>>Hey everyone. Welcome back to Las Vegas. It's the Cube live at AWS Reinvent 2022. This is our fourth day of coverage. Lisa Martin here with Paul Gillen. Paul, we started Monday night, we filmed and streamed for about three hours. We have had shammed pack days, Tuesday, Wednesday, Thursday. What's your takeaway? >>We're routed final turn as we, as we head into the home stretch. Yeah. This is as it has been since the beginning, this show with a lot of energy. I'm amazed for the fourth day of a conference, how many people are still here I am too. And how, and how active they are and how full the sessions are. Huge. Proud for the keynote this morning. You don't see that at most of the day four conferences. Everyone's on their way home. So, so people come here to learn and they're, and they're still >>Learning. They are still learning. And we're gonna help continue that learning path. We have an alumni back with us, Toron joins us, the CPO and co-founder of Dremeo. Tomer, it's great to have you back on the program. >>Yeah, thanks for, for having me here. And thanks for keeping the, the best session for the fourth day. >>Yeah, you're right. I like that. That's a good mojo to come into this interview with Tomer. So last year, last time I saw you was a year ago here in Vegas at Reinvent 21. We talked about the growth of data lakes and the data lake houses. We talked about the need for open data architectures as opposed to data warehouses. And the headline of the Silicon Angle's article on the interview we did with you was, Dremio Predicts 2022 will be the year open data architectures replace the data warehouse. We're almost done with 2022. Has that prediction come true? >>Yeah, I think, I think we're seeing almost every company out there, certainly in the enterprise, adopting data lake, data lakehouse technology, embracing open source kind of file and table formats. And, and so I think that's definitely happening. Of course, nothing goes away. So, you know, data warehouses don't go away in, in a year and actually don't go away ever. We still have mainframes around, but certainly the trends are, are all pointing in that direction. >>Describe the data lakehouse for anybody who may not be really familiar with that and, and what it's, what it really means for organizations. >>Yeah. I think you could think of the data lakehouse as the evolution of the data lake, right? And so, you know, for, for, you know, the last decade we've had kind of these two options, data lakes and data warehouses and, you know, warehouses, you know, having good SQL support, but, and good performance. But you had to spend a lot of time and effort getting data into the warehouse. You got locked into them, very, very expensive. That's a big problem now. And data lakes, you know, more open, more scalable, but had all sorts of kind of limitations. And what we've done now as an industry with the Lake House, and especially with, you know, technologies like Apache Iceberg, is we've unlocked all the capabilities of the warehouse directly on object storage like s3. So you can insert and update and delete individual records. You can do transactions, you can do all the things you could do with a, a database directly in kind of open formats without getting locked in at a much lower cost. >>But you're still dealing with semi-structured data as opposed to structured data. And there's, there's work that has to be done to get that into a usable form. That's where Drio excels. What, what has been happening in that area to, to make, I mean, is it formats like j s o that are, are enabling this to happen? How, how we advancing the cause of making semi-structured data usable? Yeah, >>Well, I think first of all, you know, I think that's all changed. I think that was maybe true for the original data lakes, but now with the Lake house, you know, our bread and butter is actually structured data. It's all, it's all tables with the schema. And, you know, you can, you know, create table insert records. You know, it's, it's, it's really everything you can do with a data warehouse you can now do in the lakehouse. Now, that's not to say that there aren't like very advanced capabilities when it comes to, you know, j s O and nested data and kind of sparse data. You know, we excel in that as well. But we're really seeing kind of the lakehouse take over the, the bread and butter data warehouse use cases. >>You mentioned open a minute ago. Talk about why it's, why open is important and the value that it can deliver for customers. >>Yeah, well, I think if you look back in time and you see all the challenges that companies have had with kind of traditional data architectures, right? The, the, the, a lot of that comes from the, the, the problems with data warehouses. The fact that they are, you know, they're very expensive. The data is, you have to ingest it into the data warehouse in order to query it. And then it's almost impossible to get off of these systems, right? It takes an enormous effort, tremendous cost to get off of them. And so you're kinda locked in and that's a big problem, right? You also, you're dependent on that one data warehouse vendor, right? You can only do things with that data that the warehouse vendor supports. And if you contrast that to data lakehouse and open architectures where the data is stored in entirely open formats. >>So things like par files and Apache iceberg tables, that means