The Data Stack Show - The PRQL: Removing the Execution Engine Language Barrier with Aditya Parameswaran of Ponder

Episode Date: May 22, 2023

In this bonus episode, Eric and Kostas preview their upcoming conversation with Aditya Parameswaran of Ponder.

Welcome to the Data Stack Show prequel, where we replay a snippet from the show we just recorded. Kostas, are you ready to give people a sneak peek? I am. Of course. Let's do it. Let's do it. Kostas, I love how practical that conversation with Aditya from Ponder was. I mean, we dug into the specifics of pandas, but then we also got pretty theoretical. He has some really interesting ideas about the way that things should operate. And I think my big takeaway, and this is actually from your conversation with him, so I'm'm gonna unashamedly steal your thunder

but there's this idea i think you know he didn't necessarily use these terms but this idea of almost like artificial scarcity on execution and engines and he envisions this world where the ergonomics are such that you can use whatever language you want and then plug that into whatever execution engine you want that makes sense for your business. And currently there are a lot of limitations based on the languages and then like they're mating to different execution engines. But if you remove those barriers,

it actually becomes really interesting to think. And your point about compilers was really interesting. So when you think about sort of going from pandas to maybe like a snowflake warehouse, that doesn't seem like a normal mode of operation based on sort of typical ML workflows necessarily when you're going into production. But I love the vision. So that was really exciting. And I'll think about that a lot

because i think that is where things probably should go yeah yeah for me i mean it was like a very fascinating conversation i think so the whole focus around the user experience or like developer experience like the opportunities that exist there to build and deliver value. And all the insights from Aditya around that stuff was amazing. And also, I think, I don't know, it's like the second professor that we have now on the show after Andy from CMU. And I don't know, I kind of like it. It's really nice to have these kind of unicorns where you have these very academic people

who are also like... Totally. Maybe we should do like call them, have them like both on a show. We should do a panel because I think that's interesting. They really do... It's like they've summarized a huge legacy of

academic research into things that are very practical in the market. And a unicorn is a great way to describe that. And they have also started in part their own company. They're not just academics that talk only in theory.

They have seen how the social is made, which I think makes them like even more interesting. And I don't know. It's just like the personalities. I think like having the two of them like on a panel, it would be interesting. We need to do it. Yeah.

Someone starts out by saying, you know, I'm a database guy. Like it's probably going to be a good conversation. And that just sounds cool., I'm a database guy. Like it's probably going to be a good conversation. And that just sounds cool. Like I'm a database guy. Yeah. Yeah, absolutely. But yeah, a lot of so many sides. And I hope like we will spend more time with him to go even deeper in things around working with data systems of scale

and seeing all these things from the user perspective just like the technology. Absolutely. Well, thanks for joining the Data Sack Show. Subscribe if you haven't. Tell a friend. And we will catch you on the next one.