 From Cambridge, Massachusetts, it's theCUBE, covering MIT Chief Data Officer and Information Quality Symposium 2019, brought to you by SiliconANGLE Media. Welcome back to Cambridge, Massachusetts, everybody. You're watching theCUBE, the leader in tech coverage. My name is Dave Vellante. I'm here with my co-host, Paul Gillum. This is day one of our two-day coverage of the MIT CDO IQ conferences. CDO, Chief Data Officer IQ Information Quality. Colin Mahoney is here, good friend and longtime CUBE alum. I haven't seen you in a while, but thank you so much for taking some time. You're like a special guest. Thank you. Yeah, it's great to be here. Thank you. So this is not something that you would normally attend. I caught up with you, invited you in. This conference started as back office governance, information quality, kind of wonky stuff hidden. And then when the big data meme took off, kind of around the time we met, the Chief Data Officer role emerged, the whole Hadoop thing exploded, and then this conference kind of got bigger and bigger and bigger. Still intimate, but very high level, very senior. It's kind of come full circle, as we've been saying. Information quality still matters. You have been in this data business forever, so I wanted to invite you in just to get your perspectives, we'll talk about what's new with what's going on in your company, but let's go back a little bit. When we first met and even before, you saw it coming, you kind of invested your whole career into data. So take us back 10 years, and it was so different. Remember it was batch, it was a dupe, but it was cool. It was a lot of cool projects going on, and it's still cool, but take a look back. Yeah, so it's changed a lot. Look, I got into it a while ago. I've always loved data. I had no idea the explosion and the three V's of data that we've seen over the last decade, but data's really important, and it's just gonna get more and more important. But as I look back, I think what's really changed, and even if you just go back a decade, I mean, there is an insatiable appetite for data, and that is not slowing down. It hasn't slowed down at all. And I think everybody wants that perfect solution that they can ask any question and get immediate answers to. We went through the Hadoop boom. I had argued that we're going through the Hadoop bust, but what people actually want is still the same. They want real answers, accurate answers. They want them quickly, and they want it against all their information, all their data. And I think that Hadoop evolved a lot as well. It started as one thing 10 years ago with MapReduce, and I think in the end, what it's really been about is disrupting the storage market. But if you really look at what's disrupting storage right now, public clouds, S3, right? That's the new data lake. So there's always a lot of hype cycles. Everybody talks about, now it's cloud, everything. For maybe the last 10 years, it was a lot of Hadoop. But at the end of the day, I think what people want to do with data is still very much the same. And a lot of companies are still struggling with it, hence the role for Chief Data Officers to really figure out how do I monetize data on the one hand and how do I protect that asset on the other hand? Well, so, and the cool thing is, so this conference is not a tech conference, really. And we love tech. We love talking about this. This is why I love having you on. We kind of have a little Vertica thread that I've created here. So Colin essentially is the current CEO of Vertica. I know that's not your title or your GM and CEO Vice President, but you're running Vertica. So Michael Stonebreaker's coming on tomorrow. Chris Lynch is coming on tomorrow. We got Andy Palmer coming up tomorrow. So we have this connection. Why is that important? It's because Vertica is a very cool company and it was all about data and it was all about disrupting sort of the traditional relational database kind of doing more with data. And if you go back to the roots of Vertica, it was like, how do you do things faster? How do you really take advantage of data to really drive new business? And that's kind of what it was all about. And the tech behind it is really cool. We did your conference for many, many years. It's coming back, by the way. Is it? Yeah, this March, so March 30th. Oh, wow. Mark that down. I'm Boston at the new Encore Hotel. You've got to have a cube there, bro. Yeah, that's great. And yeah, you've done that conference with me before. So very cool customers, kind of leading edge. Yep. So I want to get to some of that, but let's talk the disruption for a minute. So you guys started with the whole architecture, MPP and so forth, and you talked about cloud. Cloud really disrupted Hadoop. What are some of the other technology disruptions that you're seeing in the market space? I think, I mean, it's hard not to talk about AI and machine learning and what one means versus the other, who knows, right? But I think one thing that is definitely happening is people are leveraging the volumes of data and they're trying to use all the processing power and storage power that we have to do things that humans either are too expensive to do or simply can't do at the same speed and scale. And so I think we're going through a renaissance where a lot more is being automated. Certainly on the Vertica roadmap, and our path has always been, initially you get the data in and then we want the platform to do a lot more for our customers. Lots more analytics, lots more machine learning in the platform. So that's definitely been a lot of the buzz around, but what's really funny is when you talk to a lot of customers, they're still struggling with just some basic stuff. Like forget about the predictive thing. First, you got to get to what happened in the past. Like let's give accurate reporting on what's actually happening. The other big thing I think is a disruption is, I think IOT, for all the height that it's getting, it's very real. Every device is kicking off lots of information. The feedback loop of A-B testing or quality testing for predictive maintenance, it's happening almost instantly. And so you're getting massive amounts of new data coming in. It's all this machine sensor type data. You got to figure out what it means