 From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Dave Vellante. Hi everybody, welcome to this special CUBE Insights, powered by ETR, Enterprise Technology Research, our partner who's got this database, this of the spending data. And what we're going to do is a breaking analysis on the analytic database market. We're seeing that cloud and cloud players are disrupting that marketplace. And that marketplace really traditionally has been known as the Enterprise Data Warehouse Market. So Alex, if you wouldn't mind bringing up the first slide, I want to talk about some of the trends in the traditional EDW market. I almost don't like to use that term anymore because it's sort of a pejorative. But let's look at it. It's a very large market. It's about $20 billion today, growing at high single digits, low double digits. It's expected to be in the $30 to $35 billion size by mid-next decade. Now historically, this is dominated by Teradata who started this market really back in the 1980s with the first appliance, the first converged appliance. Oracle with Exadata, IBM, I'll talk about IBM, a little bit, they bought a company called Natesa back in the day. And basically this month just basically killed Natesa and killed the brand. Microsoft has entered the fray. And so it's been a fairly large market. But I say it's failed to really live up to the promises that we heard about in the late 90s, early parts of the 2000, namely that you were going to be able to get a 360 degree view of your data and you're going to have this flexible, easy access to the data. You know, the reality is data warehouses were really expensive. They were slow. You had to go through a few experts to get data. It took a long time. I tell you, I've done a lot of research in this space. When you talked to the data warehouse practitioners, they would tell you, we always had to chase the chips. Anytime Intel would come out with a new chip, we'd force it in there because we just didn't have the performance to really run the analytics as we needed to. It just took so long. One practitioner described it as a snake swallowing a basketball. So you've got all those data, which is the sort of metaphor for the basketball. Just really practitioners at a hard time standing up infrastructure. And what happened is a spade of new players came into the marketplace, these MPP players, trying to disrupt the market. You had Vertica, who was eventually purchased by HP and then they sold them to Micro Focus. Green Plum was bought by EMC and really, you know, the company is de-emphasized. Green Plum, Netiza, $1.7 billion acquisition by IBM. IBM just this month, month killed the brand. They're kind of, you know, refactoring everything. Pyrexcel was interesting. It was a company based on an open source platform that Amazon, AWS did a one time license with and created Redshift. It actually put a lot of innovation. Redshift is really doing well. We'll show you some data on that. We've also at the time, saw a major shift toward unstructured data and much, much greater emphasis on analytics. It coincided with Hadoop, which also disrupted the market economics. I often joked that the ROI of Hadoop was reduction on investment. And so you saw all these data lakes being built. And of course they turned into data swamps. And yet dozens of companies come into the database space, which used to be rather boring, but Amazon with DynamoDB, SAP with HANA, data stacks, Redis, Mongo, you know, Snowflake is another one that I'm going to talk about in detail today. So you started to see the blurring of lines between relational and non-relational. And what was once thought of is no SQL, became not only SQL, SQL became the killer app for Hadoop. And so at any rate, you saw this new class of data stores emerging. And Snowflake was one of the more interesting and I want to share some of that data with you, some of the spending intentions. So over the last several weeks and months, we've shared spending intentions from ETR, Enterprise Technology Research. They're a company that manages the spending data and has a panel of about 4,500 end users. They go out and do spending intention surveys periodically. So Alex, if you bring up the survey data, I want to show you this. So this is spending intentions and what it shows is that the public cloud vendors in Snowflake who really is a database as a service offering, so cloud like, are really leading the pack here. So this sector that I'm showing is the Enterprise Data Warehouse and I've added in the analytics, business intelligence and big data section. So what this chart shows is the vendor on the left-hand side and then this bar chart has colors. The red is relieving the platform. The gray is our spending will be flat. So this is from the July survey. Expectations for the second half of 2019. So gray is flat. The dark green is increase and the lime green is we are a new customer coming on to the platform. So if you take the greens and subtract out the red, and there's two reds, the dark red is leaving, the lighter red is spending less. So if