic Cover 19 and worker safety and getting workers back to work and ensuring that you know people wearing the masks and are exercising social distancing. This is on the factory floor. Worker Insight is another major use case that we're seeing surface of lake with a lot of interest in using whether that's infrared cameras or Bluetooth beacons or infrared cameras. Any variety of devices that could be employed in the work area to help ensure that factories are operating efficiently, that workers are safe. Ah, and whether that's in a factor situation or even in an office situation or e a r in a warehouse or distribution center. And all these scenarios the the utility, the edge computing to bring to those use cases is tremendous. >>And a lot of these devices are unattended or infrequently attended. I always use the windmill example. Um, you know, you don't want to have to do a truck roll to figure out you know what the dynamics are going on, that at the windmill s, so I can instrument that. But what about the management of those devices you know from an autonomous standpoint? And and are you? What are you doing? Or are you doing anything in the autonomous managed space? >>Yeah. In fact, that's really kind of key here, because when you think about the scale, the diversity and the dynamic dynamism of equipment in these environments And as you point out, Dave, you know the lack of I t resource lack of skills on the factory floor, or even in the retail store or hotel or distribution center or any of these environments. The situation is very similar. You can't simply manage getting the right workloads to the right place at the right time. In sort of the traditional approach is, you have to really think about another autonomous approach to management and, you know, let the system the side for you. What software needs to be placed out there? Which software to put their If it's an analytic algorithm, what models to be associated with that software and getting to the right place at the right place at the right Time is a key Part of what we do in this thing that we call IBM Edge application manager is that product that we're really kind of bringing to market right now in the context of edge computing that facilitates this idea of autonomous management. >>You know, I wonder if you could comment Robb on just sort of the approach that you're taking with regard to providing products and services. I mean, we've seen a lot of, uh, situations where people are just essentially packing, packaging traditional, you know, compute and storage devices and sort of throwing it over the fence at the edge. Uh, and saying, Hey, here's our edge computing solution and another saying there's not a place for that. Maybe that will help flatten the network and, you know, provide Ah, gateway for storing on maybe processing information. But it seems to us that that that a bottoms up approach is going to be more appropriate. In other words, you've got engineers, you know who really understand operations, technology, people, maybe a new breed of developers emerging. How do you see the evolution you know of products and services and architectures at >>the edge? Yeah, so First of all, let me say IBM is taking a really pretty broad approach to edge computing we have. What I just described is IBM Edge Application Manager, which is the if you will the platform or the infrastructure on which we can manage the appointment of workloads out to the edge. But then add to that we do have a whole variety of edge and Nevil enabled applications that are being created are global service of practices and our AI applications business all are creating, um, variations of their product specific to address and exploit edge computing and to bring that advantage to the business. And of course, then we also have global services Consulting, which is a set of skilled resource, is who know we understand the transformations that business need to go through when they went, take advantage of edge computing and how to think about that in the context of both their journey to the cloud as well as now in this case, the edge. But also then how to go about implementing and delivering that, uh and then firmly further managing that now you know, coupled out then with at the end of the day you're also going to need the equipment, the devices, whether that is an intelligent automobile or other vehicle, whether that is an appellate, a robot or a camera, Um, or if those things are not intelligent. But you want to bring intelligence to them that how you augment that with servers and other forms of cluster computing that resides resident with the device. All of those are going to require participation from a very broad ecosystem. So we've been working with partners of whether that is vendors who create hardware and enabling that hardware in certifying that hardware to work with our management infrastructure or whether those are people who bring higher order services to the table that provide support for, let's, say, data cashing and facilitating the creation of applications, or whether those are device manufacturers that are embedding compute in their device equipment. All of that is part of our partnership ecosystem, Um, and then finally, you know, I need to emphasize that, you know, the world that we operate in is so vast and so large. There are so many edge devices in the marketplace, and that's growing so rapidly, and so many participants in that likewise There are a lot of other contributors to this ecosystem that we call edge computing. And so for all of those reasons, we have grounded IBM education manager on open source. We created an open source project called Open Rise, and we've been