>>Good afternoon everybody. I'm John Walls and welcome back to our coverage here on the cube of AWS Reinvent 22. We are bringing you another segment with the Global Startup Program, which is part of the AWS Start Showcase, and it's a pleasure to welcome two new guests here to the showcase. First, immediately to my right Han w lre. Good to see you Han. Good to see you. The leader of the Enterprise Solutions Architecture at aws. And on the far right, Rolin Lee, who is the co-founder and CEO of Heim Doll Data. Roland, good to see you. Great >>To be here. >>All right, good. Thanks for joining us. Well first off, for those at home, I may not be familiar with Heim Doll. What do you do? Why are you here? But I'll let you take it from there. >>Well, we're one of the sponsors here at AWS and great to be here. We offer a data access layer in the form of a proxy, and what it does is it provides complete visibility and the capability to enhance the interaction between the application and one's current database. And as a result, you'll, the customer will improve database scale, database security and availability. And all these features don't require any application changes. So that's sort of our marketing pitch, if you will, all these types of features to improve the experience of managing a database without any application >>Changes. And, and where's the cloud come into play then, for you then, where, where did it come into play for you? >>So we started out actually helping out customers on premise, and a lot of enterprise customers are moving over to the cloud, and it was just a natural progression to do that. And so aws, which is a key part of ours, partners with us to help solve customer problems, especially on the database side, as the application being application performance tends to have issues between the interaction between the application database and we're solving that issue. >>Right. Sohan, I mean, Roan just touched on it about OnPrem, right? There's still some kickers and screamers out there that, that don't, haven't bought in or, or they're about to, but you're about to get 'em. I, I'm sure. But talk about that, that conversion or that transition, if you would, from going OnPrem into a hybrid environment or to into the, the bigger cloud environment and and how difficult that is sometimes. Yes. Maybe to get people to, to make that kind of a leap. >>Well, I would say that a lot of customers are wanting to focus more on product innovation experimentation, and also in terms of having to manage servers and patching, you know, it's to take away from that initiative that they're trying to do. So with aws, we provide undifferentiated heavy lifting so that they can focus on product innovation. And one of the areas talking about Heim is that from the database side, we do provide Amazon rds, which is database and also Aurora, to give them that lift so they don't have to worry about patching servers and setting up provisioning servers as well. >>Right. So Roland, can you get the idea across to people very simply, let us take care of the, the hard stuff and, and that will free you up to do your product innovations, to do your experimentations to, to really free up your team, basically to do the fun stuff and, and let us sweat over the, the, the details basically. Right? >>Exactly. Our, our motto is not only why build when, when you can buy. So a lot of it has to do with offering the, the value in terms of price and the features such as it's gonna benefit a team. Large companies like amazon.com, Google, they have huge teams that can build data access layers and proxies. And what we're trying to do here is commercialize those cuz those are built in house and it's not readily available for customers to use. And you'd need some type of interface between the application and the database. And we provide that sort of why build when you can buy. >>Well, I was gonna say why h right? I mean what's your special sauce? Because everybody's got something, obviously a market differentiator that you're bringing into place here. So you started to touch on a little bit there for me, but, but dive a little deeper there. I mean, what, what is it that, that you're bringing to the table with AWS that you think puts you above the crowd? >>Well, lemme give you a use case here. In typical events like let's say Black Friday where there's a surge traffic that can overwhelm the database, the Heim doll data access layer database proxy provides an auto scaling distributed architecture such that it can absorb those surges and traffic and help scale the database while keeping the data fresh and up to date. And so basically traffic based on season time of day, we can, we can adjust automatically and all these types of features that we offer, most notably automated query caching, ReadWrite split for asset compliance don't require any code changes, which typically requires the application developer to make those changes. So we're saving months, maybe years of development and maintenance. >>Yeah, a lot of gray hairs too, right? Yeah, you're, you're solving a lot of problems there. What about database trends in just in general Hunt, if you will. I