>> From The Cube studios in Palo Alto in Boston, bringing you data driven insights from The Cube and ETR, this is Breaking Analysis with Dave Vellante. >> UiPath has always been an unconventional company. You know it started with humble beginnings. It's essentially a software development shop. Then it caught lightning in a bottle with its computer vision technology. It's really, it's simplification mantra and it created a very easy to deploy software robot system for bespoke departments so they could automate mundane tasks. You know the story. The company grew rapidly, was able to go public early this year. Now consistent with its out-of-the-ordinary approach, while other firms are shutting down travel and physical events, UiPath is moving ahead with Forward IV, it's annual user conference next week with a live audience there at the Bellagio in Las Vegas. It's also fast forwarding as a company, determined to lead the charge beyond RPA and execute on a more all-encompassing Enterprise automation agenda. Hello everyone and welcome to this week's Wikibond Cube Insights powered by ETR. In this breaking analysis and ahead of Forward IV, we'll update you in the RPA market the progress that UiPath has made since its IPO and bringing some ETR customer survey data that's contextualized the company's position in the overall market and relative to the competition. Here's a quick rundown of today's agenda. First I want to tell you theCube is going to be at Forward IV at the Bellagio next week. UiPath, this is their big customer event. It's live, it's a physical event. It's primarily outdoors. You have to be vaccinated to attend. Now, this not completely out of the ordinary. John Furrier and theCube were at AWS Public Sector this past week and we were at Mobile World Congress in one of the first big hybrid events of the year at Barcelona. We thought that event would kick of the fall event season, live event in earnest but the COVID crisis has caused many tech firms, most tech firms actually, to hit pause button. Not UiPath, they're moving ahead. They're going forward and we see a growing trend for smaller VIP events with a virtual component, topic maybe for another day. Now we've talked extensively about the productivity challenges and the automation mandate the pandemic has thrust upon us. Now, we've seen pretty dramatic productivity improvements as remote work kicked in but its brought new stresses. For example, according to Qualtrics, 32% of working moms said their mental health has declined since the pandemic hit. 15% of working dads said the same by the way. So, one has to question the sustainability of this perpetual workday. And we're seeing a continuum of automation solutions emerging and we'll talk about that today. We're seeing tons of M&A as well but now, in that continuum, on the left-side of the spectrum, there's Microsoft who in some ways, they stand alone and their Azure is becoming ubiquitous as a SaaS-Cloud collaboration and productivity platform. Microsoft is everywhere and in virtually every market, whether video conferencing, security, database, cloud, CRM, analytics, you name it. Microsoft is pretty much there and RPA is no different. With the acquisition of Softomotive last year, Microsoft entered the RTA market in earnest and is penetrating very deeply into the space, particularly as it pertains to personal productivity building on its software stake. Now in the middle of that spectrum if you will, we're seeing more M&A and that's defined really by the big software giants. Think of this domain as integrated software place. SAP, they acquired Contextere. They also acquired a company called Process Insights, Service now acquired Inttellebot. Salesforce acquired Servicetrace, we see Infor entering the frame and I would put even Pega, Pega systems in this camp. Software companies focused on integrating RPA into their broader workflows, into their software platforms and this is important because these platforms are entrenched Their well guardants of thoughts and complicated with lots of touchpoints and integration points and frankly they are much harder to automate because of their entrenched legacy. Now, on the far side of that spectrum, are the horizontal automation players and that's been let by UiPath with automation anywhere as the number two player in this domain. And I even put a blue prism in there more M&A recently announced that Vista is going to acquire them Vista also owns Tibco, they are going to merge those two companies. You know Tibco is come up with the integration play. So again I would put them in that you know, horizontal piece of the spectrum. So with that as background, we're going to look at how UiPath has performed since we last covered them and IPO and I'm going to bring in some ETR survey data to get the spending view from customers and we'll wrap up. Now, just to emphasize the importance of automation and the automation mandate, we talk about it all the time in this program. We use this ETR chart. It's a two dimensional view with net score which is the measure of spending momentum on the vertical axis and market share which is a proxy for pervasiveness in the data set that's on the horizontal axis. Now note that red dotted line, it signifies companies within elevated position on the net score vertical axis anything over that is considered pretty good. Very good. Now this shows every spending segment within the ETR taxonomy. And the four spending categories with the greatest velocity are AI, cloud, containers and RPA. And they have topped the charts for quite a while now. They are the only 4 categories which have sustained above that 40% line consistently throughout the pandemic and even before. Now the impressive thing about cloud of course is it has both spending momentum on the vertical axis and a very large market share or presence in the data set. The point is RPA is nascent still. It has an affinity with AI as a means of more intelligently identifying and streamlining process improvements. And so we expect those two to remain elevated and grow to the right together. UiPath pegs its TAM, total available market at 60 billion. And the reality is that could be understated. Okay, as we reported from the UiPath S1 analysis we did pre IPO, the company at that time had an ARR annual recurring revenue of $580 million and it was growing at 65% annually. And nearly 8000 customers at the time, a 1000 of which had an ARR in excess of a 100k. And the net revenue retention the company had was over 145%. So let's take a look at the pictures 6 months forward. We mentioned the $60 billion TAM, ARR now up over $726.5 million on its way to a billion ARR holding pretty steady at 60% growth as is NRR, net revenue retention and more then a 1000 new customers and 200 more with over a 100000 in ARR and a small operating profit which by the way exceeded the consensuses pretty substantially. Profitability is not shown here and no one seems to care anyway these days. It's all about growing into that TAM. Well that's a pretty good looking picture, isn't it? The company had a beat and a raise for the quarter earlier this month, so looking good right. Well you ask how come the stock is not doing better. That's an interesting question. So let's first look at the stocks performance on a relative basis. Here we show UiPath performance against Pega systems and blue prism, the other two publicly traded automation. Pure plays sort of in the case of Pega. So UiPath outperformed post its IPO but since the early summer Pega is been the big winner while UiPath slowly decelerated. You see Blue prism was at the lag until it was announced that it was in an acquisition talks with a couple of PE firms and the prospects of a bidding war sent that yellow line up as you can see. UiPath as you can see on the inset, has a much higher valuation than Pega and way higher than blue Prism. Pega interestingly is growing revenues nicely at around 40%. And I think what's happening is that the street simply wants more. Even though UiPath beat and raised, Wallstreet is still getting comfortable with management which is new to the public market game and the company just needs to demonstrate a track record and build trust. There's also some education around billings and multi-year contracts that the company addressed on its last earnings call. But the street was concerned about ARR for new logos. It appears to be slowing down sequentially and a notable decline in billings momentum which UiPath CFO addressed on the earnings call saying look they don't need the trade margin for prepaid multi year deals, given the strong cash position. Why give anything up. And even though I said nobody cares about profitability well, I guess that's true until you guide for an operating loss when you've been showing small profit in recent quarters what UiPath did. Then, obviously people start to care. So UiPath is in bit of an unknown territory to the street and it has a valuation, it's pretty rich. Very rich actually at 30 times revenue multiple or greater than 30 times revenue multiple. So that's why in my view, investors are being cautious. But I want to address a dynamic that we have seen with this high growth rocket chip companies. Something we talked about Snowflake and I think you are seeing some of that here with UiPath. Different model in the sense that Snowflake is pure cloud but I'm talking about concerns around ARR and from new logos and that growth in a sequential basis. And here's what's happening in my view with UiPath. You have a company that started within departments with a smaller average contract size, ACV maybe 25000, may be 50000 but not deep six figure deals. That wasn't UiPath's play. And because the company focused so heavily on simplicity and made it really easy to adapt, customers saw really fast ROI. I mean break-even in months. So we very quickly saw expansion into other departments. So when ACV started to rise and installations expanded within each customer, UiPath realized it had to move beyond a point product and it started thing about a platform and making acquisitions like Processgold and others and this marked a much deeper expansion into the customer base. And you can see that here in this UiPath chart that they shared at their investor deck, customers that bought in 2016 and 2017 expanded their spend 13, 15, 18, 20x So the LTV, life time value of the customer is growing dramatically and because UiPath is focused on simplicity, and has a very facile premium model much easier to try before you buy than its competitors it's CAC, Customer acquisition cost are likely much lower than some of its peers. And that's a key dynamic. So don't get freaked out by some of those concerns that we raised earlier because just like Snowflake what's happening is that the company for sure is gaining new customers, may be just not at the same rate but don't miss the forest through the trees I.e getting more money from their existing customers which means retention, loyalty and growth. Now speaking of forest, this chart is the dynamic I'm talking about, its an ETR graphic that shows the components of net score against spending momentum. Net score breaks down into 5 areas. That lime green at the top is new additions. Okay, so that's only 11% of the customer mentions. By the way we are talking about more than a 125 responses for UiPath. So it's meaningful, it's actually larger in this survey or certainly comparable to Microsoft. So that's just something right there. The next bar is the forest green. Forest green is what I want you to focus. That's customer spending 6% or more in the second half of the year relative to the first half. The gray is flat spending which is quite large. The pink or light red, that's spending customers spending 6% or worse, that's a 4% number. But look at the bottom bar. There is no bar, that's churn. 0% of the responders in the survey are churning. And Churn is the silent killer of SaaS companies. 0% defections. So you've got 46% spending more, nobody leaving. That's the dynamic powering UiPath right now and I would take this picture any day over a larger lime green and a smaller forest green and a bigger churn number. Okay, it's pretty good, not Snowflake good but it's solid. So how does this picture compare to UiPath's peers. Let's take a look at that. So this is ETR data, same data showing the granularity net score for Microsoft power automate, UiPath automation anywhere, Blue Prism and Pega. So as we said before, Microsoft is ubiquitous. What can we say about that. But UiPath is right there with a more robust platform. Not to overlook Microsoft, you can't but UiPath will you that the don't compete head to head for enterprise automation deals with Microsoft and may be they will over time. They do however compete head to head with automation anywhere. And their picture is quite strong as you can see here. You know as is Blue Prism's picture and even Pega. Although Blue Prism automation anywhere UiPtah and power automate all have net scores on this chart as you can see the tables in the upper right over 40%, Pega does not. But you can see Pega as a pure play RPA vendor it's a little bit of sort of apples and oranges there but they do sell RPA and ETR captures in their taxonomy so why not include them. Also note that UiPath has as I said before more mentions in the survey than power automate which is actually quite interesting given the ubiquity of Microsoft. Now, one other notable note is the bright red that's defections and only UiPath is showing zero defections Everybody else has at least little of the slims on defections. Okay, so take that as you will but its another data point, the one that is powerful nit only for UiPath but really for the entire sector. Now the last ETR data point that we want to share is the famous two dimensional view. Like the sector chart we showed earlier, this graphic shows the net score on the vertical axis that's against spending velocity and market share or pervasiveness on the horizontal axis. So as we said earlier, UiPath actually has a greater presence in the survey than the ever present Microsoft. Remember, this is the July survey. We don't have full results from the September-October survey yet and we can't release them until ETR is out of its quiet period but I expect the entire sector, like everything is going to be slightly down because as reported last week tech spending is moderated slightly in the second half of this year. But we don't expect the picture to change dramatically UiPath and power automate we think are going to lead in market presence and those two plus automation anywhere is going to show the strength in spending momentum as will most of the sector. We'll see who comes in above the 40% line. Okay, what to watch at Forward IV. So in summary I'll be looking for a few things. One, UiPath has hinted toward a big platform announcement that will deepen its capabilities to beyond being an RPA point tool into much more of an enterprise automation platform, rewriting a lot of the code Linux, cloud, better automation of the UI, you are going to hear all kind of new product announcements that are coming so I'll be listening for those details. I want to hear more from customers that further confirm what I've been hearing from them over the last couple of years and get more data especially on their ROI, on their land and expand, I want to understand that dynamic and that true enterprise automation. It's going to be good to get an update face to face and test some of our assumptions here and see where the gaps are and where UiPath can improve. Third, I want to talk to ecosystem players to see where they are in participating in the value chain here. What kind of partner has UiPath become since its IPO, are they investing more in the ecosystem, how do partners fit into that flywheel. Fourth, I want to hear from UiPath management Daniel Dines and other UiPath leaders, their exiting toddler wheel and coming into an adolescence phase or early adulthood. And what does that progression look like, how does it feel, what's the vibe at the show. And finally I'm very excited to participate in a live in-person event to see what's working, to see how hybrid events are evolving, we got to good glimpse at Mobile congress and this week in DC at public sector summit. As you know theCube is doing hybrid events for years and we intend to continue to lead in this regard and bring you the best real time information as possible. Okay, that's it for today. Remember these episodes are all available as podcasts wherever you listen, all you do is search breaking analysis podcast. We publish each week on Wikibound.com and Siliconangle.com and you can always connect on twitter @dvellante or email me at David.vellante@siliconangle.com Appreciate the comments on LinkedIn and don't forget to check out ETR.plus for all the survey data. This is Dave Vellante for theCube insights powered by ETR. Be well and will see you next time. (upbeat music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> UiPath has had a long, strange trip to IPO. How so you ask? Well, the company was started in 2005. But it's culture, is akin to a frenetic startup. The firm shunned conventions and instead of focusing on a narrow geographic area to prove its product market fit before it started to grow, it aggressively launched international operations prior to reaching unicorn status. Well prior, when it had very little revenue, around a million dollars. Today, more than 60% of UiPath business is outside of the United States. Despite its headquarters being in New York city. There's more, according to recent SEC filings, UiPath total revenue grew 81% last year. But it's free cash flow, is actually positive, modestly. Wait, there's more. The company raised $750 million in a Series F in early February, at a whopping $35 billion valuation. Yet, the implied back of napkin valuation, based on the number of shares outstanding after the offering multiplied by the proposed maximum offering price per share yields evaluation of just under 26 billion. (Dave chuckling) And there's even more to this crazy story. Hello everyone, and welcome to this week's Wikibon CUBE Insights, Powered by ETR. In this Breaking Analysis we'll share our learnings, from sifting through hundreds of pages (paper rustling) of UiPath's red herring. So you didn't have to, we'll share our thoughts on its market, its competitive position and its outlook. Let's start with a question. Mark Roberge, is a venture capitalist. He's a managing director at Stage 2 Capital and he's also a teacher, a professor at the B-School in Harvard. One of his favorite questions that he asks his students and others, is what's the best way to grow a company? And he uses this chart to answer that question. On the vertical axis is customer retention and the horizontal axis is growth to growth rate and you can see he's got modest and awesome and so forth. Now, so I want to let you look at it for a second. What's the best path to growth? Of course you want to be in that green circle. Awesome retention of more than 90% and awesome growth but what's the best way to get there? Should you blitz scale and go for the double double, triple, triple blow it out and grow your go to market team on the horizontal axis or should be more careful and focus on nailing retention and then, and only then go for growth? What do you think? What do you think most VCs would say? What would you say? When you want to maybe run the table, capture the flag before your competitors could get there or would you want to take a more conservative approach? What would Daniel Dines say the CEO of UiPath? Again, I'll let you think about that for a second. Let's talk about UiPath. What did they do? Well, I shared at the top that the company shunned conventions and expanded internationally, very rapidly. Well before it hit escape velocity and they grew like crazy and it got out of control and he had to reign it in, plug some holes, but the growth didn't stop, go. So very clearly based on it's performance and reading through the S1, the company has great retention. It uses a metric called gross retention rate which is at 96 or 97%, very high. Says customers are sticking with it. So maybe that's the right formula go for growth and grow like crazy. Let chaos reign, then reign in the chaos as Andy Grove would say. Go fast horizontally, and you can go vertically. Let me tell you what I think Mark Roberge would say, he told me you can do that. But churn is the silent killer of SaaS companies and perhaps the better path is to nail product market fit. And then your retention metrics, before you go into hyperbolic growth mode. There's all science behind this, which may be antithetical to the way many investors want to roll the dice and go for super growth, like go fast or die. Well, it worked for UiPath you might say, right. Well, no. And this is where the story gets even more interesting and long and strange for UiPath. As we shared earlier, UiPath was founded in 2005 out of Bucharest Romania. The company actually started as a software outsourcing startup. It called the company, DeskOver and it built automation libraries and SDKs for companies like Microsoft, IBM and Google and others. It also built automation scripts and developed importantly computer vision technology which became part of its secret sauce. In December 2015, DeskOver changed its name to UiPath and became a Delaware Corp and moved its headquarters to New York City a couple of years later. So our belief is that UiPath actually took the preferred path of Mark Roberge, five ticks North, then five more East. They slow-cooked for the better part of 10 years trying to figure out what market to serve. And they spent that decade figuring out their product market fit. And then they threw gas in the fire. Pretty crazy. All right, let's take a peak (chuckling) at the takeaways from the UiPath S1 the numbers are impressive. 580 million ARR with 65% growth. That asterisk is there because like you, we thought ARR stood for annual recurring revenue. It really stands for annualized renewal run rate. annualized renewal run rate is a metric that is one of UiPath's internal KPIs and are likely communicate that publicly over time. We'll explain that further in a moment. UiPath has a very solid customer base. Nearly 8,000, I've interviewed many of them. They're extremely happy. They have very high retention. They get great penetration into the fortune 500, around 63% of the fortune 500 has UiPath. Most of UiPath business around 70% comes from existing customers. I always say you're going to get more money out of existing customers than new customers but everybody's trying to go out and get new customers. But UiPath I think is taking a really interesting approach. It's their land and expand and they didn't invent that term but I'll come back to that. It kind of reminds me of the early days of Tableau. Actually I think Tableau is an interesting example. Like UiPath, Tableau started out as pretty much a point tool and it had, but it had very passionate customers. It was solving problems. It was simplifying things. And it would have bid into a company and grow and grow. Now the market fundamentals for UiPath are very good. Automation is super hot right now. And the pandemic has created an automation mandate to date and I'll share some data there as well. UiPath is a leader. I'm going to show you the Gartner Magic Quadrant for RPA. That's kind of a good little snapshot. UiPath pegs it's TAM at 60 billion dollars based on some bottoms up calculations and some data from Bain. Pre-pandemic, we pegged it at over 30 billion and we felt that was conservative. Post-pandemic, we think the TAM is definitely higher because of that automation mandate, it's been accelerated. Now, according to the S1, UiPath is going to raise around 1.2 billion. And as we said, if that's an implied valuation that is lower than the Series F, so we suspect the Series F investors have some kind of ratchet in there. UiPath needed the cash from its Series F investors. So it took in 750 million in February and its balance sheet in the S1 shows about 474 million in cash and equivalent. So as I say, it needed that cash. UiPath has had significant expense reductions that we'll show you in some detail. And it's brought in some fresh talent to provide some adult supervision around 70% of its executive leadership team and outside directors came to the company after 2019 and the company's S1, it disclosed that it's independent accounting firm identified last year what it called the "material weakness in our internal controls over financial report relating to revenue recognition for the fiscal year ending 2018, caused by a lack of oversight and technical competence within the finance department". Now the company outlined the steps it took to remediate the problem, including hiring new talent. However, we said that last year, we felt UiPath wasn't quite ready to go public. So it really had to get its act together. It was not as we said at the time, the well-oiled machine, that we said was Snowflake under Mike Scarpelli's firm operating guidance. The guy's the operational guru, but we suspect the company wants to take advantage of this mock market. It's a good time to go public. It needs the cash to bolster its balance sheet. And the public offering is going to give it cache in a stronger competitive posture relative to its main new competitor, autumn newbie competitor Automation Anywhere and the big whales like Microsoft and others that aspire and are watching what UiPath is doing and saying, hey we want a piece of that action. Now, one other note, UiPath's CEO Daniel Dines owns 100% of the class B shares of the company and has a 35 to one voting power. So he controls the company, subject of course to his fiduciary responsibilities but if UiPath, let's say it gets in trouble financially, he has more latitude to do secondary offerings. And at the same time, it's insulated from activist shareholders taking over his company. So lots of detail in the S1 and we just wanted to give you some of those highlights. Here are the pretty graphs. If whoever wrote this F1 was a genius. It's just beautiful. As we said, ARR, annualized renewal run rate all it does is it annualizes the invoice amount from subscriptions in the maintenance portion of the revenue. In other words, the parts that are recurring revenue, it excludes revenue from support and perpetual license. Like one-time licenses and services is just kind of the UiPath's and maybe that's some sort of legacy there. It's future is that recurring revenue. So it's pretty similar to what we think of as ARR, but it's not exact. Lots of customers with a growing number of six and seven figure accounts and a dollar-based net retention of 145%. This figure represents the rate of net expansion of the UiPath ARR, from existing listing customers over a 12 month period. Translation. This says UiPath's existing customers are spending more with the company, land and expand and we'll share some data from ETR on that. And as you can see, the growth of 86% CAGR over the past nine quarters, very impressive. Let's talk about some of the fundamentals of UiPath's business. Here's some data from the Brookings Institute and the OECD that shows productivity statistics for the US. The smaller charts in the right are for Germany and Japan. And I've shared some similar data before the US showed in the middle there. Showed productivity improvements with the personal productivity boom in the mid to late 90s. And it spilled into the early 2000s. But since then you can see it's dropped off quite significantly. Germany and Japan are also under pressure as are most developed countries. China's labor productivity might show declines but it's level, is at level significantly higher than these countries, April 16th headline of the Wall Street Journal says that China's GDP grew 18% this quarter. So, we've talked about the snapback in post-COVID and the post-isolation economy, but these are kind of one time bounces. But anyway, the point is we're reaching the limits of what humans can do alone to solve some of the world's most pressing challenges. And automation is one key to shifting labor away from these more mundane tasks toward more productive and more important activities that can deliver lasting benefits. This according to UiPath, is its stated purpose to accelerate human achievement, big. And the market is ready to be automated, for the most part. Now the post-isolation economy is increasingly going to focus on automation to drive toward activity as we've discussed extensively, I got to share the RPA Magic Quadrant where nearly everyone's a winner, many people are of course happy. Many companies are happy, just to get into the Magic Quadrant. You can't just, you have to have certain criteria. So that's good. That's what I mean by everybody wins. We've reported extensively on UiPath and Automation Anywhere. Yeah, we think we might shuffle the deck a little bit on this picture. Maybe creating more separation between UiPath and Automation Anywhere and the rest. And from our advantage point, UiPath's IPO is going to either force Automation Anywhere to respond. And I don't know what its numbers are. I don't know if it's ready. I suspect it's not, we'd see that already but I bet you it's trying to get there. Or if they don't, UiPath is going to extend its lead even further, that would be our prediction. Now personally, I would have Pegasystems higher on the vertical. Of course they're not an IPO, RPA specialist, so I kind of get what Gartner is doing there but I think they're executing well. And I'd probably, in a broader context I'd probably maybe drop blue prism down a little bit, even though last year was a pretty good year for the company. And I would definitely have Microsoft looming larger up in the upper left as a challenger more than a visionary in my opinion, but look, Gartner does good work and its analysts are very deep into this stuff, deeper than I am. So I don't want to discount that. It's just how I see it. Let's bring in the ETR data and show some of the backup here. This is a candlestick chart that shows the components of net score, which is spending momentum, however, ETR goes out every quarter. Says you're spending more, you're spending less. They subtract the lesses from the mores and that's net score. It's more complicated than that, but that's that blue line that you see in the top and yes it's trending downward but it's still highly elevated. We'll talk about that. The market share is in the yellow line at the bottom there. That green represents the percentage of customers that are spending more and the reds are spending less or replacing. That gray is flat. And again, even though UiPath's net score is declining, it's that 61%, that's a very elevated score. Anything over 40% in our view is impressive. So it's, UiPath's been holding in the 60s and 70s percents over the past several years. That's very good. Now that yellow line market share, yes it dips a bit, but again it's nuanced. And this is because Microsoft is so pervasive in the data stat. It's got so many mentions that it tends to somewhat overwhelm and skew these curves. So let's break down net score a little bit. Here's another way to look at this data. This is a wheel chart we show this often it shows the components of net score and what's happening here is that bright red is defection. So look at it, it's very small that wouldn't be churn. It's tiny. Remember that it's churn is the killer for software companies. And so