developing that, actually now, for about 4.5 years just recently, the Linux Foundation has adopted Stage one adoption of Open arising as part of its Lennox Foundation edge LF edge, uh, Reg X Foundry project. And so we think this is key to building out, Um, a ecosystem of partners who want to both contribute as well consumed value and create ecosystems around this common idea of how we manage the edge. >>Yeah, I'm glad you brought up the ecosystem, and it's too big for any one company toe to go it alone. But I want to tap your brain on just sort of architectures. And there's so many diverse use cases, you know, we don't necessarily see one uber architecture emerging, but there are some characteristics that we think are important at the edge you mentioned sort of real time or near real time. In many cases, it has to be real time you think about autonomous vehicles? Um, yeah. A lot of the data today is analog, and maybe it doesn't have to be digitized, but much of it will be, um, it's not all gonna be sent back to the cloud. It may not all have to be persisted. So we've envisioned this sort of purpose built, you know, architecture for certain use cases that can support real time. That maybe have, you know, arm based processors. Ah, or other alternative processors there that can do real time analytics at the edge and maybe sending portions of the data back. How do you see the architectures evolving from a technologist? >>Well, so certainly one of the things that we see at the edge is a tremendous premium being placed on things like energy consumption. So architectures they're able to operate efficiently with less power is ah is certainly an advantage to any of those architectures that are being brought aboard. Um, clearly, you know x 86 is a dominant architecture in any information technology endeavor. More specifically at the edge. We're seeing the emergence of lot of arm based architecture chips out there. In fact, I would guess that the majority of the edge devices today are not being created with, um, arm architectures, but it's the you know, but some of this is about the underlying architecture of the compute. But also then the augmentation of that compute the the compute Thea the CP use with other types of processing units. Whether those GPS, of course, we're seeing, you know, a number of deep use being created that are designed to be low power consuming, um, and have a tremendous amount of utility at the edge. There are alternate processing units, architectures that have been designed specifically for AI model based analytics. Uh, things like TP use and infuse and and, uh, and set around, which are very purpose built for certain kinds of intellect. And we think that those are starting to surface and become increasingly important. And then on the flip side of this is both the memory storage in network architectures which are sort of exotically different. But at least in terms of capacity, um have quite variability. Specifically, five G, though, is emerging and five g. While it's not necessarily the same computing, there is a lot of symbolism between edge and five G and the kinds of use cases that five G envisions are very similar to those that we've been talking about in the edge world as well. >>Rob, I want to ask you about sort of this notion of program ability at the edge. I mean, we've seen the success of infrastructure as code. Um, how do you see program ability occurring at the edge in terms of fostering innovation and maybe new developer bottles or maybe existing developer models at the edge? Yeah, >>we found a lot of utility in sort of leveraging what we now think of as cloud computing or cloud computing models. Uh, you know, the idea of continue ization extends itself very easily into the edge. Whether that is running a container in a docker runtime, let's say on an edge device which is, you know, resource constrained and purpose built and needs to focus on sort of a very small footprint or even edge clusters edge servers where we might be running a cluster of containers using our kubernetes platform called open shift. Um, you know the course of practices of continuous integration, continuous delivery. What we write a Otherwise think of his Dev ops. Ah, and, of course, the benefits they continue. Realization brings to the idea of component architectures. Three. Idea of loose coupling. The separation of concerns, the ability to mix and match different service implementations to be opposed. Your application are all ideas that were matured in the cloud world but have a lot of utility in the edge world. Now we actually call it edge native programming. But you can think of that as being mostly cloud native programming, with a further extension that there are certain things you have to be aware of what you're building for the edge. You have to recognize that resource is air limited. Unlike the cloud where we have this notion of infinite resource, you don't have that at the edge. Find and constrained resources. Be worried about, you know, Layton sees and the fact that there is a network that separates the different services and that network can be and reliable. It can introduce his own forms of Layton sees it, maybe bandwidth constrained and those air issues that you now have to factor into your thinking as you build out the logic of your application components. But I think by building on the cloud native programming about me paradigm. You know, we get to exercise sort of all of the skills that have been developing and maturing in the cloud world. Now, for the edge >>that makes sense. My last question is around security. I mean, I've often sort of tongue in cheek said, you know, building a moat around the castle