mean, this is your space, right? I mean, what we're hearing about from Heindel, you know, in terms of solutions they're providing, but what are you seeing just from the macro level in terms of what people are doing and thinking about the database and how it relates to the cloud? Right. >>And some of the things that we're seeing is that we're seeing an explosion of data, relevant data that customers need to be able to consume and also process as well. So with the explosion of data, there's also, we see customers trying to modernize their application as well through microservices, which does change the design patterns of like the applications we call the access data patterns as well. So again, going back to that, a differentiated heavy lifting, we do have something called purpose built databases, right? It's the right tool for the right purpose. And so it depends on what their like rpo, rto their access to data pattern. Is it a base, is it an acid? So we want to be able to provide them the options to build and also innovate. So with that, that's why we have the Amazon rds, the also the, we also have Redshift, we also have Aurora and et cetera. The Rediff is more of the BI side, but usually when you ingest the data, you have some level of processing to get more insight. So with that, that's why customers are moving more of towards the managed service so that they can give that lift and then focusing on that product and innovation. Yeah. >>Have we kind of caught up or are we catching up to this just the tsunami of data to begin with, right? Because I mean, that was it, you know, what, seven, eight years ago when, when that data became kind of, or becoming king and, and reams and reams and reams and all, you know, can't handle it, right? And, and are we now able to manage that process and manage that flow and get the right data into the right hands at the right time? We're doing better with that. >>I would say that it, it definitely has grown in size of the amount of data that we're ingesting. And so with the scalability and agility of the cloud, we're able to, I would say, adapt to the rapid changes and ingestions of the data. So, so that's why we have things like Aurora servers to have that or auto scale so they can do like MySQL or Postgres and then they can still, like what you know, I'm trying to do is basically don't have to co do like any code changes. It would be a data migration. They still use the same underlying database on also mechanisms, but here we're providing them at scale on the cloud. >>Yeah. Our proxies, they must have for all databases. I mean, is that, is that essential these days? >>Well, good question John. I would say yes. And this is often built in house, as I mentioned, for large companies, they do build some type of data access layer or proxy and, or some utilize some orm, some object relational map to do it. And what again, what we're trying to do is offer this, put this out into the market commercially speaking, such that it can be readily used for, for all the customers to use rather than building it from scratch all the time. >>You know what I didn't ask you was Roy, how does AWS come into play for you then? And, and as in the startup mode, the focus that they've had in startups in general, but in you in particular, I mean, talk about that partnership or that relationship and the value that you're extracting from that. >>The ad AWS partnership has been absolutely wonderful. The collaboration, they have one of the best managed service databases. The value that it that adds in terms of the durability, the manageability, what the Heim doll data does is it compliments Amazon rds, Amazon Redshift very well in the sense that we're not replacing the database. What we're doing is we are allowing the customer to get the most out of the managed service database, whether it be Redshift or Aurora Serverless, rds, all without code changes. And or the analogy that I would give John is a car, a race car may be very fast, but it takes a driver to get to those fast speeds. We're the driver, the Hyundai proxy provides that intelligence so that you can get the most out of that database engine. >>And, and Hfi would then touch on, first off AWS and the emphasis that you have put on startups and are obviously, you know, kind of putting your money where your mouth is, right? With, with the way you've encouraged and nurtured that environment. And they would be about Heim doll in general about where you see this going or what you would like to have, where you want to take this in the next say 12 months, 18 months. >>I think it's more of a better together story of how we can basically coil with our partners, right? And, and basically focusing on helping our customers drive that innovation and be collaboration. So as Heim, as a independent service vendor isv, most customers can leverage that through a marketplace where basically it integrates very nicely with aws. So that gives 'em that lift and it goes back to the undifferentiated heavy lifting on the Hein proxy side, if you will, because then you have this proxy in the middle where then it helps them with their SQL performance. And I've seen use