Asynq vs RQ (Redis Queue)
Asynq
github.comRQ (Redis Queue)
python-rq.orgSide by side
| Figure | Asynq | RQ (Redis Queue) |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Task Queue Software | 7.9 (#15) | 8.2 (#9) |
| Monitoring | The project lists Prometheus metrics integration and a web UI and CLI for inspecting and remotely controlling queues and tasks. | RQ provides queue monitoring and can send webhooks when jobs finish or fail. |
| Purpose | Asynq is a Go library for queueing tasks and processing them asynchronously with workers, backed by Redis. | RQ is a Python library for queueing jobs and processing them in the background with workers. |
| Security | The GitHub security page says the project has no security policy file and no published security advisories. | RQ warns that its default pickle serializer is not secure and advises using it only with trusted Redis instances; JSON is an alternative serializer. |
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.