>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> Application performance management AKA APM, you know it's been around since the days of the mainframe. Now, as systems' architectures became more complex, the technology evolved to accommodate client-server, web-tier architectures, mobile and now of course, cloud-based systems. A spate of vendors have emerged to solve the sticky problems associated with ensuring consistent and predictable user experiences. The market has grown, I mean it's decent size, it's about $5 billion globally. It's growing at a consistent 10% CAGR. It's got a variety of established companies and new entrants that are attacking this space. Hi everyone, welcome to this week's Wikibon Cube Insights powered by ETR. My name is Dave Vellante and today, we welcome back ETR's Erik Bradley, who was the chief engagement strategist at Aptiviti which is the holding company of our data partner, ETR. Erik, my friend, great to see you. Thanks so much for coming on and spending some time with us. >> Oh, always enjoy it Dave. Great to see you too and I'm just glad I got some fresh material for ya. >> As always, you have fresh data. Now, Erik just recently hosted an ETR VENN session and on this particular topic, APM. Now VENNs are an open round table, they're exclusively available to ETR's clients and what we do is we sometimes come in theCUBE and we summarize those sessions in our Breaking Analysis. Now Erik, yo let's start with a summary slide here, guys, if you could bring that up, we just want to make a couple of points and... So as I said Erik, I mean this started back, you know in the System/390 days. Now, distributed systems and cloud of course create a lot more complexity, you got data that's really fragmented. You got user data, you got application data, you have infrastructure data and it gets complicated and you've got guys in lab coats having to come in and diagnose these stuff, lot of tribal knowledge. What are you seeing in the space? >> Well yeah, you know to start back, you know it's funny when the panel I hosted, one of the guys even brought up Tivoli, how long ago that was right? Then of course you get, you know you have the solar winds and you had people like that trying to just kind of monitor your network. You know what we've heard a lot about now is infrastructure has really become code-based. So when that happens, you really start wondering to yourself the lines are blurring between infrastructure and application because at the end of the day, what you're really monitoring is code. So it has gotten incredibly complex, you have OnPrem, you have hybrid, you have multi-cloud approach so it has gotten extremely complex and there's also now a third wave of next-gen vendors getting involved in the mix as well. As you're aware, New Relic and Datadog, obviously, Splunk has been in logging and monitoring for a long time. You also had some of the traditional players throw their hat in the ring through acquisition, that you know AppDynamics gobbled up by Cisco and obviously Splunk trying to continue to reinvent themselves a little bit by SignalFx. So it is a very crowded, complex space, it is a complicated problem but it's also a problem that needs to be solved. You know, we were looking at, you said in your intro about, it's only about a $5 billion market right now but there's been a lot of data out there from industry analysts saying that that's going to grow quite handsomely over the next five years and it could get up to 13, 14, 15 billion. And when I asked my panel about that, I had one gentleman say without a doubt, they see the next 10 years that spending in this space will continue. And when you pry and ask why, they simply state that digital transformation is not going to stop, it's marching forward, whether anyone likes it or not and as it does, monitoring is going to be critical, it's only going to increase and increase and increase. So right now, to your point, it's a small market but it's a growing market and there's a lot of entrance in there and their whole goal is to reduce this complexity that you're talking about. >> Now, one of the things we heard from the panel, guys if you bring up that same slide again, you know the third point on that slide was what's closely tied to digital transformation. You heard a number of individuals say, "Look, your digital business is critical, it's all about monitoring your applications and your data and your infrastructure. And we heard a lot that they wanted a, a single pane of glass and you made a number of points about the market. What are your thoughts on both the digital transformation, maybe the COVID acceleration of that mandate and that notion of a single pane of glass, is that aspirational or is it, in your view, something that is actually technically feasible? >> Not only is it technically feasible, it has to happen. It's going to be demanded by the large enterprise, they can't continue to monitor hundreds and hundreds of applications. They need something that not only can give them observability through their entire stack, but they need to be able to view it in one way, there's enough fatigue in monitoring and logging. And actually it goes even further than one pane of glass, they're demanding that these systems can now actually employ machine learning algorithms to be proactive. It's not enough to just say, "Okay, I observed this," you have to let me know that this may happen in the future and what to do about it. So not