The PRQL: Making the Data Stack Serverless in the Cloud with Mike Driscoll of Rill Data

Eric Dodds 00:05
Welcome to The Data Stack Show prequel. This is a short bonus episode where we preview the upcoming show. You’ll get to meet our guests and hear about the topics we’re going to cover. If they’re interesting to you, you can catch the full length show when it drops on Wednesday. We are here with Michael Driscoll from real data. Michael, thank you so much for joining us on the show today. All right, well, give us your brief background. How did you originally get into data? And what are you doing at Rill today?

Mike Driscoll 00:37
Yeah, thanks. My, my background is actually probably not that dissimilar from a few of your guests you’ve had over the years, I actually started my career as a software developer, working for the Human Genome Project, a couple of decades back. And naturally, there’s a lot of data and the Human Genome Project. And that was really my the beginning of a multi decade love affair of working with data at scale heterogeneous data. And since then, I’ve started a few companies. My first startup was an etailer, called customink.com. We sell T shirts on the internet. I later started a consultancy called data sporer, we did a lot of consultant work for banks and folks in the big data era, I then went on to start a company called meta markets, which was acquired by Snapchat or snap the makers of Snapchat that did analytics for advertising. And now I’ve got real data, we’re a few years into that journey and focused on an operational business intelligence product with REL.

Kostas Pardalis 01:52
All right, that’s quite a genuine goal. And I know that’s part of this journey alternative looks like some very interesting technologies, like druid. And from the conversation we have there, we’re like, I’ve learned a few things that I wasn’t aware about druid and the relationship in health, like with bi and what were like the initial ideas behind it. And I’m super excited like to get into that and like, learn more about like how things you know, like how you started, like building druid while you did that, and how you ended up like today, actually, with real data that has like the joints on like the back end, but it’s more than like a query engine. Right. So I’m super excited to get into the details. What about you what you’re, like excited to talk about today? Yeah, well, I

Mike Driscoll 02:45
think there’s a, I think, a few big macro trends that we’re seeing in the data world. Today, I would say I would be delighted to talk about some of the emerging data engines that that are out there for powering fast analytics at scale, really, at any scale. So druid and ClickHouse. Know, also, duck dB, we all know is an exciting new engine. But I think the other trend that, for me is particularly exciting is the trend towards serverless frameworks. I think if we’ve those of us, and I know you all of you pay close attention to this space. I think that there’s a lot of new frameworks out there for really taking not just, you know, data technologies to the cloud, but making them serverless in the cloud. And so I look at Yeah, you know, almost any area of The Data Stack Show, I think is being remade to be truly serverless at scale in the cloud. And that’s, that’s a pretty exciting. That’s a pretty exciting area that’s going to take several years to play out.

Kostas Pardalis 04:06
Yeah, I’m calling Christians will probably like a little bit talk about that to show Eric, what do you think? Should we dive in?

Eric Dodds 04:14
Let’s do it. All right. That’s a wrap for the prequel. The full length episode will drop Wednesday morning. Subscribe now so you don’t miss it.