 Hey, I'm John Furrier here with an exclusive interview with Ali Goshi, who's the CEO of Databricks. Ali, great to see you. Preview for re-invent. We're going to launch this story. Exclusive Databricks material on the keynotes after the keynotes prior to the keynotes and after the keynotes that re-invent. So great to see you. You know, you've been a partner of AWS for a very, very long time. I think five years ago, I think I first interviewed you. You were one of the first to publicly declare that this was a place to build a company on and not just post an application, but refactor capabilities to create essentially a platform in the cloud, on the cloud, not just an ISV, independent software, kind of an old term. We're talking about real platform-like capability to change the game. Can you talk about your experience as an AWS partner? Yeah, look, so we started in 2013, I swiped my personal credit card on AWS and some of my co-founders did the same and we started building and we were excited because we just thought this is a much better way to launch a company because you can just much faster get the time to market and launch your thing and you can get the end users much quicker access to the thing you're building. So we didn't really talk to anyone at AWS, we just swiped the credit card and eventually they told us, hey, do you wanna buy extra support? You're asking a lot of advanced questions from us. Maybe you wanna buy our advanced support and we said, no, no, no, we're very advanced ourselves. We know what we're doing. We're not gonna buy any advanced support. So, we just built this startup from nothing on AWS without even talking to anyone there. So at some point, I think around 2017, they suddenly saw this company with maybe 100 million ARR pop up on their radar and it's driving massive amounts of compute, massive amounts of data and it took a little bit in the beginning just us to get to know each other. Because as I said, it's like we were not on their radar and we weren't really looking, we were just doing our thing. And then over the years, the partnership has deepened and deepened and deepened and then with Andy Jassy really leaning into the partnership you mentioned us at ReInvent. And then we sort of figured out a way to really integrate the two service, the Databricks platform with AWS. And today it's an amazing partnership. We're directly connected with the general managers for the services. We're connected at the CEO level. The sellers get compensated for pushing Databricks. We have multiple offerings on their marketplace. We have a native offering on AWS. We're prominently always sort of marketed and we're aligned also vision-wise in what we're trying to do. So yeah, we've come a very, very long way. Do you consider yourself a SaaS app or an ISV? Or do you see yourselves more of a platform company? Because you have customers. How would you categorize your category as a company? Well, it's a data platform, right? And actually the strategy of the Databricks is take what's otherwise five, six services in the industry or five, six different startups, but do them as part of one data platform that's integrated. So in one word, the strategy of Databricks is unification. We call it the data lake house, but really the idea behind the data lake house is that of unification. Or in more words, it's the whole is greater than the sum of its parts. So you could actually go and buy five, six services out there or actually use five, six services from the cloud vendors, stitch it together, and it kind of resembles Databricks. Our power is in doing those integrated together in a way in which it's really, really easy and simple to use for end users. So yeah, we're a data platform. I wouldn't, you know, ISV that's an old term, you know, independent software vendor. You know, I think, you know, we have actually a whole slew of ISVs on top of Databricks that integrate with our platform. And, you know, in our marketplace, as well as in our partner connect, we host those ISVs that then, you know, work on top of the data that we have in the Databricks data lake house. You know, I think one of the things your journey has been great to document and watch from the beginning. I gotta give you guys credit over there and props, congratulations. But I think your, the poster child is a company to what we see enterprises doing now. So go back in time, when you guys swipe the credit card, you didn't need any technical support because you guys had brains, you had refactoring, rethinking. It wasn't just banging out software. You had, you were doing some complex things. It wasn't like it was just write some software hosted on a server. It was really a lot more. And as a result, your business worth billions of dollars, I think 38 billion or something like that. Big numbers, big numbers of great revenue growth as well, billions in revenue. You have customers, you have an ecosystem. You have data applications on top of Databricks. So in a way, you're a cloud on top of the cloud. So is there a cloud on top of the cloud? So you have ISVs, Amazon has ISVs. Can you take us through what this means and at this point in history? Because this seems to be an advanced version of benefits of platforming and refactoring leveraging, say AWS. Yeah. So look, when we started, there was really only one game in town, it was AWS. So it was one cloud. And the strategy of the company then was, well, Amazon has this beautiful set of services that they're building bottom up. They have storage compute networking