cases where customers were, have some legacy system that they may not have time to modernize the application. So they use this as a lift to keep, keep going as they try to modernize. But also I've seen customers who use are trying to use it as a, a way to give that performance lift because they may have a third party software that they cannot change the code by putting this in there that helps optimize their lines of business or whatever that is, and maybe can be online store or whatever. So I would say it was a better together type of story. >>Yeah. Which is, there's gotta be a song in there somewhere. So peek around the corner and if you wanna be headlights here right now in terms of 12, 18 months, I mean, what, you know, what what next to solve, right? You've already taken, you've slayed a few dragons along the way, but there are others I'm sure is it always happens in innovation in this space. Just when you solve a problem you've just dealt or you have to deal with others that pop up as maybe unintended consequences or at least a new challenge. So what would that be in your world right now? What, what do you see, you know, occupying your sleepless nights here for the next year or so? >>Well, for, for HOMEDALE data, it's all about improving database performance and scale. And those workloads change. We have O ltp, we have OLA with artificial intelligence ml. There's different type of traffic profiles and we're focused on improving those data profiles. It could be unstructured structured. Right now we're focused on structured data, which is relational databases, but there's a lot of opportunity to improve the performance of data. >>Well, you're driving the car, you got a good navigator. I think the GPS is working. So keep up the good work and thank you for sharing the time today. Thank you. Thank you, joy. Do appreciate it. All right, you are watching the cube. We continue our coverage here from AWS Reinvent 22, the Cube, of course, the leader in high tech coverage.

>>live from Miami, Florida It's the Q covering IBM is data in a I forum brought to you by IBM. >>We're back in Miami and you're watching the cubes coverage of the IBM data and a I forum. Tony hi. Amiss here is a distinguished engineer for Ditch the Digital and Cloud Business Analytics at IBM. Tony, first of all, congratulations on being a distinguished engineer. That doesn't happen often. Thank you for coming on the Cube. Thank you. So your area focus is on the B I and the Enterprise performance management space. >>Um, and >>if I understand it correctly, a big mission of yours is to try to modernize those make himself service, making cloud ready. How's that going? >>It's going really well. I mean, you know, we use things like B. I and enterprise performance management. When you really boil it down, there's that's analysis of data on what do we do with the data this useful that makes a difference in the world, and then this planning and forecasting and budgeting, which everyone has to do whether you are, you know, a single household or whether you're an Amazon or Boeing, which are also some of our clients. So it's interesting that we're going from really enterprise use cases, democratizing it all the way down to single user on the cloud credit card swipe 70 bucks a month >>so that was used to be used to work for Lotus. But Cognos is one of IBM's largest acquisitions in the software space ever. Steve Mills on his team architected complete transformation of IBM is business and really got heavily into it. I think I think it was a $5 billion acquisition. Don't hold me to that, but massive one of the time and it's really paid dividends now when all this sort of 2000 ten's came in and said, Oh, how Duke's gonna kill all the traditional b I traditional btw that didn't happen, that these traditional platforms were a fundamental component of people's data strategies, so that created the imperative to modernize and made sure that there could be things like self service and cloud ready, didn't it? >>Yeah, that's absolutely true. I mean, the work clothes that we run a really sticky were close right when you're doing your reporting, your consolidation or you're planning of your yearly cycle, your budget cycle on these technologies, you don't rip them out so easily. So yes, of course, there's competitive disruption in the space. And of course, cloud creates on opportunity for work loads to be wrong, Cheaper without your own I t people. And, of course, the era of digital software. I find it myself. I tried myself by it without ever talking to a sales person creates a democratization process for these really powerful tools that's never been invented before in that space. >>Now, when I started in the business a long, long time ago, it was called GSS decision support systems, and they at the time they promised a 360 degree view with business That never really happened. You saw a whole new raft of players come in, and then the whole B I and Enterprise Data Warehouse was gonna deliver on that promise. That kind of didn't happen, either. Sarbanes Oxley brought a big wave of of imperative around these systems because compliance became huge. So that was a real