that forest green is existing customers spending more at 49%, that's big. That lime green is new customers. So again, it's from the S1, 70% of UiPath's revenue comes from existing customers. And this really kind of underscores that. Now here's more evidence in the ETR data in terms of land and expand. This is a snapshot from the January survey and it lines up UiPath next to its competitors. And it cuts the data just on those companies that are increasing spending. It's so that forest green that we saw earlier. So what we saw in Q1 was the pace of new customer acquisition for UiPath was decelerating from previous highs. But UiPath, it shows here is outpacing its competition in terms of increasing spend from existing customers. So we think that's really important. UiPath gets very high scores in terms of customer satisfaction. There's, I've talked to many in theCUBE. There's places on the web where we have customer ratings. And so you want to check that out, but it'll confirm that the churn is low, satisfaction is high. Yeah, they get dinged sometimes on pricing. They get dinged sometimes, lately on service cause they're growing so fast. So, maybe they've taken the eye off the ball in a couple of counts, but generally speaking clients are leaning in, they're investing heavily. They're creating centers of excellence around RPA and automation, and UiPath is very focused on that. Again, land and expand. Now here's further evidence that UiPath has a strong account presence, even in accounts where its competitors are presence. In the 149 shared accounts from the Q1 survey where UiPath, Automation Anywhere and Microsoft have a presence, UiPath's net score or spending velocity is not only highly elevated, it's relative momentum, is accelerating compared to last year. So there's some really good news in the numbers but some other things stood out in the S1 that are concerning or at least worth paying attention to. So we want to talk about that. Here is the income statement and look at the growth. The company was doing like 1 million dollars in 2015 like I said before. And when it started to expand internationally it surpassed 600 million last year. It's insane growth. And look at the gross profit. Gross margin is almost 90% because revenue grew so rapidly. And last year, its cost went down in some areas like its services, less travel was part of that. Now jump down to the net loss line. And normally you would expect a company growing at this rate to show a loss. The street wants growth and UiPath is losing money, but it's net loss went from 519 million, half a billion down to only 92 million. And that's because the operating expenses went way down. Now, again, typically a company growing at this rate would show corresponding increases in sales and marketing expense, R&D and even G&A but all three declined in the past 12 months. Now reading the notes, there was definitely some meaningful savings from no travel and canceled events. UiPath has great events around the world. In fact theCUBE, Knock Wood is going to be at its event in October, in Las Vegas at the Bellagio . So we're stoked for that. But, to drop expenses that precipitously with such high growth, is kind of strange. Go look at Snowflake's income statement. They're in hyper-growth as well. We like to compare it to Snowflake is a very well-run company and it's in hyper-growth mode, but it's sales and marketing and R&D and G&A expense lines. They're all growing along with that revenue. Now, perhaps they're growing at a slower rate. Perhaps the percent of revenue is declining as it should as they achieve operating leverage but they're not shrinking in absolute dollar terms as shown in the UiPath S1. So either UiPath has applied some magic automation mojo to it's business (chuckling). Like magic beans or magic grits with my cousin Vinny. Maybe it has found the Holy grail of operating leverage. It's a company that's all about automation or the company was running way too hot on the expense side and had a cut and clean up its income statement for the IPO and conserve some cash. Our guess is the latter but maybe there's a combination there. We'll give him the benefit of the doubt. And just to add a bit more to this long, strange trip. When have you seen an explosive growth company just about to go public, show positive cashflow? Maybe it's happened, but it's rare in the tech and software business these days. Again, go look at companies like Snowflake. They're not showing positive cashflow, not yet anyway. They're growing and trying to run the table. So you have to ask why is UiPath operating this way? And we think it's because they were so hot and burning cash that they had to reel things in a little bit and get ready to IPO. It's going to be really interesting to see how this stock reacts when it does IPO. So here's some things that we want you to pay attention to. We have to ask. Is this IPO, is it window dressing? Or did UiPath again uncover some new productivity and operating leverage model. I doubt there's anything radically new here. This company doesn't want to miss the window. So I think it said, okay, let's do this. Let's get ready for IPO. We got to cut expenses. It had a lot of good advisors. It surrounded itself with a new board. Extended that board, new management, and really want to take advantage of this because it needs the cash. In addition, it really does want to maintain its lead. It's got Automation Anywhere competing with it. It's got Microsoft looming large. And so it wants to continue to lead. It's made some really interesting acquisitions. It's got very strong vision as you saw in the Gartner Magic Quadrant and obviously it's executing well but it's really had to tighten things up. So we think it's used the IPO as a fortune forcing function to really get its house in order. Now, will the automation mandate sustain? We think it will. The forced match to digital worked, it was effective. It wasn't pleasant, but even in a downturn we think it will confer advantage to automation players and particularly companies like UiPath that have simplified automation in a big way and have done a great job of putting in training, great freemium model and has a culture that is really committed to the future of humankind. It sounds ambitious and crazy but talk to these people, you'll see it's true. Pricing, UiPath had to dramatically expand or did dramatically expand its portfolio and had to reprice everything. And I'm not so worried about that. I think it'll figure that pricing out for that portfolio expansion. My bigger concern is for SaaS companies in general. I don't like SaaS pricing that has been popularized by Workday and ServiceNow, and Salesforce and DocuSign and all these companies that essentially lock you in for a year or two and basically charge you upfront. It's really is a one-way street. You can't dial down. You can only dial up. It's not true Cloud pricing. You look at companies like Stripe and Datadog and Snowflake. It is true Cloud pricing. It's consumption pricing. I think the traditional SaaS pricing model is flawed. It's very unfairly weighted toward the vendors and I think it's going to change. Now, the reason we put cloud on the chart is because we think Cloud pricing is the right way to price. Let people dial up and dial down, let them cancel anytime and compete on the basis of your product excellence. And yeah, give them a price concession if they do lock in. But the starting point we think should be that flexibility, pay by the drink. Cancel anytime. I mentioned some companies that are doing that as well. If you look at the modern SaaS startups and the forward-thinking VCs they're really pushing their startups to this model. So we think over time that the term lock-in model is going to give way to true consumption-based pricing and at the clients option, allow them to lock-in for a better price, way better model. And UiPath's Cloud revenue today is minimal but over time, we think it's going to continue to grow that cloud. And we think it will force a rethink in pricing and in revenue recognition. So watch for that. How is the street going to react to Daniel Dines having basically full control of the company? Generally, we feel that that solid execution if UiPath can execute is going to outweigh those concerns. In fact, I'm very confident that it will. We'll see, I kind of like what the CEO says has enough mojo to say (chuckling) you know what, I'm not going to let what happened to for instance, EMC happen to me. You saw Michael Dell do that. You saw just this week they're spinning out VMware, he's maintaining his control. VMware Dell shareholders get get 40.44 shares for every Dell share they're holding. And who's the biggest shareholder? Michael Dell. So he's, you got two companies, one chairman. He's controlling the table. Michael Dell beat the great Icahn. Who beats Carl Icahn? Well, Michael Dell beats Carl Icahn. So Daniel Dines has looked at that and says, you know what? I'm not just going to give up my company. And the reason I like that with an if, is that we think will allow the company to focus more on the long-term. The if is, it's got to execute otherwise it's so much pressure and look, the bottom line is that UiPath has really favorable market momentum and fundamentals. But it is signing up for the 90 day short clock. The fact that the CEO has control again means they can look more long term and invest accordingly. Oftentimes that's easier said than done. It does come down to execution. So it is going to be fun to watch (chuckling). That's it for now, thanks to the community for your comments and insights and really always appreciate your feedback. Remember, I publish each week on Wikibon.com and siliconangle.com and these episodes are all available as podcasts. All you got to do is search for the Breaking Analysis podcast. You can always connect with me on Twitter @dvellante or email me at david.vellante@siliconangle.com or comment on my LinkedIn posts. And we'll see you in clubhouse. Follow me and get notified when we start a room, which we've been doing with John Furrier and Sarbjeet Johal and others. And we love to riff on these topics and don't forget, please check out etr.plus for all the survey action. This is Dave Vellante, for theCUBE Insights Powered by ETR. Be well everybody. And we'll see you next time. (gentle upbeat music)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante snowflake's eye-popping ipo this week has the industry buzzing we have had dozens and dozens of inbound pr from firms trying to hook us offering perspectives on the snowflake ipo so they can pitch us on their latest and greatest product people are pumped and why not an event like this doesn't happen very often hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll give you our take on the snowflake ipo and address the many questions that we've been getting on the topic i'm also going to discuss at the end of this segment an angle for getting in on the ground floor and investments which is not for the faint of heart but it's something that i believe is worth talking about now let's first talk about the hottest ipo in software industry history first i want to say congratulations to the many people at snowflake you know the big hitters yeah they're all the news slootman mooglia spicer buffett benioff even scarpelli interestingly you know you don't hear much about the founders they're quite humble and we're going to talk about that in some future episodes but they created snowflake they had the vision and the smarts to bring in operators that could get the company to this point so awesome for them but you know i'm especially happy for the rank and file and the many snowflake people where an event like this it really can be life-changing versus the billionaires on the leaderboard so fantastic for you okay but let's get into the madness as you know by now snowflake ipod at a price of 120. now unless you knew a guy he paid around 245 at the open that's if you got in otherwise you bought at a higher price so you kind of just held your nose and made the trade i guess you know but snowflakes value it went from 33 billion to more than 80 billion in a matter of minutes now there's a lot of finger pointing going on this is this issue that people are claiming that it was underpriced and snowflake left four billion dollars on the table please stop that's just crazy to me snowflakes balance sheet is in great shape thanks to this offering and you know i'm not sure jamming later stage investors even more would have been the right thing to do this was a small float i think it was around 10 percent of the company so you would expect a sharp uptick on day one i had predicted a doubling to a 66 billion dollar valuation and it ended up around 70. now the big question that we now get is is this a fair valuation and can snowflake grow into its value we'll address this in more detail but the short answer is snowflake is overvalued in my opinion right now but it can grow into its valuation and of course as always they're going to be challenges now the other comment we get is yeah but the company is losing tons of money and i say no kidding that's why they're so valuable we've been saying for years that the street right now is rewarding growth because they understand that to compete in software you need to have massive scale so i'm not worried in the least about snowflakes bottom line not yet eventually i'm going to pay much closer attention to operating cash flow but right now i want to see growth i want to see them grow into their valuation now the other common question we get is should i buy when should i buy what are the risks and can snowflake compete with the biggest cloud vendors i'll say this before we get into it and i've said before look it's it's very rare that you're not going to get better buying opportunities than day one of an ipo and i think in this case you will i remember back in 2015 it was i think it was the first calendar for quarter and servicenow missed its earnings and the stock got hit and we had the opportunity to interview frank slootman then ceo of servicenow right after that and i think it's instructive to hear what he said let's listen roll the clip well yeah i think that a lot of the high-flying cloud companies and obviously we're one of them you know we're we're priced to perfection right um and that's that's not an easy place to be for uh for for anybody and you know we're not really focused on that it's it's this is a marathon you know every quarter is one mile marker you can't get too excited about you know one versus the other we're really pacing ourselves we're building you know an enterprise that's going to be here for for a long time you know and after that we saw the stock drop as low as 50 today servicenow is a 450 stock so my point is that snowflake like servicenow is going to be priced to perfection and there will be bumps in the road possibly macro factors or other and if you're a believer you'll have opportunities to get in so be patient now finally i'm going to make some comments later but i'll give you the bumper sticker right now i mean i calculated the weighted average price that the insiders paid on the the s1 that they paid for snowflake and it came out to around six dollars a share and i heard somebody say on tv it was five dollars but my weighted average math got me to six dollars regardless on day one of the ipo the insiders made a 50x return on their investment if you bought on day one you're probably losing some money or maybe about even and there are some ground floor opportunities that exist that are complicated and may be risky but if you're young and motivated or older and have some time to research i think you'll be interested in what i have to say later on all right let's compare snowflake to some other companies on a valuation basis this ought to be interesting so this chart shows some high flyers as compared to snowflake we show the company the trailing 12-month revenue the market cap at the close of the 16th which is the day that snowflake ipod and then we calculate and sort the data on the revenue multiple of the trailing 12 months and the last column is the year-on-year growth rate of the last quarter and i used trailing 12 months because it's simple and it's easy to understand and it makes the revenue multiple bigger so it's more dramatic and many prefer to use a forward revenue uh but that's why i put the growth rate there you can pick your own projected revenue growth and and do the math yourself so let's start with snowflake 400 million dollars in revenue and that's based on a newish pricing model of consumption not a sas subscription that locks you in for a year or two years or three years i love this model because it's true cloud and i've talked about it a while so for a while so i'm not going to dwell on it today but you can see the trailing 12-month revenue multiple is massive and the growth rate is 120 which is very very impressive for a company this size zoom we put zoom in the chart just because why not and and the growth grade is sick so so who knows how that correlates to the revenue multiple but as you can see snowflake actually tops the zoom frothiness on that metric now maybe zoom is undervalued i should take that back let's see i think crowdstrike is really interesting here and as a company that we've been following and talking about quite a bit in my last security breaking analysis they were at a 65 x trailing 12-month revenue multiple and you see how that's jumped since they reported and they beat expectations but they're similar in size to snowflake with a slower growth rate in a lower revenue multiple so there's some correlation between that growth rate and the revenue multiple sort of now snowflake pulled back on day two it was down early uh this morning as you would expect with both the market being off and maybe some profit taking you know if you got in an allocation at 120 why not take some profits and play with house money so snowflake's value is hovering today it actually bounced back is hovering today you're just under 70 billion and that that brings the revenue multiple down a bit but it's still very elevated now if you project 2x growth let's say 100 for next year and the stock stays in some kind of range which i think it likely will you could see snowflake coming down to crowdstrike revenue multiples in 12 months it'll depend of course on snowflakes earnings reports which i'm sure are going to beat estimates for the next several quarters and if if it's growing faster than these others at that time it should command a premium you know wherever the market prices market's going to go up it's going to go down but we'll look at all these companies i think on a relative basis snowflakes still should command a premium at higher growth rates so you can see also in this chart you've got shopify awesome mongodb twilio servicenow and their respective growth rates shopify incredibly impressive [ __ ] and twilio as well servicenow is like the old dog in this mix so that's kind of interesting now the other big question we get is can snowflake grow in to its valuation this is a chart we shared with you a bit ago and it talks to snowflake's total available market and its expansion opportunity there tam expansion this is something we saw slootman execute at servicenow when everybody underestimated that company's value and i'll briefly explain here look snowflake is disrupting the traditional data warehouse and data lake markets data lake spending is relatively small it's under 2 billion but data lakes they're inexpensive and that's what made them attractive the edw market however the enterprise data warehouse market is it's much much larger now traditional edws they're they're big they're slow they're cumbersome they're expensive and they're complicated but they've been operationalized and are critical for companies reporting and basic analytics but they've failed to live up to their promise of the 360 degree view of the customer and real-time analytics you know i had a customer tell me a while ago that my data warehouse it's like a snake swallowing a basketball he gave me example where a change in a regulation this was a financial company it would occur and it would force a change in the data model in their data warehouse and they'd have to ingest all this new data and the data warehouse choked and every time intel came out with a new processor they'd rush out they'd throw more compute at the problem he called this chasing the chips now what snowflake did was to envision a cloud native world where you could bring compute to massive data volumes on an elastic basis and only pay for what you use sounds so simple but technically snowflakes founders and those innovations of that innovation of separating compute from storage to leverage the flexibility of the cloud it really was profound and clearly based on this week's performance was the right call now i'll come back to this in a bit now where we think snowflake is going is to build a data cloud and and you can see this in the chart where your data can be ingested and accessed to perform near real-time analytics with machine learning and ai and snowflake's advantage as we've discussed in the past is that it runs on any cloud and it can ingest data from a variety of sources now there are some challenges here we're not saying that snowflake is going to participate in all these use cases that we show however with its resources now we expect snowflake to create new capabilities organically and then do tuck-in acquisitions that will allow it to attack many more more use cases in adjacent markets and so you look at this chart and the third layer if that's 60 billion it means snowflake needs to extend into the fourth layer because its valuation is already over 60 billion it's not going to get 100 market share so we call this next layer automated decision making this is where real time analytics and systems are making decisions for humans and acting in real time now clearly data is going to be a pretty critical part of this equation now at this point it's unclear that snowflake has the capability to go after this space as much of the data in this area is probably going to live at the edge but snowflake is betting on becoming a data data layer across clouds and presumably at the edge and as you can see this market is enormous so there's no lack of tam in our view for snowflakes that brings us to the other big question around competition everybody's talking about this look a lot of the investment thesis behind snowflakes snowflake is that slootman and his army including cfo mike scarpelli and what they did at servicenow will be repeated scarpelli is this operational guru he keeps the engine running you know with very very tight controls and you know what it's a pretty good bet snoopman and scarpelli and their team i'm not denying that but i will tell you that snowflake's competition is much more capable than what servicenow faced in its early days now here's a picture of some of the key competitors this is one of our favorites the xy graph and on the vertical axis is net score or spending momentum that is etr's version of velocity based on their quarterly surveys now i'm showing july survey october is in the works it's in the field as i speak on the horizontal axis is market share or pervasiveness in the data set so it's a proxy for market share it's it's based on mentions not dollars and and that's why microsoft is so far to the right because they're huge and they're everywhere and they get a lot of mentions the more relevant data to us is the position of snowflake it remains one of the highest net scores in the entire etr survey based not just the database sector aw aws is its biggest competitor because most of snowflake's business runs on aws but google bigquery you can see there is is technically the most capable relative to snowflake because it's a true cloud native database built from the ground up whereas aws took a database that was built for on-prem par excel and brilliantly really made it work in the cloud by re-architecting many of the pieces but it still has legacy parts to it now here's oracle oracle's huge it's slow growth overall but it's making investments in r d we've talked about that a lot and that's going to allow it to hold on to its customers huge base and you can see teradata and cloud era cloudera is a proxy for data lakes which are low cost as i said and cloudera which acquired hortonworks is credited with the commercialization of that whole big datum and hadoop movement and then teradata is in there as well which of course they've been around forever now there are a zillion other database players we've heard a lot of them from a lot of them this week is on that inbound pr that i talked about but these are the ones that we wanted to focus on today the bottom line is we expect snowflakes vertical axis spending momentum to remain elevated and we think it will continue to steadily move to the right now let's drill into this data a bit more here we break down the components of etr's net score and this is specifically for snowflake over time now remember lime green is new adoptions the forest green is spending more relative to last year than more five percent more uh than last year or or greater gray is flat spending the pink is less spending and the bright red is we're leaving the platform the line up top that's netscore which subtracts the red from the green is an indicator of spending velocity the yellow line at the bottom is market market share or pervasiveness in the survey based on mentions now note the the blue text there that's etr's number one takeaway on snowflake two h-20 spending intentions on snowflake continue to trend robustly mostly characterized by high customer acquisition and expansion rates new adoptions market share among all customers is simultaneously growing impressive let's now look at snowflake against the competition in fortune 500 customers now here we show net score or again spending momentum over time for some of the key competitors and you can see snowflakes net score has actually increased since the april survey again this is the july survey this was taken the april survey was taken at the height of the us lockdown so snowflake's net score is actually higher in the fortune 500 than it was overall which is a good proxy for spend because fortune 500 spends more google mongodb and microsoft also also show meaningful momentum growth since the april survey you know notably aws has come off its elevated levels from last october and april it's still strong but that's something that we're going to continue to watch finally let's look at snowflakes market share or pervasiveness within the big three cloud vendors again this is a cut on the fortune 500 and you can see there are 125 respondents within the big three cloud and the fortune 500 and 21 snowflake respondents within that base of 125 and you can see the steady and consistent growth of share not huge ends but enough to give some confidence in the data now again note the etr callout but this trend is occurring despite the fact that each of the big three cloud vendors has its own competitive offering okay but i want to stress this is not a layup for snowflake as i've said this is not servicenow part two it's a different situation so let's talk about that look the competition here is not bmc which was servicenow's target as much as i love the folks at bmc we're talking here about aws microsoft and google amazon with redshift is dialed into this i've said often that they have copycatted snowflake in many cases and last fall at re invent we heard andy jassy make a big deal about separating compute from storage and he took a kind of a swipe at snowflake without mentioning them by name but let's listen to what andy jassy had had to say and then we'll come back and talk about it play the clip then what we did is because we have nitro like i was talking about earlier we built unique instances that have very fast bandwidth so that if you actually need some of those data from s3 for a query it moves much faster than if you just had to leave it there with without that high speed bandwidth instance and so with ra3s you get to separate your storage from your compute if it turns out by the way on your local ssds that you're not using all the ssd on that local ssd you only pay for what you use so a pretty significant enhancement for customers using redshift at the same time if you think about the prevailing way that people are thinking about separating storage from compute letting people scale separately that way as well as how you're going to do this large-scale compute where you move the storage to the a bunch of awaiting compute nodes there are some issues with this that you got to think about the first is think about how much data you're going to have at the scale that we're at but then just fast forward a few years think about how much data you're going to actually have to move over the network to get to the compute and we so look first of all jassy is awesome he stands up at these events for like reinvent for two hours and it connects trends and business to technology he's got a very deep understanding of the tech he's amazing however what aws has done in separating compute and storage is good but it's not as elegant architecturally as snowflake aws essentially has tiered the storage off the cluster to lower the overall costs but you really you can't turn off the compute completely with snowflake they've truly separated compute and storage and the reason is that redshift is great but it's built on an on-prem architecture that was originally an on-prem architecture that they had to redo so when jassy talks about moving the data to compute what he's really saying is our architecture is such that we had to do this workaround which is actually quite clever but this whole narrative about the prevailing ways to separate compute from storage that's snowflake and moving the data's use the word data's plural to the compute it really doesn't apply to snowflake because they'll just move the compute to the data thank you hadoop for that profound concept now does this mean snowflake is going to cakewalk over redshift not at all aws is going to continue to innovate so snowflake had better keep moving fast multi-cloud new workloads adjacent markets tam expansion etc etc etc microsoft they're huge but as usual there's not a lot to say you know about them they're everywhere they put out 1.0 products they eventually get them right because with their heft they get mulligans that they turn into pars or birdies but i think snowflake is going to bring some innovations to azure and that they're going to get good traction there in my opinion now google bigquery is interesting by all accounts it gets very high technical marks google's playing the long game and i would expect that snowflake is going to have a harder time competing in google cloud than it does within aws and what i'm predicting for azure but we'll see the last point here is that many are talking about the convergence of analytic and operational and transaction databases and the thinking is this doesn't necessarily bode well for specialists like snowflake and i would say a couple of things here first is that while it's definitely true you're not seeing snowflake positioning today as responding at the point of transaction to say for instance influence and order in real time and this may have implications at the edge it's going to have a lot of real-time inferencing but we've learned there are a lot of ways to skin a cat and we see integration layers and innovative approaches emerging in the cloud that could address this gap and present opportunities for snowflake now the other thing i'd say is you know maybe that thinking misses something altogether with the idea of snowflake in that third data layer that we showed you in our tam chart that data as a service layer or data cloud which is maybe a giant opportunity that they are uniquely positioned to address because they're cloud agnostic they've got the vision and they've got the architecture to allow them to very simply ingest data and then serve it up to businesses nonetheless we're going to see this battle continue between what i've often talked about these integrated suites and converged databases in the case of oracle converged pipelines in the case of the cloud guys versus the best of breed players like snowflake we talk about this all the time and there really isn't one single answer it's really horses for courses and customer preferences okay well you know i know you've been waiting for for me to tell you about the angles on ground floor investing and you probably think this is going to be crazy but bear with me and i got to caution you this is a bit tongue-in-cheek and it's one big buyer beware but as i said the insiders on snowflake had a 50x return on day one you probably didn't so i want to talk about the confluence of software engineering crypto cryptography and game theory powered by the underlying value of blockchain and we're talking here about innovations around a new internet in a distributed web or d-web where many distributed computers come together to form one computer that guarantees trust between two or more users for a variety of use cases not just financial store like bitcoin but that too and the motivation behind this is the fact that a small number of companies say five or six today control the internet and have essentially co-opted the major protocols like tcp http smtp pop3 etc etc and these people that we're showing here on this chart they're working on these new innovations there are many of them but i just name a few here olaf carlson we he started poly chain capital to invest in core infrastructure around these new computing paradigms this gentleman mark nadal is someone who's working on new d apps tim berners-lee who invented the internet he's got a project called solid at mit and it emphasizes data ownership and privacy and of course satoshi got it all started when she invented bitcoin and created the notion of fractional shares and by the way the folks at andreessen horowitz are actively making bets in this space so you know maybe this is not so crazy but here's the premise if you're a little guy and you wanted to invest in snowflake you couldn't until late in the game if you wanted to invest in the lamp stack directly in the late 90s there was no way to do that you had to wait for red hat to go public or to get a piece of the linux action but in this world that we're talking about here there are opportunities that are not mainstream and often they're based yes on cryptocurrencies again it's dangerous there are scams and and losers but if you do your homework there are actually vehicles for you to get in on the ground floor and you know some of these innovations are going to take off you could get a 50x or 100 bagger but you have to do your research and there's no guarantee that these innovations are going to be able to take on the big internet giants but there are people really smart technologists and software engineers that are young they're mission driven and they're forming a collective voice against a dystopian future because they want to level the playing field on the internet and this may be the disruptive force that challenges today's giants and if your game i would take a look at the space and see if it's worth throwing a few dollars at okay a little tangent from snowflake but i wanted to put that out there snowflake wow closes its first trading week as a company worth 66 billion dollars roughly the same as goldman sachs worth more than vmware and the list goes on i mean what's what's more is there to say other than remember these episodes are all available as podcasts so please subscribe i publish weekly on wikibon.com and siliconangle.com so please check that out and please comment on my linkedin post or feel free to email me at david.velante at siliconangle.com this is dave vellante for the cube insights powered by etr thanks for watching everyone we'll see you next time you