and then they'll have databases and so on, but it's a lot of services. So let us not directly compete with AWS and try to take out one of their services. Let's not do that, because frankly, we can't. We were not at that size. They had the scale, they had the size and they were the only cloud vendor in town. So our strategy instead was, let's do something else. Let's not compete directly with, say, a particular service they're building. Let's take a different strategy. What if we had a unified holistic data platform where it's just one integrated service end to end? So think of it as Microsoft Office, which contains PowerPoint and Word and Excel and even access if you want to use it. What if we build that? And AWS has this really amazing knack for releasing things, services, lots of them, every re-invent. And they're sort of a DevOps person's dream. And you can stitch these together and you have to be technical. How do we elevate that and make it simpler and integrated? That was our original strategy. And it resonated with a segment of the market. And the reason it worked with AWS so that we wouldn't butt heads with AWS was because we weren't a direct replacement for this service or for that service. We were taking a different approach and it'll be us because credit goes to them. They're so customer obsessed. They would actually do what's right for the customer. So if the customer said, we want this unified thing, their sellers would actually say, okay, so then you should use Databricks. So they truly are customer obsessed in that way. And I really mean it, John. Things have changed over the years. They're not the only cloud anymore. Azure is real, GCP is real. There's also Alibaba. And now over 70% of our customers are on more than one cloud. So now what we hear from them is not only do we want a simplified unified thing, but we want it also to work across the clouds because those of them that are seriously considering multiple clouds, they don't want to use a service on cloud one and then use a similar service on cloud two, but it's a little bit different. Now they have to do twice the work to make it work. John, it's hard enough as it is. This data stuff and analytics, it's not a walk in the park. You had a higher administrator in the back office that clicks a button and it just, now you're a data driven digital transformed company. It's hard. If you now have to do it again on the second cloud with different set of services and then again on a third cloud with a different set of services, that's very, very costly. So the strategy then has changed that how do we take that unified simple approach and make it also the same and standardized across the clouds, but then also integrated as far down as we can on each of the clouds so that you're not giving up any of the benefits that the particular cloud has. I think one of the things that we see and I want to get your reactions of this is this rise of the super cloud as we call it. I think you're involved in the sky paper that I saw your position paper came out after we had introduced super cloud, which is great. Congratulations to the Berkeley team. We're in the hat here. But you guys are, I think a driver of this because you're creating the need for these things. You're saying, okay, we went on one cloud AWS and you didn't hide that. Now you're publicly saying there's other clouds too increased ham for your business and customers have multiple clouds in their infrastructure for the best of breed that they have. Okay, get that. But there's still a challenge around the innovation growth that's still around the corner. We still have a supply chain problem. We still have skill gaps. You guys are unique at Databricks as other these big examples of super clouds that are developing enterprises don't have the Databricks kind of talent. They need turnkey solutions. So Adam and the team at Amazon are promoting more solution oriented approaches higher up on the stack. You're starting to see kind of like, I won't say templates but almost like application specific headless like low code, no code capability to accelerate clients who are wanting to write code for the modern era, right? So this kind of, and then now, as you guys pointed out with these common services, you're pushing the envelope. So you're saying, hey, I need to compete. I don't want to go to my customers and have them to have a staff for this cloud and this cloud and this cloud because they don't have the staff or if they do, they're very unique. So what's your reaction is is this kind of shows your leadership as a partner of AWS and the clouds but also highlights I think what's coming and you share your reaction. Yeah, look, it's, first of all, I wish I could take credit for this, but I can't because it's really the customers that have decided to go on multiple clouds. It's not Databricks that push this or some other vendor that's Snowflake or someone who pushed this and now enterprises listen to us and they picked two clouds. That's not how it happened. The enterprises picked two clouds or three clouds themselves and we can get into why, but they did that. So this largely just happened in the market. We as data platforms responded to what they're then saying which is they're saying, I don't want to redo this again on the other cloud. So I think the writing is on the wall. I think it's super obvious what's going to happen next. They will say any service I'm using, it better work exactly the same on all the clouds. That's what's going to happen. So in the