you can use any engine on that data. You can use s SQL Query Engine, you can use Spark, you can use flin. You know, there's a dozen different engines that you can use on that, both at the same time. But also in the future, if you ever wanted to try something new that comes out, some new open source innovation, some new startup, you just take it and point out the same data. So that data's now at the core, at the center of the architecture as opposed to some, you know, vendors logo. Yeah. >>Amazon seems to be bought into the Lakehouse concept. It has big announcements on day two about eliminating the ETL stage between RDS and Redshift. Do you see the cloud vendors as pushing this concept forward? >>Yeah, a hundred percent. I mean, I'm, I'm Amazon's a great, great partner of ours. We work with, you know, probably 10 different teams there. Everything from, you know, the S3 team, the, the glue team, the click site team, you know, everything in between. And, you know, their embracement of the, the, the lake house architecture, the fact that they adopted Iceberg as their primary table format. I think that's exciting as an industry. We're all coming together around standard, standard ways to represent data so that at the end of the day, companies have this benefit of being able to, you know, have their own data in their own S3 account in open formats and be able to use all these different engines without losing any of the functionality that they need, right? The ability to do all these interactions with data that maybe in the past you would have to move the data into a database or, or warehouse in order to do, you just don't have to do that anymore. Speaking >>Of functionality, talk about what's new this year with drio since we've seen you last. >>Yeah, there's a lot of, a lot of new things with, with Drio. So yeah, we now have full Apache iceberg support, you know, with DML commands, you can do inserts, updates, deletes, you know, copy into all, all that kind of stuff is now, you know, fully supported native part of the platform. We, we now offer kind of two flavors of dr. We have, you know, Dr. Cloud, which is our SaaS version fully hosted. You sign up with your Google or, you know, Azure account and, and, and you're up in, you're up and running in, in, in a minute. And then dral software, which you can self host usually in the cloud, but even, even even outside of the cloud. And then we're also very excited about this new idea of data as code. And so we've introduced a new product that's now in preview called Dr. >>Arctic. And the idea there is to bring the concepts of GI or GitHub to the world of data. So things like being able to create a branch and work in isolation. If you're a data scientist, you wanna experiment on your own without impacting other people, or you're a data engineer and you're ingesting data, you want to transform it and test it before you expose it to others. You can do that in a branch. So all these ideas that, you know, we take for granted now in the world of source code and software development, we're bringing to the world of data with Jamar. And when you think about data mesh, a lot of people talking about data mesh now and wanting to kind of take advantage of, of those concepts and ideas, you know, thinking of data as a product. Well, when you think about data as a product, we think you have to manage it like code, right? You have to, and that's why we call it data as code, right? The, all those reasons that we use things like GI have to build products, you know, if we wanna think of data as a product, we need all those capabilities also with data. You know, also the ability to go back in time. The ability to undo mistakes, to see who changed my data and when did they change that table. All of those are, are part of this, this new catalog that we've created. >>Are you talk about data as a product that's sort of intrinsic to the data mesh concept. Are you, what's your opinion of data mesh? Is the, is the world ready for that radically different approach to data ownership? >>You know, we are now in dozens of, dozens of our customers that are using drio for to implement enterprise-wide kind of data mesh solutions. And at the end of the day, I think it's just, you know, what most people would consider common sense, right? In a large organization, it is very hard for a centralized single team to understand every piece of data, to manage all the data themselves, to, you know, make sure the quality is correct to make it accessible. And so what data mesh is first and foremost about is being able to kind of federate the, or distribute the, the ownership of data, the governance of the data still has to happen, right? And so that is, I think at the heart of the data mesh, but thinking of data as kind of allowing different teams, different domains to own their own data to really manage it like a product with all the best practices that that we have with that super important. >>So we we're doing a lot with data mesh, you know, the way that cloud has multiple projects and the way that Jamar allows you to have multiple catalogs and different groups can kind of interact and share data among each other. You know, the fact that we can connect to all these different data sources, even outside your data lake, you know, with Redshift, Oracle SQL Server, you know, all the different databases that are out there and join across different