>> Live from Barcelona, Spain, it's theCUBE, covering KubeCon CloudNativeCon Europe 2019. Brought to you by Red Hat, the Cloud Native Computing Foundation, and ecosystem partners. >> Hi and welcome back, I'm Stu Miniman with my co-host Corey Quinn, and you're watching theCUBE, the worldwide leader in live tech coverage of KubeCon CloudNativeCon 2019. Happy to welcome to the program a first-time guest, Jeff Brewer, who's the Vice President and Chief Architect of Small Business and Self-Employed Group at Intuit. He's going to talk about your cloud journey. Jeff, thanks so much for joining us. >> You're welcome, I'm glad to be here. >> All right, so, Jeff, the easy part of this is, I think, most of our audience has probably heard of Intuit, but maybe give us that first setting of, you know, the part of the group you're in, and your role, and then we want to get into that journey. >> Yeah, yeah, no, it's great. So, yeah, first of all, thanks for having me here and I'm what's called the Chief Architect of the Small Business and Self-Employed Group. Intuit is about powering prosperity around the world. That's our fairly new mission. And helping both taxpayers with TurboTax and QuickBooks is our other big project. So, think of me as the Chief Architect for the QuickBooks group. And so, mostly for small businesses, helping small businesses survive through their first year, survive and prosper continuing on, so. >> And your charter there, is that the infrastructure there, you're not trying to help the world rid those malicious attacks of like, oh no, I got the new TurboTax and it didn't work well because, disclaimer, you know, I'm not paid, I've used it for many years and it's super easy for me. >> Yeah so, as a Chief Architect, I set the technical direction of the overall QuickBooks franchise both the desktop version which is our older version that, you know, has been around for 20, 25 years, and our QuickBooks Online version, which is about, only about 15 years old and is our SAS offering. And so, I do things like choose technologies that we adopt. I do things like set what are the most important technology priorities whether it's breaking things up into microservices, our cloud strategy, Kubernetes, going to cloud native, all that kind of stuff. >> Okay, so, you are a member of the Technical Oversight Committee, but we're actually going to bring you back a little bit later to talk about that, so, we'll put a pin in that. But give us a little bit as to kind of what led to this journey towards cloud and, you know, all of those pieces that you were just talking about. >> Yes, so, like many other companies with, you know, lots of legacy and lots of code that we've developed over about 35 years of existence, we actually started out in the early 2000's with building our own data centers, right. And it's very expensive, very ambitious, but at the time, there really wasn't a public cloud. But we realized that, you know, putting servers under our desks and stuff like that, you know, we really needed to grow to a more robust data center. And, you know, as we progressed in that journey, we figured out we're not the experts at maintaining and developing all the complicated networking you have to do, reliability, resiliency. We had some outages, this is 10 years ago or so, where a truck drove into a light post outside one of our data centers and took us down for a day. And that's just not acceptable for our customers. The public cloud was just starting out, AWS was a big partner out there, and our CIO, and CEO, met with the AWS executives and really decided that we needed a great partner in public cloud that really was their technical expertise. And so, we began this journey, mostly I would describe it as lift and shift, of technologies and services that we already had. We had to rewrite a few of them to make them actually work with the cloud. But by and large, most of our code is written in Java and that ports pretty well. So, we started on that journey and really right now, we are mostly running in the public cloud. We have a few legacy systems that are still running in our private data centers, but we're planning on decommissioning those. And with the public cloud, a journey we really have seen quite a, improvement in our reliability, our downtime, we can fail over between availability zones, it's just been fantastic from our overall availability, recoverability standpoint. But what we realized during that journey was that the, that the AWS native experience for our developers, while AWS is just an amazing, amazing partner, it wasn't quite the developer experience we wanted. >> It had some sharp edges. >> Yeah, we worked with them on that, and that's why we started looking at cloud-native technologies, things already developed by the community. AWS is part of the community, as well, and so they were extremely supportive in our journey to want to, from the developer experience standpoint, really start to press on these cloud-native technologies. >> Wonderful. As you went down that entire path, whenever a company goes public and they put in their S1 that they're doing some committed level of giant deal with AWS, people immediately chime in with, oh, they could save so much money by building and running their own data centers. How do you stand on that particular perspective? >> So, what's really interesting about our, our public cloud journey, right, it's not necessarily about saving a lot of money, right? And we realized that, you know, Intuit, as a mature company, you know, we're not a start-up looking to shave every little penny off of every little server. What we really want is reliability for our customers, we want awesome operations, and so, the public cloud journey actually hasn't been a huge, huge cost savings, but it has been a huge improvement in all these other levels, so it does amazing things for our customers. And we're looking to cloud native as just another, you know, bump up in that overall thing, where we get immediate mean time to recovery, where things go down, things go wrong, and we get those pods and those services right back up and running. >> Can you elaborate a little bit about the application that you're talking about, like when I first heard you say, you know, we just lifted and shifted there, it's like, oh wait, you know, a lot of times that is when we kind of claw things back because it's costs more than I thought or it didn't run as well as I thought. >> It turns out the mainframe's hard to move because they didn't build an AWS 400 yet, something doesn't happen. >> So, the challenges there, and then, you know, connect the dots with that to what you're calling the cloud native piece of this, as to what your application development looks like. >> So, I'll use QuickBooks Online as an example. Massive property, over four million customers. >> I'm one of them. >> And it started out as a, as kind of our first really big foray into SAS, right? And luckily, at the time we wrote it, mostly in Java. But it was written as this huge, monolithic piece of code, right. And so, millions of lines of code, you can imagine, large memory footprints, all that kind of stuff. And so, during our first, for public cloud, we just looked at, well, we're not going to rewrite these millions and millions of lines of code, but we want to get into public cloud. Lucky for us, EC2 instances, things like that, can run those large memory footprints. But once there, we really started examining, okay, what does this look like as microservices? Because when you have over 400 engineers working on a single code base, imagine what doing a release, a release is a ceremony, right? It's like this huge thing, you have-- >> It takes a many page calendar in order to do those things. >> Exactly, and so, what we really wanted to do is press into the microservices journey and say, okay, what if instead of having this huge oil tanker, you know, driving down the, you know, sailing down the ocean, what if we could be a bunch of speedboats, right, and use that analogy. And that's where cloud native comes in, because that's really what it's meant to do, right? A bunch of independent teams doing dev ops, you build it, you run it, right? You write the code, you run the code. And so, it plays right into to this, this ability to be very agile, give each team, you can imagine at a scale of 4000 engineers, you want little pizza team, you know, to be independent and do their own releases, and not have to coordinate all with each other. >> So, Jeff, which of the, you know, CNTF pieces are you using at Intuit, and I would like you to go in a little bit, you know, Kubernetes, a lot of people, it's like, oh well, I want portability, and it sounds like you're all in, primarily, on one public cloud, so that's probably not the first thing on your list, so, help us understand the landscape from your eyes. >> So, really it's about, it's about developer productivity. So yes, we do have this very good, strong partnership with AWS, and that is our public cloud provider. And so, the cloud-native technology, using, obviously, Kubernetes, obviously, you know, we're running Docker in the background for running the containers and all that infrastructure. We have our own open source called Argo, which we're using for deployments in the community, so we're contributing a little bit back to community, as well. We're using Istio and Envoy as a service match to really secure the interservice communications and support all the routing and whatnot. And we're also leaning very heavily now into serverless technologies, and so, we write our app, QBO or QuickBooks Online, as a stateful application, but we're realizing the power of having these really stateless small functions, and so we want to do that, as well. And the way we look at it as, Lambda is a fantastic technology for something like that, but the developer experience, we want the same developer experience for our containers that we do from our functions, right? And if you really think about it, it's just about deploying, it's how you deploy. Do I deploy into containers and then a pod structure, like in Kubernetes? Or do I deploy to a functions as a service? It should run on the infrastructure, and so, from a developer standpoint, from the end developer that's actually developing the applications and services that our customers are using, we want the declarative infrastructure of Kubernetes, we want the ease of deployment and of operations. You can just imagine a development team not having to learn the huge depth that's behind that Kubernetes, that developer experience is just unbelievable and second to none. And you can imagine these teams sitting around, you know, at lunch time, doing their release, something goes wrong, they're on the call, they're solving the problems for their customers, in fact, doing another release, if there's any problems. And so, that's where we really, really lean in heavily to these cloud technologies, the cloud-native technologies, so we can get even faster at the developers. >> Do you find that making it more accessible and having a consistent developer experience has, I guess, broadened the ability of your developers to iterate more rapidly, or is more about ensuring consistency across the board? In other words, is it a speed value for you or is it more about just consistency, so you can wind-up up-to-point to multiple architectures? >> It's really about both. We see, you know, agility is often confused with speed and velocity, but we see that enabling a developer to release code to production in just a few minutes is extremely, extremely powerful to the overall velocity because what they're more likely to do is they're more likely to experiment, be bold, try new things, and then get immediate feedback for the customer. There's this experimentation loop that you want it to move as fast as possible. And so, not only that, but to your second part about the consistency, for a company like Intuit with 4000 developers, you want mobility in your organizations, and so, you want someone to feel very natural going from one small pizza team to another, and have the same tools, the same deployment architecture, and the same thing, right? So, you're not retraining them on a ton of different technologies. >> Alright, so, Jeff, you know, what could the ecosystem, you know, the partners you're working with, the various ecosystem, what could they do to make your life easier? I mean, the one that comes to mind for me is, you know, today, serverless, you know, Lambda, specifically, and Kubernetes. There are some ways to get them, you know, work at little bit, but, you know, is that top of your mind or are there other things? >> That is actually really top of my mind. We have a lot of teams experimenting with Lambda. We're running huge workloads in Lambda, but we're very much worried about this. If there's teams working on that and it's very, it's very fragmented. Some teams are deploying Lambdas off their laptops, other teams are, you know, using CICD processes. And so, we want that experience to be consistent, secure and everything. And so, as it moves to more production workloads, right, we would really like the Kubernetes and the CNCF Foundation to really have a story about serverless itself. I think it's probably more aptly called functions as a service or running functions. And I think a lot of thing happens is that it's treated as a versus. It's like, oh, I'm going to skip over that containers to Kubernetes thing and go to serverless, because it's versus, right? It's not versus, it's a choice for the developer about what to I want to deploy in functions, in short-running functions, or do I want to deploy in containers? Everything else up to that point is the same. And so, I'd really like to see, and that, as my role on the Technical Oversight Committee, that's something I'm really focused on for the end users 'cause I see that a lot in the end user's communities. They're dealing with the same things that we are on that functions as a service. >> Alright, so, Jeff, before I let you go, Intuit's an award winner, so, congratulations on that. >> Thank you. >> I want final word from you. Talk a little bit about the award and two, talk your peers that might be, you know, they've heard about Kubernetes, but, you know, we're into the, we've crossed the chasm in the majority, but that means there's a lot of people that are still relatively early. What do you recommend to them, what tips would you give them, and start with the award though. >> Yeah, so, we're extremely honored to be the CNCF end user award winner. Our cloud journey has been a really interesting one that came really out of a, also, out of an acquisition that we did of some fantastic Kubernetes experts about 14 of them, a little company called Applatix that had this Argo project. And their mission was to make Kubernetes accessible to the overall community. And by acquiring them, we left their mission the same, but they're really helping Intuit, and we're not selling their, they're helping the community for free, when they were charging before as enterprise customers. And that's something I'd overall recommend for the peers and the companies thinking about going on a cloud native journey is it's about those people that you can find here at the conference, right, about those experts that you can hire, just a few of them, have them come into your company, explain these things, and it turns the entire company around. We now have hundreds and hundreds of teams going through and onboarding, we call it modern SAS, internally, onboarding onto this technology because they started out with that nugget or that kernel. >> Alright, well, Jeff, modern SAS, love the story, thank you so much and thanks for joining us and we will see you later to talk about the TOC. >> Glad to be here, thank you very much. >> Thank you very much. >> For Corey Quinn, I'm Stu Miniman, and that was Jeff Brewer from Intuit, we'll be back with lots more coverage and thank you for watching theCUBE. (dynamic digital music)

>> Announcer: From Boston, Massachusetts, it's the Cube. Covering Cloud Foundry Summit 2018. Brought to you by The Cloud Foundry Foundation, >> Hi I'm Stu Miniman and this is the Cube's coverage of the Cloud Foundry Summit 2018 here in Boston, Massachusetts. Happy to welcome back one of our earliest and favorite guests of the Cube Chad Sakac Who's at Pivotal now and he handles PKS and Dell technologies. Chad, great to see you, thanks for joining us, welcome to the Boston area, you come through this area a lot but it's great to see you. >> It's good to see you too. This is, by the way, my first CF summit. So it's interesting, you and I have talked together at Dell Technologies World, Dell EMC World, and EMC World for years. >> Stu: VMWorld. >> And VMWorld. This is a different scene. >> Alright Chad, this is my third time doing this show. I was at the first one back in 2014, last year we did the Cube there; every year it's like 'oh wait, there's this cool new technology; containers, maybe, how's Pivotal going to deal with that? This year, wait, Kubernetes, cloud natives everywhere. Maybe give us your point of view, as to how this fits in. >> So I feel like I'm a kid in a candy store. My job inside Pivotal is to drive PKS. Pivotal Container Service, that's built on top of Kubernetes. And there's a lot of Kubernetes action occurring here. If I had to net it out, I'd say a couple things. Number one, we've moved past the early hype cycle, and actually went through several hype cycles that blew up, so Docker is going to take over the world, not correct. What turned out to be correct is Docker would become the container standard, right? >> It's Mobi now, right? >> Right. Then, we went in to the battles of different cluster container managers. It's Swarm, it's Mesos Marathon, it's Kubernetes and there were lots of others, and then you get through that early hype period and things settle down to the point where they're actually productive, and everyone now kind of agrees, that Kubernetes is the standard container cluster manager for broad sets of workloads, great. Now the debate is Cloud Foundry, the structured PaaS-World, right? The structured platform opinionated, versus the little more wild west and open eco system of Kubernetes, and then early stage Kubernetes projects, like Istio and others, right? I think this has two chapters now, in front of us. Number one, and this is my focus I think for the next few years, is how do we make Kubernetes simple enough, easy enough, and frankly, enterprise ready. Not that it's not ready today, but a lot of Kubernetes projects that our customers are all over the map, difficult to sustain. We want to bring a lot of the lessons learned over the years of Cloud Foundry to Kubernetes. And I'm happy to say, that just a couple days ago, we released PKS 1.O.2 and 1.1, which we haven't announced the date but we've always said that we're going to be in constant compatibility with GKE, and the core Kubernetes. Since GKE shortly will have Kubernetes 1.10 support you can expect a 1.1 of PKS. So mission number one is make Kubernetes a great platform, and I am determined and stubborn, and will make PKS the best enterprise platform for customers that are putting workloads on Kubernetes. That said, Kubernetes isn't steady still and neither is the ecosystem. And you can see that there's a lot of discussion over what is the intersection between Cloud Foundry and Kubernetes? I think that over time it's inevitable that these things come together more. But again, I think that's going to occur over years. Not in a heartbeat. >> And even, I've been at the Kubernetes show and have been at this show a few times, it's not a monolithic stack, we're building distributed, lots of different pieces. You go to the Cloud Foundry, I'm sorry, the show that's Kub-Con, there's so many different projects there, I mean Istio was all the buzz, talk about the service national, there's all these little pieces there. And at this show, we're talking about Zip Car came and talked about they love everything in this eco system. They don't use some of the core components, but they use all these other pieces. As you and I've talked many times, Chad, people go read, Chad writes a little bit about some of these things to give you all the details there, but this stuff's pretty complicated. There's some in the Kubernetes community that's like it's never going to get simple. Remember when we thought Cloud computing was simple? And if you've been to any Amazon show and you go through, it is more complicated to configure a compute instance at Amazon, than it is to buy a Dell server these days. Because there's more options out there. Look, customers need options, many of them want things to be packaged and serviced and buy it as a service, but some love to put those pieces together and it's a spectrum and I loved at this show, Google and Microsoft up on stage, talking, 'hey, open communities, collaborating together'. Maybe not merging everything, but working together, understanding where things fit and it's not one or the other, it's many customers will choose both. >> You and I are both nerds at heart, I hope you don't take offense to that. >> I've already been doing Star Wars quotes this week. >> I wear it with pride. I'm always fascinated by the technology itself, but one thing that's been really cool about my experience alongside, and now inside Pivotal, and you can see it here at the CF Summit, is that the Pivotal obsession, is about the customer and the outcome. We build a platform that is an essential part of that, but teaching the world how to build better software is a noble mission. And the thing that's the most exciting for me is actually when the customers talk. So if you went to any of the customer discussions, did you see any of them, did you see the T-Mobile one? >> I saw T-Mobile up on the key note, I actually did an interview with T-Mobile. Had an interview with US Air Force. >> The Air Force One is amazing. >> Awesome. >> It's fascinating, from a technological standpoint, to say how do you use these tools? But it's the story of what you do with it, that actually matters so much more. I'll leave the, no, I won't leave the customer name out of it. So in talking with the T-Mobile crew, they love the Pivotal application service. So they are using it, it's an essential part of how T-Mobile works. They talked about it on stage, that's why I don't mind talking about it. And if you ask them, it's not an or. They also have massive projects, massive application workloads, that don't fit in PaaS, but are Docker images, they're currently doing some strange stuff with Swarm, and blah blah. And they're like 'Man, if you guys can basically deliver a great platform that we can consume instead of trying to construct and maintain, we trust you, you iterate with us, you work with us, we'll be able to focus more on the outcome. The thing that I'm actually going to be the most curious to hear feedback from customers over the next couple of years, is how do they navigate what workloads are best put into Kubernetes, how does Kubernetes sets of ecosystems start to not calcify, but firm up, right? It's going to be loose. But it will start to align more over time. >> Yeah our research team actually calls it, we need to get to a place where it's plastic. It should be not just scalable up and down but side to side a little bit more too. Once you have it, you can be able to go. >> Figuring out over time, and helping, with customers, figure out 'Hey, this is a Kafka or Crunchy data.' Post grass instance, or it's an ISV stack, or it's an application they've home grown, but they don't want it fully compartmentalized and put on paths, and they decide that they want to put it on Kubernetes, awesome. What is the value and the return of doing further work on that app to really make it Cloud Native, pull out all config, turn it into sets of small micro services, and then it's better fit for the PaaS part of PCF. Figuring out that formula over the next few years is going to be really cool. >> You mentioned culture. And that's been something you and I, Chad, lived through. It was the server vs the storage vs the network and the virtualization admin, and then the cloud admin. I talked to the US Air Force guy, and he was like, 'We actually have the people take off their uniforms, because rank would have a certain meaning inside there.' But you've got the Devs, you've got OPS, you've got still the infrastructure pieces on tub, what are you seeing from the customers you're talking to; what are some of the big challenges that are slowing people back from reaching this Utopia of fast, fast, fast, agile, inter-operable, wonderful times? >> How do I answer that one? That's a loaded question, brother. The biggest impediment is human nature. It's these damn humans, if we could just get all the humans out. >> Well everybody's mine, mine, mine. >> We'll go to low code, no code, eliminate all the humans, it'll be dreamy. >> I did one of those interviews today, too. Absolutely, you don't need all programmers, the business people can do it. >> The human tendency for control, and the need for control, I think it's probably deep seated in our, we're living in a world where we know intellectually that we don't have control over everything, but we hate that. Because we want to create control in our lives, that basically is the thing that sets up boundaries between people, and they get really hung up on their function. That's not new, the word's changed, like you said. Used to be server people vs storage people. Then it was virtualization teams vs the silo teams. And now it's the intersection of the DEV team and the DevOps team, the operations team. How do they intersect? The places where they're the most successful, is that they don't get hung up on that and the people blend the roles. Now the trick is, how do you do that in a big company? I wrote a blog, I'm not trying to advertise, virtualgeek.io I wrote a blog on this which was a synthesis of all the customer dialogues I've been having over the last few years. And the pattern I've seen that is most successful, is actually to recognize that there are stacks, and the stacks, I don't mean this particular technology choice, but the way that the whole stack driven by the business and the application and then the abstraction it sits on, and then you have to build your actual operations team underneath that. That creates a whole operational model which in itself is a stack, and just so it doesn't sound like I'm describing something that's nonsensical, a stack can be in big enterprises, there's a main frame based app, that's running on a main frame, that's being supported by a main frame operations team, and then right beside it there's another stack, which is all X86 workloads that are static. So they don't need an IAS they just need to run on a kernel mode VM abstraction. And then under that you've got the team that supports. Then you've got the workload that