next five years, every enterprise will say, I'm going to use this service but you better make sure that this service works equally well on all of the clouds. And obviously the multi-cloud vendors like us are there to do that. But I actually think that what you're going to see happening is that you're going to see the cloud vendors changing the existing services that they have to make them work on the other clouds. That's what's going to happen, I think. Yeah, and I think I would add that. First of all, I agree with you. I think that's going to be a forcing function because I think you're driving it. You guys are in a way, one are just an actor in the driving this because you're on the front end of this and there are others and there will be people following. But I think to me, I'm a cloud vendor. I got to differentiate. If I'm Adam Sileski, I got to say, hey, I got to differentiate. So I don't want to get stuck in the middle, so to speak, am I going to innovate on the hardware, AKA infrastructure, or am I going to innovate at the higher level services? So what we're talking about here is the tail of two clouds within Amazon, for instance. So do I innovate on the silicon and get low level into the physics and squeeze performance out of the hardware and infrastructure, but I focus on ease of use at the top of the stack for the developers. So again, there's a tail of two clouds here. So I got to ask you, how do they differentiate number one and number two, I never heard a developer ever say, I want to run my app or workload on the slower cloud. So I mean, that's one of the PCs, you wanted to go, I want the fastest processor. So again, you can have common level services, but where is that performance differentiation with what do the clouds do in European? Yeah, look, I think it's pretty clear. I think this is no surprise, probably 70% or so of the revenue is in the lower infrastructure layers, compute, storage, networking. They have to win that. They have to be competitive there. As you said, you can say, oh, I guess my CPUs are slower than the other cloud, but who cares, I have amazing other services which only work on my cloud, by the way, right? That's not going to be a winning recipe. So I think all three are laser focused on, we're going to have specialized hardware and the nuts and bolts of the infrastructure, we can do it better than the other cloud for sure. And you can see lots of innovation happening there, right? The Graviton chips, we see huge price performance benefits in those chips. I mean, it's real, right? It's basically a 20, 30% free lunch. Why wouldn't you go for it? There's no downside. There's no gotcha or no catch, but we see Azure doing the same thing now. They're also building their ARM chips and we know that Google builds specialized machine learning chips, TPUs, tensor processing units. So their legs are focused on that. I don't think they can give up that or focused on the higher levels. If they had to pick bets, and I think actually in the next few years, most of us have to make more, we have to be more deliberate and calculated in the picks we do. I think in the last five years, most of us have said, we'll do all of it, you know? We'll do all of it. That would spark, Ollie. Hadoop was pretty obvious trend that was ever only shown on that bandwagon. You guys picked a big bet with Spark. Look what happened with you guys. So again, I love this betting kind of concept because as the world matures, growth slows down and shifts, and that next wave of value coming in, aka customers, they're going to integrate with a new ecosystem, a new kind of partner network for AWS and the other cloud. But with AWS, they're going to need to nurture the next data bricks. They're going to need to still provide that SaaS, ISV-like experience for basic software hosting or some application. But I got to get your thoughts on this idea of multiple clouds because if I'm a developer, the old days was whole tastes within our decade. Full stack developer. Oh, I know that. I think it's two years ago, yeah. Yeah, it's like it's the decade ago, full stack. And then the cloud came in, you kind of had the half stack and then you would do some things. It seems like the cloud is trying to say, we want to be the full stack or not, or is it still going to be, I'm an application like a PC and a Mac, I'm going to write the same application for both hardwares. I mean, what's your take on this? Are they trying to do full stack and you see them more like? Absolutely. I mean, look, of course they are going. I mean, they have over 300. I think Amazon has over 300 services, right? That's not just compute storage networking. It's the whole stack, right? But my key point is, I think they have to nail the core infrastructure storage compute networking because the three clouds that are there competing, they're formidable companies with formidable balance sheets. And it doesn't look like any of them is going to throw in the towel and say, we give up. So I think it's going to intensify and given that they have a 70% revenue on that infrastructure layer, I think they, if they have to pick their bets, I think they'll focus it on that infrastructure layer. I think the layer above where they're also placing bets, they're doing that, the full stack, right? But there I think the demand will be, can you make that work on the other clouds? And therein lies an innovators dilemma because if I make it work on the other clouds, then I'm foregoing that 70% revenue of the infrastructure. I'm not getting