only is it feasible, it's something that is being demanded by the end-user market and the players that survive are the ones that already have that in their roadmap. >> Now, as we always like to do in these sessions, we're going to bring up some ETR data and we like to position the companies. So what we do is, we're going to bring up some of the pure players, pure-play companies and you can see them on this slide. But Erik, and when we talk about companies in this space, they are well over a dozen. It's just again for reference, you know it's Cisco with AppD, you mentioned that before Dynatrace is one of the leaders, New Relic has been around for awhile and is doing well, Splunk, Datadog. Now of course, and we're not showing them here, AWS, Microsoft and Google cause they just sort of, they pollute the chart. But so I want to start with the guys that are on this view and maybe talk about a few. Elastic came up a lot, certainly AppD came up a little, Dynatrace was obviously mentioned, especially in large organizations. Lot of conversations about New Relic. So let's go through them. Where do you want to start here? >> Yeah there's a lot to go through and we did spend the majority of the panel talking about the individual players, the differences between them and also what we thought their longer term prospects were but yeah, we'll go through each one. I think maybe to start with, let's go back in time a little bit, right? Cisco is a wonderful acquirer, they do a great job at M&A. A lot of companies will acquire something and let it die on the vine. Cisco has proven recently that they are reinventing themselves as a full platform play, whether that be through, you know, kind of, their networking reach or whether it be through the security. And AppDynamics is one of those that actually kind of gives you a little bit of both with being able to monitor. It is a great play for people that are already involved with Cisco. Now, I don't think you're going to see too many people that are non-Cisco customers run out and buy it. There you're going to see some of them, maybe the pure plays or one of my guests called the third wave of vendors. And that third wave is really about a Datadog and a New Relic. Let's talk about Datadog first. >> Yeah let's bring that back up guys, if you would. Now let me just, sorry to interrupt you Erik (indistinct) The vertical axis here is net score, that's the ETR's primary metric, and that's an indication of spending velocity, the higher, the better. And on the horizontal axis is market share. Now we're showing the July data, the October data is in the field, you know once ETR releases that to its clients, then we'll share that with you. But the first thing that jumps out at me is other than Elastic Erik, I mean, I'm not blown away by the spending momentum in this space but let's talk about that and then some of your thoughts on the specific vendors. >> Yeah, you know I'll go back because you asked a little bit about the digital transformation, I don't think I answered it fully. So to your comment about maybe not being impressed with the spend, I think this is one where the spend is going to come, kind of as a laggard because you're not going to rush out and go buy the software to monitor until you've built out the, what needs to be monitored. So as we're seeing this increase in the digital transformation, and I think you and I had a conversation in the past, but when COVID first hit and I did a series of panels, we had one person say that this virus is going to increase digital transformation by five to 10 years. Now that was an amazing statement. Basically, if you were on the fence, if you didn't, if you weren't already heading down to digital transformation, you needed to play catch up quickly. So now that you are doing that right, now that you're moving from OnPrem to a multicloud or a hybrid cloud environment, you have to get observability, you have to get monitoring into it. So now these players start to play catch up and this is where you're going to see the proof of concepts and you're going to see people trying to decide which direction they're going to take their company. Now back to the actual vendors. I believe that there is some differentiation, right? So we'll just take, for instance, Splunk. Splunk is obviously probably the biggest boy on the block when it comes to just straight up logging and monitoring. They've leveraged that big boy position to really, you know, add some costs, kind of intimidate their customers they've been compared in the past of the type of things that Oracle used to do from their cost perspective. And that's opened up some new competition, Datadog is one of those. According to my panel, Datadog is viewed more for logging and monitoring than it is truly full end-to-end observability throughout your entire network and application system. So that is one of the areas that's there. Now, to stay on those two names for a quick second, Splunk obviously has some holes in what they're trying to offer, they went out and tried to buy SignalFx to fill one of those holes. Now according to my panel again, did a great job filling that hole, problem is if you have a boat with three holes, you can't put your fingers everywhere. So they think, hey listen, Splunk scrape, they're going to keep the company they have and I know that we can talk a little bit more about valuations and the equity side later, but I think it's very clear that their sales and revenue are trending flat