can be containerized, and don't need a full blown PaaS. And then you've got another one, which is a full blown application service model. Each one of those stacks ends up with different people, processes and tools, because they're mapped to the cultural operational model of that stack. And the thing that I'm trying to guide customers when I'm talking to them is, don't reject that; that's actually reality. Yes you should move as much as you can to the highest order abstraction you can. That's goodness and it pays dividends all the way down the stack. But don't go and say, that this workload, by definition has to go there. Or because you operate this way in this stack and this group operates this way, that by definition you're stupid and they're smart. The other rule is that- >> Chad, the answer to everything is server-less. >> By the way, I should have said that's another abstraction even to the right of the application service model. So the thing I've found, is a key kind of pattern of good, is that between the stacks, people and process are not allowed to transverse them, because the process is linked to how you operate. The only thing that goes between them, because in the end, for any customer, the stuff that touches all of those, is to become religious about one thing, which is that API's and data, and how those transit, those different stacks, that you have to be very clear on. Do you know what I mean? On the blog I drew a picture, but it was terrible. It was a terrible drawing. >> I've done whiteboards with you, Chad, I understand. Great, so. Sound's like you've got your hands full. Lots of us read the S1, so Pivotal's marching towards an IPO. You've only been there a very short time, you've know Pivotal since the beginning and all the pieces since Greenplum's part of the MC, Cloud Foundry part of VMware. Anything that you've learned since you've been inside Pivotal now that there's misconceptions? One of the things I always find is, we always learn about something the first time and then don't think it changes. >> It's funny actually, that's an insightful question. Having joined the team, it's weird because to many of them, I'm new, I'm a new Pivot. But to many of them they know that I've always been there. And I was reminding some of the originals, the crazy tortured path that we've taken to get to today. The original effort was hey, people are doing new things data's at the core of it. And that was the trigger for the Greenplum acquisition. And several of the people who are the senior leaders of Pivotal now came in through that. And then Paul Maritz was the CEO of VMware at the time, hey, I'm seeing people build new apps in new ways, by the way there's this crazy team inside VMware working on this thing called Cloud Foundry. And they were like a red headed stepchild. That's not PC, but like a black sheep? Or I don't know what metaphor you want to use, but basically they were working on something that had nothing to do with kernel mode virtualization at its core. >> Yeah it was a Cloud native peg in a VM square. >> And at the time, VMware isn't what they are now too. And then people forget this but I wrote a blog about it, so it's on the internet permanently. There was a Greenplum project, which was a great idea, that says people want to collaborate with data sets, and data scientists want to work together and it's really hard. Let's build a thing, which is like a social media portal, for Greenplum which was called Chorus. And the Chorus project was completely sideways. And they were like we don't know how we're going to get this thing on track on time, and they asked around the Valley, and people said hey, you should go talk to these guys, Pivotal Labs, up in San Francisco. What they do is they help people when they're stuck. They went, and I remember when Bill Cook and Scott Yara came back to Hoppington and said 'This was awesome, they've changed the way we think about how we build software, we think we should buy them.' And that got added, I remember when Paul Maritz said 'Spring is available.' it's like the most widely used modern JAVA framework, and that was also stuff in Spring Rif. All of these weird bits, in essence became the essence of Pivotal. You know what I've learned through that? Is these journeys are not in a straight line. Everyone's. >> Like our careers, Chad. >> Like our careers man. That's the first part, the second thing is, and this is going to be a challenge for Pivotal, honest, if we're very transparent as always, is Pivotal's brand is now so linked with Pivotal Cloud Foundry. And that's a good thing, like those customers raving about the business outcomes that they are getting. But inside Pivotal, the strategic change, the strategic pivot ha ha ha, to do a full embrace of Kubernetes versus the traditional opinionated versus plastic debates, I wouldn't say that we have 100% of the company fully embracing it yet, because companies are themselves, organic. But across the vast majority of the company it is something understood that it is an imperative for us. If we want to help the customers and the world build better software, we've got to do it for stuff that fits into PaaS, and stuff that doesn't. And so I've learned over the last few weeks about how many people share that passion that I have, and I think we can make something awesome with PKS. >> Alright, well with that Chad, we'll have to leave it there for now, looking forward to seeing you at more events. Congrats on the new role, I'm sure if people haven't already, Chad does have a new site for his blog, virtualgeek.io instead of the previous one. Chad, always a pleasure. Got the Cube here at Cloud Foundry Summit, I'm Stu Miniman, thanks for watching the Cube. (upbeat tempo)

>> Announcer: Live from San Juan, Puerto Rico, it's theCUBE, covering Blockchain Unbound. Brought to you by Blockchain Industries. (Caribbean music) >> Welcome back, everyone. We're here for exclusive CUBE coverage in Puerto Rico for Blockchain Unbound, a great conference where entrepreneurs and leaders are all here, coming together at a global level. You've got investors, you've got entrepreneurs, you've got the ecosystem developing. We've got it covered for you, I'm John Furrier, your host of theCUBE. Next guest, Joe Mohen, CEO of Chimes, industry executive, a lot of experience doing an ICO, doing some great work, Joe welcome to theCUBE. >> Thank you, it's a pleasure to be here. >> So, tell us first what Chimes is doing. You've got an interesting approach with music. What are you guys doing? Is there an ICO in the future? Have you done an ICO? Give the quick update. >> Okay, sure. Chimes is a digital media company, and we are consolidating music-related search results on Google in a similar way to what Amazon did with IMDB, consolidating film and television results many years ago. Amazon built an audience of about quarter of a billion to half a billion monthly users, and we expect we can create an audience on that order of magnitude over time. Just like IMDB is the third largest entertainment website in the world, it is our objective to create the fourth largest one. >> What's the value proposition there? Acquire audience, use that audience to tokenize? How does the token economics fit into all this? >> Well, first, like any media company, the first thing you have to get is an audience, right? I remember I interviewed for a job at CBS when I was out of college, and in the interview they said, "Do you know what we make here?" And I said, "You make TV shows." They go, "No, we make audiences." So we have to make an audience with a good product. The audience will be driven primarily by search, okay? But we also do have a double ICO in our future. First, we monetize the big audience. You can monetize with advertising, but that's not enough to make big money anymore, right, we all know that. So we have a layer of crypto products over and above that that we're going to be launching, including, for example, inter-country commerce, hiring producers in another country, hiring songwriters, et cetera, but automating that so we can do it on scale with smart contract. So we are creating a micro-currency that we can use on the website. We're doing an ICO for that but that's not for the purpose of raising capital. >> That's more part of the business model. >> That's part of the business model. >> That's not the financial aspect of it. >> Correct, and that's done so we can scale international commerce with automation. We're doing an actual ICO for the equity, for securities tokens as well. I've done a full IPO myself. My first company, I had Microsoft and Novell as my shareholders and it was a full S1, full registration. >> Interviewer: You went through the whole process. >> Yeah, but I also did a Form 10 once, ten years ago, for another reason. So what we're doing is possibly the first, certainly one of the first, but I think the first registration with the SEC of a company actually doing an ICO. And we're doing that using, I don't want to call it a loophole in securities laws, but there is a provision in the 1934 Securities Act called Section 12G. And what this does is it allows us basically to go public by telling the SEC we're doing it without having to delay it to wait for their permission. A Form 10 looks just like an S1, but when you file it, it's automatically effective 60 days after you file it, period. And so what we're doing is-- >> Period, full stop, no issues, no questions. >> Joe: No issue, right. >> So do you have to fill out all the same paperwork, the S1, >> Correct. >> the normal format, do the business plan, the normal paperwork? >> Joe: No, right, in 1930-- >> But there's no comments coming back? You just chip it to them? >> Comments come back and you have to clear them, just like with a prospectus, just like with an S1, however that doesn't delay it becoming effective. It's effective 60 days later. >> So they can be commenting during the 60 day time clock going on, but after 60 days, you're in. >> It's effective. So we'll continue to clear comments, but the thing is, with tokens, who knows how long that'll take? Is the SEC going to shepherd something through with crypto, or are they going to make it take five years? I don't know! Who knows? So, the thing is, we are complying with all of the laws for registration, but 60 days after we file it, it's effective. What we're doing is, in the pre-sale for the tokens, we're not issuing the tokens themselves to the buyers of the pre-sale for six months. The reason for that is they will have met the statutory holding period. So once the Form 10 is effective, those buyers can sell freely on token exchanges-- >> And what's the statutory holding period, six months? >> Generally six months. There's a few exceptions for affiliates, like an insider like me. >> I'm confused, a holding period kicks in before or after six months? >> After six months, the statutory holding period is satisfied. >> So you're going to wait to delay them anyway six months. >> Joe: Yes. >> So that covers the holding period. >> Correct, and then we file the Form 10, and 60 days later, they can trade and anybody can buy them. >> So do you file a Form 10 before the six month holding period? >> It'll be at about the same time. The reason being is because we have to get all the ducks in a row to be a public company. >> Cutting edge advice here, this is fantastic. So you're basically going to be the first ICO that actually files with the SEC. >> Correct. >> I mean, who does that, nobody. You! >> Watch us! >> John: That's awesome. >> Basically, we're using a provision, it's like we went back in time to 1934, got them to put something in the 1934 Securities Act for the purposes of ICO's, and then we came back to 2018 with the time machine-- >> Are you from the future? Back to the future! You went back and jerry rigged it. Hey, we should put this Form 10 in there! >> Joe: There you go! That's right. >> It could come in handy some day during the crypto bubble. >> Joe: That's right. >> So let's back to the cryptocurrency thing. I think you're onto something that I think is a tell sign that I haven't seen yet. I've been seeing some formation of it. You are using two types of tokens. Your business model is do security token for funding, trade that puppy through the Form 10. Utility token, a separate ICO for the product, and that's going to have one token, two tokens? >> There's one utility token, so to speak, one currency token, and that has its own regulations that you have to manage to also. But that's designed to appreciate, but not to go up 17 times. >> Okay, I want to dig into that for a second, because you mentioned scale. You're going to scale your business model with the utility token. That's the purpose of the utility token. So let's get into how you're going to do these smart contracts. Let's just say that a producer in Europe somewhere, in Italy, says, "Hey, I'm going to do something "with Joe in the UK." And they form a collaboration. >> Joe: That's right. >> Do they use that utility token or a new token gets created? >> No, that utility token. It's called a Chime, the Chime token. And what happens with that token is you can build in the contract administration through the token. Right now, you can do international deals. People do them every day. The difficulty is if you've got an audience of a half a billion people a month, for example, to do that on scale and automate it... Right now, if you do a deal with somebody in Japan, you, the American, has to have an American lawyer and a Japanese lawyer. And if there's a dispute, good luck suing. I, one time, a customer in Hong Kong, owed me a million and a half bucks and he's like, "Sue me." I'm in New York, he's in Hong Kong, and good luck. >> Did you do the New York thing? I'm flying over there and going to break your legs! >> We bitched and complained, threatened them, and ultimately we settled on 30 cents on the dollar, so we did, that's exactly what happened. With a situation like this, with smart contracts, neither side has to hire two sets of lawyers in the other country-- >> So Chime takes care of that. You want Chime to take care of that administrative inefficiency? >> Correct. The company might still get involved in administering exceptions but not everyone single one. What the smart contract does is it allows you to scale international business. The key is international business, and that's a new efficiency into the market, and that's a great-- >> And in the business model, what does that scale mean to you for operationalizing it? More people, do you have to hire them? >> More cash. No, less people and more cash because there's more automation, right? It means more software development-- >> Where's the cash coming from? >> We have a lot of revenue products. Like the obvious, like every other website, we have subscription revenue and advertising revenue. Subscription revenue comes from like... You know how IMDB is the LinkedIn of the TV and film business? So we'll have that too. >> It's not really large, though. It can be. >> Amazon could make it larger if they wanted to. They have their reasons for doing it the way they do it. But, in our case, I'll give you an example of some revenue products. Let's say you want to crowdfund a project. So let's say you want a bunch of Taylor Swift fans to crowdfund a project for her to do a duet with Kanye West. Sounds preposterous, but it's goofy enough. You'd be amazed, Stormy Daniels is crowdfunding a project for her legal bills with Donald Trump, and I betcha it's going to get funded, right? >> John: I would agree. >> So there's a lot of nutty stuff that gets crowdfunded. >> The wisdom of the crowd is actually efficient. >> Yes, that's right, and the whims of the crowd. But also, I'll give you another example. Let's say people want, if they go to a webpage about an artist, the band All American Rejects, for example, and Wheeler, one of the band members... Ten years ago, you could have given your niece a gift of a CD of All American Rejects. Well, good luck now. They wouldn't even know what a CD is in many cases, right? But what you could do is say, "Hey, you know what? "I'll give you a gift of a Google Hangouts chat with him, "And I'll pay $200 for that, or $500 for it." >> It's probably a bot, but anyway, how do you make this happen? This is really important. You're creating value by allowing people to collaborate in a way that's different, so that scales. Is that going to be done in the Chime contract or it's all going to be part of one currency? >> One currency, that's right. We're very careful. We brought in as an advisor, Rod Garrett, who gave one of the keynotes here yesterday. Rod Garrett is the money supply economist from UCSB, but he was also former VP of the New York Fed, he was the leader at the New York Fed for cryptocurrency. Rod is one of the smartest people I've ever met. >> You know him? >> Very well now, and you know what, Rod can explain the most complex things in simple words, which means he actually understands them. So we've actually used Fisher's equation to help model the utility token value over time. And, again, it's designed to appreciate, but we don't want nutty appreciation because then it'll be useless as a currency, right? We have fixed supply, the Bitcoin principle, the fixed supply and stable market so we can keep it reasonably stable. >> You're using the utility token to create value on your network so the creators can capture that value. >> Correct. >> That's what you're doing with the utility. The security is the money making side. How are you backing the security token, with equity or cash flow? >> Equity, and very important, really important, if you did a percentage of revenue or royalties, it wouldn't work, and I'll tell you why. It wouldn't scale, because we're looking five years out, 10 years out, for this to be a good investment. We want investors to buy it. And if you, let's say you need to do a secondary, because an acquisition becomes available, because you're low on money or whatever. Then how do you do a secondary if you've already given away 20% of your revenue to token holders. What if you have to do a secondary or tertiary capital round? How many rounds were necessary for Spotify, I happen to know Spotify, it was six, right? Facebook, Google, how many founds of financing did they do? A lot, and by the way, they still might do more. >> So basically the revenue share is hair on the deal. It really puts a lot of hair on the deal. >> Destroys it, in my opinion, destroys it. It's a dressing thing, but look, if you're really going to grow to a major company and have, be it five or 10 year success, it kills it. This is my opinion. >> What percentage of equity, say they're going to do a 50 million dollar raise, hard cap, soft cap, say 25, that's what seems to be the norm right now, what would be a percentage of equity converting to tokens that you'd see? >> In Chimes' case, we have a Common A class of stock. We're creating a preferred class of stock called a Series T which, if fully sold, would be about 43% of the equity of the company. They had to do it preferred stock, because there's too many, in Delaware Corporate Law, which all the tech companies are all Delaware, common stock would be very difficult to make a token. You can do whatever you want with preferred. So the preferred is more flexible, so it's actual equity, actual shares, it's not a derivative, it's not a rev share, it's not a royalty, it's actual equity. >> It's paper that converts nicely and it scales on the business side. >> So you say, "What's the evaluation?" >> We're selling 100 million dollars worth of the equity, or we're offering 100 million dollars of the equity, the pre-sale evaluation is a little over 200 million. In Chimes' cases, that's because we're not a startup, we're an early stage company. >> How old is the company? >> Pardon me? >> How old is the company? >> Three and a half years. >> So you weren't born yesterday. >> We acquired music databases that were built at a cost of tens of millions of dollars in Europe, funded by the richest guy in Europe, who built it out and then got tired of it, tired of funding it, and then we were able to pick it up basically for equity deals. We picked it up and we're buying a second music database also that's a very big one. So it's not like we're a startup with an idea and a business plan. >> No, you've got assets, and you've got momentum, good management, you obviously know what you're doing. It's awesome. You've got a great scalability mindset. You've got a nicely packaged, clear target. >> That's right, so we're probably a little bit different than a lot of crypto startups, in that, a lot of brilliant entrepreneurs that you see here, but we've been around the block with having to do IPO's, having to do exits, having to do... And you know, I'm a contrarian, right? I was getting a lot of advice yesterday from a lot of really smart people saying, "Hey, raise the money overseas through a foundation." >> "Everyone's doing it!" >> Look, I'm going to take a contrarian approach. >> I'm just going to comply with the law, by doing the registration. And they say, "What if your utility token has to comply "with money transfer laws?" Then we'll comply with them! It's like look, the contrarian approach is, whatever the law is, follow it! It gives us the flex-- >> The thing is you're actually doing what they want you to do, notifying them of what you're doing, and you have a utility! >> By separating out the token into two, one that has the attributes of currency, one that has the attributes of an equity, neither one is screwing up the other. >> I agree, that's really smart, and very novel. A lot of smart people are going down that road because it's actually known things people can understand. Security token is paperwork that you can do. >> Yes, but I'll tell you the other thing that feels very important, a pretty important point to make. By doing registration, the resale can go to anybody. My personal opinion, is you know these second market type of approaches that you can only resale them to accredited investors or to foreign investors or whatever, I think that's mistake. I think what happens is people who take that approach are going to find that the resale value of the token, or the token that has securities is going to be about 10% of what it would have been otherwise. >> If they only do accredited? >> Well yeah, because here's the thing. First, it's not only that they got to be accredited-- >> How do you get around the security token? >> Because it's registered. The waitress working the bar here can buy a publicly traded equity if it's registered, right? She can buy a publicly traded token-- >> That's the Form 10 that you were talking about. >> Right, Form 10 registers the company. The initial batch of trading will be done under 144 because the token holds will evolve over six months, so they can sell them at their leisure, right? There are exceptions, by the way, like an affiliate might have to do some form filing. I would have to file a Form 3, you know, the usual stuff. But, a regular token investor, he can do whatever he wants. And I can call them investors. I can do business in the United States. I don't have to pretend I'm domiciled in a country you've never heard of, right? So it's like look, I'm an American, my staff is mostly American, we do business in America, let's follow American law instead of-- >> Joe, this is a great conversation. We're getting down and dirty under the hood, capital structure, business models, Chimes' really interesting approach. Joe, thanks for sharing that great data here on theCUBE. Section 12G of the 1934 Securities Act. Form 10 is the secret weapon that was built by aliens before us to allow us to get this special clause in there for crypto. I'd love to continue this conversation another time. I think there's four or five things we just identified, great great topics, thanks for sharing. It's theCUBE's coverage here in Puerto Rico, I'm John Furrier, we'll be back with more after this short break. (digital jingle)

>> Voiceover: Live from San Francisco, it's The Cube. Covering AWS Summit 2017. Brought to you by Amazon Web Services. >> Hi, welcome back to The Cube. We are live in San Francisco at the AWS Summit. We've had a great day so far. I'm Lisa Martin here with my co-host George Gilbert. We are very excited to be joined by Datadog. K Young the Director of Strategic Alliances from Datadog, welcome to The Cube. >> Thank you, hi. Glad to be here. >> So, tell us, besides loving your shirt, as I've already told you, tell us and our viewers a little bit about who Datadog is and what do you do. >> Alright, so Datadog does infrastructure monitoring and application performance monitoring. So what that means is we're able to not only look at your hosts and the resources they have available to them, meaning CPU and memory and that sort of thing, but also all the software that's running on top of it. So, if it's off the shelf software, like a database, like Postgres, or maybe it's EngineX, we understand over 200 different off-the-shelf types of software, integrate with them directly so all you have to do is turn on those integrations, and we can tell you whether those pieces of software are performing at the rate that they ought to, with a sufficiently low number of errors. That's the infrastructure monitoring side of things. Then application performance monitoring, is where you can actually trace execution of requests, individual requests, across different services, or microservices, and tell where time is being spent and track metadata so that in a forensic case, you can go back and determine, oh this type of call is producing a lot of errors. Oh, and those errors are coming from here, and then, you know, maybe a lot of time is being spent here, and then because Datadog also does infrastructure monitoring, drill down into, okay well, what's happening under the hood? Maybe we're having problems because our infrastructure itself is misbehaving in some way. >> You have some pretty big customers: Salesforce, Airbnb, Samsung. I was just reading yesterday, an article that was published, that you've been, Datadog, in the top five businesses profiled by IDC as the multi-cloud management vendors to look out for. So, some pretty big accolades, some pretty big customers. How long have you been in business? >> K Young: Since 2010. >> Lisa: 2010. And tell us about what you're doing with Amazon. >> What we're doing with Amazon. So, let's see, where to begin. Amazon, a lot of people come to Datadog when they have complex systems to manage, meaning highly dynamic, or high scale, or they've adopted Docker, and their infrastructure is changing frequently. More frequently than infrastructure used to change ten years ago. Because Datadog makes it easy or ... Easy, possible even, to make sense of what's happening, even as your infrastructure changes on an hourly basis. So, a lot of customers come to us around the time they're interested in using dynamic infrastructure. Sometimes that's on Amazon, and sometimes that's when you're On-Prem but you're adopting Docker, for example, or microservices. We get a lot of business on Amazon. I think it's fair to say Amazon loves us, because it makes it so much easier to use their service and to adopt their service. And we're sort of the defacto infrastructure monitoring service for Amazon. >> So, you talking about containers, microservices, hyperscale. Is there a break with earlier monitoring and management software that didn't handle the ephemeral nature of applications and infrastructure? Is that the change? >> Yeah, that's basically it. Ten years ago, you as an assistant administrator or operations person, would have known the names of every one of your servers, and you kind of treat them affectionately. "Oh, you know, old Roger is misbehaving again, we got to give it a reboot." These days you don't know, in many cases, how many servers you have, much less what's running on them. So, it used to be that you could set up monitoring where you say, "Okay, I need to look at these things. They should be doing these set of tasks." And you set it up and basically forget it for six months or a year. Now, what's happening on any given machine or what's inside of a container, is churning very, very frequently. And so, to make sense of that, you have to use tags. So to tag all of your infrastructure with what it's doing, maybe what environment it is, like if it's staging or production, whether it's in AWS or On-Prem. Maybe it's a part of a build. And then you can look at your infrastructure and its performance through those lenses. You don't have to think in advance, "Oh, I'm going to want to know what's happening in US-East-1 in production with build number 1180." You can just do that on the fly with Datadog. And that's the sort of thing that we make possible. It's necessary for modern applications and modern services, that really wasn't possible before. >> So, it sounds like it's fairly straightforward at the infrastructure level to know what metrics and events you want to collect, in the sense that, you know, CPU utilization, memory utilization and, you know, maybe even a database number of connections and query time, but as you move up at the application level, the things that you want to ask could become very different between apps. >> K Young: Yeah. >> And then very different across Cloud or On-Prem. >> Yeah, that's right. So, there's sort of two classes of different things you could want to ask. Datadog accepts totally custom metric, so we know about, as I said, 200 different technologies, and we can collect everything automatically. But then, you're going to have your own application and you're going to want to send us things that are specific to your business. We take those just as well. So, for example, I think we have one customer who tracks when cash register drawers open or close. You know, that's not built in, but they can send those metrics to us. They get graphed the same way. We can set alerts on it the same way. We can use sophisticated machine learning to make projections about how we expect those patterns to be in the future, and if the cash registers don't open at the right rate, we can let somebody know that something has gone wrong. So, we can collect any kind of metrics. Then on top of that, we've got application performance monitoring. Right, so that's where you've written custom code, and Datadog, since it's already running on all of your servers, can track requests as it moves from service to service, or between microservices, and recompile that request into a visualization that will show you everything that happened, how long it took, and allows you to drill in and get metadata about each thing. So, you can actually reconstruct where time is going or whether there are problems. >> Why don't I ask you about some of the trends? As I mentioned a minute ago reading that article, or the mention of Datadog by IDC as one of the top five multi-cloud management vendors. What are some of the trends that you were seeing with respect to hypercloud, multi-cloud? You know, we've heard some conversation today from AWS, but I'd love to get your feedback, as the Director of Strategic Initiatives, what are you seeing? >> So, the trend that ... I'm going to answer this, but the trend that we were seeing a few years ago was more and more people were adopting Cloud, period. And that's continued and continued and continued. 