>>Good morning live from Las Vegas, Lisa Martin and Dave Lanta here covering snowflake summit 22. Dave, it's great to be here in person. The keynote we just came from was standing room only. In fact, there was overflow. People are excited to be back and to hear from the company in person the first time, since the IPO, >>Lots of stuff, lots of deep technical dives, uh, you know, they took the high end of the pyramid and then dove down deep in the keynotes. It >>Was good. They did. And we've got Doug Hench with us to break this down in the next eight to 10 minutes, VP and principle analyst at constellation research. Doug, welcome to the cube. >>Great to be here. >>All right, so guys, I was telling Dave, as we were walking back from the keynote, this was probably the most technical keynote I've seen in a very long time. Obviously in person let's break down some of the key announcements. What were some of the things Dave that stood out to you and what they announced just in the last hour and a half alone? >>Well, I, you know, we had a leave before they did it, but the unit store piece was really interesting to me cuz you know, the big criticism is, oh, say snowflake, that doesn't do transaction data. It's just a data warehouse. And now they're sort of reaching out. We're seeing the evolution of the ecosystem. Uh, sluman said it was by design. It was one of the questions I had for them. Is this just kind of happen or is it by design? So that's one of many things that, that we can unpack. I mean the security workload, uh, the, the Apache tables, we were just talking about thatt, which not a lot of hands went up when they said, who uses Apache tables, but, but a lot of the things they're doing seem to me anyway, to be trying to counteract the narrative, that snow, I mean that data bricks is put out there about you guys. Aren't open, you're a walled garden and now they're saying, Hey, we're we're as open as anybody, but what are your thoughts, Doug? >>Well, that's the, the iceberg announcement, uh, also, uh, the announcement of, of uni store being able to reach out to, to any source. Uh, you know, I think the big theme here was this, this contrast you constantly see with snowflake between their effort to democratize and simplify and disrupt the market by bringing in a great big tent. And you saw that great big tent here today, 7,000 people, 2,007,000 plus I'm told 2000 just three years ago. So this company is growing hugely quickly, >>Unprecedented everybody. >>Yeah. Uh, fastest company to a billion in revenue is Frank Salman said in his keynote today. Um, you know, and I think that there's, there's that great big tent. And then there's the innovations they're delivering. And a lot of their announcements are way ahead of the J general availability. A lot of the things they talked about today, Python support and some, some other aspects they're just getting into public preview. And many of the things that they're announcing today are in private preview. So it could be six, 12 months be before they're generally available. So they're here educating a lot of these customers. What is iceberg? You know, they're letting them know about, Hey, we're not just the data warehouse. We're not just letting you migrate your old workloads into the cloud. We're helping you innovate with things like the data marketplace. I see the data marketplace is really crucial to a lot of the announcements they're making today. Particularly the native apps, >>You know, what was interesting sluman in his keynote said we don't use the term data mesh, cuz that means has meaning to the people, lady from Geico stood up and said, we're building a data mesh. And when you think about, you know, the, those Gemma Dani's definition of data mesh, Snowflake's actually ticking a lot of boxes. I mean, it's it's is it a decentralized architecture? You could argue that it's sort of their own wall garden, but things like data as product we heard about building data products, uh, uh, self-serve infrastructure, uh, computational governance, automated governance. So those are all principles of Gemma's data mesh. So I there's close as anybody that, that I've seen with the exception of it's all in the data cloud. >>Why do you think he was very particular in saying we're not gonna call it a data mesh? I, >>I think he's respecting the principles that have been put forth by the data mesh community generally and specifically Jamma Dani. Uh, and they don't want to, you know, they don't want to data mesh wash. I mean, I, I, I think that's a good call. >>Yeah, that's it's a little bit out there and, and it, they didn't talk about data mesh so much as Geico, uh, the keynote or mentioned their building one. So again, they have this mix of the great big tent of customers and then very forward looking very sophisticated customers. And that's who they're speaking to with some of these announcements, like the native apps and the uni store to bring transactional data, bring more data in and innovate, create new apps. And the key to the apps is that they're made available through the marketplace. Things like data sharing. That's pretty simple. A lot of, uh, of their competitors are talking about, Hey, we can data share, but they don't have the things that make it easy, like the way to distribute the data, the way to monetize the data. So now they're looking forward monetizing apps, they changed the name from the data marketplace to the, to the snowflake marketplace. So it'll be apps. It will be data. It'll be all sorts of innovative products. >>We talk about Geico, uh, JPMC is speaking at this conference, uh, and the lead technical person of their data mesh initiative. So it's like, they're some of their customers that they're putting forth. So it's kind of interesting. And then Doug, something else that you and I have talked about on the, some of the panels that we've done is you've got an application development stack, you got the database over there and then you have the data analytics stack and we've, I've said, well, those things come together. Then people have said, yeah, they have to. And this is what snowflake seems to be driving towards. >>Well with