I get excited every time I see a paper from Bradish. I've learned so much about high performance software from studying systems that he has worked on. (not to diminish his many co-authors and contributors)
Interesting. I've been on/off working on something, though it's an append-only hash index thing (based on Erlang's Bitcask): https://git.sr.ht/~tombert/feocask
I haven't done any benchmarks on it yet so I have no idea how well it performs, but I have a very strict "no explicit lock" policy, so everything is handled with separate files with a reconciliation service that uses a vector clock to determine ordering.
NOTE: A lot of this is AI-assisted, treat what I have written as more of a whiteboard proof of concept. I'm in the process of rewriting it by hand to do some more aggressive optimizations.
I think a fair comparison would be against a whitepaper? Clearly this is an exploratory venture and not production grade software.
You managed to clone the repo an run your test by yourself, whatever the outcome is this is a plus against the standard model for scientific research.
Also, a breath of fresh air among every other show HN thread using hundreds of adjectives to describe the "behavior" of a fully vibed system. I think this is a good model for presenting engineering projects.
> You managed to clone the repo an run your test by yourself, whatever the outcome is this is a plus against the standard model for scientific research.
That's so true, which is kinda funny since one of the cornerstone of scientific thinking is reproducibility.
I get excited every time I see a paper from Bradish. I've learned so much about high performance software from studying systems that he has worked on. (not to diminish his many co-authors and contributors)
Some of his other projects:
[0] https://github.com/microsoft/garnet [1] https://github.com/microsoft/FASTER [2] https://github.com/microsoft/Trill
Interesting. I've been on/off working on something, though it's an append-only hash index thing (based on Erlang's Bitcask): https://git.sr.ht/~tombert/feocask
I haven't done any benchmarks on it yet so I have no idea how well it performs, but I have a very strict "no explicit lock" policy, so everything is handled with separate files with a reconciliation service that uses a vector clock to determine ordering.
NOTE: A lot of this is AI-assisted, treat what I have written as more of a whiteboard proof of concept. I'm in the process of rewriting it by hand to do some more aggressive optimizations.
I've tested with wal enabled, got deadlock several times, so looks raw for now
I think a fair comparison would be against a whitepaper? Clearly this is an exploratory venture and not production grade software.
You managed to clone the repo an run your test by yourself, whatever the outcome is this is a plus against the standard model for scientific research.
Also, a breath of fresh air among every other show HN thread using hundreds of adjectives to describe the "behavior" of a fully vibed system. I think this is a good model for presenting engineering projects.
> You managed to clone the repo an run your test by yourself, whatever the outcome is this is a plus against the standard model for scientific research.
That's so true, which is kinda funny since one of the cornerstone of scientific thinking is reproducibility.
IMHO they're using the best tool for this, nix.