tailwind for it. Then her duke was gonna solve all these problems that really didn't happen. And now you've got a I, and it feels like the combination of those systems of record those data warehouse systems, the traditional business intelligence systems and all this new emerging tech together are actually going to be a game changer. I wonder if you could comment on >>well so they can be a game changer, but you're touching on a couple of subjects here that are connected. Right? Number one is obviously the mass of data, right? Cause data has accelerated at a phenomenal pace on then you're talking about how do I then visualize or use that data in a useful manner? And that really drives the use case for a I right? Because A I in and of itself, for augmented intelligence as we as we talk about, is only useful almost when it's invisible to the user cause the user needs to feel like it's doing something for them that super intuitive, a bit like the sort of transition between the electric car on the normal car. That only really happens when the electric car can do what the normal car can do. So with things like Imagine, you bring a you know, how do cluster into a B. I solution and you're looking at that data Well. If I can correlate, for example, time profit cost. Then I can create KP eyes automatically. I can create visualizations. I know which ones you like to see from that. Or I could give you related ones that I can even automatically create dashboards. I've got the intelligence about the data and the knowledge to know what? How you might what? Visualize adversity. You have to manually construct everything >>and a I is also going to when you when you spring. These disparage data sets together, isn't a I also going to give you an indication of the confidence level in those various data set. So, for example, you know, you're you're B I data set might be part of the General ledger. You know of the income statement and and be corporate fact very high confidence level. More sometimes you mention to do some of the unstructured data. Maybe not as high a confidence level. How our customers dealing with that and applying that first of all, is that a sort of accurate premise? And how is that manifesting itself in terms of business? Oh, >>yeah. So it is an accurate premise because in the world in the world of data. There's the known knowns on the unknown knowns, right? No, no's are what you know about your data. What's interesting about really good B I solutions and planning solutions, especially when they're brought together, right, Because planning and analysis naturally go hand in hand from, you know, one user 70 bucks a month to the Enterprise client. So it's things like, What are your key drivers? So this is gonna be the drivers that you know what drives your profit. But when you've got massive amounts of data and you got a I around that, especially if it's a I that's gone ontology around your particular industry, it can start telling you about drivers that you don't know about. And that's really the next step is tell me what are the drivers around things that I don't know. So when I'm exploring the data, I'd like to see a key driver that I never even knew existed. >>So when I talk to customers, I'm doing this for a while. One of the concerns they had a criticisms they had of the traditional systems was just the process is too hard. I got to go toe like a few guys I could go to I gotta line up, you know, submit a request. By the time I get it back, I'm on to something else. I want self serve beyond just reporting. Um, how is a I and IBM changing that dynamic? Can you put thes tools in the hands of users? >>Right. So this is about democratizing the cleverness, right? So if you're a big, broad organization, you can afford to hire a bunch of people to do that stuff. But if you're a startup or an SNB, and that's where the big market opportunity is for us, you know, abilities like and this it would be we're building this into the software already today is I'll bring a spreadsheet. Long spreadsheets. By definition, they're not rows and columns, right? Anyone could take a Roan Collin spreadsheet and turn into a set of data because it looks like a database. But when you've got different tabs on different sets of data that may or may not be obviously relatable to each other, that ai ai ability to be on introspect a spreadsheet and turn into from a planning point of view, cubes, dimensions and rules which turn your spreadsheet now to a three dimensional in memory cube or a planning application. You know, the our ability to go way, way further than you could ever do with that planning process over thousands of people is all possible now because we don't have taken all the hard work, all the lifting workout, >>so that three dimensional in memory Cuba like the sound of that. So there's a performance implication. Absolutely. On end is what else? Accessibility Maw wraps more users. Is that >>well, it's the ability to be out of process water. What if things on huge amounts of data? Imagine you're bowing, right? Howdy, pastors. Boeing How? I don't know. Three trillion. I'm just guessing, right? If you've got three trillion and