Message queues are usually a core part of any distributed architecture, and the options are endless: Kafka, RabbitMQ, NATS, Redis Streams, SQS, ZeroMQ... and then there's the “just use Postgres” camp for simpler use cases.
I’m trying to make sense of the tradeoffs between:
- async fire-and-forget pub/sub vs. sync RPC-like point to point communication
- simple FIFO vs. priority queues and delay queues
- intelligent brokers (e.g. RabbitMQ, NATS with filters) vs. minimal brokers (e.g. Kafka’s client-driven model)
There's also a fair amount of ideology/emotional attachment - some folks root for underdogs written in their favorite programming language, others reflexively dismiss anything that's not "enterprise-grade". And of course, vendors are always in the mix trying to steer the conversation toward their own solution.
If you’ve built a production system in the last few years:
1. What queue did you choose?
2. What didn't work out?
3. Where did you regret adding complexity?
4. And if you stuck with a DB-based queue — did it scale?
I’d love to hear war stories, regrets, and opinions.
Mostly because it has been very reliable for years in production at a previous company, and doesn’t require babysitting. Its recent versions also has new features that make it is a descent alternative to Kafka if you don’t need to scale to the moon.
And the logo is a rabbit.
inb4 "oh but you wont be taken seriously" well... datadog.