I personally think Celery is a bit over-engineered and not all backends are as developed as the others. It's a solid tool though. I used it to process millions of images, Instagram used it for years (they probably still do, but I'm not up to date). The two things are unrelated :D
I think it's a bit more complicated to maintain in production than RQ because it does so many things and can use different combinations of backends.
A good way of choosing: do you need RabbitMQ for complicated queue topologies or need to basically build trees of subtasks? If yes, use Celery, otherwise you can stick with RQ which by only supporting Redis makes it all a bit easier.
We can use Flower to have nice visualizations (flower.readthedocs.io/en/latest/sc...) or RabbitMQ admin if we're using Rabbit as backend (Redis can also be used).
Also, do you find it easier to maintain in production?
I don't know as I don't have any experience with django-rq
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Does it offer a GUI/dashboard where we can see how our jobs are doing like in django-rq??
Also, do you find it easier to maintain in production?
Celery has flower.
I personally think Celery is a bit over-engineered and not all backends are as developed as the others. It's a solid tool though. I used it to process millions of images, Instagram used it for years (they probably still do, but I'm not up to date). The two things are unrelated :D
I think it's a bit more complicated to maintain in production than RQ because it does so many things and can use different combinations of backends.
A good way of choosing: do you need RabbitMQ for complicated queue topologies or need to basically build trees of subtasks? If yes, use Celery, otherwise you can stick with RQ which by only supporting Redis makes it all a bit easier.
As always, it depends on what you need :)
We can use Flower to have nice visualizations (flower.readthedocs.io/en/latest/sc...) or RabbitMQ admin if we're using Rabbit as backend (Redis can also be used).
I don't know as I don't have any experience with django-rq