zlacker

As a contributor, I think it's interesting when comments focus on the language (Python vs Rust) vs the architecture (local vs remote). Inference is embarrassingly parallelizable, with Python Flask or Postgres replicas. I think the interesting thing is that data retrieval costs tend to dominate other costs, and yet are often ignored.

ML algorithms get a lot focus and hype. Data retrieval, not as much.

>>montan+(OP)
For anyone who skips the intro and just goes to the results, this is what they see: https://imgur.com/tEK73e8

A suggestion: clean up the blog post's charts and headers to make it much, much more clear that what's being compared isn't python vs postgresml.

>>chaps+Ad
Another suggestion: Don't build you identity around a language or platform. They come and go. Except SQL. It's been around for longer than either of us.

>>montan+qf
Agreed, which is why I use postgres for most of my work unless I can't avoid it.

>>montan+(OP)
that is reason many older developer tend to do everything biz logic etc all in db store procedure/functions/view, etc. The cost of getting the data is native, no connection pooling needed, and with V8/python integration in the PG, it is non trivial what language you use. If you are dealing with large amount of data in a db, why not just do everything there. DB like sql has cursor, merge, that makes manipulating large set of data much easier than moving it on to another language environment.