really quick and then you actually have to do something and act on it within seconds. And that's a whole new area for so many people. That's not the traditional enterprise data warehouse. And back to your comment on Stonebreaker, he got a lot of this right from the beginning. And I think he looked at the architectures. He took a lot of the best in class designs. We didn't necessarily invent everything, but we put a lot of that together. And then I think the other thing you got to do is constantly reinvent your platform. We came out with our Eon mode to run cloud native. We just got rated the top cloud data warehouse from a net promoter score rating perspective. So, but we got to keep going. We got to keep reinventing ourselves but leverage everything that we've done in the past as well. So, one of the things you said which is kind of relevant for here, Paul, is you're still seeing a real data quality issue that customers are wrestling with. And that's a big theme here, isn't it? Absolutely. And the, I mean, it's, what sort of goes around comes around. As Dave said earlier, that we're still talking about information quality 13 years after this conference began. Have the tools to improve quality improved all that much? I think the tools have improved. I think that's another area where machine learning, you know, if you look at Tamer and I know you're going to have Andy here tomorrow, they're leveraging a lot of the augmented things you can do with the processing to make it better. But I think one thing that makes the problem worse now is it's gotten really easy to pour data in. It's gotten really easy to store data without having to have the right structure, the right quality, you know, 10 years ago, 20 years ago, everything was perfect before it got into the platform, right? Everything was, there was quality, everything was there. What's been happening over the last decade is you're pumping data into these systems. Nobody knows if it's redundant data. Nobody knows if the quality is any good. And the amount of data is massive. It's cheap to store. So people keep pumping it in. But I think that creates a lot of issues when it comes to data quality. So I do think the technology has gotten better. I think there's a lot of companies that are doing a great job with it. But I think the challenge has definitely upped. So, go ahead. I'm sorry, you mentioned earlier that we're seeing the death of Hadoop. I'd like you to elaborate on that. Hadoop actually came up this morning in the keynote. It's part of what Axl Smith Klein did. Came up in a conversation I had with the CEO of Experian last week. I mean, it's still out there. Why do you think it's in decline? I think, I mean, first of all, if you look at the Hadoop vendors that are out there, they've all been struggling. I mean, some of them are shutting down. You know, two of them have merged and they've gotten killed lately. I think there are some very successful implementations of Hadoop. I think Hadoop as a storage environment is wonderful. I think it can process a lot of data on Hadoop. But the problem with Hadoop is it became the panacea that was going to solve all things data. It was going to be the database. It was going to be the data warehouse. It was going to do everything. That's usually the kiss of death, isn't it? It's the kiss of death. And the killer app on Hadoop, ironically, became SQL. I mean, SQL is the killer app on Hadoop. If you want a SQL engine, you don't need Hadoop. But what we did was in the beginning, Mike sort of made fun of it, Stonebreaker, and joked a lot about he's heard of MapReduce. It's called Group Buy. And that created a lot of tension between the early Vertica and Hadoop. I think in the end, we embraced it. We sit next to Hadoop. We sit on top of Hadoop. We sit behind it. We sit in front of it. It's there. But I think what the reality check of the industry has been, certainly by the business folks in these companies, it has not fulfilled all the promises. It has not fulfilled a fraction of the promises that they bet on. And so they need to figure those things out. So I don't think it's going to go away completely, but I think its best success has been disrupting the storage market. And I think there's some much larger disruptions of technologies that, frankly, are better than HDFS to do that. And the cloud, it was a game changer. A lot of murder in the cloud. Which is ironic, you know, cloud era. They didn't really have a cloud strategy. Not that it's Hortonworks, not that it's MapR. And, you know, just so happened Amazon had one. Google had one. Microsoft has one. So it's just convenient. How is that affecting your business? I mean, we're seeing this massive migration to the cloud. It's actually been great for us. So one of the things about Vertica is we run everywhere. And we made a decision a while ago. We had our own data warehouses of service offering. It might have been ahead of its time. Never really took off. What we did instead is we pivoted and we said, you know what, we're going to invest in that experience. So it's a SaaS-like experience, but we're going to let our customers have full control over the cloud. And if they want to go to Amazon, they can. If they want to go to Google, they can. If they want to go to Azure, they can. And we really invested in that and that experience. We're up on the Amazon marketplace. We have lots of customers running up on Amazon cloud, as well as Google and Azure now. And then about two years ago, we went down and did this endeavor to completely re-architect our product so that we could separate compute and storage so that our customers could actually take advantage of the cloud economics as well. That's been huge for us. So you scale independently. Scale independently, cloud-native, add compute, take away compute. And for our existing customers, they're loving the hybrid aspect. They love that they can still run on-premise. They love that they can run up on a public cloud. They love that they can run in both places. So we will continue to invest a lot in that. And it is really, really important. And frankly, I think cloud has helped Vertica a lot because being able to provision hardware quickly, being able to tie into these public clouds, into our customers' accounts, give them control, has