ratus VS gocelery

The Go ecosystem has many brilliant distributed task queue libraries, but sometimes we still have to settle for some bloated cross-platform solution in order to work with components written in other languages. To solve this problem, we created Ratus, which is a service, not a library. It translated concepts of distributed task queues into a set of resources that conform to REST principles and provides an easy-to-use HTTP API. Ratus is implemented in Go, and comes with a Go client library. Asynchronous task queues are typically used for long-running background tasks, so the overhead of the HTTP API is not significant compared to the time spent by the tasks themselves. On the other hand, the HTTP-based RESTful API can be easily accessed by all languages without using dedicated client libraries.

To solve this problem, we created Ratus, which is a service, not a library. It translated concepts of distributed task queues into a set of resources that conform to REST principles and provides an easy-to-use HTTP API. Ratus is implemented in Go, and comes with a Go client library. The current default storage engine is MongoDB (in-memory store coming soon), we will also try to integrate existing Go task queue libraries.

I've been working on https://github.com/hyperonym/ratus which is a RESTful asynchronous task queue server, it also comes with a Go client library.

I had a look at: 1. machinery - https://github.com/RichardKnop/machinery 2. go-celery - https://github.com/gocelery/gocelery 3. asynq - https://github.com/hibiken/asynq 3. taskq - https://github.com/vmihailenco/taskq

What about https://github.com/gocelery/gocelery ?

go-celery (https://github.com/gocelery/gocelery): Celery port in Go. Not much recent activity so a bit worried it's abandoned.

Please note that this blog post uses a Golang application (thanks to gocelery!) as an example, but the same applies to Python or any other application that uses the Celery protocol.