 Welcome back everyone to theCUBE's coverage here in Seattle, Washington for AWS's Marketplace Seller Conference. It's the big news within the Amazon partner network combining with Marketplace, forming the Amazon partner organization, part of a big reorg, as they grow to the next level, next-gen cloud, mid-game, on the chessboard. CUBE's got to cover. I'm John Furrier, hosting CUBE. A great guest here from Databricks, both CUBE alumni's, Jack Anderson, GM of the, and VP of the Databricks partnership team for AWS, you handle that relationship, and Joe Minick, vice president of product and partner marketing. You guys have the keys to the kingdom with Databricks and AWS. Thanks for joining me, thanks for good to see you again. Thanks for having us back. John, great to be here. So I feel like we're at re-invent 2013, small event, no stage, but there's a real shift happening with procurement. Obviously it's a no-brainer on the macro. People should be buying online, self-service, cloud-scale, but Amazon's got billions being sold through their Marketplace. They've reorganized their partner network. You can see kind of what's going on. They've kind of figured it out. Like let's put everything together and simplify and make it less of a website marketplace. Merge our partners to have more synergy and frictionless experiences so everyone can make more money and customers can be happier. Yeah, that's right. I mean, you're running a relationship. You're in the middle of it. Well, Amazon's mental model here is that they want the world's best ISVs to operate on AWS so that we can collaborate and co-architect on behalf of customers. And that's exactly what the APO and Marketplace allow us to do is to work with Amazon on these really unique use cases. You know, I interviewed Ali many times over the years. I remember many years ago, I think six, maybe six, seven years ago, we were talking, he's like, we're all in on AWS. Obviously now the success of Databricks, you've got multiple clouds to see that. Customers will have choice. But I remember the strategy early on. It was like, we're going to be deep. So this speaks volumes to the relationship you have years. Jack, take us through the relationship that Databricks has with AWS from a partner perspective, Joel, and from a product perspective, because it's not like you guys at Johnny come lately, new to the scene. You've been there, almost president creation of this wave. What's the relationship and how does it relate to what's going on today? So most people may not know that Databricks was born on AWS. We actually did our first $100 million of revenue on Amazon. And today we're obviously available on multiple clouds. But we're very fond of our Amazon relationship. And when you look at what the APN allows us to do, we're able to expand our reach and co-sell with Amazon and marketplace broadens our reach. And so we think of marketplace in three different aspects. We've got the marketplace private offer business, which we've been doing for a number of years. Matter of fact, we were driving well over 100% year-over-year growth in private offers. And we have a nine figure business. So it's a very significant business. And when a customer uses a private offer, that private offer counts against their private pricing agreement with AWS. So they get pricing power against their private pricing. So it's really important. It goes on their Amazon bill. In May, we launched our pay as you go on demand offering. And in five short months, we have well over a thousand subscribers. And what this does is it really reduces the barriers to entries, low friction. So anybody in an enterprise or startup or public sector company can start to use Databricks on AWS and pay a consumption based model and have it go against their monthly bill. And so we see customers, you know, doing rapid experimentation, pilots, POCs. They're really learning the value of that first use case. And then we see rapid use case expansion. And the third aspect is the consulting partner private offer CPPO. Super important in how we involve our partner ecosystem of our consulting partners and our resellers that are able to work with Databricks on behalf of customers. So you get the big contracts with the private offer. You got the product market fit, kind of people iterating with data, coming in with the buy as you go. And also the integration piece all fitting in there. Okay, so those are the offers. That's the current and what's in marketplace today. Is that the products? What are people buying? I mean, I guess, what's the, Joel, what are people buying in the marketplace? And what does it mean for them? So fundamentally what they're buying is the ability to take silos out of their organization. And that's, that is the problem that Databricks is out there to solve, which is when you look across your data landscape today, you've got unstructured data, you've got structured data, you've got real-time streaming data. And your teams are trying to use all of this data to solve really complicated problems. And as Databricks, as the Lakehouse company, what we're helping customers do is how do they get into the new world? How do they move to a place where they can use all of that data across all of their teams? And so we allow them to begin to find through the marketplace those rapid adoption use cases where they can get rid of these data warehousing, data lake silos they've had in the past, get their unstructured