to down, whereas some of these other names still have great acceleration in their sales. So Splunk and Datadog both are really facing pressure from Elastic or generally just open-source. >> I was struck by the panel and how much emphasis they, how much complaining they did about Splunk pricing. Generally, I feel like hey, if your price is too high is the biggest objection, that's actually not a bad thing for a company but the way they kept hitting on it and said, "Hey, we're actively looking for alternatives" and Datadog was one of those and given the momentum that Datadog has, I don't think that that's necessarily a positive. But you know Splunk has a lot of loyal customers but you know to your point if you go back to the slide, Elastic came up very, very strong and they are head and shoulders from a spending momentum above the rest of the crowd here. >> Right. And you know, so you're right. If the only problem with a vendor or a technology is cost, usually you live with it because that means it's giving you what you need. So okay, it's expensive but it's also the best in breed and that's where Splunk has been for a very long time. And I think they're resting on their laurels knowing that. Enter Elastic and you say to these guys, the panel, I asked them, well okay, you can make Elastic work but is it truly a viable alternative from a technology standpoint? And the answer to that was not only is it viable, it's half the price. So if you can bring something in that can do the job the same and it's half the cost, it's really difficult not to at least try. And I had one of the other gentlemen who was a Datadog customer said, "Listen, we love Datadog, we were a huge customer and then I started getting enormous bills and I just switched over to open-source, I switched to Elastic, I switched to Kibana, I switched to Kafka and I can do this search myself. Now the difference is not every enterprise has the human skillset to do so and I'm not saying Splunk's going to turn around to disappear tomorrow, not even close. Because there is a difference in spending that money with the vendor or spending that money developing the human skillset to use open-source. But the bigger backdrop here is there are more alternatives than there used to be, there's more competition and the space is getting very crowded. >> Yeah, comment on open-source. I mean open-source is free like a puppy. But the thing about that, and we had one of the panelists was a very senior consultant, exclusively work with very large companies, he told a story about one of the companies years ago, he came in to solve a problem. The problem was they had 70% availability and then they had no visibility on their infrastructure and there's really no great, no good monitor, they get them up to whatever, five nines or two, three nines or wherever they got them to, but dramatic improvement. And so, but he said, "Look it, I work with companies with billions of dollars, $3 billion IT budgets so they don't rely on open-source for this stuff, they're happy to spend." But there's a huge market, particularly in the mid size where we heard that New Relic plays in a big way, it might be more receptive to open-source. >> Couple of great points there Dave, honestly. I'm going to jump over to the use case that was given by that person who was in a healthcare role. And essentially the part I didn't write into my summary was that his CEO was two days away from shutting down the entire business because he was so frustrated that he had no observability and Dynatrace was the one that was able to step in and fix that. And this gentleman did say that the majority of the companies that he does work with which are all in the Fortune 100, Dynatrace has a stranglehold in that spot. So that's really interesting to note. Now on the flip side, when pushed a little bit more later in the panel, he said, "Dynatrace is sort of resting on its laurels from a product roadmap standpoint and that's going to open up the possibility of a New Relic getting in," a transition to New Relic as you mentioned on their small to medium sized business. They recently launched a new pricing strategy which is basically a free version to get you involved to kind of get their hooks into you and see if you can work it out. And basically what they're trying to do there I think is, you know, make up for their lack of marketing. As you saw the panel that we spoke about said, "New Relic's technology is fantastic." They have the ability to provide a single pane of glass which is the Holy Grail in this space and they have the ability to provide machine learning and proactive type of ability which again are the two things that all of the end-users are asking for. The problem is that most people might not be aware of it because New Relic doesn't have as flashy a marketing department, they don't have the dollars as much as the others to go out there and compete with the Splunk and Dynatrace and Cisco. But from a roadmap perspective, it was almost unanimous that our panel agreed, New Relic is by far, one of the leaders from a functionality standpoint. >> Yeah, if you guys bring that slide up one more time, the X Y. I mean, I look at where New Relic is and I'm like wow, I'm surprised. I mean this company, I mean they were the hot company for awhile and I think still have the capability. You're talking about the technology. NRDB, New Relic database is like, it kicks ass. In fact, you know Erik, somebody brought up in the panel