 From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. Virtually all tech companies have expressed caution in their respective earnings calls, and why not? I know you're sick of talking about the macroeconomic environment, but it's full of uncertainties and there's no upside to providing aggressive guidance when sellers are in control. They punish even the slightest miss. Moreover, the spending data confirms the softening market across the board. So it's becoming expected that CFOs will guide cautiously. But companies facing execution challenges, they can't hide behind the macro, which is why it's important to understand which firms are best positioned to maintain momentum through the headwinds and come out the other side stronger. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this Breaking Analysis, we'll do three things. First, we're going to share a high-level view of the spending pinch that almost all sectors are experiencing. Second, we're going to highlight some of those companies that continue to show notably strong momentum and relatively high spending velocity on their platforms, albeit less robust than last year. And third, we're going to give you a peek at how one senior technology leader in the financial sector sees the competitive dynamic between AWS, Snowflake, and Databricks. So I landed on the red eye this morning and opened my eyes and then opened my email to see this. My barrens daily had a headline telling me how bad things are and why they could get worse. The S&P Thursday hit a new closing low for the year. The safe haven of barns are sucking wind. The market hasn't seemed to find a floor. Central banks are raising rates. Inflation is still high, but the job market remains strong. Oh, not to mention that the U.S. debt service is headed toward a trillion dollars per year and the geopolitical situation is pretty tense. And Europe seems to be really struggling. Yeah, so the Santa Claus rally is really looking pretty precarious, especially if there's a liquidity crunch coming. Guess why they call barrens, barrens. Last week, we showed you this graphic ahead of the UI path event. For months, the big four sectors, cloud, containers, AI, and RPA, have shown spending momentum above the rest. Now this chart shows net score or spending velocity on specific sectors and these four have consistently trended above the 40% red line for two years now until this past ETR survey. ML slash AI and RPA have decelerated, as shown by the squiggly lines and our premise was that they are more discretionary than the other sectors. The big four is now the big two. Cloud and containers. But the reality is almost every sector in the ETR taxonomy is down, as shown here. This chart shows the sectors that have decreased in a meaningful way. Almost all sectors are now below the trend line and only cloud and containers as we showed earlier are above the magic 40% mark. Container platforms and container orchestration of those gray dots. And no sector has shown a significant increase in spending velocity relative to October, 2021 survey. In addition to ML slash AI and RPA, information security, yes, security, virtualizations, video conferencing, outsourced IT, syndicated research, syndicated research, that's Gartner, IDC, Forrester, they stand out as seemingly the most discretionary. Although we would argue that security is less discretionary, but what you're seeing is a share shift as we previously reported toward modern platforms and away from point tools. But the point is there is no sector that is immune from the macroeconomic environment. Although remember, as we reported last week, we're still expecting 5% to 6% IT spending growth this year relative to 2021, but it's a dynamic environment. So let's now take a look at some of the key players and see how they're performing on a relative basis. This chart shows the net score or spending momentum on the Y axis and the pervasiveness of the vendor within the ETR survey measured as the percentage of respondents citing the vendor in use. As usual, Microsoft and AWS stand out because they are both pervasive on the X axis and they're highly elevated on the vertical axis. For two companies of this size to demonstrate and maintain net scores above the 40% mark is extremely impressive. Although AWS is now showing much higher on the vertical scale relative to Microsoft, which is a new trend. Normally we see Microsoft dominating on both dimensions. Salesforce is impressive as well because it's so large, but it's below those two on the vertical axis. Now Google is meaningfully large, but relative to the other big public clouds, AWS and Azure, we see this as disappointing. John Blackledge of Cowan went on CNBC this past week and said that GCP by his estimates are 75% of Google Cloud's reported revenue. And is now only five years behind AWS and Azure. Now our model is saying no way. Google Cloud Platform by our estimate is running at about $3 billion per quarter or more like 60% of Google's reported overall cloud revenue. You have to go back to 2016 to find AWS running at that level in 2018 for Azure. So we would estimate that GCP is six years behind AWS and four years behind Azure from a revenue performance standpoint. Now tech wise, you can make a stronger case for Google. They have really strong tech, but revenue is in our view a really good indicator. Now we circle here service now because they have become a generational company and impressively remain above the 40% line. We were at CrowdStrike with theCUBE two weeks ago and we saw firsthand what we see as another generational company in the making. And you can see the company spending momentum is quite impressive. Now HashiCorp and Snowflake have now surpassed Kubernetes to claim the top net score spots. Now we know Kubernetes isn't a company but ETR tracks it as though it were just for context. And we've highlighted Databricks as well showing momentum, but it doesn't have the market presence of Snowflake. And there are a number of other players in the green, Pure Storage, Workday, Elastic, JFrog, Datadog, Palo Alto, Zscaler, Cyberock, Fortinet, those last ones are in security. But again, they're all off their recent highs of 2021 and early 2022. Now speaking of AWS, Snowflake and Databricks, our colleague Eric Bradley of ETR recently held an in-depth interview with a