and structured data onto one data platform, an open data platform that is no longer adherent to any proprietary formats and standards, something they can very easily integrate into the rest of their data environment. Apply one common data governance layer on top of that so that from the time they ingest that data to the time they use that data to the time they share that data inside and outside of their organization, they know exactly how it's flowing. They know where it came from, they know who's using it, they know who has access to it, they know how it's changing. And then with that common data platform, with that common governance solution, they'd being able to bring all of those use cases together across their real-time streaming, their data engineering, their BI, their AI, all of their teams working on one set of data. And that lets them move really, really fast, and it also lets them solve challenges they just couldn't solve before. A good example of this, one of the world's now largest data streaming platforms runs on Databricks with AWS. And if you think about what does it take to set that up? Well, they've got all this customer data that was historically inside of data warehouses, that they have to understand who their customers are. They have all this unstructured data, they've built their data science models, they can do the right kinds of recommendation engines and forecasting around. And then they've got all this streaming data going back and forth between clickstream data from what the customers are doing with their platform and the recommendations they want to push back out. And if those teams were all working in individual silos, building these kinds of platforms would be extraordinarily slow and complex. But by building it on Databricks, they were able to release it in record time and have grown at record pace to not be the number one platform. That's impacting product development. Absolutely. I mean, this is like, the difference between lagging months of product development to like days, pretty much what you just got getting at this. So total agility, I got that. Okay, now I'm a customer, I want to buy in the marketplace, but I also, you've got direct sales force out there. So how do you guys look at this? Is there channel conflict? Are there comp programs? Because one of the things I heard today on the stage from AWS's leadership, Chris was up there speaking and Mona, I was, hey, he's the CRO Conference Chief Revenue Officer Conversation, which means someone's getting compensated. So if I'm the sales rep at Databricks, what's my motion to the customer? Do I get paid? Does Amazon sell it? Take us through that. Is there channel conflict? Is there, or not a inlet? Well, I'd add what Joel just talked about with what the solution, the value of the solution. Our entire offering is available on AWS Marketplace. So it's not a subset, it's an entire Databricks offering. And- The flagship, all the top, everything. The flagship, the complete offering. So it's not segmented, it's not a sub-segment, it's, you know, you can use all of our different offerings. Now, when it comes to seller compensation, we view this two different ways, right? One is that AWS is also incented, right? Versus selling a native service to recommend Databricks for the right situation. Same thing with Databricks, our sales force wants to do the right thing for the customer, if the customer wants to use Marketplace as their procurement vehicle. And that really helps customers because if you get Databricks and five other ISVs together, and let's say each ISV is spending, you're spending a million dollars, you have five million dollars of spend, you put that spend through the flywheel with AWS Marketplace, and then you can use that in your negotiations with AWS to get better pricing overall. So that's how we do it. So customers are driving this, sounds like. For sure. So they're looking at this and saying, hey, I'm going to just get purchasing power with all my relationships because it's a solution architectural market, right? Yeah, it makes sense because if most customers will have a primary and secondary cloud provider, if they can consolidate multiple ISVs spend through that same primary provider, you get pricing power. Okay, Joe, we're going to date ourselves, at least I will. So back in the old days, it used to be do a Barney deal with someone, hey, let's go to market together, you got to get paper, you do a BizDev deal, and then you got to say, okay, now let's coordinate our sales teams. A lot of moving parts that we're getting at here is that the alternative for Databricks or any company is to go find those partners and do deals versus now Amazon, it's a center point for the customer. So that you can still do those joint deals, but this seems to be flipping the script a little bit. Well, it is, but we still have VARs and consulting partners that are doing implementation work, very valuable work, advisory work that can actually work with Marketplace through the CPPO offering. So the Marketplace allows multiple ways to procure your solution. So it doesn't change your business structure, it just makes it more efficient? That's correct. That's a great way to say it. That's great. So that's it, so that just makes it more efficient. So you guys are actually incented to point customers to the Marketplace? Yes, absolutely. Economically. Economically, it's the right thing to do for the customer, it's