18 months ago, if you went and talked to a large financial services organization and you told them, we do monitoring. Okay, they're interested. Well, we run only in the Cloud, so you actually have to send your data to the Cloud. They'd show you the door very politely. And now, they say, "Oh well, we're going to the cloud, now, too." It's a great place to be. Now, we're seeing organizations of all sizes, all types, are in the Cloud. So, the next leading trend is containerization and microservices. So, we actually published a Docker adoption report. We've done it three times now. We refreshed it yesterday. We do it about every six months, and we take a look at all of the usage that we can see. Because we have this somewhat unique vantage point of being able to see tens of thousands of customer's usage, real usage, of infrastructure, and look at, okay, which percent are using Docker? When they use it, do they dabble with it? Do they fully adopt it? Do they eventually abandon it? What are they running on it? So, we published a very long report. Anyone who's interested can actually Google "Docker adoption" and we'll be the top hit there. We've got eight different fact that talk about how quickly it's being adopted. Docker adoption is really quite remarkable. We're seeing a 40% growth in true adoption, not just dabbling, since last year. At the same time, we've seen a more than 100% increase, a more than doubling, of the companies that use Docker, that are using orchestrators, like Kubernetes, to manage even more sophisticated and rapidly changing fleets of machines. And that's really meaningful, because orchestration with containers really enables microservices, which enables Devox, which enables people to move quickly with very little friction and own specific parts of a stack. >> Does that mean that their On-Prem operations are beginning to look more and more in terms of processes like the Clouds? That it's not just a VM, but they're actually orchestrating things? >> Yes, it does. And people will run orchestration on top of the Cloud, or they'll run it On-Prem. But yeah, it's exactly the same. It's the same idea. If you're On-Prem you have a physical machine, you're running several containers in it, and they can just be very fluid and dynamic. >> And then how does machine learning ... How do you fit machine learning into the, whether it's at the infrastructure level or at the application performance management level, do you run it and get a baseline of what's normal? Or ... >> So there's some very deep math behind what we do, so we're able to project where metrics ought to be in the future. Across any number of different categories or tags that you give us, it's important that we do that very accurately 'cause we don't have false positives in our alerts, meaning we don't want to wake people up unnecessarily. We also don't want to have false negatives, meaning we don't want not alert when we should have. So there's a lot of math that goes into that and we can take care of very complex periodicity even while trends are happening within metrics, and doing that at scale, so it happens in real time is a challenge, but one that we're very proud of our solution. >> So you've been able to really derive some differentiation in the market. One of the things I was also reading was that a lot of the business, I mentioned some of those great brands, is in the U.S. and your CIO has been quite vocal about wanting to change that. What's happened in the last year, maybe with big rounds of Fund-Me raise, that's going to help you get more global as even Amazon was talking about expansion and geographies this morning? >> Well so it's even been a while since we've raised money, a year and a half now, I guess, but the company is doing so well. It's a great place to be. The company's doing so well that we're just able to expand our operations and look bigger and bigger. Our two founders are actually French, or they were born in France, at any rate. And so we have a Paris office and we're moving pretty aggressively into Europe now. >> Lisa: Fantastic. >> One question on, again, the hybrid-cloud migration. Whether it's On-Prem to, say, Azure, or On-Prem to Azure and Amazon, would the use of Datadog make it easier for the customer to, essentially, run the same workloads on either of the Clouds? >> Absolutely. So we see a lot of people coming to Datadog at the moment when they need to move from pure On-Prem to maybe hybrid or maybe fully into the Cloud. Because you can set up Datadog to look at both those environments and understand the performance characteristics and then move over bytes of into the Cloud and make sure that nothing's falling apart and that everything is behaving exactly as you expect. >> And then how about for those who say, "Well, we want to be committed to two Clouds, because we don't want to be beholden." >> K Young: Right. >> Do you help with that? >> Yeah, we don't help with literally, like, data movement, which is sometimes one of the challenges. >> But in managing, it's sort of pane of glass? >> Yes, exactly. It's all one pane of glass and you can take ... Once metrics are in Datadog, it doesn't really matter where they came from, you can overlay requests per second or latency and frame Google's Cloud right alongside latency that you're seeing in AWS on the same graph or next to each other, but you can set alerts if they deviate too much from each other. >> So it's kind of an abstraction layer or at least a commonality that customers would be able to have those applications and different clouds from different providers and be able to see the performance of the application and the infrastructure. And so one last question for you, as we're getting ready up to wrap here, you know there's a lot of debate about hybrid-cloud and there's reports that say in the next few years, companies will have to be multi-cloud, just look at the Snap and IPO filing from a couple months ago. Big announcement. Two billion dollars over five years with Google. And then, revise that S1 filing to announce a billion dollar deal with Amazon. >> K Young: Yeah. >> So I'm just curious. Are you seeing that maybe with the enterprises, like a Snap, more and more that, by default, whether it's for redundancy of infrastructure operations, is that a trend that you're also seeing? That you're quite well-positioned to be able to facilitate? >> Yeah, we're definitely seeing ... You know, it's clear that Amazon is in the commanding position, for sure, but we are definitely seeing more and more interest in actual action and other Clouds as well. >> Fantastic. Well, we thank you first of all for being on the program today. Great. Congratulations on the success that you've had with Amazon, with others, and with the market differentiation. Congrats on expanding globally as well, and we look forward to having you back on the program. >> Right. Well, thanks very much for having me. >> Excellent. So K Young, Director of Strategic Alliances from Datadog. On behalf of K, my co-host George Gilbert, I'm Lisa Martin. You're watching The Cube live from the AWS Summit in San Francisco, but stick around 'cause we're going to be right back. (techno music) (dramatic music)

>> Announcer: Live from Munich, Germany, it's The CUBE, covering DataWorks Summit Europe 2017. Brought to you by Heartenworks. >> Okay, welcome back everyone, we are here live in Munich, Germany For DataWorks 2017, the DataWorks Summit, formally Hadoop Summit. I'm John Furrier with Silicone Angle's theCUBE, my co-host Dave Vellante, wrapping up day two of coverage here with Christoph Schubert, who's the Senior Director of SAP Big Data, handles all the go-to-market for SAP Big Data, @sapbigdata is the Twitter handle. You have a great shirt there, Go Live >> Go Live or go home. (Laughs) >> John: You guys are a part. Welcome to theCUBE. >> Christoph: Thank you, I appreciate it. >> Thanks for joining us and on the wrap up. You and I have known each other, we've known each other for a long time. We've been in many Sapphires together, we've had many conversations around the role of data, the role of architecture, the role of how organizations are transforming at the speed of business, which is SAP, it's a lot of software that powers business, under transformation right now. You guys are no stranger to analytics, we have the HANA Cloud Platform now. >> Christoph: We know a thing or two about that, yeah. (laughs) >> You know a little bit about data and legacy as well. You guys power pretty much most of the Fortune 100, if not all of them. What's your thoughts on this? >> Yeah, good point. On the topic of some numbers, about 75% of the world GDP runs through SAP systems eventually. So yes, we know a thing or two about transactional and analytical systems, definitely. >> John: And you're a partner with Hortonworks >> With Hortonworks and other Cloud providers, Hadoop Providers, certainly, absolutely but in this case, Hortonworks. We have, specifically, a solution that runs on Hadoop Spark and that allows, actually, our customers to unify much, much larger data sets with a system of records that we now do so many of them around the world for new and exciting new cases. >> And you were born in Munich. This is your hometown. >> This is actually a home gig for me, exactly. So, yes, unfortunately I'll also be presenting in English but yeah, I want to talk German, Bavarian, all the time. (laughs) >> I see my parents tonight. >> I wish we could help you >> but we don't speak Bavarian. But we do like to drink the beer though. It's the fifth season but a lot of great stuff here in Germany. Dave, you guys, I want to get your thoughts on something. I wanted to get you, just 'cause you're both, you're like an analyst, Christoph as well. I know you're over at SAP but, you know, you have such great industry expertise and Dave obviously covers the stuff everyday. I just think that the data world is so undervalued, in my mind. I think the ecosystem of startups that are coming out in the, out of the open source ecosystems, which are well-defined, by the way, and getting better. But now you have startups doing things like VIMTEC, we just had a bank on. Startups creating value and things like block chain on the horizon. Other new paradigms are coming on, is going to change the landscape of how wealth is created and value is created and charged. So, you've got a whole new tsunami of change. What's your thoughts on how this expands and obviously, certainly, Hortonworks as a public company and Cloudera is going public, so you expect to see that level up in valuation. >> They're in the process, yes. >> But I still think they're both undervalued. Your thoughts. >> Well it's not just the platform, right? and that what, I think, where Hadoop also came from. The legacy of Hadoop is that you don't have to really think about how you want to use your data. You have to, don't think ahead what kind of schema you want to apply and how you want to correlate your data. You can create a large data lake, right? That's the term that was created a long time ago, that allows customers to just collect all that data and think in the second stage about what to use with it and how to correlate it. And that's exactly, now, we're also seeing in the third stage, to not just create analytics but also creating applications instead of analytics or on top of analytics, correlating with data that also drives the business, the core business, from an OLTP perspective or also from an OLAP perspective. >> I mean, Dave, you were the one who said Amazon's a trillion dollar TAM, will be the first trillion dollar company and you were kind of, but you looked at the thousand points of Live with Cloud enables, all these aggregated all together, what's your thoughts on valuation of this industry? Because if Hortonworks continues on this peer play and they've got Cloudera coming in and they're doing well, you could argue that they're both undervalued companies if you count the ecosystem. >> Well, we always knew that big data was going to be a heavy lift, right? And I would agree with what Christoph was saying, was that Hadoop is profound in that it was no schema on right and ship five magabytes of code to a pedabyte of data. But it was hard to get that right. And I remember something you said, John, at one of our early SAP Sapphires, When the big data meme was just coming through. You said, "You know, SAP is not just big data, it's fast data". And you were talking about bringing transaction and analytic data together. >> John: Right. >> Again, something that has only recently been enabled. And you think about, you know, continuous streaming. I think that, now, big data has sort of entered the young-adulthood phase, we're going to start seeing steep part of that S-curve returns, and I think the hype will be realized. I think it is undervalued, much like the internet was. It was overvalued, then nobody wanted to touch it, and then it became. Actually, if you think back to 1999, the internet was undervalued in terms of what it actually achieved. >> John: Yeah. >> I think the same or similar thing is going to happen with big data. And since we have an SAP guest on, I'll say as well, We all remember the early days of ERP. >> Mhm, oh yeah. >> It wasn't clear >> Nope. >> Who was going to emerge as the king. >> Right. >> There were a few solutions. You're right. >> That's right. And, as well, something else we said about big data, it was the practitioners of ERP that made the most money, that created the most value and the same thing is happening here. >> Yeah. In fact, on that topic, I believe that 2017 and 2018 will be the big years for big data, so to speak. >> John: Uh huh. >> In fact, because of some statistics. >> John: In what way? >> Well, we just did >> Adoption, S-curve? >> Right, exactly. Utilizing the value of big data. You're talking about valuation here, right? 75% of CEOs of the top 1000 believe that the next three years are more important to their business than the last 50. And so that tells me that they're willing to invest. Not just the financial market, where I believe really run the most sophisticated big data analytics and models today. They had real use cases with real results very quickly. And so, they showed many how it's done. They created sort of the new role of a data scientist. They have roles like an AML officer. It's a real job, they do nothing else but anti-money laundering, right? So, in that industry they've shown us how to do that and I think others will follow. >> Yeah, and I think that when you look at this whole thing about digital transformation, it's all about data. >> John: Yeah. >> I mean, if you're serious about digital transformation, you must become a data-driven company and you have to hop on that curb. Even if you're talking to the, you know, bank today who got on in 2014, which was relatively late, but the pace at which they're advancing is astronomical. >> John: Yeah. >> I don't remember his name, a British mathematician, created, about 11 years already, that according to the phrase "Data is the new oil". >> John: Mhm. >> And I think it's very true because crude oil, in its original form, you also can't use it. >> John: It has to be refined. >> Right, exactly. It has to be refined to actually use it and use the value of it. Same thing with data. You have to distill it, you have to correlate it, you have to align it, you have to relate it to business transactions so the business really can take advantage of it. >> And then we're seeing, you know, to your point, you've got, I don't know, a list of big data companies that are now in public is growing. It's still small, not much profit. >> I mean, I just think, and this is while I'm getting your reaction, I mean, I'm just reading right now some news popping on my dashboard. Google just released some benchmarks on the TPU, the transistor processing unit, >> Dave: Right. >> Basically a chip dedicated to machine learning. >> Yep. >> You know, so, you're going to start to see some abstraction layers develop, whether it's a hardened-top processor hardware, you guys have certainly done innovation on the analytic side, we've seen that with some of the specialty apps. Just to make things go faster. I mean, so, more and more action is coming, so I would agree that this S-curve is coming. But the game might shift. I mean, this is not an easy, clear path. There's bets being made in big data and there's potential for huge money shift, of value. >> See, one of the things I see, and we talked to Hortonworks about this, the new president, you know, betting all on open source. I happen to think a hybrid model is going to win. I think the rich get richer here. SAP, IBM, even Oracle, you know, they can play the open source game and say, "Hey, we're going to contribute to open source, we're going to participate, we're going to utilize open source, but we're also going to put the imprimatur of our install base, our business model, our trusted brands behind so-called big data." We don't really use that term as much anymore. It's the confluence of not only the technology but the companies who, what'd you say, 75% of the world's transactions run though SAP at some point? >> Christoph: Yeah. >> With companies like SAP behind it, and others, that's when this thing, I think, really takes off. >> What I think a lot of people don't realize, and I've been a customer, also, for a long time before I joined the vendor side, and what is under-realized is the aspect of risk management. Once you have a system and once you have business processes digitized and they run your business, you can't introduce radical changes overnight as quickly anymore as you'd like or your business would like. So, risk management is really very important to companies. That's why you see innovation within organizations not necessarily come from the core digitization organization within their enterprise, it often happens on the outside, within different business units that are closer to the product or to the customer or something. >> Something else that's happening, too, that I wanted to address is this notion of digitization, which is all about data, allows companies to jump industries. You're seeing it everywhere, you're seeing Amazon getting into content, Apple getting into financial services. You know, there's this premise out there that Uber isn't about taxicabs, it's about logistics. >> John: Yeah. >> And so you're seeing these born-digital, born in the cloud companies now being able to have massive impacts across different industries. Huge disruption creates, you know, great opportunities, in my view. >> Christoph: Yeah. >> David: What do you think? >> I mean, I just think that the disruption is going to be brutal, and I want to, I'm trying to synthesize what's happening in this show, and you know, you're going to squint through all the announcements and the products, really an upgrade to 2.6, a new data platform. But here in Europe the IOT thing just, to me, is a catalyst point because it's really a proof point to where the value is today. >> David: Mhm. >> That people can actually look at and say, "This is going to have an impact on our business tier digitization point" and I think IOT is pulling the big data industry and cloud together. And I think machine learning and things that come over the top on it are only going to make it go faster. And so that intersection point, where the AI, augmented intelligence, is going to come in, I think that's where you're going to start to see real proof points on value proposition of data. I mean, right now it's all kind of an inner circle game. "Oh yeah, got to get the insights, optimize this process here and there" and so there's some low hanging fruit, but the big shifting, mind blowing, CEO changing strategies will come from some bigger moves. >> To that point, actually, two things I want to mention that SAP does in that space, specifically, right? Startups, we have a program actually, SAP.io, that Bill McDermont also recently introduced again, where we invest in startups in this space to help foster innovation faster, right? And also connecting that with our customers. >> John: What is it called? >> SAP.io Something to look out for. And on the topic of IOT, we made, also, an announcement at the beginning of the year, Project Leonardo. >> Yeah. >> It's a commitment, it's a solution set, and it's also an investment strategy, right? We're committed in this market to invest, to create solutions, we have solutions already in the cloud and also in primus. There are a few companies we also purchased in conjunction with Loeonardo, RT specifically. Some of our customers in the manufacturing space, very strong opportunity for IOT, sensor collection, creating SLAs for robotics on the manufacturing floor. For example, we have a complete solution set to make that possible and realize that for our customers and that's exactly a perfect example where these sensor applications in IOT, edge, compute rich environments come together also with a core where, then, a system of references like machine points, for example, matter because if you manage the SLA for a machine, for example, you just not only monitor it, you want to also automatically trigger the replacement of a part, for example, and that's why you need an SAP component, as well. So, in that space, we're heavily investing, as well. >> The other think I want to say about IOT is, I see it, I mean, cloud and big data have totally disrupted the IT business. You've seen Dell buying EMC, HP had to get out of the cloud business, Oracle pivoted to the cloud, SAP obviously, going hard after the cloud. Very, very disruptive, those two trends. I see IOT as not necessarily disruptive. I see those who have the install base as adopting IOT and doing very, very well. I think it's maybe disruptive to the economy at large, but I think existing companies like GE, like Siemens, like Dimar, are going to do very, very well as a result of IOT. I mean, to the extent they embrace digitization, which they would be crazy not to. >> Alright guys, final thoughts. What's your walkaway from this show? Dave, we'll start with you. >> I was going to say, you know, Hadoop has definitely not failed, in my mind, I think it's been wildly successful. It is entering this new phase that I call sort of young-adulthood and I think it's, we know it's gone mainstream into the enterprise, now it's about, okay, how do I really drive the value of data, as we've been discussing, and hit that steep part of the S-curve. Which, I agree, it's going to be within the next two years, you're going to start to see massive returns. And I think this industry is going to be realized, looked back, it was undervalued in 2017. >> Remember how long it took to align on TCP/IP? (laughter) >> Walk away, I mean interoperability was key with TCP/IP. >> Christoph: Yeah. One of the things that made things happen. >> I remember talking about it. (laughter) >> Yeah, two megabits per second. Yeah, but I mean, bringing back that, what's your walkaway? Because is it a unification opportunity? Is it more of an ecosystem? >> A good friend of mine, also at SAP on the West Coast, Andreas Walter, he shared an observation that he saw in another presentation years ago. It was suits versus hoodies. Different kind of way to run your IT shop, right? Top-down structure, waterfall projects, and suits, open source, hack it, quickly done, you know, get in, walk away, make money. >> Whoa, whoa, whoa, the suits were the waterfall, hoodies was the agile. >> Christoph: That's correct. >> Alright, alright, okay. >> Christoph: Correct. So, I think that it's not just the technology that's coming together, it's mindsets that are coming together. And I think organizationally for companies, that's the bigger challenge, actually. Because one is very subscribed, change control oriented, risk management aware. The other is very progressive, innovative, fast adopters. That these two can't bring those together, I think that's the real challenge in organizations. >> John: Mhm, yeah. >> Not the technology. And on that topic, we have a lot of very intelligent questions, very good conversations, deep conversations here with the audience at this event here in Munich. >> Dave, my walkaway was interesting because I had some preconceived notions coming in. Obviously, we were prepared to talk about, and because we saw the S1 File by Cloudera, you're starting to see the level of transparency relative to the business model. One's worth one billion dollars in private value, and then Hortonworks pushing only 2700 million in a public market, which I would agree with you is undervalued, vis a vis what's going on. So obviously, you're going to see my observation coming in from here is that I think that's going to be a haircut for Cloudera. The question is how much value will be chopped down off Cloudera, versus how much value of Hortonworks will go up. So the question is, does Cloudera plummit, or does Cloudera get a little bit of a haircut or stay and Hortonworks rises? Either way, the equilibrium in the industry will be established. The other option would be >> Dave: I think the former and the numbers are ugly, let's not sugarcoat it. And so that's got to change in order for this prediction that we're making. >> John: Former being the haircut? >> Yeah, the haircut's going to happen, I think. But the numbers are really ugly. >> But I think the question is how far does it drop and how much of that is venture. >> Sure. >> Venture, arbitrage, or just how they are capitalized but Hortonworks could roll up. >> But my point is that those numbers have to change and get better in order for our prediction to come true. Okay, so, but in your second talk, sorry to interrupt you but >> No, I like a debate and I want to know where that line is. We'll be watching. >> Dave: Yeah. >> But the value in, I think you guys are pointing out but I walk away, is IOT is bigger here, and I already said that, but I think the S-curve is, you're right on. I think you're going to start to see real, fast product development around incorporating data, whether that's a Hortonworks model, which seems to be the nice unifying, partner-oriented one, that's going to start seeing specialized hardware that people are going to start building chips for using flash or other things, and optimizing hard complexities. You pointed that out on the intro yesterday. And putting real product value on the table. I think the cards are going to start hitting the table in ecosystem, and what I'm seeing is that happening now. So, I think just an overall healthy ecosystem. >> Without a doubt. >> Okay. >> Great. >> Any final comments? >> Let's have a beer. >> Great to see you in Munich. (laughter) >> We'll have a beer, we had a pig knuckle last night, Dave. We had some sauerkraut. >> Christoph: (speaks foreign word) >> Yeah, we had the (speaks foreign word). Dave, we'll grab the beer, thanks. Good to be with you again. Thanks to the crew, thanks to everyone watching. >> Thanks, John. >> The CUBE, signing off from Munich, Germany for DataWorks 2017. Thanks for watching, see ya next time. (soft techno music)