doesn't work anymore. The queen i e. The data has left the castle. She's everywhere. So what about the security model? I mean, I feel like the edge is moving so fast you feel confident or what gives you confidence >>that we can secure the edge. You know, the edges does introduce some very interesting and challenging concerns with respect to security because, frankly, the compute is out there in the wild. You know, you've got computers in the store you've got, you know, people walking around the kiosks you have in the manufacturing site, you know, workers that are, you know, in the midst of all of this compute capability and so the attack surface is substantially bigger. And that's been a big focus for us, is how to the only way validate in 30 of the software that was But it also takes advantage of one of the key characters with edge computing to bring to the table, which is, if you think about it. You know, when you've got personal and private information being entered into quote system, the more often you move that personal private data around, and certainly the more that you move it to a central location and aggregate that with other data, the more of a target becomes more vulnerable, exposed that data becomes and by using edge computing, which moves the workloads out to the edge where that did has been created in some sense, you can process on it there and then move it back. They need central location, you don't have to aggregate it. And that actually in itself is a counterbalance of all of the other issues that we also describe about security by essentially not moving the personal privacy and in protecting by keeping it exactly where it began. >>You know, Rob, this is an exciting topic. Is a huge opportunity for IBM and Ginny in and talk about the trillion dollar opportunity and hybrid cloud and the Edge is a multi $1,000,000,000 opportunity for IBM and, uh So you just got to go get her done. But I really appreciate you coming on the Cube and sharing your insights. That awesome topic in the best interest of the David. Yeah. Thank you. Thank you for the thank you. Stay safe and thank you for watching everybody. This is Dave Volante for the Cube. This is our coverage of IBM. Think 2020 the digital. Think >>we'll be right back after this short break? >>Yeah, yeah, yeah, yeah.

>> Announcer: Live from Las Vegas! It's theCUBE. Covering Edge 2016. Brought to you by IBM. Here's your host, Dave Vellante. >> Welcome back to IBM Edge everybody. This is theCUBE's fifth year covering IBM Edge. We were at the inaugural Edge five years ago in Orlando. Marc Linster is here and he's joined by Lenley Hensarling. Marc is the Senior Vice President of Product Development. And Lenley is the Senior Vice President of Product Management and Strategy at EDB, Enterprise Database. Gentlemen, welcome to theCUBE. Thanks for coming on. >> Male Voice: Thank you. >> Okay, who wants to start. Enterprise Database, tell us about the company and what you guys are all about. >> Well the company has been around for little over 10 years now. And our job is really to give companies the ability to use Postgres as the platform for their digital business. So think about this, Postgres is a great open source database. Great capabilities for transactional management of data. But also multi-model data management. So think about standard SQL data but think also about document oriented, think about key-value pair. Think about GIS. So a great capability that is very, very robust. Has been around for quite a few years. And is really ready to allow companies to build on them for the new digital business but also to migrate off their existing commercial databases that are too expensive. >> What's the history of Postgres? Can you sort of educate me on that? >> Sort of the same roots back with System R, where DB2 came from, Oracle came from. So Berkeley, that's where the whole thing started out. Postgres is really the successor to Ingres. >> Dave: Umhmm. >> And then it turned into PostgreSQL. And it has been licensed under open source license, the Postgres license since 1996. And it's a very, very vibrant open source community that has been driving forward for many years now. And our view is the best available relational and multi-model database today. >> It's the mainspring of relational database management systems essentially >> Marc: Yeah. >> is what you're saying. And Lindley, from a product standpoint, how do you productize that, open source. >> Open source really, companies that have a distribution of open source for database and operating system, whatever the open source company most people are acquainted with, is Red Hat and Linux right. And so, we do the same thing that they do but for Postgres database. We take the distribution, we add testing, we add some other functionality around it so you can run Postgres responsively as Marc likes to say. So high availability, capability, fail-over management, replication, a backup solution. And instead of leaving it as an exercise for a customer, who wants to use open source, we test all this together. And then we validate it and we give them a complete package with documentation and services that they can access to help them be successful it. >> So if Michael Stonebraker were sitting right here, I say Michael, what do you think about Postgres? I'd say I had to start Vertica because we needed a new way. Yet, sort of PostgreSQL, is the killer remains the killer platform in the industry, doesn't it? >> Male Voice: Umhmm. Why is that? It's interesting when you talk to guys like Stonebraker, it's sort of dogma almost. But yet, customers, talk with their wallet. >> And it is, >> He did a very, very nice job of