the right thing to do for our relationship with Amazon, especially when it comes back to co-selling, right? Because Amazon now is leaning in with ISVs and making recommendations for an ISV solution. And our teams are working backwards from those use cases to collaborate and land them. Yeah, I want to get that out there. Go ahead, Joel. So one of the other things I might add to that too, and why this is advantageous for companies like Databricks to work through the Marketplace, is it makes it so much easier for customers to deploy a solution. It's very literally one click through the Marketplace to get Databricks set up inside of your environment. And so if you're looking at how do I help customers most rapidly adopt these solutions in the AWS cloud, the Marketplace is a fantastic accelerator to that. You know, it's interesting, I want to bring this up and get your reaction to it because to me, I think this is the future of procurement. So from a procurement standpoint, I mean, again, dating myself, EDI back in the old days, all that craziness. Now this is all the internet, basically through the console. I get the infrastructure side, spin up and provision some servers, all been good. You guys have played well there in the Marketplace. Now as you get into more of what I call the business apps, and they brought this up on stage, a little nuance. Most enterprises aren't yet there of integrating tech on the business apps into the stack. This is where I think you guys are a use case of success where you guys have been successful with data integration. It's an integrator's dilemma, not an innovator's dilemma. So like, I want to integrate. So now I have integration points, Databricks. But I want to put an app in there. I want to provision an application, but it has to be built. It's not, you don't buy it, you've got to build stuff. And this is the nuance. What's your reaction to that? Am I getting this right or am I off? Because no one's going to be buying software like they used to. They buy software to integrate it in. Yeah, no, I think everything's integrated. I think AWS has done a great job at creating a partner ecosystem to give customers the right tools for the right jobs. And those might be with third parties. Databricks is doing the same thing with our Partner Connect program, right? We've got customer partners like FiveTran and DVT that augment and enhance our platform. And so you're looking at multi-ISV architectures and all of that can be procured through the AWS marketplace. Yeah, it's almost like bundling and unbundling. I was talking about this with Dave Vellante about SuperCloud, which is why wouldn't a customer want the best solution in their architecture, period? In its class. If someone's got API security or an API gateway, well, you know, I don't want to be forced to buy something because it's part of a suite. And that's where you see things get suboptimized where someone dominates the category and they have, oh, you got to buy my version of this. Yeah, Joel and I were talking, we were actually saying what's really important about Databricks is that customers control the data. Right, you want to comment on that? Yeah, let's say what you're pushing on there, we think is extraordinarily, you know, the way the market is going to go is that customers want a lot of control over how they build their data stack. And everyone's unique in what tools are the right ones for them. And so one of the, you know, philosophically, I think really strong places Databricks and AWS have lined up is we both take an approach that you should be able to have maximum flexibility on the platform. And as we think about the Lakehouse, one thing we've always been extremely committed to as a company is building the data platform on an open foundation. And we do that primarily through Delta Lake and making sure that to Jack's point with Databricks, the data is always in your control. And then it's always stored in a completely open format. And that is one of the things that's allowed Databricks to have the breadth of integrations that it has with all the other data tools out there because you're not tied into any proprietary format. But instead are able to take advantage of all the innovation that's happening out there in the open source ecosystem. When you see other solutions out there that aren't as open as you got, you guys are very open. By the way, we love that too. We think that's a great strategy. But what's the, what am I foreclosing if I go with something else? That's not as open. What's the customer's downside as you think about what's around the corner in the industry? Because if you believe it's going to be open, open source, which I think open source software is the software industry. And integration is a big deal because software's going to be plentiful. I mean, let's face it, it's a good time to be in the software business. But cloud's booming. So what's the downside from your Databricks perspective? You see a buyer clicking on Databricks versus that alternative, what's potentially is, should they be a nervous about down the road if they go with a more proprietary or locked in approach? Well, I think the challenge with proprietary ecosystems is you become beholden to the ability of that provider to both build relationships and convince other vendors that they should invest in that format. But you're also then beholden to the pace which that provider is able to innovate. And I think