you subtract the reds from the greens, you get what's called the net score. So the higher the net score, the better. So you can see here the net score of Snowflake is 81%. So the very, very high. You can also see AWS and Microsoft are very high and Google. So the cloud vendors of which I would consider Snowflake, a cloud vendor, I got the cloud model, all kicking butt. Now look at Oracle, look at the incumbents. Oracle, IBM and Teradata. Oracle and IBM are in the single digits for a net score and Teradata is in a negative 10%. So that's obviously not a good sign for those guys. So you're seeing share gains from the cloud company, Snowflake, AWS, Microsoft and Google, at the expense of certainly of Teradata, but likely IBM and Oracle. Oracle is a little different animal. They've got Exadata and they're putting a lot of investments in there. Maybe talk about that a little bit more. Now you see on the right-hand side this black says shared accounts. So the N in this survey, this July survey that ETR did is 1,068. So of 1,068 customers, ETR is asking them, okay, what's your spending going to be on enterprise data warehouse and analytics big data platforms? And you can see the number of accounts out of that 1,068 that are being cited. So Snowflake only had 52 and I'll show you some other data from past surveys. AWS 319, Microsoft the big whale here, a trillion dollar valuation, 851 going down the line. You see Oracle, a very large number in Teradata and IBM pretty large as well. Certainly enough to get statistically valid results. So take away here is Snowflake, very, very strong and the other cloud vendors, the hyperscalers, AWS, Microsoft and Google and their data stores doing very well in the marketplace and challenging the incumbents. Now the next slide that I want to show you is a time series for selected suppliers. I can only show five on this chart. But it's the spending intentions again in that EDW and analytics BI big data segment. And it shows the spending intentions from January 17 survey all the way through July 19. So you can see the periods that ETR takes this, the snapshots and again, the latest July survey is over 1,000 N. The other ones are very, very large too. So you can see here at the very top, Snowflake is that yellow line and they just showed up in the January 19 survey. And so you're seeing now, actually go back one, yeah January 19 survey and then you see them in July. You see the net score, the July net score that I'm showing that 35, that's the number of accounts out of the corpus of data that Snowflake had in the survey back in January. And now it's up to 52. You can see they lead the pack. It just in terms of the spending intentions in terms of mentions, AWS and Microsoft also up there very strong. You see a big gap down to Oracle and Teradata. And I didn't show IBM, I didn't show Google. Google actually would be quite high too just around where Microsoft is. But you can see the pressure that the cloud is placing on the incumbents. So what are the incumbents going to do about it? Well, certainly you're going to see in the case of Oracle spending a lot of money trying to maybe rethink the architecture, refactor the architecture. Oracle Open World's coming up shortly. I'm sure you're going to see a lot of new announcements around Exadata. They're putting a lot of wood behind the Exadata arrow. So we'll keep in touch with that and stay tuned. But you can see again, the big takeaways here is the cloud guys are really disrupting the traditional EDW marketplace. All right, let's talk a little bit about Snowflake. So I'm going to highlight those guys and maybe give a little bit of inside baseball here. But what you need to know about Snowflake, so I've put some points here, just some quick points on the slide, Alex, if you want to bring that up. Very fast growing cloud and SaaS based data warehousing player. Growing that couple hundred percent annually, they're annual recurring revenue, very high. These guys are getting ready to do an IPO. I'll talk about that a little bit. They were founded in 2012, and it kind of came out of stealth and hiding in 2014 after bringing Bob Muglia on from Microsoft as the CEO. It was really, the background of these guys is they're three engineers from Oracle who are probably bored out of their mind. And we're like, you know what? We got this great idea. Why should we give it to Oracle? Let's go pop out and start a company. And as such, they started Snowflake. They really are disrupting the incumbents. They've raised over $900 million in venture and they've got almost a $4 billion valuation. Last May, they brought on Frank Slutman. And this is really a pivot point, I think, for the company. And they're getting ready to do an IPO. And so let's talk a little bit about that in a moment. But before we do that, I want to bring up just this really simple picture. Alex, if you bring this slide up, this block diagram. This is like a kindergarten, so that people like, I can even understand it. But basically the innovation around the Snowflake architecture was that