I love them both too but that might not be the best metric unless you’re planning to run lots of little read queries. If you’re doing CRUD, simulating that workflow may favor Postgres given the transactional read/write work that needs to take place across multiple concurrent connections.

> I love them both too but that might not be the best metric unless you’re planning to run lots of little read queries.

Exactly. Back in the real world,anyone who is faced with that sort of usecase will simply add memory cache and not bother with the persistence layer.

Not sure that’s always right either though. For example Mapbox used to use an SQLite database as the disk cache for map tile info. You cannot possibly store that amount of data in memory, so it’s a great use case.

This is mostly about thread communication. With SQLite you can guarantee no context switching. Postgres running on the same box gets you close but not all the way. It's still in a different process.

This. Run an app on the same box as PG and you can easily be plagued by out of memory etc (as there's memory contention between the two processes).

A total performance delta of <3s on ~300k transactions is indeed the definition of irrelevant.

Also:

> PostgreSQL (localhost): (. .) SQLite (in-memory):

This is a rather silly example. What do you expect to happen to your data when your node restarts?

Your example makes as much sense as comparing Valkey with Postgres and proceed to proclaim that the performance difference is not insignificant.

Why are you comparing PostgreSQL to an in-memory SQLite instead of a file-based one? Wow, memory is faster than disk, who would have thought?

Because it doesn't make a difference, because `SELECT 1` doesn't need to touch the database:

    Running 100,000 `SELECT 1` queries:
    PostgreSQL (localhost): 2.71 seconds
    SQLite (in-memory): 0.07 seconds
    SQLite (tempfile): 0.07 seconds

(https://gist.github.com/leifkb/d8778422d450d9a3f103ed43258cc...)

Why are you doing meaningless microbenchmarks?

Are you claiming that this does not show the speed difference between socket vs in process communication?

> Because it doesn't make a difference, because `SELECT 1` doesn't need to touch the database:

I hope you understand that your claim boils down to stating that SQLite is faster at doing nothing at all, which is a silly case to make.

The original claim being discussed is about the overhead of an in-process database vs. a database server in a separate process, not about whether SQLite or PostgreSQL have a faster database engine.

Queries for small SaaS are usually in the thousands of records, if not hundreds.

How about pg on Unix socket?

    Running 100,000 `SELECT 1` queries:
    PostgreSQL (localhost): 2.84 seconds
    PostgreSQL (Unix socket): 1.93 seconds
    SQLite (in-memory): 0.07 seconds
    SQLite (tempfile): 0.06 seconds

(https://gist.github.com/leifkb/b940b8cdd8e0432cc58670bbc0c33...)

You appear to have benchmarked how quickly Python can access memory vs how quickly Python can open and close a socket. I'm not sure the DBs were required in any way.

seems about right

Most important is that that local SQLite gets proper backups, so a restore goes without issues

Gets proper backups if you back it up the right way https://sqlite.org/backup.html

Would be nice to see PGLite[1] compared too

1: https://pglite.dev/

Interesting, but I'm not sure how relevant it would be for a SaaS that on average queries hundreds to thousands of rows.

It is insignificant if you're doing 100k queries per day, and you gain a lot for your 3 extra seconds a day.