senior executive at a large financial institution to dig into the analytics space. And there were some interesting takeaways that we'd like to share. The first is a discussion about whether or not AWS can use SERP Snowflake as the top dog in analytics. I'll let you read this at your leisure, but I'll pull out some call outs as indicated by the red lines. This individual's take was quite interesting. Note the comment that quote, this is my area of expertise. This person cited AWS's numerous databases as problematic, but Redshift was cited as the closest competitors to Snowflake. This individual also called out Snowflake's current cross-cloud advantage, what we sometimes call SuperCloud, as well as the value add in their marketplace as a differentiator. But the point is this person was actually making, the point that this person was actually making is that cloud vendors make a lot of money from Snowflake. AWS, for example, sees Snowflake as much more of a partner than a competitor. And as we've reported, Snowflake drives a lot of EC2 and storage revenue for AWS. Now as well, this doesn't mean AWS does not have a strong marketplace. It does, probably the best in the business. But the point is Snowflake's marketplace is exclusively focused on a data marketplace and the company's challenge or opportunity is to build up that ecosystem and to continue to add partners and create network effects that allow them to create long-term, a long-term sustainable moat for the company, while at the same time, staying ahead of the competition with innovation. Now, the other comment that caught our attention was Snowflake's differentiators. This individual cited three areas. One, the well-known separation of compute and storage, of course, AWS has replicated sort of, maybe not as elegant in the sense that you can't, you can reduce the compute load with Redshift, but unlike Snowflake, you can't shut it down. Two, Snowflake's data sharing capability, which is becoming quite well-known and a key part of its value proposition. And three, its marketplace. And again, key opportunity for Snowflake to build out its ecosystem, close feature gaps that it's not necessarily going to deliver on its own, and really importantly, create governed and secure data sharing experiences for anyone on the data cloud or across clouds. Now, the last thing this individual addressed in the ETR interview that we'll share is how Databricks and Snowflake are attacking a similar problem, i.e. simplifying data, data sharing and getting more value from data. The key messages here are there's overlap with these two platforms, but Databricks appeals to a more techie crowd. You open a notebook when you're working with Databricks, you're more likely to be a data scientist, whereas with Snowflake, you're more likely to be aligned with the lines of business within sometimes an industry emphasis. We've talked about this quite often on breaking analysis. Snowflake is moving into the data science arena from its data warehouse strength, and Databricks is moving into analytics in the world of SQL from its AI and ML position of strength, and both companies are doing well, although Snowflake was able to get to the public markets in IPO, Databricks has not. Now, even though Snowflake is on the quarterly shot clock, as we saw earlier, it has a larger presence in the market, and that's at least partly due to the tailwind of an IPO, and of course, a stronger go-to-market posture. Okay, so we wanted to share some of that with you, and I realize it's a bit of a tangent, but it's good stuff from a qualitative practitioner perspective. All right, let's close with some final thoughts, look forward a little bit. Things in the short term are really hard to predict. We've seen these oversold rallies peter out for the last couple of months because the world is such a mess right now, and it's really difficult to reconcile these countervailing trends. Nothing seems to be working from a public policy perspective. Now, we know tech spending is softening, but let's not forget it, five to 6% growth, it's at or above historical norms, but there's no question the trend line is down. Now that said, there are certain growth companies, several mentioned in this episode, that are modern and vying to be generational platforms. They're well positioned, financially sound, disciplined with strong cash positions, with inherent profitability. What I mean by that is, they can dial down growth if they wanted to dial up EBIT, but being a growth company today is not what it was a year ago because of rising rates, the discounted cash flows are just less attractive. So earnings estimates, along with revenue multiples on these growth companies are reverting toward the mean. However, companies like Snowflake and CrowdStrike and some others are able to still command a relative premium because of their execution and continued momentum. Others, as we reported last week, like UiPath, for example, despite really strong momentum and customer spending have had execution challenges, Okta is another example of a company with strong spending momentum, but is absorbing off zero, for example. And as a result, they're getting hit harder from a valuation standpoint. The bottom line is sellers are still firmly in control. The bulls have been humbled and the traders aren't buying growth tech or much tech at all right now. But long-term investors are looking for entry points because these generational companies are going to be worth significantly more five to 10 years down the line. Okay, that's it for today. Thanks for watching this breaking analysis episode. Thanks to Alex Meyerson and Ken Schiffman on production and Alex manages our podcast as well. Kristen Martin and Cheryl Knight, they helped get the word out on social media and in our newsletters and Rob Hof is our editor-in-chief over at Silicon Angle. He does some wonderful editing for us, so thank you, thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, all you do is search breaking analysis podcast. I publish each week on wikibon.com and siliconangle.com and you can email me at david.volante at siliconangle.com or DM me at dvolante or comment on my LinkedIn post. And please check out etr.ai for the very best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching and we'll see you next time on breaking analysis.