been great. And we're going to continue on that path. It's Vertica's an ISV. I mean, your software company. We're a software company. And I know you were part of HP for a while, and HP wanted to mash that in and run on its hardware, but software runs great in the cloud. I mean, to you, it's another hardware platform. It's another hardware platform. What do you care? So give us the update on micro-focus. Micro-focus acquired Vertica as part of the HPE software business. How many years ago now? Two years ago? Less than two years ago, yeah. Okay, so how's that going? It's going great. There's the update here. Yeah, so first of all, I mean, it is great. HP and HP were wonderful to Vertica, but it's great being part of a software company. Micro-focus is a software company. And more than just a software company, it's a company that has a lot of experience bridging the old and the new. Leveraging all the investments you've made, but also thinking about cloud and all these other things that are coming down the pike. I think for Vertica, it's been really great because as you've seen, Vertica's gotten its identity back again. And that's something that Micro-focus is very good at. You can look at what Micro-focus did with SUSE, the Linux company, which actually now just recently spun out of Micro-focus, but letting organizations like Vertica that have this culture, have this product, have this passion, really focus on our market and our customers and doing the right thing by then has been just really great for us and operating as a software company. The other nice thing is that we do integrate with a lot of other products, some of which came from the HPE side, some of which came from Micro-focus. Security products is an example. The other really nice thing is we've been doing this sort of in-source thing at Micro-focus where we open up our source code to some of the other teams in Micro-focus and they've been contributing now in amazing ways to the product in ways that we just never would be able to scale, but with 4,000 engineers strong in Micro-focus, we've got a much larger development organization that can actually contribute to the things that Vertica needs to do. And as we go into the cloud and as we do a lot more operational aspects, the experience that these teams have has been incredible and security's another great example there. So overall it's been great. We've had four different owners of Vertica. Our job is to continue what we do on the innovation side and the culture, but so far Micro-focus has been terrific. Well, I'd like to say you're kind of getting that mojo back because you guys as an independent company were doing your own thing and then you did for a while inside of HPE. We did. And then that obviously changed because they wanted more integration, but in Micro-focus they know what they're doing. They know how to do acquisitions. They've been very successful. It's a very well-run company. Operationally. This HPE was really interesting spinning that out because now RELL is part of IBM. So now you've got, you know, SUSE as the lone independent. Alone independent, yeah. I do want to go back to a technology question. Are, is NoSQL the next Hadoop? I mean, are these databases, it seems to be that the hot fad now is NoSQL. It can do anything. Is the promise overblown? I, you know, I think, I mean, NoSQL has been out almost as long as Hadoop. And I, you know, we always say not only SQL, right? Mike said this from day one, best tool for the job. You know, nothing is going to do every job well. So I think that there are, you know, whether it's key value stores or other types of NoSQL engines, document DBs, now you have some of these DBs that are running on different chips. I mean, there's always, yeah, graph DBs. There's always going to be specialty things. I think one of the things about our analytic platform is we can do like time series is a great example. Vertica is a great time series database. We can compete with specialized time series databases, but we also offer a lot of the other things that you can do with Vertica that you wouldn't be able to do in a database like that. So I always think there's going to be specialty products. I also think some of these can do a lot more workloads than you might think, but I don't see as much around the NoSQL movement is say I did a few years ago. But so, and you mentioned the cloud before is kind of your position that I think is a tailwind, not to put words in your mouth, but you're in the Amazon marketplace. I mean, they have products that are competitive. They do, they do. But so how are you differentiating there? I think the way we differentiate, whether it's Redshift from Amazon or BigQuery from Google or even what Azure DB does is first of all, Vertica I think from feature functionality and performance standpoint is ahead, number one. I think the second thing, and we hear this from a lot of customers, especially at the C level is they don't want to be locked into these full stacks of the clouds. Having the ability to take a product and run it across multiple clouds is a big thing because the stack lock-in now, the full stack lock-in of these clouds is scary. It's really easy to develop in their ecosystems, but you get very locked into them. And I think a lot of people are concerned about that. So that works really well for Vertica. But I think at the end of the day, it's just the robustness of the product. We continue to innovate. When you look at separating compute and storage, believe it or not, a lot of these cloud native databases don't do that. And so we can actually leverage a lot of the cloud hardware better than the native cloud databases do themselves. So like I said, we have to keep going. Those guys aren't going to stop. And we actually have great relationships with those companies. We work really well with the clouds. They seem to care just as much about their cloud ecosystem as their own database products. And so I think that's going to continue as well. Well, Colin, congratulations on all the success. It's awesome to see you again. And really appreciate it coming to you. I appreciate the invite. It's great to be here. All right. Keep it right there, everybody. Paul and I will be back with our next guest from MIT. You're watching The Cube.