Procrastinate vs RQ (Redis Queue)
Procrastinate
procrastinate.readthedocs.ioRQ (Redis Queue)
python-rq.orgSide by side
| Figure | Procrastinate | RQ (Redis Queue) |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Task Queue Software | 7.7 (#22) | 8.2 (#9) |
| Monitoring | The command-line interface provides health checks, and its interactive shell can inspect and administer jobs, tasks, queues, and locks. | RQ provides queue monitoring and can send webhooks when jobs finish or fail. |
| Purpose | Procrastinate is an open-source distributed task processing library for Python that uses PostgreSQL to store task definitions, manage locks, and dispatch tasks. | RQ is a Python library for queueing jobs and processing them in the background with workers. |
Plans
In their own words
Procrastinate
Procrastinate has no write-up on Specifiction yet; its figures are above.
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.