that they thought that snowflake could compete in this market because essentially Snowflake's positioning is this data cloud. But you know, here's New Relic, they have a purpose-built database specifically for monitoring an APM so you would think that with that technology, they could really make some moves. And then I just want to bring in two other companies to the mix here. Honeycomb who I think even their founder and former CEO now CTO, she coined the term I believe, observability. And there's another company that is run by Jeremy Burton, company's called Observe, okay (indistinct) and it's funded by the Silicon Valley Mafia. So that's going to be an interesting one to watch, they're coming out, well they're out of stealth but they're doing a launch on October 7th. So I think those are two companies that could disrupt this space and I would expect to see, as you said, it's a latent momentum in net score from a dataset standpoint because people are trying to plug the holes cause of COVID, you know security, work from home, that pivot and now it's really on to digital transformation and that's where APM really comes in. >> It really does and again, it comes back to that comment someone made a long time ago that everything's becoming code as software eats the world and everything becomes code, you need the ability to kind of monitor that code, enter Honeycomb. And as you know, we have two different studies at ETR, one of them is for emerging technology. Honeycomb is in our emerging technology study that's more of a private series B to series E round stage whereas our main study is for companies that are pre IPO or already public. But Honeycomb is a little bit different in my opinion, that they're focused very much so on the developers or the software engineers. They're a very microservices oriented type of product whereas some of the other ones may have started as an infrastructure monitoring and then kind of work their way backward into application. But Honeycomb certainly needs to be observed and it's funny when you talk about that, the one thing I think is, "Oh great, more players." The crowded space gets even more crowded. And I think well you know, kind of foreshadowing something you and I will be speaking about in a little bit but there's a lot of players in this space and there's a lot of other possible interest in there. You mentioned Snowflake. It actually wasn't brought up from our panelists, it was a question that came from one of my clients that said, "Hey, I'm curious, can snowflake play in this space?" And the panel thought about it for a second and said, "There's absolutely no reason why they can't, they most certainly can." And we all know the cash they have so I mean the easiest way to play in that would maybe be to buy some of the technology, integrate it in and yeah, they have that portability. And if I can real quickly, they've just, one of the things that came out that was so important about this, we haven't spoken about the vendors is, is the public cloud. The public cloud offers this. They offer monitoring, they'll give it to you for free. If I'm going to run Kubernetes at Google, I'm going to get the monitoring for free which is super nice, right? But if I have an enterprise that has multicloud or hybrid cloud, and I'm working outside of that public cloud silo, it doesn't work. This is the exact conversation you and I had about Snowflake. AWS Redshift's fantastic but it doesn't work outside of AWS. So if every one of our enterprises continues on the digital transformation, they need portability. They have to be able to go across any architecture structure and that's why these independent providers are really starting to gain steam when you would think they could never compete with the public cloud. >> Yeah man, that's a great point. And we've talked about this in the context of Snowflake that who are you going to trust with your multi-cloud strategy? Are you going to trust AWS? Are you going to trust Google? Yeah, okay, they got Anthos but we kind of know why they're taking that posture. Microsoft, look, I'm probably going to partner with somebody who can, who's maybe I have a relationship with them with my OnPrem and that is really sort of agnostic to the various clouds so I'm glad you brought that up. And you know the point you're making about Honeycomb is a good one and I'll add that, again, it gets more complex with microservices and containers, that's spinning them up, spinning them down. Sometimes these, first of all, these microservices, sometimes aren't that micro and second of all, you're sometimes talking about hundreds of thousands of containers so it's a really increasingly complex environment. All right. What I want to do is-- >> You didn't even touch on serverless, we'll do that some other day. >> Oh, yeah, I mean absolutely. A hundred percent, right. So, now let's take a look at some of the valuations, guys if you bring that up for me. So I put this little chart together and it's always instructive. Now I like to, simple guy Erik so I like to... So you see, the company, I take a trailing 12-month revenue and then the market cap as of 9/25. And then just a simple revenue multiple, just to get a sense, it's not a hardcore valuation model but it's interesting and there usually is a correlation to the growth rate, I just pulled that off the latest quarterly growth rate. I mean, look at Datadog. I mean that's like Snowflake pre IPO valuations. I mean you're really, right