uni store, they're reaching out and trying to bring transactional data in, right? Hey, don't limit this to analytical information. And there's other ways to do that, like CDC and streaming, but they're very closely tying that again to that marketplace, with the idea of bring your data over here and you can monetize it. Don't just leave it in that transactional database. So a, another reach to a broader play across a big community that they're >>Building different than what we saw last week at Mongo, different than what you know, Oracle does with, with heat wave. A lot of ways to skin a cat. >>That was gonna be my next question to both of you is talk to me about all the announcements that we saw. And, and like we said, we didn't actually get to see the entire keynote had come back here. Where are they from a differentiation perspective in terms of the competitive market? You mentioned Doug, a lot of the announcements in either private preview or soon to be public preview early. Talk to me about your thoughts where they are from a competitive standpoint. >>Again, it's that dichotomy between their very forward looking announcements. They're just coming on with things like Python support. That's just becoming generally available. They're just introducing, uh, uh, machine learning algorithms, like time series built into the database. So in some ways they're catching up while painting this vision of future capabilities and talking about things that are in development or in private preview that won't be here for a year or two, but they're so they're out there, uh, talking about a BLE bleeding edge story yet the reality is the product sometimes are lagging behind. Yeah, >>It's interesting. I mean, they' a lot of companies choose not to announce anything until it's ready to ship. Yeah. Typically that's a technique used by the big whales to try to freeze the market, but I think it's different here. And the strategy is to educate customers on what's possible because snowflake really does have, you know, they're trying to differentiate from, Hey, we're not just a data warehouse. We have a highly differentiatable strategy from whether it's Oracle or certainly, you know, Mongo is more transactional, but, but you know, whether it's couch base or Redis or all the other databases out there, they're saying we're not a database, we're a data cloud. <laugh> right. Right. Okay. What is that? Well, look at all the things that you can do with the data cloud, but to me, the most interesting is you can actually build data products and you can monetize that. And their, the emphasis on ecosystem, you, they look at Salman's previous company would ServiceNow took a long time for them to build an ecosystem. It was a lot of SI in smaller SI and they finally kind of took off, but this is exceeding my expectations and ecosystem is critical because they can't do it all. You know, they're gonna O otherwise they're gonna spread themselves to >>That. That's what I think some competitors just don't get about snowflake. They don't get that. It's all about the community, about their network that they're building and the relationships between these customers. And that they're facilitating that with distribution, with monetization, things that are hard. So you can't just add sharing, or you can share data from one of their, uh, legacy competitors, uh, in, in somebody else's marketplace that doesn't facilitate the transaction that doesn't, you know, build on the community. Well, >>And you know, one of the criticisms too, of the criticism on snowflake goes, they don't, you know, they can't do complex joins. They don't do workload management. And I think their answer to that is, well, we're gonna look to the ecosystem to do that. Or you, you saw some kind of, um, cost governance today in the, in the keynote, we're gonna help you optimize your spend, um, a little different than workload management, but related >>Part of their governance was having a, a, a node, uh, for every workload. So workload isolation in that way, but that led to the cost problems, you know, like too many nodes with not enough optimization. So here too, you saw a lot of, uh, announcements around cost controls, budgets, new features, uh, user groups that you could bring, uh, caps and guardrails around those costs. >>In the last couple minutes, guys talk about their momentum. Franks Lutman showed a slide today that showed over 5,900 customers. I was looking at some stats, uh, in the last couple of days that showed that there is an over 1200% increase in the number of customers with a million plus ARR. Talk about their momentum, what you expect to see here. A lot of people here, people are ready to hear what they're doing in person. >>Well, I think this, the stats say it all, uh, fastest company to a, to a billion in revenue. Uh, you see the land and expand experience that many companies have and in the cost control, uh, announcements they were making, they showed the typical curve like, and he talked about it being a roller coaster, and we wanna help you level that out. Uh, so that's, uh, a matter of maturation. Uh, that's one of the downsides of this rapid growth. You know, you have customers adding new users, adding new clusters, multi clusters, and the costs get outta control. They want to help customers even that out, uh, with reporting with these budget and cost control measures. So, uh, one of the growing pains that comes with, uh, adding so many customers so quickly, and those customers adding so many users and new, uh, workloads quickly, >>I know we gotta break, but last point I'll make about the key. Uh, keynote is SL alluded to the fact that they're not taking the foot off the gas. They don't see any reason to, despite the narrative in the press, they have inherent profitability. If they want to be more profitable, they could be, but they're going for growth >>Going for growth. There is so much to unpack in the next three days. You won't wanna miss it. The Cube's wall to oil coverage, Lisa Martin for Dave Valenti, Doug hen joined us in our keynote analysis. Thanks so much for walking, watching stick around. Our first guest is up in just a few minutes.