architecting it. It is a database that is extensible. The reason we add the first JSONB or document oriented implementation in the relational database space is because it was designed to make it easy to add new capabilities, new datatypes, new indexes, et cetera, into the same transactional model. That's why we have JSONB. That's why we have PostGIS. That's why we have key-value pair. So it was really well architected. And when you think about who else, not just Vertica has taken this engine >> Dave: Yeah. >> It is in Netezza, it is in a bunch of other. >> Dave: Master Data. >> Lenley: Greenplum. >> Greenplum yes. So it's a really robust architecture. Very, very nicely designed. It just does the job and it does it really well. Which is, what you want a database to do, right. It's not that exciting but it's really stable. It really works. The data is still there tomorrow. That's what really the requirements are. >> And to translate a little bit, Marc mentioned PostGIS, which is geo spacial capability for the Postgres database. And so we distribute that along with Postgres and test it so that you know it works. And he mentioned H-Store, so that's how you can actually store internet of things data really well into Postgres. And we talk about SQL, noSQL databases, so they're document databases. And the ability to have personalization at the same level you can in a document oriented database but in a structured SQL database are the kinds of things that have been added to Postgres over the years. Again, it's because of the basic architecture that Stonebraker put in place as an object relational database. >> It's so interesting to look at the history of database. Talk about Stonebraker, he's been on a number of times. It's just fascinating to listen to one of the fathers of this industry. But 10 years ago, database was like such a boring topic. And now it's exploded. Now you got Amazon going after Oracle. Oracle fighting the good fight. So many noSQL databases coming in. SQL becoming the killer big data app if you will. >> Male Voice: Umhmm. >> Why all of a sudden did database get so interesting? >> What happened was, application models changed. Led by Facebook, led by Amazon and Google. They said, let's refactor the applications and let's refactor the way we handle storage. >> Dave: Umhmm. >> And that led to the rise of the polyglot of databases is what a lot of people are saying. You have fit for purpose solutions and you may have three or four or five of them in your overall architecture. One thing about Postgres is, we're able to, because of the datatypes support that Marc mentioned, fit into that well. We don't try and do everything so if somebody says, I'm going to use Mongo for data capture, or I'm going to use Cassandra for capturing my internet of things data. We have what we call foreign data wrappers in the Postgres world. We call them just Enterprise DB Adapters but to Mongo, to Casandra, to Hadoop and can do bidirectional data there and just keep that data at rest over there in the other world. But be able to project relational schema onto it. We can push our data into those. We've got a great use case we've been talking about with a customer who had over a petabyte of data. And in the past what you do is, you'd go buy an expensive archiving solution and add that to it. Now, you just use Hadoop distributed file system. Push the data off there as it ages and have a foreign data wrapper that allows you to still query that data when it's out of your basic operational dataset. And move forward. >> Can I call that a connector or? >> Lenley: Yeah, a connector, that's not a bad idea. >> And it's interesting because If you guys remember Hadapt, probably. [Male Voices] Yeah. Yes. >> They came out, they were the connector killer. >> Male Voice: Umhmm. >> And it failed. >> Male Voice: Yeah. >> Seems like connectors are just fine. >> Male Voice: Yeah. >> And one of the really interesting things is, we call it data federation right. With philosophy here is, leave the data where it is. There are some data that should live in Hadoop or Cassandra. If I'm doing an e-commerce site with transactions and click streams, well, the click streams really should live in Hadoop. That the night natural place for them. The transactions should be in a transactional database. With the foreign data wrapper, I can run queries without moving the data, that will allow me to say, well, before you bought the brown teddy bear, which pages did you look at? >> Dave: Yeah. >> And I can do that integrated system and I can do a fit for purpose architecture. And that's what we think is really exciting. >> And that's fundamental to this new sort of programming or application models. >> Male Voice: That's right. >> The one that you were talking about is moving five megabytes of code to a petabyte of data. As opposed to moving data which we know has gravity and speed of light issues and so forth. >> Thank you for that little brief education. Appreciate it. So let's get into your business now, your relationship with IBM. What customers are doing. You mentioned IoT data so talk more about your business and your relationship with IBM and what you guys are doing for customers. >> There are a couple of things. We mentioned Oracle. And there are all the new databases. And then there's your, dare we say, legacy, proprietary databases as well. And people are looking to become more efficient in how they spend. We've done another thing with Postgres. We've added Oracle compatibility in terms of datatypes. So we support all the datatypes that Oracle does. And we support PL/SQL, they're sort of variant of stored procedure language. And implemented a lot of the packages