around there with smaller revenue, smaller growth rate, Snowflakes up in the whatever 120% range but well eye-popping. You know the same valuation as Splunk, I mean that's just amazing. What do you make of this data? >> Well, you know I was an equity analyst for almost 15 years on the Wall Street side. So the, my first caveat is a trailing revenue to the multiple is not always the same because people are looking at what the forward expected revenue will be but I actually do see the correlation here. And when you brought this up, my eyes popped open. I do not understand why Datadog has a 27 billion market cap on a trailing 350 million in revenue. I just don't know if their forward looking growth really warrants that and at the same time, then you look at a Splunk, right? I mean they have two and a half billion in revenue but their growth rate's down and truthfully, when I see a -5% growth rate, I don't know why you weren't at 12% sales either. I would argue that there's quite a few names on here that could be in for a reckoning, ETR actually as far back as a year ago caught this in our data and said, "Hey, there's some inflection points here and I think investors need to pay attention to them." And since we came out with the July report, a lot of these names we're talking about, despite insane valuations in the equity markets are flat to down. And, you know I do think that, hey if they stay stagnant and their technology is right but it's a crowded space, I think we're really leading to the point where as one of my panelists said, this industry is ripe for consolidation. These players are not all going to be here in 12 months, it's that simple. >> Yeah and by the way, thank you for mentioning that as a former equity analyst, you were right (indistinct) 12 months, it's kind of the rear-view mirror. But I'll tell you, two reasons why I do that. One is, I put the growth rate in there so you can pick your own growth rate and your own forward revenue. The other is it's really easy for me to get TTM off a Yahoo as opposed to >> Right exactly. >> And so truth be told. But, guys bring that back up one more time cause I want to make a point about New Relic. I mean I think they are potentially right for an M&A because they got great technology. Now remember Elliot Management is in there and when Elliot's is in there, stuff's going to happen. They're going to start cleaning house, they're going to really create changes, they don't just get in in a big way and sit back and watch, they are extremely active. And the New Relic, leader in this space, great technology, great heritage. So either they got to clean up and get that valuation back up maybe as you pointed out, little bit better marketing posture, et cetera or they get taken out. >> Yeah and let's think about the two things that coincide, right? You have one of the world's best activist funds get involved in Elliot Management. And as you said, they don't get involved to just sort of watch or observe as we're talking about here today, they are very active in trying to get some sort of a, you know, corporate action done. And at the same time, all of a sudden New Relic comes out with a new pricing model. They're trying to create a moat around the small to medium business, right? They're trying to grow their footprint. Now the great thing about getting involved in small to medium businesses, it starts off for free but you grow with them. So I don't think those two are a coincidence, let me just put it that way. I think that they're coming in, they're trying to entrench themselves in a new market and set themselves up for future growth and I truly believe that based on the product roadmap and the feedback we were getting from the end-users in my panel, New Relic has the ability to look across all architecture, it has the ability to provide a single pane of glass and it has the ability to incorporate machine learning for proactive response. Their roadmap is fantastic, they have an active manager inside as an investor, I don't think they're going to be around for much, much longer. And obviously that you look around and you wonder who the acquirers will be and it might be one of the major cloud players. >> Yeah that would be interesting. I mean it gives them a play in a multicloud world and either they're going to just use that for their own advantage or they will actually see that as an opportunity, we'll be itching to watch. Alright, anything we didn't cover that you want to touch on or give us your final thoughts, please Erik. >> You know I would also just sort of mention a little bit about Splunk. This is a company that has a tremendous amount of revenue, a tremendous installed customer base but many, many times we've seen it before and Oracle is the greatest example. They kind of forget about their customers and they don't treat them properly. And I can't tell you how many people I have mentioned to me said, "Hey when this all went down in the viral pandemic and I went to Splunk and I asked for a little bit of pricing flexibility, I asked for this, I asked for that and they just wouldn't give it to me." And I wrote an article once called (indistinct) never forget similar to an elephant. And when they come out the other side, they're going to find a way to replace them. And today I also wrote an article that it was our 200th interview and I entitled it, The Splunk Funk. And basically it's about all the alternatives that are now out there, not just open source, but other