 From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. As we've been reporting, there's a new class of workloads emerging in the cloud. You know, early cloud was all about IS, spinning up storage, compute, and networking infrastructure to support startups, SaaS, easy experimentation, dev test, and increasingly moving business workloads into the cloud. Modern cloud workloads are combining data. They're infusing machine intelligence into applications, AI. They're simplifying analytics and scaling with the cloud to deliver business insights in near real time. And at the center of this mega trend is a new class of data stores and analytic databases, what some call data warehouses, a term that I think is outdated really for today's speed of doing business. Welcome to this week's Wikibon CUBE Insights, powered by ETR. In this breaking analysis, we update our view of the emerging cloud native analytic database market. Today, we want to do three things. First, we'll update you on the basics of this market, what you really need to know in the space. Next thing we're going to do, is we're going to look into the competitive environment, and as always, we'll dig into the ETR spending data to see which companies have the momentum in the market and maybe ahead of some of the others. Finally, we're going to close with some thoughts on how the competitive landscape is likely to evolve. And we want to answer the question, will the cloud giants overwhelm the upstarts or will the specialist continue to thrive? Let's take a look at some of the basics of this market. We're seeing the evolution of the enterprise data warehouse market space. It's an area that has been critical to supporting reporting and governance requirements for companies, you know, especially post-Sarbanes-Oxley, right? However, historically, as I've said many times, EDW has failed to deliver on its promises of a 360 degree view of the business and real-time customer insights. Classic enterprise data warehouses are too cumbersome, they're too complicated, they're too slow and don't keep pace with the speed of the business. Now, EDW is about a $20 billion market, but the analytic database opportunity in the cloud we think is much larger. Why is that? It's because cloud computing unlocks the ability to rapidly combine multiple data sources, bring data science tooling into the mix, very quickly analyze data and deliver insights to the business. More importantly, even more importantly, allow the line of business pros to access data in a self-service mode. It's a new paradigm that uses the notion of DevOps as applied to the data pipeline, Agile data, or what we sometimes call data ops. This is a highly competitive marketplace. In the early part of last decade, you saw Google bring big query to market. Snowflake was founded, AWS did a one-time license deal to acquire the IP to par Excel, an MPP database on which it built Redshift. In the latter part of the decade, Microsoft threw its hat in the ring with SQL DW, which Microsoft has now evolved into Azure Synapse. They did so at the build conference a few weeks ago. And there are other players as well, like IBM. So you can see there's a lot at stake here. The cloud vendors want your data because they understand this is one of the key ingredients of the next decade of innovation. No longer is Moore's law the main spring of growth. We've said this many times. Rather today, it's data-driven and AI to push insights and scale with the cloud. Here's the interesting dynamic that is emerging in the space. Snowflake is a cloud specialist in this field having raised more than a billion dollars in venture, a billion, four, a billion, five. And it's up against the big cloud players who are moving fast and often stealing moves from Snowflake and driving customers to their respective platforms. Here's an example that we reported on at last year's re-invent. It's an article by Tony Baer. He wrote this on ZDNet talking about how AWS RA3 separates compute from storage. And of course, this was a founding architectural principle for Snowflake. Here's another example from the information. They were reporting on Microsoft here turning up the heat on Snowflake. And you can see the highlighted text where the author talks about Microsoft trying to divert customers to its database. So you got this weird dynamic going on. Snowflake doesn't run on prem. It only runs in the cloud, runs on AWS, runs on Azure, runs on GCP. The cloud players, again, they all want your data to go into their database. So they want you to put their data into their respective platforms. At the same time, they need SAS ISVs to run in the cloud because it sells infrastructure services. So is Snowflake, are they going to pivot to run on prem to try to differentiate from the cloud giants? I asked Frank Slutman, Snowflake CEO about the on-prem opportunity and his perspective earlier this year. Let's listen to what he said. Okay, we're not doing this endless hedging that people have done for 20 years, sort of keeping a leg in both worlds. Forget it, this will only work in the public cloud because this is how the utility model works, right? I think everybody is coming to this realization, right? I mean, the excuses are running out at this point. We think that people will come to the public cloud a lot sooner than we will ever come to the private cloud. It's not that we can't run a private cloud, it just diminishes the potential and the value that we bring. Okay, so pretty definitive statements by Slutman. Now the question I want to pose today is can Snowflake compete given the conventional wisdom that we saw in the media articles that the cloud players are going to hurt Snowflake in this market? And if so, how will they compete? Well, let's see what the customers are saying and bring in some ETR survey data. This chart shows two of our favorite