(upbeat music) >> Announcer: Live from Munich, Germany, it's the Cube covering DataWorks Summit Europe, 2017. Brought to you by Hortonworks. >> Hey, welcome back everyone. We're here live in Munich, Germany, at the DataWorks 2017 Summit. I'm John Furrier, my co-host Dave Vellante with the Cube, and our next two guests are Gianthomas Volpe, head of customer development e-media for Alation. Welcome to the Cube. And we have Bertrand Cariou, who's the director of solution marketing at Trifecta with partners. Guys, welcome to the Cube. >> Thank you. >> Thank you for having us. >> Big fans of both your start-ups and growing. You guys are doing great. We had your CEO on our big data SV, Joe Hellerstein, he talked about the rang, all the cool stuff that's going on, and Alation, we know Stephanie has been on many times, but you guys are start ups that are doing very well and growing in this ecosystem, and, you know, everyone's going public. Cloud Air has filed their S1, great news for those guys, so the data world has changed beyond Hadoop. You're seeing it, obviously Hadoop is not dead, but it's still going to be a critical component of a larger ecosystem that's developing. You guys are part of that. So I want to get your thoughts of why you're here in Europe, okay? And how you guys are working together to take data to the next level, because, you know, we're hearing more and more data is a foundational conversation starter, because now there's other things happening, IOT, business analysts, you guys are in the heart of it. Your thoughts? >> You know, going to be you. >> All in, yeah, sure. So definitely at Alation what we're seeing is more and more people across the organization want to get access to the data, and we're kind of breaking out of the traditional roles around IP managing both metadata, data preparation, like Trifecta's focused on. So we're pretty squarely focused on how do we bring that access to a wider range of people? How do we enable that social and collaborative approach to working with that data, whether it's in a data lake so, or here at DataWorks. So clearly that's one of the main topics. But also other data sources within the organization. >> So you're freeing the data up and the whole collaboration thing is more of, okay, don't just look at IT as this black box of give me some data and now spit out some data at me. Maybe that's the old way. The new way is okay, all of the data's out there, they're doing their thing, but the collaboration is for the user to get into that data you know, ingestion. Playing with the data, using the data, shaping the data. Developing with the data. Whatever they're doing, right? >> It's just bringing transparency to not only what IT is doing and making that accessible to users, but also helping users collaborate across different silos within an organization, so. We look at things like logs to understand who is doing what with the data, so if I'm working in one group, I can find out that somebody in a completely different group in the organization is working with similar data, bringing new techniques to their analysis, and can start leveraging that and have a conversation that others can learn from, too. >> So basically it's like a discovery platform for saying hey, you know, Mary in department X has got these models. I can leverage that. Is that kind of what you guys are all about? >> Yeah, definitely. And breaking through that, enabling communication across the different levels of the organization, and teaching other people at all different levels of maturity within the company, how they can start interacting with data and giving them the tools to up skill throughout that process. >> Bertrand, how about the Trifecta? 'Cause one of the things that I find exciting about Europe value proposition and talking to Joe, the founder, besides the fact that they all have GitHub on their about page, which is the coolest thing ever, 'cause they're all developers. But the more reality is is that a business person or person dealing with data in some part of a geography, could be whether it's in Europe or in the US, might have a completely different view and interest in data than someone in another area. It could be sales data, could be retail data, it doesn't matter but it's never going to be the same schema. So the issue is, got to take that away from the user complexity. That is really fundamental change. >> Yeah. You're totally correct. So information is there, it is available. Alation helps identify what is the right information that can be used, so if I'm in marketing, I could reuse sales information, associating maybe with web logs information. Alation will give me the opportunity to know what information is available and if I can trust it. If someone in finance is using that information, I can trust that data. So now as a user, I want to take that data, maybe combine the data, and the data is always a different format, structure, level of quality, and the work of data wrangling is really for the end user, you can be an analyst. Someone in the line of business most of the time, these could be like some of the customers we are here in Germany like Munich Re would be actuaries. Building risk models and or claimed for casting, payment for casting. So they are not technologies at all, but they need to combine these data sets by themselves, and at scale, and the work they're doing, they are producing new information and this information is used directly to their own business, but as soon as they share this information, back to the data lake, Alation will index this information, see how it is used, and put it to this visibility to the other users for reuse as well. >> So you guys have a partnership, or is this more of a standard API kind of thing? >> So we do have a partnership, we have plan development on the road map. It's currently happening. So I think by the end of the quarter, we're going to be delivering a new integration where whether I'm in Alation and looking for data and finding something that I want to work with, I know needs to be prepared I can quickly jump into Trifecta to do that. Or the other way around in Trifecta, if I'm looking for data to prepare, I can open the catalog, quickly find out what exists and how to work with it better. >> So basically the relationship, if I get this right is, you guys pass on your expertise of the data wrangling all the back processes you guys have, and advertise that into Alation. They discover it, make it surfaceable for the social collaboration or the business collaboration. >> Exactly. And when the data is wrangled, it began indexed and so it's a virtual circle where all the data that is traded and combined is exposed to the user to be reused. >> So if I were Chief Data Officer, I'd say okay, there's three sequential things that I need to do, and you can maybe help me with a couple of them. So the first one is I need to understand how data contributes to the monetization of my company, if I'm a public company or a for profit company. That's, I guess my challenge. But then, there are other two things that I need to give people access to that data, and I need quality. So I presume Alation can help me understand what data's available. I can actually, it kind of helps with number one as well because like you said, okay, this is the type of data, this is how the business process works. Feed it. And then the access piece and quality. I guess the quality is really where Trifecta comes in. >> GianThomas: Yes. >> What about that sequential flow that I just described? Is that common? >> Yeah >> In your business, your customer base. >> It's definitely very common. So, kind of going back to the Munich Re examples, since we're here in Munich, they're very focused on providing better services around risk reduction for their customers. Data that can impact that risk can be of all kinds from all different places. You kind of have to think five, ten years ahead of where we are now to see where it might be coming from. So you're going to have a ton of data going in to the data lake. Just because you have a lot of data, that does not mean that people will know how to work with it they won't know that it exists. And especially since the volumes are so high. It doesn't mean that it's all coming in at a greatly usable format. So Alation comes in to play in helping you find not only what exists, by automating that process of extraction but also looking at what data people are actually using. So going back to your point of how do I know what data's driving value for the organization, we can tell you in this schema, this is what's actually being used the most. That's a pretty good starting point to focus in on what is driving value and when you do find something, then you can move over to Trifecta to prepare it and get it ready for analysis. >> So keying on that for a second, so in the example of Munich Re, the value there is my reduction in expected loss. I'm going to reduce my risk, that puts money in my bottom line. Okay, so you can help me with number one, and then take that Munich Re example into Trifecta. >> Yes, so the user will be the same user using Alation and Trifecta. So is an actuary. So as soon as the actuary items you find the data that is the most relevant for what you'll be planning, so the actuaries are working with terms like development triangles over 20 years. And usually it's column by column. So they have to pivot the data row by row. They have to associate that with the paid claims the new claims coming in, so all these information is different format. Then they have to look at maybe weather information, or additional third party information where the level of quality is not well known, so they are bringing data in the lake that is not yet known. And they're combining all this data. The outcome of that work, that helps in the Reese modeling so that could be used by, they could use Sass or our older technology for the risk modeling. But when they've done that modeling and building these new data sets. They're, again, available to the community because Alation would index that information and explain how it is used. The other things that we've seen with our users is there's also a very strong, if you think about insurances banks, farmer companies, there is a lot of regulation. So, as the user, as you are creating new data, said where the data coming from. Where the data is going, how is it used in the company? So we're capturing all that information. Trifecta would have the rules to transform the data, Alation will see the overall eye level picture from table to the source system where the data is come. So super important as well for the team. >> And just one follow up. In that example, the actuary, I know hard core data scientists hate this term, but the actuaries, the citizen data scientist. Is that right? >> The actuaries would know I would say statistics, usually. But you get multiple level of actuaries. You get many actuaries, they're Excel users. They have to prepare data. They have to pin up, structure the data to give it to next actuary that will be doing the pricing model or the next actuary that will risk modeling. >> You guys are hitting on a great formula which is cutting edge, which is why you guys are on the startups. But, Bertrand I want to talk to you about your experience at Informatica. You were the founder the Informatica France. And you're also involved in some product development in the old, I'd say old days, but like. Back in the days when structured data and enterprise data, which was once a hard problem, deal with metadata, deal with search, you had schemes, all kinds of stuff to deal with. It was very difficult. You have expertise. I want you to talk about what's different now in this environment. Because it's still challenging. But now the world has got so much fast data, we got so much new IOT data, especially here in Europe. >> Oh yes. >> Where you have an industrialized focus, certainly Germany, like case in point, but it's pretty smart mobility going on in Europe. You've always had that mobile environment. You've got smart cities. A lot of focus on data. What's the new world like now? How are people dealing with this? What's your perspective? >> Yes, so there's and we all know about the big data and with all this volume, additional volume and new structure of data. And I would say legacy technology can deal as you mentioned, with well structured information. Also you want to give that information to the masses. Because the people who know the data best, are the business people. They know what to do with the data, but the access of this data is pretty complicated. So where Trifecta is really differentiating and has been thinking through that is to say whatever the structure of the data, IOT, Web Logs, Value per J son, XML, that should be for an end user, just metrics. So that's the way you understand the data. The next thing when play with data, usually you don't know what the schema would be at the end. Because you don't know what the outcome is. So, you are, as an end user, you are exploring the data combining data set and the structure is trading as you discover the data. So that is also something new compared to the old model where an end user would go to the data engineer to say I need that information, can you give me that information? And engineers would look at that and say okay. We can access here, what is the schema? There was all this back and forth. >> There was so much friction in the old way, because the creativity of the user is independent now of all that scaffolding and all the wrangling, pre-processing. So I get that piece of the Citizen's Journal, Citizen Analyst. But the key thing here is you were shrecking with the complexity to get the job done. So the question then comes in, because it's interesting, all the theme here at DataWorks Summit in Europe and in the US is all the big transformative conversations are starting with business people. So this a business unit so the front lines if you will, not IT. Although IT now's got to support that. If that's the case, the world's shifting to the business owners. Hence your start up. Is that kind of getting that right? >> I think so. And I think that's also where we're positioning ourselves is you have a data lake, you can put tons of data in it, but if you don't find an easy way to make that accessible to a business user, you're not going to get a value out of it. It's just going to become a storage place. So really, what we've focused on is how do you make that layer easily accessible? How do you share around and bring some of the common business practices to that? And make sure that you're communicating with IT. So IT shouldn't be cast aside, but they should have an ongoing relationship with the business user. >> By the way, I'll point out that Dave knows I'm not really a big fan of the data lake concept mainly because they've turned it into data swamps because IT deploys it, we're done! You know, check the box. But, data's getting stale because it's not being leveraged. You're not impacting the data or making it addressable, or discoverable or even wrangleable. If that's a word. But my point is that's all complexities. >> Yes, so we call it sort of frozen data lake. You build a lake, and then it's frozen and nobody can go fishing. >> You play hockey on it. (laughs) >> You dig and you're fishing. >> And you need to have this collaboration ongoing with the IT people, because they own the infrastructure. They can feed the lake with data with the business. If there is no collaboration, and we've seen that multiple times. Data lake initiatives, and then we come back one year after there is no one using the lake, like one, two person of the processing power, or the data is used. Nobody is going to the lake. So you need to index the data, catalog the data to know what is available. >> And the psychology for IT is important here, and I was talking yesterday with IBM folks, Nevacarti here, but this is important because IT is not necessarily in a position of doing it because doing the frozen lake or data swamp because they want to screw over the business people, they just do their job, but here you're empowering them because you guys are got some tech that's enabling the IT to do a data lake or data environment that allows them to free up the hassles, but more importantly, satisfy the business customer. >> GeanThomas: Exactly. >> There's a lot of tech involved. And certainly we've talked to you guys about that. Talk about that dynamic of the psychology because that's what IT wants. So what's that dev ops mindset for data, data ops if you will or you know, data as code if you will, constantly what we've been calling it but that's now the cloud ethos hits the date ethos. Kind of coming together. >> Yes, I think data catalogs are subtly different in that traditionally they are more of an IT function, but to some extent on the metadata side, where as on the business side, they tended to be a siloed organization of information that business itself kept to maintain very manually. So we've tried to bring that together. All the different parties within this process from the IT side to the govern stewardship all the way down to the analysts and data scientists can get value out of a data catalog that can help each other out throughout that process. So if it's communicating to end users what kind of impact any change IT will make, that makes their life easier, and have one way to communicate that out and see what's going to happen. But also understand what the business is doing for governance or stewardship. You can't really govern or curate if you don't know what exists and what matters to the business itself. So bring those different stages together, helping them help each other is really what Alation does. >> Tell about the prospects that you guys are engaging in from a customer standpoint. What are some of the conversations of those customers you haven't gotten yet together. And and also give an example of a customer that you guys have, and use cases where they've been successful. >> Absolutely. So typically what we see, is that an organization is starting up a data lake or they already have legacy data warehouses. Often it's both, together. And they just need a unified way of making information about those environments available to end users. And they want to have that better relationship. So we're often seeing IT engaged in trying to develop that relationship along with the business. So that's typically how we start and we in the process of deploying, work in to that conversation of now that you know what exists, what you might want to work with, you're often going to have to do some level of preparation or transformation. And that's what makes Trifecta a great fit for us, as a partner, is coming to that next step. >> Yeah, on Mobile Market Share, one of our common customers, we have DNSS, also a common customer, eBay, a common customer. So we've got already multiple customers and so some information about the issue Market Share, they have to deal with their customer information. So the first thing they receive is data, digital information about ads, and so it's really marketing type of data. They have to assess the quality of the data. They have to understand what values and combine the value with their existing data to provide back analytics to their customers. And that use case, we were talking to the business users, my people selling Market Share to their customers because the fastest they can unboard their data, they can qualify the quality of the data the easiest it is to deliver right level of quality analytics. And also to engage more customers. So it was really was to be fast onboarding customer data and deliver analytics. And where Alatia explain is that they can then analyze all the sequel statement that the customers, maybe I'll let you talk about use case, but there's also, it was the same users looking at the same information, so we engage with the business users. >> I wonder if we can talk about the different roles. You hear about the data scientists obviously, the data engineer, there might be a data quality professional involved, there's certainly the application developer. These guys may or may not even be in IT. And then you got a DVA. Then you may have somebody who's statistician. They might sit in the line of business. Am I overcomplicating it? Do larger organizations have these different roles? And how do you help bring them together? >> I'd say that those roles are still influx in the industry. Sometimes they sit on IT's legs, sometimes they sit in the business. I think there's a lot of movement happening it's not a consistent definition of those different roles. So I think it comes down to different functions. Sometimes you find those functions happening within different places in the company. So stewardship and governance may happen on the IT side, it might happen on the business side, and it's almost a maturity scale of how involved the two sides are within that. So we play with all of those different groups so it's sometimes hard to narrow down exactly who it is. But generally it's on the consumptions side whether it's the analyst or data scientists, and there's definitely a crossover between the two groups, moving up towards the governance and stewardship that wants to enable those users or document curing the data for them all the way to the IT data engineers that operationalize a lot of the work that the data scientists and analysts might be hypothesizing and working with in their research. >> And you sell to all of those roles? Who's your primary user constituency, or advocate? >> We sell both to the analytics groups as well as governance and they often merge together. But we tend to talk to all of those constituencies throughout a sales cycle. >> And how prominent in your customer base do you see that the role of the Chief Data Officer? Is it only reconfined within regulated industries? Does he seep into non-regulated industries? >> I'd say for us, it seeps with non-regulated industries. >> What percent of the customers, for instance have, just anecdotally, not even customers, just people that you talk to, have a Chief Data Officer? Formal Chief Data Officer? >> I'd say probably about 60 to 70 percent. >> That high? >> Yeah, same for us. In regulated industries (mumbles). I think they play a role. The real advantage a Chief Data and Analytical Officer, it's data and analytics, and they have to look at governance. Governance could be for regulation, because you have to, you've got governance policy, which data can be combined with which data, there is a lot. And you need to add that. But then, even if you are less regulated, you need to know what data is available, and what data is (mumbles). So you have this requirement as well. We see them a lot. We are more and more powerful, I would say in the enterprise where they are able to collaborate with the business to enable the business. >> Thanks so much for coming on the Cube, I really appreciate it. Congratulations on your partnership. Final word I'll give you guys before we end the segment. Share a story, obviously you guys have a unique partnership, you've been in the business for awhile, breaking into the business with Alation. Hot startups. What observations out there that people should know about that might not be known in this data world. Obviously there's a lot of false premises out there on what the industry may or may not be, but there's a lot of certainly a sea change happening. You see AI, it gives a mental model for people, Eugene Learning, Autonomous Vehicles, Smart Cities, some amazing, kind of magical things going on. But for the basic business out there, they're struggling. And there's a lot of opportunities if they get it right, what thing, observation, data, pattern you're seeing that people should know about that may not be known? It could be something anecdotal or something specific. >> You go first. (laughs) >> So maybe there will be surprising, but like Kaiser is a big customer of us. And you know Kaiser in California in the US. They have hundreds or thousands of hospitals. And surprisingly, some of the supply chain people where I've been working for years, trying to analyze, optimizing the relationship with their suppliers. Typically they would buy a staple gun without staples. Stupid. But they see that happening over and over with many products. They were never able to sell these, because why? There will be one product that have to go to IT, they have to work, it would take two months and there's another supplier, new products. So how to know- >> John: They're chasing their tail! >> Yeah. It's not super excited, they are now to do that in a couple of hours. So for them, they are able, by going to the data lakes, see what data, see how this hospital is buying, they were not able to do it. So there is nothing magical here, it's just giving access to the data who know the data best, the analyst. >> So your point is don't underestimate the innovation, as small as it may seem, or inconsequential, could have huge impacts. >> The innovation goes with the process to be more efficient with the data, not so much building new products, just basically being good at what you do, so then you can focus on the value you bring to the company. >> GianThomas what's your thoughts? >> So it's sort of related. I would actually say something we've seen pretty often is companies, all sizes, are all struggling with very similar, similar problems in the data space specifically so it's not a big companies have it all figured out, small companies are behind trying to catch up, and small companies aren't necessarily super agile and aren't able to change at the drop of a hat. So it's a journey. It's a journey and it's understanding what your problems are with the data in the company and it's about figuring out what works best for your solution, or for your problems. And understanding how that impacts everyone in the business. So it's really a learning process to understand what's going- >> What are your friends who aren't in the tech business say to you? Hey, what's this data thing? How do you explain it? The fundamental shift, how do you explain it? What do you say to them? >> I'm more and more getting people that already have an idea of what this data thing is. Which five years ago was not the case. Five years ago, it was oh, what's data? Tell me more about that? Why do you need to know about what's in these databases? Now, they actually get why that's important. So it's becoming a concept that everyone understands. Now it's just a matter of moving its practice and how that actually works. >> Operationalizing it, all the things you're talking about. Guys, thanks so much for bringing the insights. We wrangled it here on the Cube. Live. Congratulations to Trifecta and Alation. Great startups, you guys are doing great. Good to see you guys successful again and rising tide floats all boats in this open source world we're living in and we're bringing you more coverage here at DataWowrks 2017, I'm John Furrier with Dave Vellante. Stay with us, more great content coming after this short break. (upbeat music)

>> Narrator: Live from Munich, Germany it's the CUBE, covering Dataworks Summit Europe 2017. Brought to you by Hortonworks. >> Okay, welcome back everyone here at day two coverage of the CUBE here in Munich, Germany for Dataworks 2017. I'm John Furrier, my co-host Dave Vellante. Two days of wall to wall coverage SiliconANGLE Media's the CUBE. Our next guest is Raj Verma, the president and COO of Hortonworks. First time on the CUBE, new to Hortonworks. Welcome to the CUBE. >> Thank you very much, John, appreciate it. >> Looking good with a three piece suit we were commenting when you were on stage. >> Raj: Thank you. >> Great scene here in Europe, again different show vis-a-vis North America, in San Jose. You got the show coming up there, it's the big show. Here, it's a little bit different. A lot of IOT in Germany. You got a lot of car manufacturers, but industrial nation here, smart city initiatives, a lot of big data. >> Uh-huh. >> What's your thoughts? >> Yeah no, firstly thanks for having me here. It's a pleasure and good chit chatting right before the show as well. We are very, very excited about the entire data space. Europe is leading many initiatives about how to use data as a sustainable, competitive differentiator. I just moderated a panel and you guys heard me talk to a retail bank, a retailer. And really, Centrica, which was nothing but British Gas, which is rather an organization steeped in history so as to speak and that institution is now, calls itself a technology company. And, it's a technology company or an IOT company based on them using data as the currency for innovation. So now, British Gas, or Centrica calls itself a data company, when would you have ever thought that? I was at dinner with a very large automotive manufacturers and the kind of stuff they are doing with data right from the driving habits, driver safety, real time insurance premium calculation, the autonomous drive. It's just fascinating no matter what industry you talk about. It's just very, very interesting. And, we are very glad to be here. International business is a big priority for me. >> We've been following Hortonworks since it's inception when it spun out of Yahoo years ago. I think we've been to every Hadoop World going back, except for the first one. We watched the transition. It's interesting, it's always been a learning environment at these shows. And certainly the customer testimonials speaks to the ecosystem, but I have to ask you, you're new to Hortonworks. You have interesting technology background. Why did you join Hortonworks? Because you certainly see the movies before and the cycles of innovation, but now we're living in a pretty epic, machine learning, data AI is on the horizon. What were the reasons why you joined Hortonworks? >> Yeah sure, I've had a really good run in technology, fortunately was associated with two great companies, Parametric Technology and TIBCO Software. I was 16 years at TIBCO, so I've been dealing with data for 16 years. But, over the course of the last couple of years whenever I spoke to a C level executive, or a CIO they were talking to us about the fact that structured data, which is really what we did for 16 years, was not good enough for innovation. Innovation and insights into unstructured data was the seminal challenge of most of the executives that I was talking to, senior level executives. And, when you're talking about unstructured data and making sense of it there isn't a better technology than the one that we are dealing with right now, undoubtedly. So, that was one. Dealing with data because data is really the currency of our times. Every company is a data company. Second was, I've been involved with proprietary software for 23 years. And, if there is a business model that's ready for disruption it's the proprietary software business model because I'm absolutely convinced that open source is what I call a green business model. It's good for planet Earth so as to speak. It's a community based, it's based on innovation and it puts the customer and the technology provider on the same page. The customer success drives the vendor success. Yeah, so the open source community, data-- >> It's sustainables, pun intended, in the sense that it's had a continuing run. And, it's interesting Tier One software is all open source now. >> 100%, and by the way not only that if you see large companies like IBM and Microsoft they have finally woken up to the fact that if they need to attract talent and if they want to be known as talk leaders they have to have some very meaningful open source initiatives. Microsoft loves Linux, when did we ever think that was going to happen, right? And, by the way-- >> I think Steve Bauman once said it was the cancer of the industry. Now, they're behind it. But, this is the Linux foundation has also grown. We saw a project this past week. Intel donated a big project to the Linux now it's taking over, so more projects. >> Raj: Yes. >> There's more action happening than ever before. >> You know absolutely, John. Five years ago when I would go an meet a CIO and I would ask them about open source and they would wink, they say "Of course, "we do open source. But, it's less than 5%, right? Now, when I talk to a CIO they first ask their teams to go evaluated open source as the first choice. And, if they can't they come kicking and screaming towards propriety software. Most organizations, and some organizations with a lot of historical gravity so as to speak have a 50/50 even split between proprietary and open source. And, that's happened in the last three years. And, I can make a bold statement, and I know it'll be true, but in the next three years most organizations the ratio of proprietary to open source would be 20 proprietary 80 open source. >> So, obviously you've made that bet on open source, joining Hortonworks, but open is a spectrum. And, on one end of the spectrum you have Hortonworks which is, as I see it, the purest. Now, even Larry Ellison, when he gets onstage at Oracle Open World will talk about how open Oracle is, I guess that's the other end of the spectrum. So, my question is won't the Microsofts and the Oracles and the IBM, they're like recovering alcoholics and they'll accommodate their platforms through open source, embracing open source. We'll see if AWS is the same, we know it's unidirectional there. How do you see that-- >> Well, not necessarily. >> Industry dynamic, we'll talk about that later. How do you see that industry dynamic shaking out? >> No, absolutely, I think I remember way back in I think the mid to late 90s I still loved that quote by Scott McNeely, who is a friend, Dell, not Dell, Digital came out with a marketing campaign saying open VMS. And, Scott said, "How can someone lie "so much with one word?" (laughs) So, it's the fact that Oracle calling itself open, well I'll just leave it at, it's a good joke. I think the definition of open source, to me, is when you acquire a software you have three real costs. One is the cost of initial procuring that software and the hardware and all the rest of it. The second is implementation and maintenance. However, most people miss the third dimension of cost when acquiring software, which is the cost to exit the technology. Our software and open source has very low exit barriers to our technology. If you don't like our technology, switch it off. You own the software anyways. Switch off our services and the barrier of exits are very, very low. Having worked in proprietary software, as I said, for 23 years I very often had conversations with my customers where I would say, "Look, you really "don't have a choice, because if you want to exit "our technology it's going to probably cost you "ten times more than what you've spent till date." So, it a lock in architecture and then you milk that customer through maintenance, correct? >> Switching costs really are the metric-- >> Raj: Switching costs, exactly. >> You gave the example of Blockbuster Camera, and the rental, the late charge fees. Okay, that's an example of lock in. So, as we look at the company you're most compared with, now that's it's going public, Cloudera, in a way I see more similarities than differences. I mean, you guys are sort of both birds of a feather. But, you are going for what I call the long game with a volume subscription model. And, Cloudera has chosen to build proprietary components on top. So, you have to make big bets on open. You have to support those open technologies. How do you see that affecting the long term distance model? >> Yeah, I think we are committed to open source. There's absolutely no doubt about it. I do feel that we are connected data platform, which is data at rest and data in motion across on prem and cloud is the business model the going to win. We clearly have momentum on our side. You've seen the same filings that I have seen. You're talking about a company that had a three year head