that they have as well. So we can migrate workloads from Oracle over into an open source based solution. And give a lot cost effectiveness options to customers. >> Dave: Steal. This is a way that I can sort of have Oracle licensed database licensed and maintenance avoidance. >> Lenley: Yes. Yeah. >> Where possible, right. >> Where it makes sense. Where it makes sense. >> Obvious my quorum, I keep, but let's face it, the number one cost component of a TCO analysis of an Oracle customer is the database license and maintenance cost. >> Male Voice: That's right. >> It's not the people. One of the few examples I can think of where that's the case. There's always the people cost. [Male Voice] That's right, that's right. IT is very labor intensive. But for an Oracle customer, it's the database license. Cuz they license by Core. >> Male Voice: Yup. Cores are going through the roof. >> Male Voice: That's right. It's been great for Oracle's business. Although, wouldn't you agree, Oracle sees the writing on the wall that the SAS is really sort of the new control point for the industry. You see the acquisition of NetSuite and competition with Workday >> Male Voice: Yup. >> and the like. >> But the database remains the heart of the business. >> And really it's movement to the cloud, both private cloud and public cloud. And so we've been doing work there. We've had public cloud database as a service solution on Amazon for, what, [Marc] Four years. >> Four years, Marc. And have gained a lot experience with that. And were running that sort of running a retail, you can license the database and we'll provision it there. And so what we've done recently is change our perspective and said, let's put this into hands of customers. And let them standup their own database as a service. But also do it in a way that they can choose what workload should go to Amazon and what workload might go to their private cloud, built on open stack. And be able to arbitrage that if you will. Because they now have a way to provision the databases and make a choice about where to put it. >> So that's a bring your own license model that you just talked about? >> Bring your own license model or >> Are you in the Marketplace and, >> We're in the Marketplace in Amazon, where we can supply it that way. But customers have shown a preference for bring your own license. They want to make the best enterprise deal they can with a vendor like us or whomever else. And then have control over it. >> Amazon obviously wants you to be in the Marketplace. I won't even mention but I talked to some CEOs of database companies and they say, you know, we're in the Marketplace but we get in the Marketplace, next thing you know, Amazon is pushing them towards DynamoDB or you know. >> Male Voice: That's right, that's right. >> Now Amazon's come out with Aurora and Oracle migration and you know the intent to go after that business. Amazon's moving up the stack and you got to be careful. >> They are. But the thing about Amazon is that, they're a pure play in the cloud company. >> Dave: Yup. >> And all of the data shows that it's like a mix, it's going to be a hybrid cloud. Half the company in this world [Dave] Not Angie Jassie's data >> Eighty percent of the people in the cloud are going to be on-prem, still continuing their journey through virtualization. >> Dave: Yeah, that's right. >> Let along going to the cloud. But we want to be something that let's them put what they want in the public cloud and let's them manage on the private cloud in the same manner. So they can provision databases with a few clicks. Just like they do on Amazon. But do it in their data center. >> You doing that with Softlayer as well or not yet? >> Lenley: Not yet. >> Marc: Not yet. >> We've built this provisioning capability ourselves. And it came out of the work we did putting up databases on Amazon. >> So what are you guys doing here at Edge. Edge is kind of infrastructure show. Database is infrastructure. >> We're talking about our work with Power. >> Power is a big partner for us. Power is I think very, very interesting for our database customers. Because of the much higher clock speeds and the capabilities that the Power processor has. When I'm looking at Power, I get more oomph out of a single core which really for a database customer is very, very interesting. Because all databases are licensed by Core. >> Dave: Right. >> So it's a much better deal for the customer. And specifically for Postgres, Postgres scales very well with higher clock speeds. So by having, let's say, by growing performance, not by adding more cores but by making the individual cores faster, that plays very, very well to the Postgres capabilities. >> Okay, so you are a Power partner, part of that ecosystem that IBM is appealing to to grow the OpenPOWER base. And what kind of workloads are you seeing your customers demand and where you're having success? >> Across the board. Database is mostly infrastructure capabilities so there's a lot of interest that we're seeing that, for all kinds of applications really. >> What's the typical Power customer look like these days? You got some Oracle, you got some DB2, you guys are running on there, what's the mix? Paint the picture for us. >> I think the typical Power customer is the typical enterprise company. And, [Dave] Little bit of everything. >> It's a little bit of everything. But one of the key things is that, people are also looking at what they've got and the skills they have in place. You were talking about people cost right. [Dave] Yeah. >> And their understanding of management. Their understanding of how to manage the relationship with the vendor even. And then saying, look, how