it. The other cloud vendor is going to get it. So should I do that or not? Second, is the other cloud vendor is going to be welcoming of me making my service work on their cloud if I am competing cloud, right? And what kind of terms of service are they giving me? And am I going to really invest in doing that? And I think right now, we, you know, most, the vast, vast, vast majority of the services only work on the one cloud that, you know, it's built on. It doesn't work on others, but this will shift. Yeah, I think the innovators dilemma is also a very good point and also add, it's an integrators dilemma too, because now you talk about integration across services. So I believe that the super cloud movement is going to happen before sky. And I think what I'm explained by that, what you guys did and what other companies are doing by representing advanced, I call platform engineering, refactoring an existing market really fast, time to value and capital market cap is going to be really fast. I think there's going to be an opportunity for those to emerge. That's going to set the table for global multi-cloud ultimately in the future. So I think you're going to start to see the same pattern of what you guys did, get in, leverage the hell out of it, use it, not in the way just to host, but to refactor and take down territory on markets. So number one, and then ultimately you get into, okay, I want to run some SLA across services that there's a little bit more complication. I think that's where you guys put that beautiful paper out on sky computing. Okay, that makes sense. Now, if you go to today's market, okay, I'm betting on Amazon because they're the best. This is the best cloud wins scenario, not the most robust cloud. So if I'm a developer, I want the best. How do you look at their bet when it comes to data? Because now they've got machine learning, Swamy's got a big keynote on Wednesday. I'm expecting to see a lot of AI and machine learning. I'm expecting to hear an end-to-end data story. This is what you do. So as a major partner, how do you view the moves Amazon's making and the bets they're making with data and machine learning and AI? First, I want to lift off my hat to AWS for being customer obsessed. So I know that if a customer wants Databricks, I know that AWS and their sellers will actually help us get that customer-deployed Databricks. Now, which of the services is the customer going to pick? Is it going to pick ours? Or the end-to-end, what Swamy's going to present on stage, right? So that's the question we're bringing in. But I wanted to start with by just saying they are customer obsessed. So I think they're going to do the right thing for the customer and I see the evidence of it again and again and again. So kudos to them. They're amazing at this, actually. Ultimately, our bet is customers want this to be simple, integrated, okay? So yes, there are hundreds of services that together give you the end-to-end experience and they're very customizable that AWS gives you. But if you want just something simple integrated that also works across the clouds, then I think there's a special place for Databricks. And I think the Lakehouse approach that we have, which is an integrated, completely integrated, we integrate data lakes with data warehouses, integrate workflows with machine learning, with real-time processing, all these in one platform. I think there's going to be tailwinds because I think the most important thing that's going to happen in the next few years is that every customer is going to now be obsessed given the recession and the environment we're in. How do I cut my costs? How do I cut my costs? And we learn this from the customers. They're adopting the Lakehouse because they're thinking, instead of using five vendors or three vendors, I can simplify it down to one with you and I can cut my cost. So I think that's going to be one of the main drivers of why people bet on the Lakehouse because it helps them lower their TCO, total cost of ownership. And it's as simple as that. Like I have three things right now. If I can get the same job done of those three with one, I'd rather do that. And by the way, if it's three or four across two clouds and I can just use one and it just works across two clouds, I'm going to do that. Because my boss is telling me, I need to cut my budget. And I'd rather not do layoffs and they're asking me to do more. How can I get smaller budgets, not lay people off and do more? I have to cut. I have to optimize. What's happened in the last five, six years is there's been huge sprawl of services and startups. You know most of them, all these startups, all of them, all the activity, all the VC investments. Well, those companies sold their software, right? Even if a startup didn't make it big, they still sold their software to some vendors. So the ecosystem is now full of lots and lots and lots of different software. And right now people are looking, how do I consolidate? How do I simplify? How do I cut my costs? That's what I've learned. And you guys have a great solution. You're both some arms dealer and innovator. So I have to ask this question because you're a professor of the industry as well as at Berkeley. You've seen in a lot of the historical innovations. If you look at the moment we're in right now with the recession, okay, we had COVID. Okay, it changed how people work. You have people working at home provisioning V-Land. All that's more infrastructure. Okay, yeah, technology and cloud health. But we're in a