 It's theCUBE, covering the virtual Vertica Big Data Conference 2020, brought to you by Vertica. Hello everyone and welcome to theCUBE's exclusive coverage of the Vertica Virtual Big Data Conference. You're watching theCUBE, the leader in digital event tech coverage. And we're broadcasting remotely from our studios in Palo Alto and Boston. And we're pleased to be covering wall to wall this digital event. Now, as you know, originally BDC was scheduled this week at the new Encore Hotel and Casino in Boston. Their theme was Win Big with Big Data. Oh sorry, Win Big with Data, that's right, got it. And I know the community was really looking forward to that meetup, but look, we're making the best of it given these uncertain times. We wish you and your families good health and safety and this is the way that we're going to broadcast for the next several months. Now we want to unpack Colin Mahoney's keynote, but before we do that, I want to give a little context on the market. First, theCUBE has covered every BDC since its inception, since the BDC's inception that is. It's a very intimate event with a heavy emphasis on user content. Now historically, the data engineers and DBAs in the Vertica community, they comprise the majority of the content at this event. And that's going to be the same for this virtual or digital production. Now theCUBE is going to be broadcasting for two days. What we're doing is we're going to be concurrent with the virtual BDC. We got practitioners that are coming on the show, DBAs, data engineers, database gurus. We got security experts coming on and really a great lineup. And of course we'll also be hearing from Vertica execs Colin Mahoney himself right off the keynote, folks from product marketing, partners and a number of experts, including some from Micro Focus, which is the, of course, owner of Vertica. But I want to take a moment to share a little bit about the history of Vertica. The company, as you know, was founded by Michael Stonebreaker. And Vertica really started out as a SQL platform for analytics. It was the first or at least one of the first to really nail the MPP column store trend. Not only did Vertica have an early mover advantage in MPP, but the efficiency and scale of its software relative to traditional DBMS and also other MPP players is underscored by the fact that Vertica and the Vertica brand really thrives to this day. But I have to tell you, it wasn't without some pain and I'll talk a little bit about that. And I'm really talking about how we got here today. So first, you know, you think about traditional transaction databases like Oracle or IBM DB2 or even enterprise data warehouse platforms like Teradata. They were simply not purpose built for big data. Vertica was along with a whole bunch of other players like Netiza, which was bought by IBM, Astrodata, which is now Teradata, Actian, ParXL, which was the basis for Redshift, Amazon's Redshift, Green Plum, was bought in the early days by EMC. And these companies were really designed to run as massively parallel systems that smoked traditional RDBMS and EDW for particular analytic applications. You know, back in the big data days, I often joked that like an NFL draft there was a run on MPP players like when you see a run on pulling guards. You know, once one goes, they all start to fall. And that's what you saw with the MPP columnar stores, IBM, EMC, and then HP getting into the game. So it was like 2011 and Leo Apatecker, he was the new CEO of HP. Frankly, he had no clue in my opinion with what to do with Vertica and totally missed one of the biggest trends of the last decade, the data trend, the big data trend. HP picked up Vertica for a song. It wasn't disclosed, my guess is that it was around 200 million. So rather than build a bunch of smart tuck-ins around Vertica, which I always call the diamond in the rough, Apatecker basically permanently altered HP for years. He kind of ruined HP in my view with a $12 billion purchase of autonomy, which turned out to be one of the biggest disasters in recent M&A history. HP was forced to spin merge and ended up selling most of its software to Microsoft, Micro Focus. Luckily, during its time at HP, CEO Meg Whitman largely was distracted with what to do with the mess that she inherited from Apatecker. So Vertica was left alone. Now the upshot is Colin Mahoney, who was then the GM of Vertica and still is. By the way, he's really the CEO. You know, he just doesn't have the title. I actually think they should give that to him. But anyway, he's been at the helm the whole time. And Colin, as you'll see in our interview, is a rock star. He's got technical and business chops. People love him in the community. Vertica's culture is really engineering driven and they're all about data. Despite the fact that Vertica is a 15 year old company, they've really kept pace and not been polluted by legacy baggage. Vertica early on embraced Hadoop and the whole open source movement. And that helped give it tailwinds. It leaned heavily into cloud as we're going to talk about further this week. And they got a good story around machine intelligence and AI. So, whereas many traditional database players are really getting hurt and some are getting killed by cloud database providers, Vertica is actually doing a pretty good job of servicing its install base. It is in a reasonable position to compete for new workloads. On its last earnings call, the micro focus CFO, Stephen