can I move into the new world of digital transformation and start my own private cloud options and things like that in an efficient way. That makes efficient use of hardware I have in place and has a growth curve and new hardware that's coming out that fits my workloads. >> Dave: Umhmm. >> And the profiles that Marc was talking about. >> And also the resources. Which is very interesting when we look at these new digital applications with Postgres. Because you can do so much in Postgres from geographic information systems to document oriented to key-value. But you can do that with your existing developers through existing DBAs. They don't need to go to school to learn a new database. And that's also a very, very, interesting capability. So you can use your existing team to do new stuff. [Male Voice] Yup. >> What's happening in IoT, what problems are you solving there and where's the limit? >> Sensor data collection. >> Lenley: Yeah. Real interesting because sensor data tends to come in all different forms. We have customer who collects temperature sensor, temperature data. But the sensors are all sending different data packets. So because we can do document oriented or key-value, we can easily accommodate that. In the old days with the relational model, I had to do all kinds of tricks to sort of stuff all that into a relational table. My table would be almost empty at the end because I'd have to add columns for every vendor et cetera. Here, now I can use put all that into the same format and provide it for analysis. So that's a real interesting capability. >> And it's interesting too because we've got really strong geo spacial data support. And the intersection of that, with IoT is a big deal. They track your iPhone, they know where we are. They know what's going on. That's sensor data. They know which lights in which building, which you know, louvers that are controlling HVAC are malfunctioning or not. They want to know specifically where it is, not just what the sensor is. And some of that stuff moves around. And it gets replaced in a new place in the building and such. So we're well setup to handle those types of workloads. >> What's interesting, when IBM bought the weather company, [Lenley] Yeah. >> And they thought okay great, they're getting all these data scientists and weather data, that's cool. They can monetize that but it's an IoT play, isn't it? [Male Voice] Right. Right. >> Talk about sensor. >> It's reference data. It's reference data for other company specific IoT plays. To have a broader set of sensors out there in their region and understand what's happening with weather and things. And then play that against what their experience is, managing new building or manufacturing processes, everything. >> So what's the engagement model. I'm a customer, I want to do business with you. How do I do it, how do I engage? >> Well, a lot of our businesses direct with us. Others through partners. And then a lot of customers come to us because they want to get off legacy systems. But really, what they do is, once they understand the database and the capabilities, they say, okay yeah, you can do the Oracle stuff. But what I'm really going to do with you is my new things. Because that's really exciting and it helps me kind of put a lid on the commercial license growth. So maybe I'm not going to get off it, but I will stop growing it. So I will start doing my new stuff on Postgres. Whenever I modernize something, Postgres is going to be my database of choice. If I already open up an application with its whole stack, this is one of the changes I'm going to make. And then the database as service, is very, very interesting. So these four entry vectors and what happens is, quite a few customers after a short time when they started with project or applications, they end up making Postgres as one of their database standards. Not the only one. But they make it one of the database standards so it gets into the catalog and every new project then has to consider Postgres. >> It's interesting, there's a space created as Microsoft sort of put all their wood behind the era of becoming a competitor to high end Oracle. And with this last release, they probably are on there, arguable. But they've also raised their prices too. And they've made the solution more complex. So there's this space that was vacated for like a ton of workloads and Postgres fits in there just about perfectly. We see enterprise after enterprise come to us with a sheet that says, now we're going to get some of this noSQL stuff. We're going to keep Oracle or DB2 over here for these really high end things. Run my financials, run my sales order processing, my manufacturing. And then we got this space in here. We got a slot for relational database and we want to go open source. Because of the cost savings. Because of other factors. It's ability to grow and not be bound to, hey, what if the vendor decides they're going to go for a new cooler thing and make me upgrade. >> Dave: Right. >> And I want to stay there and know that there's still being an investment made. And so there's a vibrant community around it. And it just fits that slot perfectly. >> You got to pay for that digital transformation and all these IoT initiates. You can't just keep pouring [Male Voice] Somehow. >> down to database licenses. [Male Voice] That's right. >> Tell me, we have to leave it there. >> Thanks very much >> Male Voice: Alright. >> for coming to theCUBE. >> Thanks so much. >> We appreciate the time. You welcome. [Male Voice] Enjoy it. Keep it right there buddy. We'll be right back with our next guest. This is theCUBE. We're live from IBM Edge 2016, be right back. (upbeat music)