databases in addition to your data lake, that that's all stuff that companies want with their data mesh. >>What are some of your favorite customer stories that where you've really helped them accelerate that data mesh and drive business value from it so that more people in the organization kind of access to data so they can really make those data driven decisions that everybody wants to make? >>I mean, there's, there's so many of them, but, you know, one of the largest tech companies in the world creating a, a data mesh where you have all the different departments in the company that, you know, they, they, they were a big data warehouse user and it kinda hit the wall, right? The costs were so high and the ability for people to kind of use it for just experimentation, to try new things out to collaborate, they couldn't do it because it was so prohibitively expensive and difficult to use. And so what they said, well, we need a platform that different people can, they can collaborate, they can ex, they can experiment with the data, they can share data with others. And so at a big organization like that, the, their ability to kind of have a centralized platform but allow different groups to manage their own data, you know, several of the largest banks in the world are, are also doing data meshes with Dr you know, one of them has over over a dozen different business units that are using, using Dremio and that ability to have thousands of people on a platform and to be able to collaborate and share among each other that, that's super important to these >>Guys. Can you contrast your approach to the market, the snowflakes? Cause they have some of those same concepts. >>Snowflake's >>A very closed system at the end of the day, right? Closed and very expensive. Right? I think they, if I remember seeing, you know, a quarter ago in, in, in one of their earnings reports that the average customer spends 70% more every year, right? Well that's not sustainable. If you think about that in a decade, that's your cost is gonna increase 200 x, most companies not gonna be able to swallow that, right? So companies need, first of all, they need more cost efficient solutions that are, you know, just more approachable, right? And the second thing is, you know, you know, we talked about the open data architecture. I think most companies now realize that the, if you want to build a platform for the future, you need to have the data and open formats and not be locked into one vendor, right? And so that's kind of another important aspect beyond that's ability to connect to all your data, even outside the lake to your different databases, no sequel databases, relational databases, and drs semantic layer where we can accelerate queries. And so typically what you have, what happens with data warehouses and other data lake query engines is that because you can't get the performance that you want, you end up creating lots and lots of copies of data. You, for every use case, you're creating a, you know, a pre-joy copy of that data, a pre aggregated version of that data. And you know, then you have to redirect all your data. >>You've got a >>Governance problem, individual things. It's expensive. It's expensive, it's hard to secure that cuz permissions don't travel with the data. So you have all sorts of problems with that, right? And so what we've done because of our semantic layer that makes it easy to kind of expose data in a logical way. And then our query acceleration technology, which we call reflections, which transparently accelerates queries and gives you subsecond response times without data copies and also without extracts into the BI tools. Cause if you start doing bi extracts or imports, again, you have lots of copies of data in the organization, all sorts of refresh problems, security problems, it's, it's a nightmare, right? And that just collapsing all those copies and having a, a simple solution where data's stored in open formats and we can give you fast access to any of that data that's very different from what you get with like a snowflake or, or any of these other >>Companies. Right. That, that's a great explanation. I wanna ask you, early this year you announced that your Dr. Cloud service would be a free forever, the basic DR. Cloud service. How has that offer gone over? What's been the uptake on that offer? >>Yeah, it, I mean it is, and thousands of people have signed up and, and it's, I think it's a great service. It's, you know, it's very, very simple. People can go on the website, try it out. We now have a test drive as well. If, if you want to get started with just some sample public sample data sets and like a tutorial, we've made that increasingly easy as well. But yeah, we continue to, you know, take that approach of, you know, making it, you know, making it easy, democratizing these kind of cloud data platforms and, and kinda lowering the barriers to >>Adoption. How, how effective has it been in driving sales of the enterprise version? >>Yeah, a lot of, a lot of, a lot of business with, you know, that, that we do like when it comes to, to selling is, you know, folks that, you know, have educated themselves, right? They've started off, they've followed some tutorials. I think generally developers, they prefer the first interaction to be with a product, not with a salesperson. And so that's, that's basically the reason we did that. >>Before we ask