How Databricks Went $1M to $7B+ ARR in 10 Years | Ron Gabrisko, CRO

Turner Novak (0:03)

Ron, welcome to the show.

Ron Gabrisko (0:04)

Hi, thanks for having me. Excited to be here.

Turner Novak (0:07)

Yeah, this will be, I think this will be a fun conversation. So you joined Databricks before you guys were, we really had a business, I think it was less than a million in revenue.

And as of the time we're speaking, I think the public disclosure is 6.9 billion in revenue. And I think actually by the time we publish this, I think it's gonna be even higher. So this is gonna be pretty fun, going deep on just how you did it, how you got there.

Ron Gabrisko (0:31)

Yeah, it's been absolutely amazing journey. I mean, we're still growing super, super fast. We say it's top of the second inning, still early days. So it's been, it's an amazing business. It's been, it's been a great journey.

Turner Novak (0:45)

I love those baseball analogies. Like when you're on an earnings call and like the CEO goes super deep is like, we're still getting in the seats. Like the game hasn't, like we haven't even thrown the first pitch yet, like.

Ron Gabrisko (0:54)

Well, I'm a baseball player, you know, early days, that's what I wanted to be, a major league baseball player and.

Turner Novak (0:59)

Oh, really?

Ron Gabrisko (1:00)

Yeah. Now I'm, I sell software, I guess is the closest thing I could get to the big leagues.

Turner Novak (1:07)

What do you think is the kind of like the key to success for Databricks? Like if you just had to sum it up in a couple of sentences.

Ron Gabrisko (1:12)

The company's been around 13 I think I've been here 10 and a half years. So, you know, company was less than a million. I think most of that growth has been over those 10 years. But yeah, company's been around almost that long. Yeah, I mean, I think the keys to success at Databricks, I can talk about how we built it in each stage. But overall, like we made, first of all, we have seven of the greatest, smartest founders on the planet, all PhDs from Berkeley.

They were at the, like I said, the frontier of data and AI, way before AI was even cool. So again, this is back in 2014, 2015

They made some really strategic bets early on. One was on go all in on Cloud, one was go all in on open-source, and the last was go all in on data and AI. That wasn't really the vogue back then. Then I would say since then, we have the best engineering and innovation machine, our product is the best I've ever sold, it's the best on the planet. Then I think we have the best go to market team on the planet. To achieve that growth at this scale is fairly unprecedented. So I think the combination of those two things, and obviously great people, great culture, that's been the keys to success for sure.

Turner Novak (2:42)

I want to talk more about all those things. I guess going in order though.

So when you talk about making a bet on the Cloud, that seems obvious today.

Why was this such a big deal back 15 years ago?

Ron Gabrisko (2:56)

Well, back then, Cloud was still pretty early.

Most of the infrastructure was still on-prem. I can remember, first, when I started, I took all the founders out to Wall Street. I said, hey, if we're going to make a business here, we got to sell to all the big financial services, banks, and literally, we met with most of them, and CIOs, I got CIO meetings. It's crazy, they would bring hundreds of people to meet the inventors of Spark, and Mateo would be signing autographs and stuff. That's awesome. Yeah, but they were like, we're never going to the Cloud, and we were Cloud only. They're literally never. But now, some of our biggest customers, a bunch of these big banks, they're all in on the Cloud, and it's already happened. But back then, that wasn't a no-brainer, for sure.

Turner Novak (3:52)

That's wild because it would be like someone telling you today, we're not going to use AI. We think it's fake or doesn't work or something.

What was the justification on not moving to the Cloud? Just was it not valuable enough and too hard or expensive?

Ron Gabrisko (4:08)

Early in any market, it's like security, you got to overcome legacy.

There's a lot of people saying like, the Clouds aren't as secure as our own dedicated security team, which obviously is false. I mean, these Clouds have to have better security than any one individual company. A lot of that is like security, governance, regulations. A lot of the banks, regulated markets, they're regulated. So like, you know, it's similar challenges to early days AI, right? And once you kind of solve those challenges around security, governance, scalability, regulations, things of that nature, the market takes off. And so it was a great bet. Obviously, like, you know, everything's moving to the Cloud and, you know, we could move faster than a lot of the on-prem players because they were stuck having to deal with legacy issues. So it was a great bet for sure.