vendors, even the vulnerability management players like a Rapid7, like a Tenable are getting into this space now. Fortinet, which one guy called "Fortaeverything" is a company that's really expanding. So I would just really kind of caution some of those vendors out there that don't rest on your laurels, don't take your customers for granted because sooner or later, they're going to be in a position to bite the back. >> Well I'll say this about Splunk, I've been following the company since the early part of last decade and I've done a lot of Cube interviews at their shows. They do have a passionate, passionate customer base, they got the experts that run around with that crazy hat and I've seen Splunk killers emerge for the last decade and so... But I think your point is right. I mean they've, the SignalFx acquisition was something that, it was a hole to fill and it gets them into a subscription-based model, they're going through that transition now. But I think they have some real gravity with their customer base. So, all right, let me summarize. For years, the application monitoring and management, it's really relied on alerts, logs, traces and even what I call tribal knowledge. In that world of pre-distributed systems, that was fine, like I said a trace can tell you what was going on. But things have begotten much more complicated architecturally with cloud and mobile and they're really changing fast now. Erik mentioned serverless, we talked about containers. So, today it's much harder to understand the customer experience because it's difficult to get a full picture of the data. And what I mean by that is that the user data, the application data, the infrastructure data, they're all fragmented and the Holy Grail solution really takes all this disparate data, it ingests it, it transforms it. Connects the dots if you will, across clouds, Onprem and then it shapes it, brings in machine intelligence, really creating an organic systems view that can proactively tell you that there's a problem coming. And finally, nearly absolute Nirvana is doing this in a way that non-technical people are going to be able to understand the true user experience. You know in theory, this is going to allow organizations to remediate in 110th the time with much, much lower costs and that's going to be critical in this world of digital transformation. So thank you Erik, really appreciate you coming on today. >> Always enjoy it Dave, it's always great talking to you and hopefully we'll do it again soon. >> All right, I can't wait. And thank you everybody for watching this episode of theCUBE Insights powered by ETR. Remember these episodes, they're all available on podcasts. We publish weekly on wikibon.com and siliconangle.com so you got to check that out. And don't forget, go to etr.plus for all the survey action. Would appreciate if you kindly comment on my LinkedIn post or tweet me @dvellante or email at david.vellante@siliconangle.com This is Dave Vellante. Thanks so much to Erik Bradley, be well and we'll see you next time. (bouncy music)

>> Narrator: From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE. Now here's your host, Dave Vellante. >> Hello, everyone and welcome to this week's episode of theCUBE InsightsPpowered by ETR. In this Breaking Analysis, I want to do some explanation. For the past four months, I've been sharing data from a company called Enterprise Technology Research, ETR. I've worked with the SiliconANGLE team to create a pure editorial product that blends the ETR dataset with insights that we've gleaned from theCUBE. We've been getting great engagement and I've been getting some questions that I wanted to address in today's episode. Let me first say that as a long time industry analyst, I've always valued data-based opinions, so when I met the folks at ETR, I became really intrigued and I thought working with them might be a good way to share some really awesome survey data and then blend it with context from theCUBE's huge observation space where we do, you know, 100 shows per year. Today I want to cover six things. The first thing I want to do is answer the question that I get most often which is who the heck are these guys? And I think it's really important to understand how and where ETR gets its data so I want to spend a little time on their methodology and dig into that a bit. And then next, I want to talk about this thing called net score. I refer to net score all the time. It's one of my favorite metrics and I'll show some examples and explain what it means and how I use it and I'll use real and current data on containers, VMware, I got some data on Oracle, AWS and HPE who just announced its earning. So there's actually content in this episode. It's not just a tutorial so stick with me here. And then I want to talk about the term market share and what that means in the parlance of ETR. I'm often asked what is the relationship between ETR and theCUBE so I obviously want to address that and if that doesn't answer all your questions, I can give you some ways to get more information. So first, who is ETR? Well ETR is a research company. Actually, it's a platform or a product that was built by a company called Aptiviti. The key advantage is they do primary market research, first party data, and they have a community of survey respondents that give them spending intentions data and they survey this base on a fairly regular basis. Currently, there are about 4,500 buyers in this survey base and in my