they separated their claim is that they separated the storage from the compute. And they've got this other layer called cloud services. So let me talk about that for a minute. Snowflake fundamentally rethought the architecture of the data warehouse to really try to take advantage of the cloud. So traditionally, enterprise data warehouses are static. You've got infrastructure that kind of dictates what you can do with the data warehouse. So you got to predict your peak needs and you bring in a bunch of storage and compute and you say, okay, here's the infrastructure. And this is what I got, it's static. If your workload grows or some new compliance regulation comes out or some new data set has to be analyzed, well, this is what you got. You got your infrastructure and yeah, you can add to it in chunks of compute and storage together or you can fork lift out and put in new infrastructure or you can chase more chips. As I said, it's that snake swallowing of basketball was not pretty. So very static situation. And you have to over provision whereas the cloud is all about, you know, pay by the drink. And it's about elasticity and non-demand resources. You got cheap storage and cheap compute and you can just pay for it as you use it. So the innovation from Snowflake was to separate the compute from storage so that you could independently scale those and decoupling those in a way that allowed you to sort of tune the knobs. Oh, I need more compute, dial it up. I need more storage, dial it up or dial it down and pay for only what you need. Now, another nuance here is traditionally the computing in data warehousing happens on one cluster. So you got contention for the resources of that cluster. What Snowflake does is you can spin up a warehouse on the fly. You can size it up, you can size it down based on the needs of the workload. So that workload is what dictates the infrastructure. Also, in Snowflake's architecture, you can access the same data from many, many different warehouses. So you got, again, that three layers that I'm showing here, the storage, the compute and the cloud services. So let me go through some examples so you can really better understand this. So you say you got storage data, you got customer data, you got order data, you got log files, you might have parts data, what's an inventory kind of thing. And you want to build warehouses based on that data. You might have marketing warehouse, you might have a sales warehouse, you might have a finance warehouse. Maybe there's a supply chain warehouse. So again, by separating the compute from that sort of virtualized compute from the storage layer, you can access any data, leave the data where it is, and I'll talk about this and bring the compute to the data. So that's what, in part, the cloud layer does. They've got security and governance, they've got data warehouse management in that cloud layer and resource optimization. But the key, in my opinion, is this metadata management. I think that's part of Snowflake's secret sauce, is the ability to leave data where it is and have the smarts and the algorithms to really efficiently bring the compute to the data so that you're not moving data around. If you think about how traditional data warehouses work, you put all the data into a central location so you can operate on it. Well, that data movement takes a long, long time. It's very, very complicated. So that's part of the secret sauce, is knowing what data lives where and efficiently bringing that compute to the data, this dramatically improves performance. It's a game changer and it's much, much less expensive. Now, I want to come back to Frank Slutman. This is somebody that I've, is a career that I've followed, I've known, had him on theCUBE a number of times. I first met Frank Slutman when he was at Data Domain. He took that company, took it public, and then sold it. Originally, NetApp made a bid for the company. EMC, Joe Tucci, in a defensive play, said, no, we're not going to let NetApp get it. There was a little auction. He ended up selling the company for, I think, two and a half billion dollars. Slutman came in. He helped clean up the data protection business of EMC and then left, did a stint as a VC and then took over ServiceNow. When Slutman took over ServiceNow, and a lot of people know this, the ServiceNow is the shiny toy on Wall Street today. ServiceNow was a mess when Slutman took it over. It's about a hundred, $120 million company. He and his team took it to 1.2 billion, dramatically increased the valuation. And one of the ways they did that was by thinking about the TAM and expanding that TAM. That's part of a CEO's job, is TAM expansion. Slutman is also a great operational guy and he brought in an amazing team. To do that, I'll talk a little bit about that team. In fact, well, he just brought in Mike Scarpelli, who's the CFO, was the CFO of ServiceNow, brought him in to run finance for Snowflake. So you're seeing that playbook emerge. It'll be interesting. Beth White was the CMO at Data Domain. She was the CMO at ServiceNow, helped