recession. This is the first recession where the Amazon and the other cloud, mainly Amazon web services is a major economic puzzle in the piece. So they were never around before. Even 2008, they were too small. They're now a major economic enabler player. They're serving startups, enterprises. They have super clouds like you guys. They're a force and the people, their customers are cutting back, but also they can also get faster. So agility is now an equation in the economic recovery. I want to get your thoughts. You just brought that up. Customers can actually use the cloud and Databricks to actually get out of the recovery because no one's going to say stop making profit or make more profit. So yeah, cut costs, be more efficient. But agility is also like, let's drive more revenue. So in this digital transformation, if you take this to conclusion, every company transforms, their company is the app. So their revenue is tied directly to their technology deployment. What's your reaction and comment to that? Because this is a new historical moment where cloud and scale and data actually could be configured in a way to actually change the nature of a business in such a short time. And with the recession looming, no one's got time to wait. Yeah, absolutely. Look, the secular tailwind in the market is that of, you know, 10 years ago it was software is eating the world. Now it's AI is going to eat all of software. So more and more, we're going to have, wherever you have software, which is everywhere now, because it's eating the world, it's going to be eaten up by AI and data. You know, the AI doesn't exist without data. So they're synonymous that you can't do machine learning if you don't have data. So yeah, you're going to see that everywhere. And that automation will help people simplify things and cut down the costs and automate more things. And in the cloud, you can also do that by changing your CAPEX to OPEX. So instead of I invest, you know, 10 million dollars into a data center that I buy, I'm going to have headcount to manage the software. What I would change is to OPEX and then they are going to optimize it. They want to lower the TCO. Because okay, it's in the cloud, but I do want the costs to be much lower and what they were in the previous years. Last five years, nobody cared. Who cares, you know, what it cost? You know, there's a new brave world out there. Now there's like, no, it has to be efficient. So I think they're going to optimize it. And I think this Lakehouse approach, which is integration of the lakes and the warehouse allows you to rationalize the two and simplify them. It allows you to basically rationalize the way the data warehouse. So I think much faster, we're going to see the, why do I need the data warehouse if I can get the same thing done with the Lakehouse for a fraction of the cost. That's what's going to happen. I think there's going to be focused on that simplification, but I agree with you. Ultimately, everyone knows, everybody's a software company. Every company out there is a software company. And in the next 10 years, all of them are also going to be AI companies. So that is going to continue. And I'm going to stop and right sizing right now is a key economic forcing function. Final question for you, I really appreciate you taking the time this year, reinvent, what's the bumper sticker in your mind around what's the most important industry dynamic, power dynamic, ecosystem dynamic that people should pay attention to as we move from the brave new world of, okay, I see cloud, cloud operations. I need to really make it structurally change my business. Otto, what's the most important story? What's the bumper sticker in your mind for reinvent? Bumper sticker, Lakehouse 24, you know? That's your data bricks bumper sticker. What's the event? No, we're seeing it in the market. No, no, no, no. It's AWS talks about all of their services becoming a Lakehouse because they want the center of the gravity to be S3, their Lake and what all the services directly work on that. So that's the Lakehouse. We're going to see Microsoft with Synapse, modern intelligent data platform, same thing there. We're going to see the same thing. We already seeing it on GCP with big Lake and so on. So I actually think it's the, how do I reduce my costs? And the Lakehouse integrates those two. So that's one of the main ways you can rationalize and simplify. You get in the Lakehouse, which is the name itself is a portmanteau of two things, right? Lakehouse, Lake gives you the AI. House give you the database, data warehouse. So you get your AI and you get your data warehousing in one place at the lower cost. So for me, the bumper sticker is Lakehouse 24. All right. Awesome. Ali, well, thanks for the exclusive interview, appreciate it and get to see it. Congratulations on your success. And I know you guys are going to be fine. Awesome. Thank you, John. It's always a pleasure. Always great to chat with you again. You guys are a great team. We're big fans of what you guys have done. We think you're an example of what we call SuperCloud, which get in the hype up. And again, your paper speaks to some of the innovation, which I agree with, by the way. I think that approach of not forcing standards is really smart. And I think that's absolutely correct. That having a market still innovate is going to be key standards would kill it. Yeah. I love it. We're big fans too. You're doing awesome work. We'd love to continue the partnership. So great. Great, Ali. Thanks. Amen. Take care.