In this bonus episode, Eric and Kostas preview their upcoming two-part conversation with Arjun Narayan and Frank McSherry of Materialize.
The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.
RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.co
Eric Dodds 00:05
Welcome to The Data Stack Show prequel we have one of our more special episodes coming up, because it’s actually two episodes. Kostas, we talked with the cofounders of materialized we had Arjun on the show, yet this a year and a half ago. Can you even believe that more, I think, actually, and had a really interesting conversation about streaming sequel and what they’re building. And of course, we like to have people back on the show, we had him come back on and bring his co-founder, Frank McSherry, who in his own right is a fascinating individual who has done some amazing work, both in academic research and then actually building stuff on top of timely data flow, which I know you’re really interested in. So we covered an immense amount of material. What was your What did you like most about the show? What was the part that you enjoyed the most, because it really was an incredible thing.
Kostas Pardalis 01:03
Oh, it’s just like, so many different things. To be honest, like, first of all, I find it always fascinating to see the dynamics of co founders. That says a lot about, like the company and like, especially like for me, and for you, as like, we’ve been in the position of a founder rights, and we know how special these relationships between co founders are. Absolutely. I don’t know, like, I find it really interesting for me like to see to and observe, like the interactions of these two guys. So that’s one thing like, I think, just for that, it’s worth like, going through the, the recordings, but also we have first of all, we have like a company that I love to talk about, because they do try to build like something that these radically different. Which, okay, like, to me, it makes it like always really interesting to hear from a German, like, see what’s going on, like Adam, how big have progressed and like all that stuff. So of the time I think is great after like a year to see exactly how things have changed in the company, and the product. And then of course we have frantically is I have no like he he’s special, like he has done like a lot of things in the industry. He has, he’s well known, like foresees war in privacy. But also, he has Latane introduce the new processing model, which is the time flow model that we will are going to be talking about Naiad, which is Naiad. Yes, that was the name of the project back in. Microsoft wins, he developed that. And that’s super exciting. Like if you think about it like scenes, MapReduce, which is inning of the zeros like there are lots maybe different models that they have. One of them is nine apps, it hasn’t like yet got the traction that like MapReduce has, but it seems that it’s changing. I agree. So yeah, I think it’s going to be super, super interesting to talk with them about building companies and being co founders, but also about the technology itself and little more about what Arjun is and why it’s so different and so interesting
Eric Dodds 03:30
Yeah, I agree. The story of how they met and then how their relationship progress towards materialise is fascinating. origin story about what he learned at cockroach TV. And cockroach labs, like working on cockroach TV was fascinating, especially what he learned about himself as a programmer. I thought it was fun, it was really. And then a couple other interesting things that really stuck out that I think our listeners are gonna love about this one, the decisions that they made relative to Nyad, in terms of what they impose on top of timely data flow as part of materialize, hearing about the relationship between timely data flow and what they’re building on top and why they made those decisions was absolutely fascinating. And it was one of those sections of the conversation where, you know, you sort of step back and realize these people are unbelievably brilliant and have thought very long and very hard about this. And then the last one, which I think is an interesting teaser is we all think about SQL as sort of the most, you know, one of the most ubiquitous queering languages out there, right. But origins discussion around SQL dialects and ultimately why they chose Postgres flavor. And even within that, you know, they still had to make certain decisions shins or impose certain constraints. And that whole conversation was really fascinating because, you know, of course there are different flavors of SQL that when you’re doing what materialized does that stuff comes very important. And they had a lot of hard choices to make. So if any of that sounds interesting, you’re gonna love it, especially because Brooks was there and we recorded for 90 minutes of course, it’ll be two episodes, but we went deeper I think and we’ve ever gone on multiple subjects, so you absolutely don’t want to miss this one. So subscribe if you haven’t, we’ll notify you when each episode comes out. Tell a friend and we will catch you on the next one.