start on us, and a billion dollars of funding, all right, at very high valuations. And yet, they're only one year ahead in terms of revenue. And, they have burnt probably three times more cash than we have. So clearly, and it's not my opinion, if you look at the numbers purely, the numbers actually give us the credibility that our business model and what we are doing is more efficient and is working better. One of the arguments that I often hear from analysts and press is how are your margins on open source? According to the filings, again, their margins are 82% on proprietary software, my margins on open source are 84%. So, from a health of the business perspective we are better. Now, the other is they've claimed to have been making a pivot to more machine learning and deep learning and all the rest of it. And, they actually'd like us to believe that their competition is going to be Amazon, IBM, and Google. Now, with a billion dollars of funding with the Intel ecosystem behind them they could effectively compete again Hortonworks. What do you think are their chances of competing against Google, Amazon, and IBM? I just leave that for you guys to decide, to be honest with you. And, we feel very good that they have virtually vacated the space and we've got the momentum. >> On the numbers, what jumps out at you on filing since obviously, I sure, everyone at Hortonworks was digging through the S1 because for the first time now Cloudera exposes some of the numbers. I noticed some striking things different, obviously, besides their multiple on revenue valuation. Pretty obvious it's going to be a haircut coming after the public offering. But, on the sales side, which is your wheelhouse there's a value proposition that you guys at Hortonworks, we've been watching, the cadence of getting new clients, servicing clients. With product evolution is challenging enough, but also expensive. It's not you guys, but it's getting better as Sean Connolly pointed out yesterday, you guys are looking at some profitability targets on the Ee-ba-dep coming up in Q four. Publicly stated on the earnings call. How's that different from Cloudera? Are they burning more cash because of their sales motions or sales costs, or is it the product mix? What's you thoughts on the filings around Cloudera versus the Hortonworks? >> Well, look I just feel that, I can talk more about my business than theirs. Clearly, you've seen the same filings that I have and you've see the same cash burn rates that we have seen. And, we clearly are ore efficient, although we can still get better. But, because of being public for a little more than two years now we've had a thousand watt bulb being shown at us and we have been forced to be more efficient because we were in the limelight. >> John: You're open. >> In the open, right? So, people knew what our figures are, what our efficiency ratios were. So, we've been working diligently at improving them and we've gotten better, and there's still scope for improvement. However, being private did not have the same scrutiny on Cloudera. And, some would say that they were actually spending money like drunken sailors if you really read their S1 filing. So, they will come under a lot of scrutiny as well. I'm sure they'll get more efficient. But right now, clearly, you've seen the same numbers that I have, their numbers don't talk about efficiency either in the R and D side or the sales and marketing side. So, yeah we feel very good about where we are in that space. >> And, open source is this two edged sword. Like, take Yarn for example, at least from my perspective Hortonworks really led the charge to Yarn and then well before Doctor and Kubernetes ascendancy and then all of a sudden that happens and of course you've got to embrace those open source trends. So, you have the unique challenge of having to support sort of all the open source platforms. And, so that's why I call it the long game. In order for you guys to thrive you've got to both put resources into those multiple projects and you've got to get the volume of your subscription model, which you pointed out the marginal economics are just as good as most, if not any software business. So, how do you manage that resource allocation? Yes, so I think a lot of that is the fact that we've got plenty of contributors and committers to the open source community. We are seen as the angel child in open source because we are just pure, kosher open source. We just don't have a single line of proprietary code. So, we are committed to that community. We have over the last six or seven years developed models of our software development which helps us manage the collective bargaining power, so as to speak, of the community to allocate resources and prioritize the allocation of resources. It continues to be a challenge given the breadth of the open source community and what we have to handle, but fortunately I'm blessed that we've got a very, very capable engineering organization that keeps us very efficient and on the cutting edge. >> We're here with Raj Verma, With the new president and COO of Hortonworks, Chief Operating Officer. I've got to ask you because it's interesting. You're coming in with a fresh set of eyes, coming in as you mentioned, from TIBCO, interesting, which was very successful in the generation of it's time and history of TIBCO where it came from and what it did was pretty fantastic. I mean, everyone knows connecting data together was very hard in the enterprise world. TIBCO has some challenges today, as you're seeing, with being disrupted by open source, but I got to ask you. As a perspective, new executive you got, looking at the battlefield, an opportunity with open source there's some significant things happening and what are you excited about because Hortonworks has actually done some interesting things. Some, I would say, the world spun in their direction, their relationship with Microsoft, for instance, and their growth in cloud has been fantastic. I mean, Microsoft stock price when they first started working with Hortonworks I think was like 26, and obviously with Scott Di-na-tell-a on board Azure, more open source, on Open Compute to Kubernetes and Micro Services, Azure doing very, very well. You also have a partnership with Amazon Web Services so you already are living in this cloud era, okay? And so, you have a cloud dynamic going on. Are you excited by that? You bring some partnership expertise in from TIBCO. How do you look at partners? Because, you guys don't really compete with anybody, but you're partners with everybody. So, you're kind of like Switzerland, but you're also doing a lot of partnerships. What are you excited about vis-a-vis the cloud and some of the other partnerships that are happening. >> Yeah, absolutely, I think having a robust partner ecosystem is probably my number one priority, maybe number two after being profitable in a short span of time, which is, again, publicly stated. Now, our partnership with Microsoft is very, very special to us. Being available in Azure we are seeing some fantastic growth rates coming in from Azure. We are also seeing remarkable amount of traction from the market to be able to go and test out our platform with very, very low barriers of entry and, of course, almost zero barriers of exit. So, from a partnership platform cloud providers like Amazon, Microsoft, are very, very important to us. We are also getting a lot of interest from carriers in Europe, for example. Some of the biggest carriers want to offer business services around big data and almost 100%, actually not almost, 100% of the carriers that we have spoken to thus far want to partner with us and offer our platform as a cloud service. So, cloud for us is a big initiative. It gives us the entire capability to reach audiences that we might not be able to reach ringing one door bell at a time. So, it's, as I said, we've got a very robust, integrated cloud strategy. Our customers find that very, very interesting. And, building that with a very robust partner channel, high priority for us. Second, is using our platform as a development platform for application on big data is, again, a priority. And that's, again, building a partner ecosystem. The third is relationships with global SIs, Extensia, Deloitte, KPMG. The Indian SIs of In-flu-ces, and Rip-ro, and HCL and the rest. We have some work to do. We've done some good work there, but there's some work to be done there. And, not only that I think some of the initiatives that we are launching in terms of training as a service, free certification, they are all things which are aimed at reaching out to the partners and building, as I said, a robust partner ecosystem. >> There's a lot of talk a conferences like this about, especially in Hadoop, about complexity, complexity of the ecosystem, new projects, and the difficulties of understanding that. But, in reality it seems as though today anyway the technology's pretty well understood. We talked about Millennials off camera coming out today with social savvy and tooling and understanding gaming and things like that. Technology, getting it to work seems to not be the challenge anymore. It's really understanding how to apply it, how to value data, we heard in your panel today. The business process, which used to be very well known, it's counting, it's payroll, simple. Now, it's kind of ever changing daily. What do you make of that? How do you think that will effect the future of work? Yeah, I think there's some very interesting questions that you've asked in that the first, of course, is what does it take to have a very successful big data, or Hadoop project. And, I think we always talk about the fact that if you have a very robust business case backing a Hadoop project that is the number one key ingredient to delivering a Hadoop project. Otherwise, you can tend to boil the ocean, all right, or try and eat an elephant in one bite as I like to say. So, that's one and I think you're right. It's not the technology, it's not the complexity, it's not the availability of the resources. It is a leadership issue in organizations where the leader demands certain outcomes, business outcomes from the Hadoop project team and we've seen whenever that happens the projects seem to be very, very successful. Now, the second part of the question about future of work, which is a very, very interesting topic and a topic which is very, very close to my heart. There are going to be more people than jobs in the next 20, 25 years. I think that any job that can be automated will be automated, or has been automated, right? So, this is going to have a societal impact on how we live. I've been lucky enough that I joined this industry 25 years ago and I've never had to change or switch industries. But, I can assure you that our kids, and we were talking about kids off camera as well, our kids will have to probably learn a new skill every five years. So, how does that impact education? We, in our generation, were testing champions. We were educated to score well on tests. But, the new form of education, which you and I were talking about, again in California where we live, and where my daughter goes to high school and in her school the number one, the number one priority is to instill a sense of learning and joy of learning in students because that is what is going to contribute to a robust future. >> That's a good point, I want to just interject here because I think that the trend we're seeing in the higher Ed side too also point to the impact of data science, to curriculum and learning. It's not just putting catalogs online. There's now kind of an iterative kind of non-linear discovery to proficiency. But, there's also the emotional quotient aspect. You mentioned the love of learning. The immersion of tech and digital is creating an interdisciplinary requirement. So, all the folks say that, what the statistic's like half the jobs that are going to be available haven't even been figured out yet. There's a value creation around interdisciplinary skill sets and emotional quotient. >> Absolutely. >> Social, emotional because of the human social community connectedness. This is also a big data challenge opportunity. >> Oh, 100% and I think one of the things that we believe is in the future, jobs that require a greater amount of empathy are least susceptible to automation. So, things like caring for old age people in the world, and nursing, and teaching, and artists, and all the rest will be professions which will be highly paid and numerous. I also believe that the entire big data challenge about how you use data to impact communities is going to come into play. And also, I think John, you and I were again talking about it, the entire concept of corporations is only 200 years old, really, 200, 300 years old. Before that, our forefathers were individual contributors who contributed a certain part in a community, barbers, tailors, farmers, what have you. We are going to go back to the future where all of us will go back to being individual contributors. And, I think, and again I'm bringing it back to open source, open source is the start of that community which will allow the community to go back to its roots of being individual contributors rather than being part of a organization or a corporation to be successful and to contribute. >> Yeah, the Coase's Penguin has been a very famous seminal piece of work. Obviously, Ronald Coase who's wrote the book The Nature of the Firm is interesting, but that's been a kind of historical document. You look at blockchain for instance. Blockchain actually has the opportunity to disrupt what the Nature of the Firm is about because of smart contracts, supply chain, and what not. And, we have this debate on the CUBE all the time, there's some naysayers, Tim Conner's a VC and I were talking on our Friday show, Silicon Valley Friday show. He's actually a naysayer on blockchain. I'm actually pro blockchain because I think there's some skeptics that say blockchain is really hard to because it requires an ecosystem. However, we're living in an ecosystem, a world of community. So, I think The Nature of the Firm will be disrupted by people organizing in a new way vis-a-vis blockchain 'cause that's an open source paradigm. >> Yeah, no I concur. So, I'm a believer in that entire concept. I 100%-- >> I want to come back to something you talked about, about individual contributors and the relationship in link to open source and collaboration. I personally, I think we have to have a frank conversation about, I mean machines have always replaced humans, but for the first time in our history it's replacing cognitive functions. To your point about empathy, what are the things that humans can do that machines can't? And, they become fewer and fewer every year. And, a lot of these conferences people don't like to talk about that, but it's a reality that we have to talk about. And, your point is right on, we're going back to individual contribution, open source collaboration. The other point is data, is it going to be at the center of that innovation because it seems like value creation and maybe job creation, in the future, is going to be a result of the combinatorial effects of data, open source, collaboration, other. It's not going to because of Moore's Law, all right. >> 100%, and I think one of the aspects that we didn't touch upon is the new societal model that automation is going to create would need data driven governance. So, a data driven government is going to be a necessity because, remember, in those times, and I think in 25, 30 years countries will have to explore the impact of negative taxation, right? Because of all the automation that actually happens around citizen security, about citizen welfare, about cost of healthcare, cost of providing healthcare. All of that is going to be fueled by data, right? So, it's just, as the Chinese proverb says, "May you live in interesting times." We definitely are living in very interesting times. >> And, the public policy implications are, your friend and one of my business heroes, Scott McNeally says, "There's no privacy in "the internet, get over it." We interviewed John Tapscott last week he said "That's unacceptable, "we have to solve that problem." So, it brings up a lot of public policy issues. >> Well, the social economic impact, right now there's a trend we're seeing where the younger generation, we're talking about the post 9/11 generation that's entering the workforce, they have a social conscience, right? So, there's an emphasis you're seeing on social good. AI for social good is one of the hottest trends out there. But, the changing landscape around data is interesting. So, the word democratization has been used whether you're looking at the early days of blogging and podcasting which we were involved in and research to now in media this notion of data and transparency and open source is probably at a tipping point, an all time high in terms of value creation. So, I want to hear your thoughts on this because as someone who's been in the proprietary world the mode of operation was get something proprietary, lock it dowm, build a fence and a wall, protect it with folks with machine guns and fight for the competitive advantage, right? Now, the competitive advantage is open. Okay, so you're looking at pure open source model with Hortonworks. It changes how companies are competing. What is the competitive advantage of Hortonworks? Actually, to be more open. >> 100%. >> How do you manage that? >> No absolutely, I just think the proprietary nature of software, like software has disrupted a lot of businesses, all right? And, it's not a resistance to disruption itself. I mean, there has never been a business model in the history of time where you charge a lot of money to build a software, or sell a software that you built and then whatever are the defects in that software you get paid more money to fix them, all right? That's the entire perpetual and maintenance model. That model is going to get disrupted. Now, there are hundreds of billions of dollars involved in it so people are going to come kicking and screaming to the open source world, but they will have to come to the open source world. Our advantage that we're seeing is innovation now in a closed loop environment, no matter what size of a company you are, cannot keep up with the changing landscape around you from a data perspective. So, without the collective innovation of the community I don't really think a technology can stay at par with the changes around them. >> This is what I say about, this is what I think is such an important point that you're getting at because we were started SiliconANGLE actually in the Cloudera office, so we have a lot of friends that work there. We have a great admiration for them, but one of the things that Cloudera has done through their execution is they have been very profit oriented, go public at all costs kind of thing that they're doing now. You've seen that happen. Is the competitive advantage that you're pointing out is something we're seeing that similar that Andy Jasseys doing at AWS, which is it's not so much to build something proprietary per se, it's just to ship something faster. So, if you look at Amazon's competitive advantage is that they just continue to ship product faster and faster and faster than companies can build themselves. And also, the scale that they're getting with these economies is increasing the quality. So, open source has also hit the naysayers on security, right? Everyone said, "Oh, open source is not secure." As it turns out, it's more secure. Amazon at scale is actually becoming more secure. So, you're starting to see the new competitive advantage be ship more, be more open as the way to do business. What do you think the impact will be to traditional companies whether it's a startup competing or an existing bank? This is a paradigm shift, what's the impact going to be for a CIO or CEO of a big company? How do they incorporate that competitive advantage? Yeah, I think the proprietary software world is not going to go away tomorrow, John, you know that. There so much of installed software and there's a saying from where I come from that "Even a dead elephant is worth a million dollars," right? So, even that business model even though it is sort of dying it'll still be a good investment for the next ten years because of the locked in business model where customers cannot get out. Now, from a perspective of openness and what that brings as a competitive differentiators to our customer just the very base at which, as I've said I've lived in a proprietary world, you would be lucky if you were getting the next version of our software every 18 months, you'd be lucky. In the open source community you get a few versions in 18 months. So, the cadence at which releases come out have just completely disrupted the proprietary model. It is just the collective, as I said, innovative or innovation ability of the community has allowed us to release, to increase the release cadence to a few months now, all right? And, if our engineering team had it's way it'll further be cut short, right? So, the ability of customers, and what does that allow the customer to do? Ten years ago if you looked for a capability from your proprietary vendor they would say you have to wait 18 months. So, what do you do, you build it yourself, all right? So, that is what the spaghetti architecture was all about. In the new open source model you ask the community and if enough people in the community think that that's important the community builds it for you and gives it to you. >> And, the good news is the business model of open source is working. So, you got you guys have been public, you got Cloudera going public, you have MuleSoft out there, a lot of companies out there now that are public companies are open source companies, a phenomenal change over. But, the other thing that's interesting is that the hiring factor for the large enterprise to the point of, your point about so proprietary not updating, it's the same is true for the enterprise. So, just hiring candidates out of open source is now increased, the talent pool for a large enterprise. >> 100%, 100%. >> Well, I wonder if I could challenge this love fest for a minute. (laughs) So, there's another saying, I didn't grow up there, but a dying snake can still bite you. So, I bring that up because there is this hybrid model that's emerging because these elephants eventually they figure it out. And so, an example would be, we talked about Cloudera and so forth, but the better example, I think, is IBM. What IBM has done to embrace open source with investing years ago a billion dollars into Linux, what it's doing with Spark, essentially trying to elbow its way in and say, "Okay, "now we're going to co-opt the ecosystem. "And then, build our proprietary pieces on top of it." That, to me, that's a viable business model, is it not? >> Yes, I'm sure it is and to John's point with the Mule going IPO and with Cloudera having successfully built a $250 million, $261 million business is testimony, yeah, it's a testimony to the fact that companies can be built. Now, can they be more efficient, sure they can be more efficient. However, my entire comment on this is why are you doing open source? What is your intent of doing open source, to be seen as open, or to be truly open? Because, in our philosophy if you a add a slim layer of proprietariness, why are you doing that? And, as a businessman I'll tell you why you increase the stickiness factor by locking in your customer, right? So, let's not, again, we're having a frank conversation, proprietary code equals customer lock in, period. >> Agreed. And, as a business model-- >> I'm not sure I agree with that. >> As a business model. >> Please. (laughs) We'll come back to that. >> So, it's a customer lock in. Now, as a business model it is, if you were to go with the business models of the past, yes I believe most of the analysts will say it a stickier, better business model, but then we would like to prove them wrong. And, that's our mission as open source purely. >> I would caution though, Amazon's the mother of all lock in's. You kind of bristled at that before. >> They're not, I mean they use a lot of open source. I mean, did they open source it? Getting back to the lock in, the lock in is a function of stickiness, right? So, stickiness can be open source. Now, you could argue that Horonworks through they're relationship with partnering is a lock in spec with their stickiness of being open. Right, so I come back down to the proprietary-- >> Dave: My search engine I like Google. >> I mean Google's certainly got-- >> It's got to be locked in 'cause I like it? >> Well, there's a lot of do you care with proprietary technology that Google's built. >> Switching costs, as we talked about before. >> But, you're not paying for Si-tch >> If the value exceeds the price of the lock in then it's an opportunity. So, Palma Richie's talking about the hardened top, the hardened top. Do you care what's in an Intel processor? Well, Intel is a proprietary platform that provides processing power, but it enables a lot of other value. So, I think the stickiness factor of say IBM is interesting and they've done a lot open source stuff to defend them on Linux, for example they do a (mumbles) blockchain. But, they're priming the pump for their own business, that's clear for their lock In. >> Raj wasn't saying there's not value there. He's saying it's lock in, and it is. >> Well, some customers will pay for convenience. >> Your point is if the value exceeds the lock in risk than it's worth it. >> Yeah, that's my point, yeah. >> 1005, 100%. >> And, that's where the opportunity is. So, you can use open source to get to a value projectory. That's the barriers to entry, we seen 'em on the entrepreneurship side, right? It's easier to start a company now than ever before. Why? Because of open source and cloud, right? So, does that mean that every startup's going to be super successful and beat IBM? No, not really. >> Do you thinK there will be a red hat of big data and will you be it? >> We hope so. (laughs) If I had my that's definitely. That's really why I am here. >> Just an example, right? >> And, the one thing that excites us about this this year is as my former boss used to say you could be as good as you think you are or the best in the world but if you're in the landline business right now you're not going to have a very bright future. However, the business that we are in we pull from the market that we get, and you're seeing here, right? And, these are days that we have very often where customer pool is remarkable. I mean, this industry is growing at, depending on which analyst you're talking to somewhere between 50 to 80% ear on ear. All right, every customer is a prospect for us. There isn't a single conversation that we have with any organization almost of any size where they don't think that they can use their data better, or they can enhance and improve their data strategy. So, if that is in place and I am confident about our execution, very, very happy with the technology platform, the support that we get from out customers. So, all things seem to be lining up. >> Raj, thanks so much for coming on, we appreciate your time. We went a little bit over, I think, the allotted time, but wanted to get your insight as the new President and Chief Operating Officer for Hortonworks. Congratulations on the new role, and looking forward to seeing the results. Since you're a public company we'll be actually able to see the scoreboard. >> Raj: Yes. >> Congratulations, and thanks for coming on the CUBE. There's more coverage here live at Dataworks 2017. I John Furrier, stay with us more great interviews, day two coverage. We'll be right back. (jaunty music)