you need to figure out based on the lady's hurricane report how many parts you need to go ship toe? Where that hurricane reports report is you need to do a water scenario on massive amounts of data in a second or two. So you know that capability requires an old lap solution. However, the rest of the planet other than old people bless him who are very special. People don't know what a laugh is from a pop tart, so democratizing it right to the person who says, I've got a set of data on as I still need to do what if analysis on things and probably at large data cause even if you're a small company with massive amounts of data coming through, people click. String me through your website just for example. You know what if I What if analysis on putting a 5% discount on this product based on previous sales have that going to affect me from a future sales again? I think it's the democratizing as the well is the ability to hit scale. >>You talk about Cloud and analytics, how they've they've come together, what specifically IBM has done to modernize that platform. And I'm interested in what customers are saying. What's the adoption like? >>So So I manage the Global Cloud team. We have night on 1000 clients that are using cloud the cloud implementations of our software growing actually so actually Maur on two and 1/2 1000. If you include the multi tenant version, there's two steps in this process, right when you've got an enterprise software solution, your clients have a certain expectation that your software runs on cloud just the way as it does on premise, which means in practical terms, you have to build a single tenant will manage cloud instance. And that's just the first step, right? Because getting clients to see the value of running the workload on cloud where they don't need people to install it, configure it, update it, troubleshoot it on all that other sort of I t. Stuff that subtracts you from doing running your business value. We duel that for you. But the future really is in multi tenant on how we can get vast, vast scale and also greatly lower costs. But the adoptions been great. Clients love >>it. Can you share any kind of indication? Or is that all confidential or what kind of metrics do you look at it? >>So obviously we look, we look a growth. We look a user adoption, and we look at how busy the service. I mean, let me give you the best way I can give you is a is a number of servers, volume numbers, right. So we have 8000 virtual machines running on soft layer or IBM cloud for our clients business Analytics is actually the largest client for IBM Cloud running those workloads for our clients. So it's, you know, that the adoption has been really super hard on the growth continues. Interestingly enough, I'll give you another factoid. So we just launched last October. Cognos Alex. Multi tenant. So it is truly multi infrastructure. You try, you buy, you give you credit card and away you go. And you would think, because we don't have software sellers out there selling it per se that it might not adopt as much as people are out there selling software. Okay, well, in one year, it's growing 10% month on month cigarette Ally's 10% month on month, and we're nearly 1400 users now without huge amounts of effort on our part. So clearly this market interest in running those softwares and then they're not want Tuesdays easer. Six people pretending some of people have 150 people pretending on a multi tenant software. So I believe that the future is dedicated is the first step to grow confidence that my own premise investments will lift and shift the cloud, but multi tenant will take us a lot >>for him. So that's a proof point of existing customer saying okay, I want to modernize. I'm buying in. Take 1/2 step of the man dedicated. And then obviously multi tenant for scale. And just way more cost efficient. Yes, very much. All right. Um, last question. Show us a little leg. What? What can you tell us about the road map? What gets you excited about the future? >>So I think the future historically, Planning Analytics and Carlos analytics have been separate products, right? And when they came together under the B I logo in about about a year ago, we've been spending a lot of our time bringing them together because, you know, you can fight in the B I space and you can fight in the planning space. And there's a lot of competitors here, not so many here. But when you bring the two things together, the connected value chain is where we really gonna win. But it's not only just doing is the connected value chain it and it could be being being vice because I'm the the former Lotus guy who believes in democratization of technology. Right? But the market showing us when we create a piece of software that starts at 15 bucks for a single user. For the same power mind you write little less less of the capabilities and 70 bucks for a single user. For all of it, people buy it. So I'm in. >>Tony, thanks so much for coming on. The kid was great to have you. Brilliant. Thank you. Keep it right there, everybody. We'll be back with our next guest. You watching the Cube live from the IBM data and a I form in Miami. We'll be right back.