RQ (Redis Queue) vs Sidekiq
RQ (Redis Queue)
python-rq.orgSidekiq
sidekiq.orgSide by side
| Figure | RQ (Redis Queue) | Sidekiq |
|---|---|---|
| Price from | Free | $82.92/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 3 |
| Spec score · Task Queue Software | 8.2 (#9) | 7.9 (#16) |
| Headquarters | Jakarta, Indonesia | Lake Oswego, Oregon, United States |
| Integrations | The project documents usage patterns for Heroku, Django, Sentry, Supervisor, and systemd. | Sidekiq's wiki says server processes boot Rails, making the Rails API, including Active Record, available to jobs and workers. |
| Purpose | RQ is a Python library for queueing jobs and processing them in the background with workers. | Sidekiq is a framework for background job processing that scales applications by performing work in the background. |
| Support | The project directs users to its Discord for help and discussion about contributions and the project's future. | Commercial priority support covers one incident per quarter, has a maximum response time of two working days, and excludes the customer's application and infrastructure. |
Plans
In their own words
RQ (Redis Queue)
RQ (Redis Queue) is a Python library for placing jobs in queues and running them asynchronously in background worker processes. It is self-hosted, open source under the BSD license, and free. It requires Redis 5 or later, or Valkey 7.2 or later. RQ supports scheduled and repeating jobs, retries, bulk enqueueing, job groups, dependencies, unique jobs, and concurrency rate limits. Unique jobs cannot be combined with dependencies. Failed jobs are recorded with exception information, and custom exception handlers are supported. For monitoring, there is an `rq info` console command; RQ Dashboard is a separate web-based frontend. Documentation covers Django, including django-rq, as well as usage with Heroku, Sentry, Supervisor, and systemd. RQ serializes jobs with pickle by default, which the project warns is safe only with trusted Redis instances; JSON is an alternative. Workers need a system that supports `fork()`, so Windows requires Windows Subsystem for Linux and a bash shell. Workers must also be able to import job functions, and producers and workers must share source code.