11–20 of 43 posts
This is an announcement from 2017 about "the next five years", which time period is now squarely in the past. Did the DBMS ever come into existence? (If so: link, please). If not: Why should we be interested in this announcement in 2023?
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the pandemic first started, I had a bunch of CMU students reach out to me saying that their summer internships were rescinded and that they were looking for a project to work on so that they wouldn't have a gap in their CV…
What's your opinion of recent attempts like LingoDB, that move the query optimizer into a traditional compiler stack, in this case, MLIR?
- Materialize: 2017
- DuckDB: 2018
- RedPanda: 2019
- TigerBeetle: 2020
Earlier quoted context omitted.
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the pandemic first started, I had a bunch of CMU students reach out to me saying that their summer internships were rescinded and that they were looking for a project to work on so that they wouldn't have a gap in their CV…
> 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?
The problem with (most) query optimizers is that they take a one shot approach at optimization. I think an optimizer should be built from the groundup to support adaptive query optimization. Something similar to Berkeley's Eddies project from 20 years ago.
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
https://use-fireproof.com/docs/architecture
It's also the easiest way to write React apps. Here are some ChatGPT expert builders that I've trained to use the CSS framework of your choice with Fireproof: https://use-fireproof.com/docs/chatgpt-quick-start/#react-ex...
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…
Technology-wise, writing a toy DBMS is nothing difficult. Even undergraduates can do it.
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
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
According to my estimation, a new database engine is born every week - mostly key-value and document databases. Only a small subset of them survive after one year. According to a guess by Stonebreaker, a DBMS takes around 7 years to become mature enough for general applications.
Fair. I'm talking about databases with funding backing them (either by universities or otherwise).