you the last question, I wanna just, can you give us a speak peek into the product roadmap as we enter 2023? What can you share with us that we should be paying attention to where Drum is concerned? >>Yeah. You know, actually a couple, couple days ago here at the conference, we, we had a press release with all sorts of new capabilities that we, we we just released. And there's a lot more for, for the coming year. You know, we will shortly be releasing a variety of different performance enhancements. So we'll be in the next quarter or two. We'll be, you know, probably twice as fast just in terms of rock qu speed, you know, that's in addition to our reflections and our career acceleration, you know, support for all the major clouds is coming. You know, just a lot of capabilities in Inre that make it easier and easier to use the platform. >>Awesome. Tomer, thank you so much for joining us. My last question to you is, if you had a billboard in your desired location and it was going to really just be like a mic drop about why customers should be looking at Drio, what would that billboard say? >>Well, DRIO is the easy and open data lake house and, you know, open architectures. It's just a lot, a lot better, a lot more f a lot more future proof, a lot easier and a lot just a much safer choice for the future for, for companies. And so hard to argue with those people to take a look. Exactly. That wasn't the best. That wasn't the best, you know, billboards. >>Okay. I think it's a great billboard. Awesome. And thank you so much for joining Poly Me on the program, sharing with us what's new, what some of the exciting things are that are coming down the pipe. Quite soon we're gonna be keeping our eye Ono. >>Awesome. Always happy to be here. >>Thank you. Right. For our guest and for Paul Gillin, I'm Lisa Martin. You're watching The Cube, the leader in live and emerging tech coverage.

>> live from Mountain View, California. It's the queue covering definite create twenty nineteen. Brought to You by Cisco >> Welcome back to the cave. Lisa Martin with John Fourier. Live at Cisco Definite Create twenty nineteen at the Computer History Museum in Mountain View, California John Mayer, please to welcome to the Cube Jeff Levin, sailor collaboration Engineer from Presidio Jeff, It's great to have you joining us today. >> Yes, great to be here. >> So lots of energy. You can hear all this noise behind us. We heard this morning in the key note that the definite community is now well over half a million strong. You mentioned before we went line. This is your second definite creates before we get into our city and Cisco. Tell me a little bit about your involvement in the definite community. >> Uh, so I got >> started just looking for support, and it's not like it's a supported product. This is a new venture for everybody. So you go out and you find these little avenues to get questions answered. And WebEx teams has a great community support and just ask a question ended up answering more questions than I was asking, and, you know, that kind of like got me started down this path of, you know, people bounce ideas off each other So really, this is Ah, homecoming. And it's just people inspiring each other If you really want to learn And deep dive Obviously I'm a self learner, so I'll just sit down and really get into it. But I come here to get inspired and the Kino just >> Will you wait? Yeah. What was the key? What was the highlight for you on the Kino? What was >> anything Ashutosh has to talk about? Ashutosh is on the I guess, the incubator side. He comes up with these things, and his job is to get people excited about the FBI's. So today he had an augmented reality app with his phone and he would go around and show network coverage of a WiFi hot spot. You can go up to an access point and troubleshoot network of problems by seeing if on access, points registered or not. So my mind, I'm thinking how many times I go in the data center and look, I have to plug in a laptop to look to see what the lands on a port. Now, Aiken take that same approach too, you know, put my phone out in a data center, and okay, this witch has ah, this V lands here. I could plug it. Antonito even need to plug my laptop. >> I mean, he first introduced the beginning of that demo at Cisco Live in Barcelona. Totally blown away. He's a demo. God first. Yeah, he's amazing. But it shows the automation right and also shows the new kind of experiences. I think to me what is inspiring to me about this community. I'd love to get your reaction. This is that It kind of shows a new way to do work. And it's all about making life easier, But it's also more capability. You can see all the configurations and then ultimately writing new apse. That seems to be the theme. Create definite curiosity with all these capabilities. Is that kind of something that you're seeing as well? What's your reaction to that? That kind of this new way of doing things. >> Wow. I mean, it's we have a code competition are Presidio called Shark Tank, and it's really just to inspire people. Uh, tell me a business use case for this Use cases really ninety percent of it. You confined help you confined mentors your work. But, uh, really Just finding a use case and stuff like this coming here just thinking about new ways to do things and do things to create >> in collaboration What? Some of the things that you see that are low hanging fruit