Sidekiq VS celery

Hi there! I want to show off a little feature I made using hanami, htmx and a little bit of redis + sidekiq.

I'd say Sidekiq is the top competitor here.

There's something wrong at Redislabs, it took them over a year to get RESP3 rolled out into their hosted service, you'd expect a rollout of that to be a bit quicker when they're the owner of Redis.

It affected us when upgrading Sidekiq to version 7, which dropped support for older Redis, and their Envoy proxy setup didn't support HELLO and RESP3: https://github.com/sidekiq/sidekiq/issues/5594

That depends on how the `maxmemory-policy` is configured, and queue systems based on Redis will tell you not to allow eviction. https://github.com/sidekiq/sidekiq/wiki/Using-Redis#memory (it even logs a warnings if it detects your Redis is misconfigured IIRC).

Sidekiq https://sidekiq.org/: This one started as an open source project, once it got enough traction, the developer made a premium version of it, and makes money by selling licenses to businesses.

Sidekiq will drop in-progress jobs when a worker crashes. Sidekiq Pro can recover those jobs but with a large delay. Sidekiq is excellent overall but it’s not suitable for processing critical jobs with a low latency guarantee.

https://github.com/sidekiq/sidekiq/wiki/Reliability

> I'm not sure feature withholding has traditionally worked out well in the developer space.

I think it's worked out well for Sidekiq (https://sidekiq.org). I really like their model of layering valuable features between the OSS / Pro / Enterprise licenses.

I was studying Sidekiq's page on rate limiters. The first type of rate limiting mentioned is the concurrent limiter: only n tasks are allowed to run at any point in time. Note that this is independent of time units (e.g. per second), or how long they take to run. The only limitation is the number of concurrent tasks/requests.

So this might be my understanding, but stuff like celery is more like an orchestrator that chunks up workloads (think Hadoop with multiple nodes).

In the Django world, you'd probably rely on Celery to do this for you. You're probably looking for something similar that works with Go. https://github.com/celery/celery

I've been doing some research and there doesn't seem to be much information on this issue, aditionally there's this but without a fix yet or any workaround: https://github.com/celery/celery/issues/7792

RabbitMQ Classic mirror queues are very fragile to network partitioning. They are deprecated in favor of Quorum queues, but Celery doesn't support them yet : https://github.com/celery/celery/issues/6067

The Celery package provides some number of (undocumented!) result backends to store task results in different local, network, and cloud storages. The django-celery-result package adds options to use Django-specific ORM-based result storage, as well as Django-specific cache subsystem.

I spent 3 years building a high scale crawler on top of Celery.

I can't recommend it. We found many bugs in the more advanced features of Celery (like Canvas) we also ran into some really weird issues like tasks getting duplicated for no reason [1].

The most concerning problem is that the project was abandoned. The original creator is not working on it anymore and all issues that we raised were ignored. We had to fork the project and apply our own fixes to it. This was 4 years ago so maybe things improved since them.

Celery is also extremely complex.

I would recommend https://dramatiq.io/ instead.

[1]: https://github.com/celery/celery/issues/4426

You can use celery to process the file for extraction, saving and creating rar/zip.

Celery not usefull for long term future tasks (far future) · Issue #4522 · celery/celery (github.com)