metrics from the ETR data set. That is, net score, which is on the Y axis, net score remembers a measure of spending momentum and market share, which is on the X axis. Market share is a measure of pervasiveness in the data set. And what we show here are some of the key players in the EDW and cloud native analytic database market. I'm going to make a couple of points and then we'll dig into this a little bit further. First thing I want to share is you can see from this data, this is the April ETR survey which was taken at the height of the US lockdown for the pandemic. The survey captured respondents from more than 1200 CIOs and IT buyers asking about their spending intentions for analytic databases for the companies that we show here on this kind of XY chart. So the higher the company is on the vertical axis, the stronger the spending momentum relative to last year. And you can see Snowflake has a 77% net score. It leads all players with AWS Redshift showing very strong as well. Now in the box in the lower right, you see that chart. Those are the exact net scores for all the vendors and the shared end. Now shared end is the number of citations for that vendor within the end of the 1269. So you can see the ends are quite large, certainly large enough to feel comfortable with some of the conclusions that we're going to make today. Microsoft, they have a huge footprint and they somewhat skew the data with its very high market share due to its volume. And you can see where Google sits. It's a good momentum, not as much presence in the marketplace. We've also added a couple of on-prem vendors, Teradata and Oracle primarily on-prem, just for context. They're two companies that compete. They obviously have some cloud offerings, but again, most of their base is on-prem. So what I want to do now is drill into this a little bit more by looking at Snowflake within the individual clouds. So let's look at Snowflake inside of AWS. That's what this next chart shows. So it's customer spending momentum, NetScore, inside of AWS accounts. And we cut the data to isolate those ETR survey respondents running AWS. So there's an end there of 672 that you can see. The bars show the NetScore granularity for Snowflake and Amazon Redshift. And now note that we show 96 shared end responses for Snowflake and 213 for Redshift within the overall end of 672 AWS accounts. The colors show 2020 spending intentions relative to 2019. So let's read left to right here. The replacements are red and then, you know, that bright red. Then you see spending less by 6% or more. That's the pinkish and then flat spending, the gray, increasing spending by more than 6%. That's the forest green. And then adding to the platform new. That's the lime green. Now, remember, NetScore is derived by subtracting the reds from the greens. And you can see that Snowflake has more spending momentum in the AWS cloud than Amazon Redshift by a small margin. But look at 80% of the AWS accounts plan to spend more on Snowflake with 35%. They're adding new. Very strong, 76% of AWS customers plan to spend more in 2020 relative to 2019 on Redshift with only 12% adding the platform new. But nonetheless, both are very, very strong. And you can see here, the key point is minimal red and pink. So not a lot of people leaving. Not a lot of people spending less. It's going to be critical to see in the June each ETR survey, which is in the field this month, if Snowflake is able to hold on to these new accounts that it's gained in the last couple of months. Now let's look at how Snowflake is doing inside of Azure and compare it to Microsoft. So here's the data from the ETR survey. Same view of the data here, except we isolate on Azure accounts. The end there is 677 Azure accounts. And we show Snowflake and Microsoft cuts for analytic databases with 83 and 393 shared end responses respectively. So again, enough I feel to draw some conclusions from this data. Now note the net scores. Snowflake again, winning with 78% versus 51% for Microsoft. 51% is strong, but 78% is there's a meaningful lead for Snowflake within the Microsoft base. Very interesting. And once again, you see massive new ads. 41% for Snowflake, whereas Microsoft's net score is being powered really by growth from existing customers, that forest green. And again, very little red for both companies. So super positive there. Okay, let's take a look now at how Snowflake's doing inside of Google accounts, GCP, Google Cloud Platform. So here's the ETR data, same view of that data, but now we isolate on GCP accounts. There are fewer, 298, then you got those running Snowflake and Google analytic databases, largely BigQuery, but could be some others in there. But the Snowflake shared end is 49, it's smaller than on the other clouds because the company just announced support for GCP just about a year ago, I think it was last June. But still large enough to draw conclusions from the data, I feel pretty comfortable with that. We're not slicing and dicing it too finely. I mean, you can see Google shared in at 147. Look at the story, I sound like a broken record. Snowflake is again, winning by a meaningful margin, if you measure this net score or spending momentum. This is 77.6% net score versus Google at 54%. With Snowflake at 80% in the green, both companies, very little red. So this is pretty impressive. Snowflake has greater spending momentum than the captive cloud providers in all three of the big US based clouds. So the big question is, can Snowflake hold serve and continue to grow and how are they going to be able to do that? Look, as I said before, this is a very competitive market. We reported at how Snowflake is taking share from some of the legacy on-prem data warehouse players like Teradata and IBM. And from what our data suggests, you know, a little bit of Oracle too. I've reported how IBM has