use cases of either mundane tasks or stuff that just needs to be kind of like, abstracted away. What are some of the things >> I have a ton of those s o. Somebody came to me, a law firm that had these attorney's secretary assignments, and they wanted Secretary is to be able to schedule meetings for attorneys. You could do that in a gooey, but we're seeing more and more is away from the buoy. And it's becoming this FBI first. So anything that's not in the gooey, it's in the AP, I So that's where our values integrators has really become. This gap between the jury and the FBI. So what we did, or what I did is going active directory, have some fields filled out because they're already populated. One thing for this I read from that, and then I goto WebEx a p I and I populated, and that runs a nightly basis. >> You automate thataway. Yeah, piece of cake. But this is the trend. This is kind of what we're seeing happening with Cloud the question that comes up in the enterprises. Look, att. Hey, you know, we've been doing this thing for long times the way we do it. We, You know, ten years ago we built out this system. Don't touch it. But I love the new stuff. How do I get the new stuff in? How do I deal the old stuff, The legacy. And we got containers. Got some news stuff. A p. I's a big part of this integration fabric composing APS. I think you have to show >> that the business value it's it's saving time. It's saving people ours, and it's really checking code into get is something you wouldn't think about. Checking network config. Thing to get is something you wouldn't really think about, Uh, just a year ago. But that's really becoming the trend and having a testable code and, uh, you know, kind of Ah, if something goes wrong, I have a backup. You have somebody you know exactly who did what before it was just people hacking away. >> So let's talk about unlocking value for a second. When you were talking with John about what some of the things that blew your mind during this morning's keynote one I was hearing from you and one senses how how much easier certain functions of yourjob are going to be because of this? What value are you seeing that even just a few things that we were announced this morning is going to bring, too? Not just you and your business, but for city and Cisco's customers? >> Well, I mean So, for instance, the Iraqi thing, uh, they released bulk actions. So AP eyes. Typically, if you write the code one of the time, that's goingto limit your ability to do certain functions. Having all these AP eyes in one and point immediately, I'm thinking cloud formation templates. Name is on but ism Iraqi solution, so you could take this entire network and copy and paste. It is one slice of code. That's tremendous. >> What's the community vibe here? Definite. I mean big invention. >> It's a homecoming. I know all these people have met so many people from other areas and people competitors. We're all friends here, you know, And it's not a marketing ventured all you don't see a lot of people you know, scanning badges and bugging you on email later. This is all about just people hurting out about What they've done >> is we're getting >> the show until >> I like >> that. It's not just the hacker fond, you know, Hey, revenue event. They throw a hackathon over it and it turns out the most these events trees, a marketing event. It's completely eyes that >> unorganized as I would want it to be. There's conversations just passing by in the hallway, and I get just as much out of that as I do in a workshop. >> So you're giving a breakout session later today. Contact center. A eye for more efficient governments. >> Yes, that's a twenty minute lightning talk on just a recent project I did and taking an arm from a solution and be able to do Mohr by moving it up to the cloud. This's Amazon connect could be another one, but just basically enabling through the cloud different functionalities we're using Alexe pot, reason, elastic search, reason Landa and we're we're taking the top ten tickets this help desk would receive and trying to automate this. So I need to reset my pen. I need to transfer me to this person that was an operator before in an Excel spreadsheet. So what we did was completely not change your workflow. They're going to upload it, excels for a cheat and has three. It's going to take a Landau function to separate that spread she into a dynamo database Elastic search, going to read that database. And then Lex Boss is goingto interact with elastic search >> and his all in real time. >> It's all in real time. >> And they thought, this all natural language talking together you're working together, >> working together >> to solve those customer problems or get well that And I guess, get the customer that the ticket routed appropriately. >> Yeah, so there's take a look ups to get creation to get clothes and anything that you would typically anything that you can automate. We've done it within the ivy are and we've measured containment rates. So >> yeah, this is exactly why we've been covering. This is our third year, but here in the beginning, at the creation of the event, because what you just described is so valuable and so kind of basic. If you think about it, the number one tickets that everyone that stack ranked haven't over and over again. But breaking towns this going database for this? I got a database for this. I got a database for this. The