>> More information, click here. (soothing technological music) >> Announcer: Live from Munich, Germany, it's theCUBE. Covering Dataworks Summit Europe 2017. Brought to you by Hortonworks. (soft technological music) >> Okay welcome back everyone, we're here in Munich, Germany for Dataworks Summit 2017 formerly Hadoop Summit powered by Hortonworks. It's their event, but now called Dataworks because data is at the center of the value proposition Hadoop plus Airal Data and storage. I'm John, my cohost David. Our next guest is Scott Gnau he's the CTO of Hortonworks joining us again from the keynote stage, good to see you again. >> Thanks for having me back, great to be here. >> Good having you back. Get down and dirty and get technical. I'm super excited about the conversations that are happening in the industry right now for a variety of reasons. One is you can't get more excited about what's happening in the data business. Machine learning AI has really brought up the hype around, to me is human America, people can visualize AI and see the self-driving cars and understand how software's powering all this. But still it's data driven and Hadoop is extending into data seeing that natural extension and CloudAIR has filed their S1 to go public. So it brings back the conversations of this opensource community that's been doin' all this work in the big data industry, originally riding in the horse of Hadoop. You guys have an update to your Hadoop data platform which we'll get to in a second, but I want to ask you a lot of stories around Hadoop, I say Hadoop was the first horse that everyone rode in on in the big data industry... When I say big data, I mean like DevOps, Cloud, the whole open sourcing he does, but it's evolving it's not being replaced. So I want you to clarify your position on this because we're just talkin' about some of the false premises, a lot of stories being written about the demise of Hadoop, long-live Hadoop. Yeah, well, how long do we have? (laughing) I think you hit it first, we're at Dataworks Summit 2017 and we rebranded and it was previously Hadoop Summit. We rebranded it to really recognize that there's this bigger thing going on and it's not just Hadoop. Hadoop is a big contributor, a big driver, a very important part of the ecosystem but it's more than that. It's really about being able to manage and deliver analytic content on all data across that data's lifecycle from when it gets created at the edge to its moving through networks, to its landed and store in a cluster to analytics run and decisions go back out. It's that entire lifecycle and you mentioned some of the megatrends and I talked about this morning in the opening keynote. With AI and streaming and IoT, all of these things kind of converging are creating a much larger problem set and frankly, opportunity for us as an industry to go soft. So that's the context that we're really looking-- >> And there's real demand there. This is not like, I mean there's certainly a hype factor on AI, but IoT is real. You have data now, not just a back office concept, you have a front-facing business centric... I mean there's real customer demand here. >> There's real customer demand and it really creates the ability to dramatically change a business. A simple example that I used onstage this morning is think about the electric utility business. I live in Southern California. 25 years ago, by the way I studied to be an electrical engineer, 20 years ago, 30 years ago, that business not entirely simple was about building a big power plant and distributing electrons out to all the consumers of electrons. One direction and optimization of that grid, network and that business was very hard and there was billions of dollars at stake. Fast forward to today, now you still got those generating plants online, but you've also got folks like me generating their own power and putting it back into the grid. So now you've got bidirectional electrons. The optimization is totally different. Then how do you figure out how most effectively to create capacity and distribute that capacity because created capacity that's not consumed is 100% spoiled. So it's a huge data problem but it's a huge data problem meeting IoT, right? Devices, smart meter devices out at the edge creating data doing it in realtime. A cloud blew over, my generating capacity on my roof went down so I've got to pull from the grid, combining all of that data to make realtime decisions is we're talking hundreds of billions of dollars and it's being done today in an industry, it's not a high-tech Silicon Valley kind of industry, electric utilities are taking advantage of this technology today. >> So we were talking off-camera about you know some commentary about the Hadoop is failed and obviously you take exception to that and I and you also made the point it's not just about Hadoop but in a way it is because Hadoop was the catalyst of all this open Why has Hadoop not failed in your view >> Well because we have customers and you know the great thing about conferences like this is we're actually able to get a lot of folks to come in and talk about what they're doing with the technology and how they're driving business benefit and share that business benefit to their colleagues so we see that that it's business benefit coming along you know In any hype cycle you know people can go down a path maybe they had false expectations right early on you know six years ago years ago we were talking about hey is open source of Hadoop is going to come along and replace EDW complete fallacy right what I talked about in that opportunity being able to store all kinds of disparate data being able to manage and maneuver analytics in real time that's the value proposition is very different than some of the legacy ten. So if you view it as hey this thing is going to replace that thing okay maybe not but the point is is very successful for what is not verified that-- >> Just to clarify what you just said there that was you guys never kicked that position. CloudAIR or did with their impala was their initial on you could give me that you don't agree with that? >> Publicly they would say oh it's not a replacement but you're right i mean the actions were maybe designed to do that >> And set in the marketplace that that might be one of the outcomes >> Yeah, but they pivoted quickly when they realized that was failed strategy but i mean that but that became a premise that people locked in on. >> If that becomes your yardstick for measuring then then so-- >> Oh but but wouldn't you agree that that Hadoop in many respects was designed to solve some of the problems that edw never could >> Exactly so so you know again when you think about the the variety of data when you think about the analytic content doing time series analysis is very hard to do in a relational model so it's a new tool in the workbench to go solve analytic problems and so when you look at it from that perspective and I use the utility example the manufacturing example financial consumer finance telco all of these companies are using this technology leveraging this technology to solve problems they couldn't solve or and frankly to build new businesses that they couldn't build before because they didn't have access to that real time-- >> And so money did shift from pouring money into the edw with limited returns because you were at the steep part or the flat part of the s-curve to hey let's put it over here and this so called big data thing and that's why the market I think was conditioned to sort of come to that simple conclusion but dollars the spending did shift did it not? >> Yeah I mean if you subscribe kind of that to that herd mentality and you know the net increase the net new expenditure in the new technology is always going to outpace the growth of the existing kind of plateau technologists. That's just math. >> The growth yes, but not the size not the absolute dollars and so you have a lot of companies right now struggling in the traditional legacy space and you got this rocket ship going in-- >> And again I think if you think about kind of the converging forces that are out there in addition to you know i OT and streaming the ability frankly Hadoop is an enabler of AI when you think about the success of AI and machine learning it's about having massive massive massive amounts of data right? And I think back 25 years ago my first data Mart was 30 gigabytes and we thought that was all the data in the world Now fits on your phone so so when you think about just having the utter capacity and the ability to actually process that capacity of data these are technology breakthroughs that have been driven in the poor open source in Hadoop community when combined with the ability then to execute in clouds and ephemeral kinds of workloads you combine all that stuff together now instead of going to capital committee for 20 millioin dollars for a bunch of hardware to do an exabyte kind of study where you may not get an answer that means anything you can now spin that up in the cloud and for a couple of thousand dollars get the answer take that answer and go build a new system of insight that's going to drive your business and this is a whole new area of opportunity or even by the convergence of all that >> So I agree i mean it's absurd to say Hadoop and big data has failed, it's crazy. Okay but despite the growth i called profitless prosperity can the industry fund itself I mean you've got to make big bets yarn tezz different clouds how does the industry turn into one that is profitable and growing well I mean obviously it creates new business models and new ways of monetizing software in deploying software you know one of the key things that is core to our belief system is really leveraging and working with and nurturing the community is going to be a key success factor for our business right nurturing that innovation in collaboration across the community to keep up with the rate of pace of change is one of the aspects of being relevant as a business and then obviously creating a great service experience for our customers so that they they know that they can depend on enterprise class support enterprise-class security and governance and operational management in the cloud and on-prem in creating that value propisition along with the the advanced and accelerated delivery of innovation is where I think you know we kind of intersect uniquely in in the in the industry. >> and one of the things that I think that people point out and I have this conversation all the time of people who try to squint through the you know the wall street implications of the value proposition of the industry and this and that and I want to get your thoughts on because open source at this era that we're living in today bringing so much value outside of just important works in your your company Dave would made a comment on the intro package we're doing is that the practitioners are getting a lot of value people out in the field so these are the white space as a value and they're actually transformative can you give some examples where things are getting done that are real of real value as use cases that are that are highlighted you guys can i light I think that's the unwritten story that no one thought about it that rising tide floating all boat happening? >> Yeah yes I mean what is the most use cases the white so you have some of those use cases again it really involves kind of integrating legacy traditional transactional information right very valuable information about a company its operations its customers its products and all this kind of thing about being able to combine that with the ability to do real-time sensor management and ultimately have a technology stack that enables kind of the connection of all of those sources of data for an analytic and that's an important differentiation you know for the first 25 years of my career right it was all about what school all this data into a place and then let's do something with it and then we can push analytics back not an entirely bad model but a model that breaks in the world of IOT connected devices it's just frankly isn't enough money to spend on bandwidth to make that happen and as fast as the speed of light is it creates latency so those decisions aren't going to be able to be made in time so we're seeing even in traditional i mentioned utility business think about manufacturing oil and gas right sensors everywhere being able to take advantage not not of collecting all the central data and all of that but being able to actually create analytics based on sensor data and put those analytics outs of the sensors to make real-time decisions that can affect hundreds of millions of dollars of production or equipment are the use cases that we're seeing be deployed today and that's complete white space that was unavailable before. >> Yeah and customer demand too I mean Dave and I were also debating about the this not being a new trend this is just big data happening the customers are demanding production workload so you've seen a lot more forcing function driven by the customer and you guys have some news I want to get to and give your thoughts on HTTP or worse data platform two points dicks what's the key news their house in real time you talking about real time. >> Yeah it's about real time real time flexibility and choice you know motherhood and apple pie >> And the major highlights of that operate >> So the upgrades really inside of hive we now have operational analytic query capabilities where when you do tactical response times second sub second kind of response time. >> You know Hadoop and Hive wasn't previously known for that kind of a tactical response we've been able to now add inside of that technology the ability to view that workload we have customers who building these white space applications who have hundreds or thousands of users or applications that depend on consistency of very quick analytic response time we now deliver that inside the platform what's really cool about it in addition to the fact that it works is is that we did it inside a pipe so we didn't create yet another project or yet another thing that a customer has to integrate to or rewrite their application so any high based application cannot take advantage of this performance enhancement and that's part of our thinking of it as a platform the second thing inside of that that we've done that really it creaks to those kinds of workload is is we've really enhance the ability to incremental data acquisition right whether it be streaming whether it be patch up certs right on the sequel person doing up service being able to do that data maintenance in an active compliant fashion completely automatically and behind the scenes so that those applications again can just kind of run without any heavy lifting >> Just staying in motion kind of thing going on >> Right it's anywhere from data in motion even to batch to mini batch and anywhere kind of in between but we're doing those incremental data loads you know, it's easy to get the same file twice by mistake you don't want to double count you want to have sanctity of the transactions we now handle that inside of Hive with acid compliance. >> So a layperson question for the CTO if I may you mentioned Hadoop was not known for a sort of real-time response you just mentioned acid it was never in the early days known for a sort of acid you know complies others would say you know Hadoop the original Big Data Platform is not designed for the matrix of the matrix math of AI for example are these misconceptions and like Tim Berners-lee when we met Tim Berners-lee web 2.0 this is what the web was designed for would you say the same thing about Hadoop? >> Yeah. Ultimately from my perspective and kind of mending it out, Hadoop was designed for the easy acquisition of data the easy onboarding of data and then once you've onboarded that data it it also was known for enabling new kinds of analytics that could be plugged in certainly starting out with MapReduce in HDFS was kind of before but the whole idea is I have now the flexible way to easily acquire data in its native form without having to apply schema without having to have any formatting distort I can get it exactly as it was and store it and then I can apply whatever schema whatever rules whatever analytics on top of that that I want so the center of gravity from my mind has really moved up to yarn which enables a multi-tenancy approach to having pluggable multiple different kinds of file formats and pluggable different kinds of analytics and data access methods whether it be sequel whether it be machine learning whether the HBase will look up and indexing and anywhere kind of in between it's that it's that Swiss Army knife as it were for handling all of this new stuff that is changing every second we sit here data has changed. >> And just a quick follow-up if I can just clarification so you said new types of analytics that can be plugged in by design because of its openness is that right? >> By design because of its openness and the flexibility that the platform was was built for in addition on the performance we've also got a new update to spark and usability consume ability and collaboration for data scientists using the latest versions of spark inside the platform we've got a whole lot of other features and functions as that our customers have asked for and then on the flexibility and choice it's available public cloud infrastructures of service public cloud platform as a service on Prem x and net new on prem with power >> Just got final question for you just as the industry evolves what are some of the key areas that open source can pivot to that really takes advantage of the machine learning the AI trends going on because you start to see that really increase the narrative around the importance of data and a lot of people are scratching their heads going okay i need to do the back office to set up my IT to have all those crates stuff always open source projects all that the Hadoop data platform but then I got to get down and dirty i might do multiple clouds on the hybrid cloud going on i might want to leverage the moles canoe cool containers and super Nettie's and micro services and almost devops where's that transition happening as a CTO what do you see that that how do you talk to customers about that this transition this evolution of how the data businesses in getting more and more mainstream? >> Yeah i mean i think i think the big thing that people had to get over is we've reverse polarity from again 30 years of I want a stack vendor to have an integrated stack of everything a plug-and-play it's integrated and end it might not be a hundred percent what I want but the cost leverage that I get out of the stack versus what I'm going to go do that's perfect in this world if the opposite it's about enabling the ecosystem and that's where having and by the way it's a combination of open source and proprietary software that you know some of our partners have proprietary software that's okay but it's really about enabling the ecosystem and I think the biggest service that we as an open source community can do is to continue to kind of keep that standard kernel for the platform and make it very usable and very easy for many apps and software providers and other folks. >> A thousand flower bloom and kind of concept and that's what you've done with the white spaces as these cases are evolving very rapidly and then the bigger apps are kind of going to settling into a workload with realtime. >> Yeah all time you know think about the next generation of IT professional the next generation of business professional grew up with iphones and here comes they grew up in a mini app world i mean it download an app i'm going to try it is a widget boom and it's going to help me get something done but it's not a big stack that I'm going to spend 30 years to implement and I liked it and then I want to take to those widgets and connect them together to do things that i haven't been able to do before and that's how this ecosystem is really-- >> Great DevOps culture very agile that's their mindset. So Scott congratulations on your 2.6 upgrade and >> Scott: We're thrilled about it. >> Great stuff acid compliance really big deal again these compliance because little things are important in the enterprise great all right thanks for coming to accuse the Dataworks in Germany Munich I'm John thanks for watching more coverage live here in Germany after this short break

>> Narrator: Recovery. DataWorks Summit Europe 2017. Brought to you by Hortonworks. >> Hello everyone, welcome to The Cube's special presentation here in Munich, Germany for DataWorks Summit 2017. This is the Hadoop Summit powered by Hortonworks. This is their event and again, shows the transition from the Hadoop world to the big data world. I'm John Furrier. My co-host Dave Vellante, good to see you Dave. We're back in the seats together, usually on different events, but now here together in Munich. Great beer, great scene here. Small European event for Hortonworks and the ecosystem but it's called DataWorks 2017. Strata Hadoop is calling themselves Strata and Data. They're starting to see the word Hadoop being sunsetted from these events, which is a big theme of this year. The transition from Hadoop being the branded category to Data. >> Well, you're certainly seeing that in a number of ways. The titles of these events. Well, first of all, I love being in Europe. These venues are great, right? They're so Euro, very clean and magnificent. But back to your point. You're seeing the Hadoop Summit now called the DataWorks Summit. You're seeing the Strata Plus Hadoop is now Strata Plus, I don't even know what it is. Right, it's not Hadoop driven anymore. You see it also in Cloudera's IPO. They're going to talk about Hadoop and Hadoop Distro. They're a Hadoop Distro vendor but they talked about being a data management company and John, I think we are entering the era, or well deep into the era of what I have been calling for the last couple of years, profitless prosperity. Really where you see the Cloudera IPO, as you know, they raised money from Intel, over $600 million at a $4.1 billion dollar valuation. The Wall Street Journal says they'll have a tough time getting a billion dollar valuation. For every dollar each of these companies spends, Hortonworks and Cloudera, they lose between $1.70 and $2.50, so we've always said at SiliconANGLE, Wiki Bond and The Cube that people are going to make money in big data or the practitioners of big data, and it's hard to find those guys, it's hard to see them but that's really what's happening is the industries are transforming and those are the guys that are putting money into their bottom line. Not so much for technology vendors. >> Great to unpack that but first of all, I want to just say congratulations to Wiki Bond for getting it right again. As usual Wiki Bond, ahead of the curve and being out there and getting it right because I think you nailed it and I think Wiki Bond saw this first of all the research firms, kind of, you know, pat ourselves on the back here, but the truth is that practitioners are making the money and I think you're going to see more of that. In fact, last night as I'm having a nice beer here in Germany, I just like to listen to the conversations in the bar area and a lot of conversations around, real conversations around, you know, doing deals, and you know, deployments. You know, you're hearing about HBase, you're hearing about clusters, you're hearing about service revenue, and I think this is the focus. Cloudera, I think, in a classic Silicon Valley way, their hubris was tempered by their lack of scale. I mean, they didn't really blow it out. I mean, now they do 200 million in revenue. Nothing to shake a stick at, they did a great job, but they're buying revenue and Hortonworks is as well. But the ecosystem is the factor, and this is the wildcard. I'm making a prediction. Profitless prosperity that you point out is right, but I think that it has longevity with these companies like Hortonworks and Cloudera and others, like MapR because the ecosystem's robust. If you factor in the ecosystem revenue that is enough rising tide in my opinion. The question is how do they become sustainable as a standalone venture, that Red Hat for Hadoop never worked as Pat Gilson, you know, predicted. So, I think you're going to see a quick shift and pivot quickly by Hortonworks, certainly Cloudera's going to be under the microscope once they go public. I'm expecting that valuation to plummet like a rock. They're going to go public, Silicon Valley people are going to get their exits but. >> Excel will be happy. >> Everyone, yeah, they'll be happy. They already sold in 2013. They did a big sale, I mean, all of them cashed out two years ago when that liquidation event happened with Intel but that's fine. But now it's back to business building and Hortonworks has been doing it for years, so when you see your evaluation is less than a billion, so I'm expecting Cloudera to plummet like a rock. I would not buy the IPO at all because I think it's going to go well under a billion dollars. >> And I think it's the right call and as we know, last year, at the end of last year, Fidelity and other mutual funds devalued their holdings in Cloudera and so, you know, you've got this situation where, as you say, a couple hundred, maybe you know, on the way to 300 million in revenue, Hortonworks on the way to 200 million in revenue. Add up the ecosystem, yeah, maybe you get to a billion, throw in all of what IBM and Oracle call big data, and it's kind of a more interesting business, but you've called it same wine, new bottle. Is it a new bottle? Now, what I mean by that is the shift from Hadoop and then again, you read Cloudera's S1, it's all about AI, machine learning, you know, the cloud. Interesting, we'll talk about the cloud a little later, but is it same wine, new bottle, or is this really a shift toward a new era of innovation? >> It's not a new shift. It's the same innovation that the Hortonworks was founded on. Big data is a categorical and Hadoop was the horse they rode in on, but I think what's changing is the fact that customers are now putting real projects on the table and the scrutiny around those projects have to produce value, and the value comes down to total cost of ownership and business value. And that's becoming a data specific thing, and you look at all the successes in the big data world, Spark and others, you're seeing a focus on cloud integration and real-time workloads. These are real projects. This isn't fantasy. This isn't hype. This isn't early adopter. These are real companies saying we are moving to a new paradigm of digital transforming our companies and we need cost efficiencies but revenue-producing applications and workloads that are going to be running in the cloud with data at the heart of it. So, this is a customer-forcing function where the customers are generally excited about machine learning, moving to real-time classification of workloads. This is the deal and no hubris, no technology posturing, no open standards, jockeying can right the situation. Customers have demands and they want them filled, and we're going to have a lot of guests on here and I'm going to ask them those direct questions. What are you looking for and? >> Well, I totally agree with what you're saying and when we first met, it was right around the, you know, the mid point of the web 2.0 era, and I remember Tim Berners-Lee commenting on all this excitement, everybody's doing, he said this is what the web was invented to do, and this is what big data was invented to do. It was to produce deep analytics, deep learning, machine learning, you know, cognitive, as IBM likes to brand that, and so, it really is the next era even though people don't like to use the term big data anymore. We were talking to, you know, some of the folks in our community earlier, John, you and I, about some of the challenges. Why is it profitless, you know? Why is there so much growth but it's no profit? And you know, we have to point out here that people like Hortonworks and Cloudera, they've made some big bets, take HDSF of example. And now you have the cloud guys, particularly Amazon, coming in, you know, with S3. Look at YARN, big open source project. But you got Docker and Kubernetes seem to be mopping that up. Tez was supposed to replace MapReduce and now you've got. >> I mean, I wouldn't say mopping up, I mean. >> You've got Spark. >> At the end of the day the ecosystem's going to revolve around what the customers want, and portability of workloads, Kubernetes and microservices, these are areas that just absolutely make a lot of sense and I think, you know, people will move to where the frictionless action is and that's going to happen with Kubernetes and containers and microservices, but that just speaks to the devops culture, and I think Hadoop ecosystem, again, was grounded in the devops culture. So, yeah, there's some progress that are going to maybe go out of flavor, but there's other stuff coming up trough the ranks in open source and I think it's compelling. >> But where I disagree with what you're saying is well, the point I'm trying to make, is you have to, if you're Cloudera and Hortonworks, you have to support those multiple projects and it's expensive as hell. Whereas the cloud guys put all their wood behind one arrow, to use an old Scott McNealy phrase, and you know, Amazon, I would argue is mopping up in big data. I think the cloud guys, you know, it's ironic to me that Cloudera in the cloud era picked that name, you know, but really never had. >> John: They missed the cloud. >> They've never really had a strong cloud play, and I would say the same thing with Hortonworks and MapR. They have to play in the cloud and they talk about cloud, but they've got to support hybrid, they've got to support on param, they got to pick the clouds that they're going to support, AWS, Azure, maybe IBM's cloud. >> Look, Cloudera completely missed the cloud era, pun intended. However, they didn't miss open source but they're great at and I'm an admirer of Cloudera and Hortonworks on is that their open source ethos is what drove them, and so they kind of got isolated in with some of their product decisions, but that's not a bad thing. I mean, ultimately, I'm really bullish on Cloudera and Hortonworks because the ecosystem points I mentioned earlier are not high on the I wouldn't buy the IPO, I think I'd buy them at a discount, but Cloudera's not going to go away, Dave. They're going to go public. I think the valuation's going to drop like a rock and then settle around a billion, but they have good management. The founders still there, Michael Olson, Amr Awadallah. So, you're going to see Cloudera transform as a company. They have to do business out in the open and they're not afraid to, obviously they're open source. So, we're going to start to see that transition from a private venture backed, scale up, buy revenue. In the playbook of Silicon Valley venture capital's Excel partners and Greylock. Now they go public and get liquid and then now next phase of their journey is going to be build a public company and I think that they will do a good job doing it and I'm not down on them at all for that and I think it's just going to be a transition. >> Well, they're going to raise what? A couple 100 million dollars? But this industry, yeah, this industry's cashflow negative, so I agree with you. Open source is great, let's ra-ra for open source and it drives innovation, but how does this industry pay for itself? That's what I want to know. How you respond to that? >> Well, I think they have sustainable issues around services and I think partnering with the big companies like Intel that have professional services might help them on that front, but Michael Olson said in his founder's letter in his S1, kind of AI washing, he said AI and cognitive. But that's okay because Cloudera could easily pivot with their brain power, and same with Hortonworks to AI. Machine learning is very open source driven. Open source culture is growing, it's not going away, so I think Cloudera's in a very good position. >> I think the cloud guys are going to kill them in that game, and cloud guys and IBM are going to cream these profitless startups in that AI and machine learning game. >> We'll see. >> You disagree? >> I disagree, I think. Well, I mean, it depends. I mean, you know, I'm not going to, you know, forecast what the managements might do, but I mean, if I'm cloud looking at what Cloudera's done. >> What would you do? >> I would do exactly what Mike Olson's doing is I'd basically pivot immediately to machine learning. Look at Google. TensorFlow it's go so much traction with their cloud because it's got machine learning built into it. Open source is where the action is, and that's where you could do a lot of good work and use it as an advantage in that they know that game. I would not count out the open source game. >> So, we know how IBM makes money at that, you know, in theory anyway it wants. We know how Amazon's going to make money at that with their priority approach, Microsoft will do the same thing. How to Cloudera and Hortonworks make money? >> I think it's a product transition around getting to the open source with cloud technologies. Amazon is not out to kill open source, so I think there's an opportunity to wedge in a position there, and so they just got to move quickly. If they don't make these decisions then that's a failed execution on the management team at Cloudera and Hortonworks and I think they're on it. So, we'll keep an eye on that. >> No, Amazon's not trying to kill open source, I would agree, but they are bogarting open source in a big way and profiting amazingly from it. >> Well, they just do what Amy Jessie would say, they're customer driven. So, if a customer doesn't want to do five things to do one thing this is back to my point. The customers want real-time workloads. They want it with open source and they don't want all these steps in the cost of ownership. That's why this is not a new shift, it's the same wine, new bottle because now you're just seeing real projects that are demanding successful and efficient code and support and whoever delivers it builds the better mousetrap. In this case, the better mousetrap will win. >> And I'm arguing that the better mousetrap and the better marginal economics, I know I'm like a broken record on this, but if I take Kinesis and DynamoDB and Red Ship and wrap it into my big data play, offer it as a service with a set of APIs on the cloud, like AWS is going to do, or is doing, and Azure is doing, that's a better business model than, as you say, five different pieces that I have to cobble together. It's just not economically viable for customers to do that. >> Well, we've got some big new coming up here. We're going to have two days of wall-to-wall coverage of DataWorks 2017. Hortonworks announcing 2.6 of their Hadoop Hortonworks data platform. We're going to talk to Scott now, the CTO, coming up shortly. Stay with us for exclusive coverage of DataWorks in Munich, Germany 2017. We'll be back with more after this short break.