Alternatives

vs django-tasks

django-tasks is the third-party package that defined the django.tasks interface (DEP 0014) and served as its reference implementation. It ships a DatabaseBackend that stores and executes tasks using your application’s database.

The django-tasks DatabaseBackend is intentionally minimal. Steady Queue is also a database-backed implementation of the same interface, but adds:

  • Cron-style recurring tasks via the @recurring decorator.

  • Concurrency controls via @limits_concurrency.

  • Operational visibility: inspect, retry and discard failed tasks from the Django admin.

  • Queue pausing: pause and resume individual queues from the admin.

  • Horizontal scaling: run multiple worker or dispatcher processes across machines.

  • Configurable process topology: control the number of workers, threads per worker, polling intervals and which queues each worker handles.

  • Heartbeat-based liveness checks with automatic task recovery when a worker process dies.

If you just need simple background task execution and none of the above features matter to you, django-tasks is a fine choice. Steady Queue is the better fit when you need more operational control or advanced features.

Because both implement the same django.tasks interface, you can switch between them by changing a single line in settings.py.

vs Celery

Celery is the most widely used task queue library in the Python ecosystem. It is mature, has a huge community and supports a wide range of brokers (Redis, RabbitMQ, Amazon SQS, etc.).

The main trade-off is operational complexity: Celery requires a separate broker process (typically Redis or RabbitMQ) that must be deployed, monitored and maintained. Steady Queue uses your existing database, so there’s nothing new to operate.

Celery also has its own task definition interface (@app.task / @shared_task), whereas Steady Queue follows the standard django.tasks interface (DEP 0014), which keeps your task code portable across compliant backends.

Consider Celery if you need features like task routing to heterogeneous worker pools, support for non-relational brokers, or the rich ecosystem of third-party Celery extensions. Consider Steady Queue if you’d rather not introduce a broker dependency and your workloads fit comfortably within a relational database.

vs django-rq

django-rq integrates the RQ task queue (which uses Redis as a broker) with Django. Like Celery, it requires Redis to be running. It is simpler than Celery and easier to set up, but still adds operational overhead compared to a pure database solution.

vs Solid Queue

Solid Queue is the Ruby on Rails library that Steady Queue is ported from. If you’re coming from a Rails background, the concepts and configuration will look familiar. The main differences in the external interface are:

  • Task definition. Solid Queue works with Active Job classes; Steady Queue uses the @task decorator from DEP 0014.

  • Priority ordering. Steady Queue follows Django’s convention where larger numbers mean higher priority (e.g. priority 10 runs before priority 0). Solid Queue uses the inverse.

  • Recurring tasks. Solid Queue supports command-based recurring tasks (arbitrary shell commands on a schedule). Steady Queue only supports recurring Python task functions.

  • Instrumentation. Solid Queue emits rich ActiveSupport::Notifications events. Steady Queue uses standard Python logging and the django.tasks signals instead.