Jordan Tigani, MotherDuck CEO on DuckDB, AI and the End of Big Data

Grace Gong (0:02)

Oh, we're live. Hi Jordan, welcome to Venture with Grace.

Jordan Tigani (0:06)

Thanks, great to be here.

Grace Gong (0:08)

I'm so excited about our podcast because I feel like I learned so much interesting fact about you guys, because you guys have the best swag at every conference. So 12 days after your fire, you got like five term sheets. Is that true?

Jordan Tigani (0:25)

Yes, I think that is true.

Grace Gong (0:29)

Okay, so I want to start with like how do you get, like I guess like, you know, I know that like you were working at Google, you were the chief product officer of SingleStore before you started MotherDuck, and then you try to convince to kind of like researchers like join you, but like they were like, you gave them like kind of like co-founder vibe equity to like make sure that they only work with you guys. Maybe we could start with like, what were some core lessons that you've learned early on in your career, kind of kept you into like who you are today?

Jordan Tigani (1:02)

I have core lessons.

Grace Gong (1:05)

Like through Google, through like other things that you have done before being an entrepreneur.

Jordan Tigani (1:10)

Yeah, I think one of them is like, there's a lot of, it's easy to sort of chase the fun stuff, but I think the real openings in your career come when you actually sort of dig in deeply in something that, you know, versus just sort of chasing whatever the new hot thing is out there. I remember when we started BigQuery, one of the things that I said that I didn't want to do is, like, I don't want to just build a database. I felt like I had like bigger, grander visions of like what was possible. And like, but also digging in and building a database is like, is hard and it's important. And it builds the, like, it builds the sort of depth of knowledge and understanding that is important to sort of set you apart in the rest of your career. It can be important to, like if you are going to become an expert in something to, you know, pick something that is, that is useful. You know, I started out as an expert in like operating systems and, you know, I worked on the Windows kernel. Back when operating, you know, it's hard to imagine these days, but operating systems was once pretty cool. And now, like nobody, you know, nobody works on operating systems and it's, you know, it seems sort of like a relatively dead end kind of kind of thing. You know, there's not a lot of companies that are being built out of that. And then I moved into compilers and then compilers also is not something that is like, it's something that every software engineer kind of, you know, they take a couple of compiler courses in college and they're like, this is really cool, I want to work in this.

And that also turns out to like, it used to be you could have a career building compilers and there's lots of people building compilers and companies building compilers. That's not so much true anymore. And then it was data analysis and databases. And that turns out to be a much stickier thing. So sometimes you might have to give it a couple of tries, but I think once you can build up experience and reputation as somebody who knows how things work, then that really can start to open doors.

You get known as the person who helped build X, Y, and Z, and that's incredibly valuable. So I guess if I were to sum it up, I would just say do the hard work, dig in, and don't just chase the new fad.

Grace Gong (3:47)

For sure. Okay. So I really like what you said about doing the hard work, and then going deep into a particular sector and stuff.

So I have so many mini questions, but also the general big picture question. So from my understanding, what you guys are doing, it's essentially Snowflake is serving the big clients, and then you guys are serving a lot of these SMB, as well as fast growing companies. Why don't we start with the overall landscape of data? Why is no one serving the small companies? And obviously, it's a lot of revenue related constraints, that's a lot of that. But maybe we could start there, and then we can talk about open source and stuff.

Jordan Tigani (4:29)

Yeah, first of all, as you're building a business, it's always tempted to go after enterprise, because somebody who can write a $10 million check, even if it's a lot of work to get that $10 million check on board, it's a lot easier than $10,000 checks.