Murdoch, he said they're investing $70 to $80 million in two key growth areas, security and Vertica. Now, micro focus is running its SUSE play on these two parts of its business. What I mean by that is they're investing and allowing them to be semi autonomous, spending on R&D and go to market. And they have no hardware agenda unlike when Vertica was part of HP or HPE. I guess HP before the spin out. Now, let me come back to the big trend in the market today. And there's something going on around analytic databases in the cloud. You got companies like Snowflake and AWS with Redshift as we've reported numerous times and they're doing quite well. They're gaining share, especially of new workloads that are merging, particularly in the cloud nativist space. They combine scalable compute, storage and machine learning. And importantly, they're allowing customers to scale, compute and storage independent of each other. Why is that important? Because you don't have to buy storage every time you buy compute or vice versa and chunks. So if you scale them independently, you got granularity. Vertica is keeping pace and talking to customers, it's Vertica's lead heavily into the cloud, supporting all the major cloud platforms as we heard from Colin earlier today, adding Google. And while my research shows that Vertica has some work to do in cloud and cloud native to simplify the experience, it's more robust and mature stack, which supports many different environments, deep SQL, acid properties and DNA that allows Vertica to compete with these cloud native database suppliers. Now, Vertica might lose out in some of those native workloads, but I had to say my experience in talking to customers, if you're looking for a great MPP column store that scales and runs in the cloud or on-prem, Vertica is in a very strong position. Vertica claims to be the only MPP columnar store to allow customers to scale, compute and storage independently, both in the cloud and in hybrid environments on-prem, et cetera, cross clouds as well. So while Vertica may be at a disadvantage in a pure cloud native bake-off, it's more robust and mature stack combined with its multi-cloud strategy gives Vertica a compelling set of advantages. So we hear a lot of this from Colin Mahoney, who announced Vertica 10.0 in his keynote. He really emphasized Vertica's multi-cloud affinity, its EON mode, which really allows that separation or scaling of compute independent of storage both in the cloud and on-prem. Vertica 10, according to Mahoney, is making big bets on in-database machine learning. He talked about that AI and along with some advanced regression techniques. He talked about PMML models, Python integration, which was actually something that they talked about doing with Uber and some other customers. Now Mahoney also stressed the trend toward object stores and now Vertica now supports, let's see, S3 with EON. S3, EON in Google Cloud in addition to AWS and then pure in HDFS as well. They all support EON mode. Mahoney also stressed, as I mentioned earlier, big commitment to on-prem and the whole cloud optionality thing. So 10.0, according to Colin Mahoney, is all about really doubling down on these industry waves. As they say, enabling native PMML models, running them in Vertica and really doing all the work that's required around ML and AI. They also announced support for TensorFlow. So object store optionality is important, is what he talked about in EON mode, with the news of support for Google Cloud and as well as HDFS. And finally, a big focus on deployment flexibility. Migration tools which are a critical focus really on improving ease of use. And you hear this from a lot of customers. So these are the critical aspects of Vertica 10.0 and an announcement that we're going to be unpacking in all week with some of the experts that I talked about. So I'm going to close with this. My long-time co-host John Furrier and I have talked some time about this new cocktail of innovation. No longer is Moore's law the really main spring of innovation. It's now about taking all these data troves, bringing machine learning and AI into that data to extract insights and then operationalizing those insights at scale, leveraging cloud. And one of the things I always look for from cloud is if you've got a cloud play, you can attract innovation in the former startups. It's part of the success equation for, certainly for AWS and I think it's one of the challenges for a lot of the legacy on prem players. Vertica I think has done a pretty good job in this regard. And we're going to look this week for evidence of that innovation. One of the interviews that I'm personally excited about this week is a new wish company. I would consider them a startup called Zebrium. What they're doing is they're applying AI to do autonomous log monitoring for IT ops. And I'm interviewing Larry Lancaster, who's their CEO this week. And I'm going to press him on why he chose to run on Vertica and not a cloud database. This guy's a hardcore tech guru and I want to hear his opinion. Okay, so keep it right there. Stay with us. We're all over the Vertica virtual big data conference covering in-depth interviews and following all the news. So the cube is going to be interviewing these folks two days, wall-to-wall coverage. So keep it right there. We're going to be right back with our next guest right after this short break. This is Dave Vellante and you're watching the cube.