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Celery Alternatives
Similar projects and alternatives to celery
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Redis
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.
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gunicorn
gunicorn 'Green Unicorn' is a WSGI HTTP Server for UNIX, fast clients and sleepy applications.
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opyrator
🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.
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elasticmq
In-memory message queue with an Amazon SQS-compatible interface. Runs stand-alone or embedded.
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celery discussion
celery reviews and mentions
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Celery + Redis at Scale: Designing a Reliable and Efficient Task Queue in Production
These options configure TCP keepalive. They help detect stale or broken broker connections earlier instead of letting workers hang on dead sockets. (Find more info in this Github Issue)
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10 Useful Tools and Libraries for Python Developers
9. Celery - Handle and run background tasks
- New Year's Security Incident
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HTTP 429 Too Many Requests: Learn to Manage Request Limits
One thing to note is if you need a response from the external API or not. If you don't, you can use a task queue (ex. Celery) which allows you to control task execution (ie. external API calls) rates and implement backoff strategies effortlessly. This allows you to eventually make all the calls you want, so long as the timing they get made isn't important. If you do require a response from the API - you can switch to a Websocket approach, where responses will be streamed back to the client (from the gateway) once the calls are made.
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PostgreSQL as a Celery Broker
I came across this GitHub issue discussing PostgreSQL as a potential Celery broker. This led me to discover an interesting alternative task queue called BQ, which is built specifically to use PostgreSQL for task management.
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Hacktoberfest 2024: 3rd Contribution
The original implementation ran a Celery task that deleted notifications older than 90 days on a daily basis (original feature PR).
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RabbitMQ 4.0 Released
There are some limitations when using Quorum Queues, this was only patched recently - https://github.com/celery/celery/issues/9149
- Vanilla Python Packaging
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Automatically reload Celery workers with a custom Django command
Celery previously had an --autoreload flag that has since been removed. However, Django has automatic reloading built into its manage.py runserver command. The absence of automatic reloading in Celery workers creates a confusing development experience: updating Python code causes the Django server to reload with the current code, but any tasks that the server fires will run stale code in the Celery worker.
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Ask HN: What's the right tool for this job?
From what I've seen, there are sort of two paths. I'll provide a well known example from each.
1. lang specific distributed task library
For example, in Python, celery is a pretty popular task system. If you (the dev) are the one doing all the code and running the workflows, it might work well for you. You build the core code and functions, and it handles the processing and resource stuff with a little config.
* https://github.com/celery/celery
Or lower level:
* https://github.com/dask/dask
2. DAG Workflow systems
There are also whole systems for what you're describing. They've gotten especially popular in the ML ops and data engineering world. A common one is AirFlow:
* https://github.com/apache/airflow
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A note from our sponsor - SaaSHub
www.saashub.com | 13 Jun 2026
Stats
celery/celery is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of celery is Python.