> The conventional wisdom around Postgres-backed queues is that they don't scale.
That might have been the case 10 years ago. In the past years there have been many Postgres powered queueing systems and even Rails switched to Postgres powered queues by default (SolidQueue) more than 3 years ago.
I see a lot of back and forth about postgres' suitability as a queuing system. I wonder if there's a couple of separable problems here. Postgres backed queues - even very scalable ones - might work well for background jobs in a monolithic app backed by a single DB. Things like backgrounding sending an email etc.
But usually when I reach for a queuing system, it's because I want to decouple a part of the architecture. And in that case, it's probably better to use a dedicated queueing system instead of postgres.
I wonder if the two cases are conflated in a lot of online discussion.
We are very heavily using Postgres as a queuing system in production for many years already, not just some quiet background tasks but with millions of tasks in the queue at any given moment. I have yet so see any issues with that so I'm always a bit suspicious when people say they had to reach for something else unless you are at a crazy scale.
> It may sound surprising that a single-primary architecture can meet the demands of OpenAI’s scale; however, making this work in practice isn’t simple.
That might have been the case 10 years ago. In the past years there have been many Postgres powered queueing systems and even Rails switched to Postgres powered queues by default (SolidQueue) more than 3 years ago.
But usually when I reach for a queuing system, it's because I want to decouple a part of the architecture. And in that case, it's probably better to use a dedicated queueing system instead of postgres.
I wonder if the two cases are conflated in a lot of online discussion.
I know it's very hard to compare workloads, but famous recent example: https://openai.com/index/scaling-postgresql/
> It may sound surprising that a single-primary architecture can meet the demands of OpenAI’s scale; however, making this work in practice isn’t simple.
Shameless link to an older article about throughput with Oban (https://oban.pro/articles/one-million-jobs-a-minute-with-oba...), and in follow-up research we've sustained 12k/s with a p99 under ~100ms.