we've seen lots of times over history where a proprietary format may run ahead for a while on a lot of innovation. But as that market control begins to solidify, that desire to innovate begins to degrade. Whereas in the open formats- So abstract rents versus innovation. Exactly, exactly. I'll say it. In the open world, you have to continue to innovate. And the open source world is always innovative. If you look at the last 10 to 15 years, I challenge you to find an example where the innovation in the data and AI world is not coming from open source. And so by investing in open ecosystems, that means you are always going to be at the forefront of what is the latest. Again, not to date myself again, but you look back at the 80s and 90s, the protocol stacked for proprietary. SNA.IBM, DECNET was digital, the rest of it. And then TCPIP was part of the open systems interconnect. Revolutionary, obviously Cal had a big part of that as well as my school did. And so like, you know, that was, but it didn't standardize the whole stack and stopped that IP and TCP. But that helped interoperate. That created a nice de facto. So this is a big part of this mid game. I call it the chess board. You know, you got opening game and mid game, then you got the end game. And we're not there at the end game yet in cloud. There's always some form of lock-in, right? Andy Jassy will address it, you know, when making a decision. But if you're going to make a decision, you want to reduce, you don't want to be limited, right? So I would advise a customer that there could be limitations with the proprietary architecture. And if you look at what every customer is trying to become right now is an AI driven business, right? And so it has to do with, can you get that data out of silos? Can you organize it and secure it? And then can you work with data scientists to feed those models in a very consistent manner? And so the tools of tomorrow to Joel's point will be open and we want interoperability with those tools now. And choice is a matter too. I would say that the argument for why I think Amazon is not as locked in as maybe some other clouds is that they have to compete directly too. Redshift competes directly with a lot of other stuff but they can't play the bundling game because the customers are getting savvy to the fact that if you try to bundle an inferior product with something else, it may not work great at all and they're going to be, they're onto it. This is the- This is the- Amazon's credit, by having these solutions that may compete with native services in marketplace, they are providing customers with choice, low price, selection convenience. And access to the core value, which is the hardware, which is their platform. Okay, so I want to get you guys thought on something else I see emerging. This is again kind of cube rumination moment. So on stage, Chris unpacked a lot of stuff. I mean, this marketplace, they're touching a lot of hot buttons here. You know, price and compensation, workflows, services behind the curtain. And one of the things he mentioned was they talked about resellers or channel partners. Depending on what you talk about, we believe, Dave and I believe on a cube, that the entire indirect sales channel of the industry is going to be disrupted radically because those players were selling hardware in the old days in software. That game is going to change. So you mentioned you guys have a program. I want to get your thoughts on this. We believe that once this gets set up, they can play in this game and bring their services in, which means that the old reseller channels are going to be rewritten. They're going to be refactored with this new kind of access. Because you've got scale, you've got money, and you've got product. And you've got customers coming into the marketplace. So if you're like a reseller that sold computers to data centers or software, and you're a value-added reseller or a bab or business, you've got to evolve. You've got to be here. How are you guys working with those partners? Because you say you have a product in your marketplace there. How do I make money if I'm a reseller with Databricks with eight Amazon? Take me through that use case. Well, I'll let Jill comment, but I think it's pretty straightforward, right? Customers need expertise. They need know-how. When we're seeing customers who mass migrations to the cloud or Hadoop specific migrations or data transformation implementations, they need expertise from consulting and SI partners. If those consulting and SI partners happen to resell the solution as well, well, that's another aspect of their business, but I really think it is the expertise that partners bring to help customers get outcomes. Jill, channel big opportunity for Amazon to reimagine this. For sure. And I think, to your comment about how to resellers take advantage of that, I think what Jack was pushing on the spot on, which is it's becoming more and more about the expertise you bring to the table. And not just transacting the software, but now actually helping customers make the right choices. And we're seeing, you know, both SI's begin to be able to resell solutions and finding a lot of opportunity in that. And I think we're seeing traditional resellers begin to move into that SI model as well. And that's going to be the evolution that this goes. At the end of the day, it's about services, right? For sure. Yeah, for sure. If you got a great