beanstalkd vs RQ (Redis Queue)
beanstalkd
beanstalkd.github.ioRQ (Redis Queue)
python-rq.orgSide by side
| Figure | beanstalkd | RQ (Redis Queue) |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Task Queue Software | 8.1 (#10) | 8.2 (#9) |
| Purpose | Beanstalk is a simple, fast work queue for running time-consuming tasks asynchronously. | RQ is a Python library for queueing jobs and processing them in the background with workers. |
| Security | The project’s download page identifies the source release as MIT-licensed; the opened official pages make no security or compliance claims. | RQ warns that its default pickle serializer is not secure and advises using it only with trusted Redis instances; JSON is an alternative serializer. |
| Support | The site directs bug reports to its mailing list. | The project directs users to its Discord for help and discussion about contributions and the project's future. |
Plans
In their own words
beanstalkd
beanstalkd 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.