[tomnipotent]

That post is about how Postgres doesn't scale for write-heavy workloads and that they had to move those workloads to Cosmos DB. For the rest of the remaining mostly-read workload they have a single primary with 50 read replicas.

[dewey]

The point is that Postgres scales a very long way. Once you arrive at OpenAI / ChatGPT scale there's no shame in reaching for a dedicated queuing system.

[tomnipotent]

> scales a very long way

This ignores the fine print. It scales a very long way under specific circumstances with specific workloads. The more write-heavy your workload the less eloquently Postgres scales.

For OpenAI's use case you could swap Postgres with MySQL and it would scale just as well.

[dewey]

We are talking about Postgres as a queue here, which is heavy on tiny writes, reads and churning tables. The point is just that a RDMS like Postgres scales very far as a queue, it’s not a fight if Postgres or MySQL.

Nobody is arguing for using it for everything and forever but for most company sizes it’s perfectly fine to not reach for a dedicated queuing tool if you already have PG running.

[tomnipotent]

> on tiny writes

Postgres doesn't do "tiny writes" - it writes whole pages multiple times on every update even if you're only changing 4 bytes, combined with even more writes later on when vacuuming tables. This is one of the reasons why the historical advice was to not build high-volume queues on top of Postgres and why "oh look another post about queues on Postgres" keeps soliciting comments like this.

[ballon_monkey]

If your DB is write heavy, tune it for writes...

[tomnipotent]

You can't tune your way out of this constraint. The heap table and MVCC implementation put a hard ceiling on what can be accomplished without reaching for another tool.