service, you're going to have high gross profits. The managed service provider business is alive and well, right, because there are a number of customers that want that type of a service. I think that's going to be a really hot, hot button for you guys. I think being the way you guys are open, this channel, partner services model coming in to the fold really kind of makes for that super cloud-like experience where you guys now have an ecosystem, and that's my next question. You guys have an ecosystem going on within Databricks. For sure. On top of this ecosystem, how does that work? This is kind of like, hasn't been written up in business school and case studies yet. This isn't new. What is this? I think, you know, what it comes down to is you're seeing ecosystems begin to evolve around the data platforms, and that's going to be one of the big kind of new horizons for us as we think about what drives ecosystems. It's going to be around, well, what is the, what's the data platform that I'm using? And then all the tools that have to encircle that to get my business done. And so I think there's, you know, absolutely ecosystems inside of the AWS business on all of AWS's services across data analytics and AI. And then to your point, you are seeing ecosystems now arise around Databricks and its lake house platform as well as customers are looking at, well, if I'm standing these lake houses up and I'm beginning to invest in this, then I need a whole set of tools that help me get that done as well. I mean, you think about ecosystem theory, we're living a whole nother dream. And I'm not kidding, it hasn't yet been written up in business school case studies is that we're now in a whole nother connective tissue ecology thing happening where you have dependencies and value proposition, economics, connectedness. So you have relationships in these ecosystems. And I think one of the great things about relationships of these ecosystems is that there's a high degree of overlap. So you're seeing that, you know, the way that the cloud business is evolving, the ecosystem partners of Databricks are the same ecosystem partners of AWS. And so as you build these platforms out into the cloud, you're able to really take advantage of Best of Breed, the broadest set of solutions out there for you. Joel, Jack, I love it because you know what it means? The best ecosystem will win if you keep it open. You can see everything. If you're going to do it in the dark, you know, you don't know the outcome. I mean, this is really kind of what we're talking about. And John, can I just add that when I was at Amazon, we had a theory that there's buyers and builders, right? There's very innovative companies that want to build things themselves. We're seeing now that builders want to buy a platform, right? And so there's a platform decision being made and that ecosystem is going to evolve around the platform. It's great. I totally agree. And the word innovation kicks around. That's why, you know, when we had our super cloud panel, it was called the Innovator's Dilemma, with a slash through it called the Integrator's Dilemma. Innovation is the digital transformation. So that becomes cliche in a way, but it really becomes more of are you open? Are you integrating? If APIs are now connective tissue, what's automation? What's the service measures look like? I mean, a whole nother set of kind of thinking goes on in these new ecosystems and these new products. And that thinking has been born in Delta sharing, right? So the idea that you can have a multi-cloud implementation of data breaks and actually share data between those two different clouds. That is the next layer on top of the native cloud solution. Well, Databricks has done a good job of building on top of the goodness of, and the cap X gift from AWS. But you guys have done a great job of taking that building differentiation to the product. You guys have great customer base, great growing ecosystem. And again, I think in a shining example of what every enterprise is going to do, build on top of something, operating model, get that operating model, driving revenue. Whether you're Goldman Sachs or Capital One or XYZ Corporation. S&P Global, NASDAQ, right? We've got these, the biggest verticals in the world are solving tough problems with Databricks. I think we'd be remiss, because if Ali was here, he would really want to thank Amazon for all of the investments across all of the different functions, whether it's the relationship we have with our engineering and service teams, our marketing teams, product development. And we're going to be at re-invent, the big presence of re-invent. We're looking forward to seeing you there again. We'll see you guys there. Yeah, again, good ecosystem. I love the ecosystem, evolution's happening. This next gen cloud is here. We're seeing this evolve. Kind of new economics, new value proposition is kind of scaling up, producing more. So you guys are doing a great job. Thanks for coming on theCUBE and taking time to see you. Thanks for having us, John. Okay, CUBE Coverage here. The world's changing as APN comes to give the marketplace for a new partner organization at Amazon Web Services. CUBE's got it covered. This should be a very big growing ecosystem as this continues. Billions of being sold through the marketplace. Of course, the buyers are happy as well. So we've got it all covered. I'm John Furrier, your host of theCUBE. Thanks for watching.