experience, each quarter, about 1,000 or so respond to their requests for spending data. This group collectively represents nearly a trillion dollars in annual IT spending on enterprise tech and you can see here there's a nice mix of C-level execs, VPs, IT Management, but the respondents, they like to participate because those that do, well, they get access to the data in exchange for their information. Now there's no incentive for them to exaggerate their spending intentions. I mean it's not like, remember the old days of computer pubs where if you spend over a threshold, you get a free magazine? This is legit spending data, spending patterns that ETR vets with historical data. They also pay close attention to the income statements of public companies, attune their data and forecasts in a way that I'll address later and you can also see here that the data is global and it comprises a very strong mix of large organizations across virtually all industries and geographies. I mean it's North America heavy, but they've got representation all over the world and these guys have been at it for 10 years and they're serious data geeks. They have a team of stats folk, aka data scientists in today's terms who do some really cool things with the data like using regression analysis to compare their spending data with Wall Street consensus. Now they primarily, ETR serves Wall Street customers who are trying to gain an advantage, you know, ahead of earnings news coming out and they want to squint through the noise which is kind of what I'm trying to do here. ETR's founder, his name is Thomas Delvecchio and he's essentially created a survey panel on steroids. You know, when I worked at IDC, our Holy Grail was to create a panel and use it to track spending data. We never got there. It was too hard so what we did was we did spot surveys on hot topics like you know, data duplication last decade, to see where all the action was and then periodically, we do broader spending intention surveys. You know, but they weren't conducted on a formal quarterly cadence and what Delvecchio did is he flipped this model on its head. What I mean by that is ETR does regular quarterly broad-based spending surveys and then periodically, they drill down into the hot areas. The great thing about this model from my perspective is that you can run the analytics and do time series across the data. It's a way, way more powerful approach. Now there are other panels out there that you can tap into, but ETR's built a platform on top of what in my opinion is the best spending intentions data that I've ever seen and they've got a really nice SaaS product that allows me to cut the data by size of company, geography, market segment and I can answer questions like are containers killing VMware? And I can answer that question by slicing and dicing the data rather than having to field a completely separate survey. So what I want to do here is I want to take that example and drill into a key TR, key ETR metric that I use a lot which is called net score. Now net score represents the intensity of spend for a company. Higher net scores indicate a positive spend trajectory, and a lower net score indicates a flat or negative spend trajectory. So what I'm showing here is a cut from the ETR dataset and what I'm actually doing to answer that question that I just proposed, look at, so you see number one in the red, I'm filtering the ETR data by container platforms. So this is organizations that are spending on containers and you can see the number two there, the N is 541 organizations spending on containers and then number three, I cut the sample by VMware mentions. So out of the folks answering the survey for a given period, I want to isolate on those doing business with VMware and evaluate their spending. Notice number four, which is the net score. That's what I want you to focus on. Net score's a measure of spending momentum, as I said. So specifically for each ETR survey, ETR asks about spending. Are you adopting the platform as new? Are you spending more, spending the same or spending less? Or are you leaving the platform? And they essentially subtract the spending less from the spending more and calculate a net score and you can see in number five, the net score's over time and I superimpose these numbers with shared accounts that are mentioning VMware. Now remember, ETR allows for multiple responses of various VMware solutions so again, there are multiple responses in that shared end, but you can see that VMware's net score has hailed up around 33-34% over you know, a two-year period. So there's zero evidence that containers are hurting VMware today in this data. Now prior to 2018, by the way, I kind of ignore those spikes because the shared end is too low. It's like 12 mentions, but the rising number of shared accounts over time is yet another clear indicator of adoption between those container costumers and VMware spend. Now I can cut this by size of company, industry, a zillion different ways, but this is everyone in the dataset for the October survey. What I want to do now is take a look at what ETR calls market share. Market share in ETR language is a measure of pervasiveness. So they calculate this by taking the number of mentions of a vendor within a sector, they exclude replacements and they divide by the number of respondents within that sector. So what I'm showing here is an example using market share data for analytic databases. So focus on number one which