old world. You have a waterfall process, you have a product. Project manager. People would go in a round trip meeting after meeting, arguing aboutthe ski mus and databases. And I mean, what would it be like in the old days, if you like, went through the traditional models versus his agile? Hey, let's just put it together. Hackett string up. So maybe eyes sling the FBI's rolling up, wiring up >> siding. Me, you're moving from a static ivy are too self service. And then even more what I think you forget who coined the term. But selfie service. You know more about a user you're able to predictably say, I see you have a ticket open or go a step further and say, I see have email on this phone and we're having active sync issues and only alert those people of issues and not bother everybody else. I see you work out of this office and you're calling in. Are you calling about, uh, you know, your office closure? Because we have a temporary office for you over here, So being able to get ahead of anything and predict that's the next thing >> I know. This really also highlights when we tend to talk about us when these data conferences, where the underlying value being here is the creation and stitching together with solutions. But it's the data that's driving it right. The tickets that ranking the the task getting if these reasoning aspect of reasoning with the data predictive are prescriptive, is a personalization benefit thes air. The things that are exposed on this new way of creating >> there's there's some real exciting, very consumable AP eyes out there. One of them all name is in dico io, and this is something that you could just plug in some data. Then I'll make a prediction using just a bunch of learned data set that it already has, and I'LL give you an example WebEx team space way just chat away, and for months and months, I funnel that data to a simple FBI and it comes back and tells me Who's the angriest person who's the happiest person? There's an f b I for Who's a conservative who's a liberal. There's an A p I. For the Myers Briggs test. >> I'LL get all of this. You are the girl. What's the emiko dot io? Indeed, In dico dico i n d >> i c e o dot io >> Awesome. Well, thanks for sharing that on the AP. I think I want to get your expert opinion on this because this comes up a lot recently. At these conferences, we go to where some oh new way to develop modern applications. Blah, blah, blah, waterfalls going away. Fiber Clavell. That's good stuff. Check, check, Check. At the end of the day that the key ingredient all this is AP AP Eyes are becoming the centre point for one data sharing integration coding Middle, where a new kind of middleware evolving? What's your view on this? Because this is an essential part of integration to like If someone wants to adopt a new product, I want to bring it in. It's really >> recognizing that your use case isn't everybody's used case, so you come from a static, fully functioning product to an FBI first approach, you build the FBI, then you build things around it. So when WebEx teams is released, for instance, it had certain functionality there and certain functionality wasn't there. But you could do it to the FBI. So it's partners and Cisco kind of competing at the same time to come up with a better solution. Any time you compete, you know it's good in any time something is open. It's good. So you have these Open A P I's and you have a community trying to come up with the best solution on DH. It's >> and that's really where communities of shining too right now, because you're going to community. They're great at giving feedback. If something something's not right, raise their hand. Appoint honest >> feedback, right? >> Yeah, competition. So Cisco telling Cisco something's not working. You know, you bring in some other people that maybe they're mohr AP to tell you when something's not working. They don't have any dog in the fight. You know, they'LL tell you if something's not working, they'LL give you feedback, and it really enables a better in product and a product that's more form to tailor fit for that user. That use case, >> which is exactly how it should be. Right? So last question, Jeff, before we wrap up, you already talked about how excited you were with some of the things in the Kino was day one of to >> me >> kind of expectations or hopes and dreams for what you're going to learn the rest of today and tomorrow that will help evolve the Presidio Cisco partnership. >> I mean, one thing is just making connections out here, Uh, but learning? I think so. I'm a collab guy and I'm getting to be more of a developer, and that's making me more of a generalist again. Because as a developer, yu have to interact with more than just collab FBI's. I'm getting into wireless and enterprise and everything security. So what I get out of combat is like, this is going around seeing what's happening and other technologies and other verticals and once again, competitive ideas seeing what other people are doing. Adding to that telling them what I'm doing A >> lot of collaboration pun intended. >> Yeah, You like it If you like puns. The keynote tomorrow is gonna be amazing. >> Is it way watching? Excellent. Jeff, Thanks so much for joining. Joining me on the Cube today. We appreciate your time for Joe inferior. I'm Lisa Martin. You're watching the Cube live from Cisco Dove Net. Create twenty nineteen. Thanks for watching.