take that company. She's an amazing resource. She's kind of in retirement, she's young, but she's kind of in retirement doing some advisory roles. Wonder if Slutman will bring her back. I wonder if Dan McGee, who was ServiceNow's operational guru, wonder if he'll come out of retirement. How about Dave Schneider, who runs the sales team at ServiceNow? Well, he'll be lured over. We'll see. The kinds of things that Slutman looks for, just in my view of observing his playbook over the years. He looks for a great product, he looks for a big market, he looks for disruption, and he looks for off-the-chart ROI so his sales teams can go in and really make a strong business case to disrupt the existing legacy players. So one of the things I said that Slutman looks for is a large market. So let's look at this market. And this is the thing that people missed around ServiceNow, and to credit Pat myself and David Floor in the back. You know, we saw the TAM potential of ServiceNow as to be many, many tens of billions. You know, Gartner, when ServiceNow first came out, said, hey, I helped to ask, it's a small market, a couple billion dollars. We saw the potential to transform not only IT operations but go beyond help, desk, change management, et cetera, IT service management into lines of business. And we wrote a piece on Wikibon back then showing the potential TAM. And we think something similar could happen here. So the market today, let's call it 20 billion, growing to 30 billion, pretty big, first of all, but a lot of players in here. What if, so one of the things that we see, Snowflake potentially being able to do with its architecture and its vision is able to bring enterprise search to the marketplace. 80% of the data that's out there today sits behind firewalls, it's not searchable by Google. What if you could unlock that data and access it and query it anytime, anywhere, put the power in the hands of the line of business users to do that. Maybe think Google search for enterprises but with provenance and security and governance and compliance and the ability to run analytics for a line of business users. Just think of it as citizens data analytics. We think that TAM could be $70 plus billion. So just think about that in terms of how this company, this company, Snowflake, might go to market, by the time they do their IPO could be, they could be three, four, 500 million dollar company. So we'll see, we'll keep an eye on that. Now, because the market's so big, this is not like the ITSM, the market that ServiceNow was going after. They crushed BMC, HP was there but really not paying attention to it. IBM had a product, they had all these products that were old legacy products, they weren't designed for the cloud. And so, you know, ServiceNow was able to really crush that market and caught everybody by surprise and just really blew it out. There's a similar dynamic here in that these guys are disrupting the legacy players with a cloud-like model, but at the same time, so is Amazon with Redshift, so is Microsoft with its analytics platform. You know, Teradata is trying to figure it out. They've got an inertia of a large install base but it's a big on-prem install base. I think they struggle a little bit but their advantage is they've got customers locked in. Oracle with Exadata is very interesting. Oracle has burned the boats and gone to cloud first. And Oracle, mark my words, is re-architecting everything for the cloud. Now you can say, oh, Oracle, they're old school, they're old guard, that's fine. But one of the things about Oracle and Larry Ellison, they spend money on R&D. They're a very, very heavy investor in R&D and I think that, you know, you can see Exadata has actually been a very successful product. They will re-architect Exadata, believe you me, to bring compute to the data. They understand, you can't just move all this, InfiniBand is not going to solve their problem in terms of moving data around their architecture. So, you know, watch Oracle, you've got other competitors like Google who shows up well in the ETR surveys. They've got BigQuery and Bigtable and you've got a lot of other players here. Guys like DataStacks are in there and you've got Amazon with DynamoDB, you've got Couchbase, you've got all kinds of database players that are sort of blurring the lines, as I said, between SQL and NoSQL. But the real takeaway here from the ETR data is you've got Cloud, again, is winning. It's driving the discussion and the spending discussion within IT. Watch this company, Snowflake, they're going to do an IPO, I guarantee it, hopefully we'll see if they'll get in before the market turns down. But we've seen this play by Frank Slutman before on his team and the spending data shows that this company is hot, you see them all over Silicon Valley, you're seeing them show up in the spending data. So, we'll keep an eye on this, it's an exciting market, database market used to be kind of boring, now it's red hot. So there you have it folks, thanks for listening, it's Dave Vellante. Cube Insights, we'll see you next time.