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Building a new database management system in academia (2017)

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Re: Building a new database management system in academia (2017)

#41

If you're interested in the idea of databases built from scratch since the time this post was written in 2017 (based on GitHub contributions info), here are a few: - Materialize: 2017 - DuckDB: 2018 - RedPanda: 2019 - TigerBeetle: 2020

KùzuDB[1] is an in-process graph database built from scratch and came out of academia too. We are from Data Systems Group at University of Waterloo, started since Sep 2020, and have a small team actively work on it now. These two posts[2,3] explain where we are from and where we're going, if anyone is interested.

[1]: https://github.com/kuzudb/kuzu

[2]: https://kuzudb.com/blog/meet-kuzu.html

[3]: https://kuzudb.com/blog/what-every-gdbms-should-do-and-visio...

Re: Building a new database management system in academia (2017)

#42
post #4
post #3

Earlier quoted context omitted.

This is Andy Pavlo, so he probably got sidetracked with https://ottertune.com/ Not sure what op's intention with this was

Actually, it was a combination of three things: 1. OtterTune Start-up ( https://ottertune.com ) 2. Biological Daughter ( https://twitter.com/andy_pavlo/status/1187841279260004355 ) 3. Pandemic When the pandemic first started, I had a bunch of CMU students reach out to me saying that their summer internships were rescinded and that they were looking for a project to work on so that they wouldn't have a gap in their CV…

Can you kindly share any reading list or anything similar for someone who wants to get into database research at doctoral level? I am a recent MS(Statistics + CS) graduate working as a Data Engineering, and I am looking for material to learn about the current research landscape and getting ready for grad school application.

Re: Building a new database management system in academia (2017)

#43

Earlier quoted context omitted.

> Our future project is going to start with the optimizer first. What's your opinion of recent attempts like LingoDB, that move the query optimizer into a traditional compiler stack, in this case, MLIR?

There's also mutable that compiles to WASM and lets it get JITed by v8 https://github.com/mutable-org/mutable .

I've now read through the mutable papers, and I think it's a great idea.

A similar thing happened in physically-based rendering, with the publication of the PBTR series of books. As a result of that effort, a lot of really solid research improving various aspects of rendering occurred. Extremely influential long-term.

mutable could have a similar kind of experience if presented that way to the public.

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