stretched thin on its research and development budget. Spends about $6 billion a year, but it's, you know, we've got to spend it across a lot of different lines. You know, Oracle's got more targeted spending R&D. They can target more toward database and direct more of its free cash flow to database than IBM can. But Amazon and Microsoft and Google, they don't have that problem. They spend a ton of dough on R&D. And here's an example of the challenge that Snowflake faces. Take a look at this partial list that I threw together of recent innovations. And we show here a set of features that Snowflake has launched in 2020 and AWS since re-invent last year. I don't have time to go into these, but we do know this, that AWS is no slouch at adding features. Amazon as a company spends two X more on research and development than Snowflake is worth as a company. So why do I like Snowflake's chances? Well, there are several reasons. First, every dime that Snowflake spends on R&D, go to market and ecosystem goes into making its databases better for its customers. Now I asked Frank Slutman in the middle of the lockdown how he was allocating precious capital during the pandemic. Let's listen to his response. You know, I've said there's no layoffs on our radar. Number one, number two, we are hiring. And number three is, you know, we have a higher level of scrutiny on the hires that we're making. And I am very transparent. In other words, I tell people, look, you know, I prioritize the roles that are closest to the direct train of the business, right? It's kind of common sense. But, you know, I wanted to make sure that this is how we're thinking about it. There are some roles that are more postponable than others. Miring and engineering without any reservation because that is the long-term, you know, strategic interest of the company on the field. But, you know, that's only part of the story. And so I want to spend a moment here on some other differentiation, which is multi-cloud. Now, as many of you know, I've been sort of cynical of multi-cloud up until recently. I've said that multi-cloud is a symptom, more of a symptom of multi-vendor and then largely a bunch of vendor marketing hooey to date. But that's beginning to change. I see multi-cloud as increasingly viable and important to organizations, not only because CIOs are being asked to clean up the crime scene, as I've often joked, but also because it's increasingly becoming a strategy, right cloud for the right workload. So, first, let me reiterate that I said with the top, new workloads are emerging in the cloud. Real-time AI, insight extraction, and real-time inferencing is going to be a competitive differentiator. It's all about the data. The new innovation cocktail stems from machine intelligence applied to that data with data science tooling and simplified interfaces that enable scaling with the cloud. You've got to have simplicity if you're going to scale. And cloud is the best way to scale. It's really the only way to scale globally. So as such, we see cross-cloud exploitation as a real differentiator for Snowflake and others that build high-quality cloud-native capabilities for multiple clouds. And I want to spend a minute on this topic generally and talk about what it means for Snowflake specifically. And we've been pounding the table lately saying that building capabilities natively for the cloud versus putting a wrapper around your stack and making it run in the cloud is key. There's a big difference, why is this? Because cloud native means taking advantage of the primitive capabilities within respective clouds to create the highest performance, the lowest latency, the most efficient services for that cloud. And the most secure, really exploiting that cloud. And this is enabled only by natively building in the cloud and that's why Sluteman is so dogmatic on this issue. Multi-cloud can be a differentiator for Snowflake. Look, think about it, data lives everywhere. And you want to keep data where it lives. Ideally, you don't want to have to move it, whether it's on AWS, Azure, whatever cloud is holding that data. If the answer to your query requires tapping data that lives in multiple clouds across a data network and the app needs fast answers, then you need low-latency access to that data. So here's what I think, I think Snowflake's game is to automate by extracting, abstracting, sorry, the complexity around the data location, of course, latency is a part of that, metadata, bandwidth concerns, the time to get to query and answers, all those factors that build complexity into the data pipeline and then optimizing that to get insights irrespective of data location. So a differentiating formula is really to not only be the best analytic database, but be cloud agnostic. AWS, for example, they get a cloud agenda, you know, as do Azure and GCP. Their number one answer to multi-cloud is put everything on our cloud. Microsoft and Google Anthos, they would argue against that, but we know that behind the scenes, that's what they want. They got offerings across clouds, but Snowflake is going to make this a top priority. They can lead with that and they must be best at it. And if Snowflake can do this, it's going to have a very successful future, in our opinion. And by all accounts, and the data that we shared, Snowflake is executing well. All right, so that's a wrap for this week's Cube Insights, powered by ETR. Don't forget, all these breaking analysis segments are available as podcasts, just Google breaking analysis with Dave Vellante. I publish every week on wikibon.com and siliconangle.com. Check out ETR.plus, that's where all the survey data is, and reach out to me. I'm at dVellante on Twitter, or you can hit me up on my LinkedIn post or email me at david.vellante at siliconangle.com. Thanks for watching everyone. We'll see you next time.