takes the entire sample from the October survey and then number two and an N of 1,336 respondents. So we choose in number three, the data warehousing software segment and then select from the pull down AWS Redshift and compare that with Oracle within that sector. So you can see in the last two years that AWS has rapidly gained share. You can see in number four that the net scores where AWS has a way stronger spending momentum with 62% and negative 3% for Oracle. What I love about this dataset is the ease with which I can either call BS or validate a vendor's claim and get ahead of the market by combining the data that we collect on theCUBE and that we hear all the time with the ETR survey data. And remember, in last week's Breaking Analysis, I put up a view showing Snowflake which claims it continues to do well despite its apparent overlap with AWS Redshift and as you may recall, the ETR data clearly confirmed that Snowflake was thriving along with Redshift and eating away at Teradata's business. So it confirms their narrative. Let me share another example of how I use ETR market share. HPE just reported earnings yesterday and it missed its revenue targets and here's a chart that HPE presented as part of its earning package. Now at the highest level, HPE reports revenue across three major lines: intelligent edge, hybrid IT and financial services. Not picking on HPE, but you know, I can make this argument with pretty much any legacy computer company or any hardware company and now the narrative from these companies is we're investing in the new hot areas like edge and the world is hybrid and that's our opportunity and we are uniquely positioned and we see lots of repatriation from the cloud where people have moved to the cloud but have sort of cloud regrets and now are moving back to us. You hear this all the time from execs at these companies, but you sure don't see it in numbers. Look at the growth rate year over year in HPE's business. Edge and Hybrid IT are both shrinking in this example. Even when you adjust for currency and take out what HPE refers to as tier one sales to the big hyperscalers which is a business that HPE exited last year. Meanwhile, when you watch and you're looking at AWS and Azure numbers, they're growing at 35% for AWS, 59% year over year for Azure last quarter. Now the HPE narrative is we're focusing on margins and exiting low-value businesses and to be fair, that's true and it shows up in HPE's gross margins and operating profit and free cash flow. But I have an addition to the narrative: which is the cloud is eating away at that business and while repatriation most certainly happens, it's a figure that's not showing up on the income statement. So I look at the ETR data to answer the question how is the cloud impacting HPE's market share? So here's what I do. To answer that question, I filter the data, that I'm showing on this chart, and I select the cloud computing filter in the upper left from the pull down. I do a second filter right below, pulling down and selecting AWS, Azure and Google Cloud Platform. So there's 818 respondents in the ETR October survey that fit that criteria, cloud spenders, and then I click on the market share radio button and pull data in from January 2010 to the October '19 survey. In the October 2019 survey, you can see that the shared end shows 495 respondents that are also spending on HPE. So nearly 500 HPE responses within 800 cloud accounts. Look at the story. Like many, HPE came out of the downturn with a pent up demand. It announced the public cloud in 2011 which froze the market a little bit and by late 2014, the market clearly understood that that offering was a fail and HP exited the business in 2015 and you can see how the cloud is eating away at spending on HPE's products and you can see the net score of 10.9% in the red underscoring the headwinds that HPE is facing. Now of course, Antonio Neri, who's HP's CEO, he's doing what he has to do: cutting costs, focusing on higher margin opportunities, adopting an Azure service model, doing stock buy backs, but as I like to say, the data does not lie. Now where it really gets mind-blowing is when ETR runs regression models using Wall Street's estimates for a public company as an outcome variable and test that against the covariates and independent variables in its dataset. Now these act as predictors so not only using the data that tell the story of what happened in the past, but using it as a forecasting tool. Okay, so that's most of what I wanted to share with you today. There's a lot more, but let's leave it there for now. I want to address a relationship between theCUBE and ETR. We're essentially just friendlies. We currently have no commercial relationship. There's no money exchanging hands. There's no other incentives other than we're birds of a feather, so to speak. They give me access to their data and I use it weekly in these Breaking Analysis segments and we co-brand the content, theCUBE Insights Powered by ETR. So it's a beautiful fit between what we learn in theCUBE and this awesome dataset. Look, if you find this stuff useful, I encourage you, reach out to ETR. Their website is ETR.plus or just Google Enterprise Technology Research or you can hit me up on LinkedIn or Twitter. I'm @dvellante and I'd be happy to put you in touch. This is Dave Vellante signing out from this episode of Cube Insights Powered by ETR. Thanks for watching, everybody, and we'll see you next time. (upbeat music)