imdbench VS postgres-benchmarks

[0] https://github.com/edgedb/imdbench

Only the query compiler is in pure Python and you only hit that once per query, as the compilation result is trivially cached. The hot path is a combination of Cython, C and Rust. We have a suite of benchmarks [1] that show relative overhead of EdgeDB compared to raw Postgres is quite low.

[1] https://github.com/edgedb/imdbench

We spent a lot of time optimizing every benchmark. Here's what creator of sqlalchemy said about our code: https://github.com/edgedb/imdbench/pull/46 (and then he proposed improvements). We'll surely take a look at prefetch_related.

There's a link to a simple Benchmark right after the title.

Here are two:

https://github.com/porsager/postgres-benchmarks

https://porsager.github.io/imdbench/sql.html

and really fast (https://github.com/porsager/postgres-benchmarks) even faster than the native postgres

> On the surface I'm not sure this explanation passes the smell test. Almost irrespective of how you get the data from your network card into v8 / nodejs, you're going to be crossing c++/v8 boundaries.

yes, you are, but the differences are the object creation that occurs. a single buffer coming from c/c++ (a socket, let's say) can be parsed and turned into a large number of objects in javascript much more quickly. yes, you're passing through that barrier once, but creating all of those objects from c++ and passing through it 20-30 times is a lot more expensive.

> Out of curiosity, do you have links to these other projects where they have similar benchmarking attempts/results?

how about pg vs pg-native? https://github.com/porsager/postgres-benchmarks#results

and unfortunately, I cannot find the original discussions from when node-redis went from native to pure javascript, but it was about a 30-40% speed increase originally if memory serves (I was the one who did that original conversion after a lot of deep dives into v8 and performance crossing the barrier).

as an aside, I'm also the maintainer of plv8, and am happy to discuss the same types of performance issues of dealing with jsonb vs json (which in Postgres is text): creating objects vs a simple JSON.parse() in c++ is a significant difference.