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Comment by hangonhn | Hacker News Reader

This is something my company has been considering for a while. We've been using celery and it's not great. It gets the job done but it has its issue.

I've never heard of Oban until now and the one we've considered was Temporal but that feels so much more than what we need. I like how light Oban is.

Does anyone have experience with both and is able to give a quick comparison?

Thanks!

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Very, very different tools, though they cover similar areas.

Temporal - if you have strict workflow requirements, want _guarantees_ that things complete, and are willing to take on extra complexity to achieve that. If you're a bank or something, probably a great choice.

Oban - DB-backed worker queue, which processes tasks off-thread. It does not give you the guarantees that Temporal can because it has not abstracted every push/pull into a first-class citizen. While it offers some similar features with workflows, to multiple 9's of reliability you will be hardening that yourself (based on my experience with Celery+Sidekiq)

Based on my heavy experience with both, I'd be happy to have both available to me in a system I'm working on. At my current job we are forced to use Temporal for all background processing, which for small tasks is just a lot of boilerplate.

I’ll say that, I think this varies by language/SDK - at least with the Temporal TypeScript SDK, a simple single idempotent step background task is however many lines of code to do the actual work in an activity, and then the only boilerplate is like 3 lines of code for a simple workflow function to call the activity.

We migrated from Celery to Prefect a couple of years back and have been very happy. But ours is a small op which handles tasks in 1000s and not millions. It’s been night and day in terms of visibility and tracking. I would definitely recommend it.

It’s a heavy weight that covers a lot of use cases. But we just run simple ProcessWorkers for our regular needs and ECS worker for heavier ML tasks.

I'm just coming back to web/API development Python after 7-8 years working on distributed systems in Go. I just built a Django+Celery MVP given what I knew from 2017 but I see a lot of "hate" towards Celery online these days. What issues have you run into with Celery? Has it gotten less reliable? harder to work with?

Celery + RabbitMQ is hard to beat in the Python ecosystem for scaling. But the vast, vast majority of projects don't need anywhere that kind of scale and instead just want basic features out of the box - unique tasks, rate limiting, asyncio, future scheduling that doesn't cause massive problems (they're scheduled in-memory on workers), etc. These things are incredibly annoying to implement over top of Celery.

Yeah that list right there. That's exactly it.

We don't hate Celery at all. It's just a bit harder to get it to do certain things and requires a bit more coding and understanding of celery than what we want to invest time and effort in.

Again, no hate towards Celery. It's not bad. We just want to see if there are better options out there.

But if you are too small for celery, it seems a hard sell to buy a premium message queue?

My top problem with my celery setup has always been visibility. AI and I spent and afternoon setting up a Prometheus / grafana server, and wiring celery into it. Has been a game changer. When things go crazy in prod, I can usually single it down to a specific task for a specific user. Has made my troubleshooting go from days to minutes. The actual queue and execute part has always been easy / worked well.

For an even lighter system than Celery, I'm a big fan of

https://python-rq.org/

It's super low on the dependencies and integrates nicely as a library into python applications. It's very bare bones.

I kinda have my own https://github.com/tktech/chancy :P

I like celery but I started to try other things when I had projects doing work from languages in addition to python. Also I prefer the code work without having to think about queues as much as possible. In my case that was Argo workflows (not to be confused with Argo CD)

Most Django projects just need a basic way to execute timed and background tasks. Celery requires seperate containers or nodes, which complicates things unnecessarily. Django 6.0 luckily has tasks framework -- which is backported to earlier django versions has well, which can use the database. https://docs.djangoproject.com/en/6.0/topics/tasks/

Django 6's tasks framework is nice but so far it is only an API. It does not include an actual worker implementaiton. There is a django-tasks package which does a basic implementation but it is not prod ready. I tried it and it is very unreliable. Hopefully the community will come out with backends for it to plug celery, oban, rq etc.

Could you say a bit more about "it is very unreliable"? I'm considering using django-tasks with an rq backend [1] and would like to hear about your experiences. Did you find it dropping tasks, difficult to operate, etc.

[1] https://github.com/RealOrangeOne/django-tasks?tab=readme-ov-...

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