Celery vs Gearman

Celery is a free, open-source distributed task queue for real-time processing and scheduled jobs. It sends task messages through a broker to worker processes, and systems can run multiple workers and brokers for high availability and horizontal scaling. Celery Beat starts tasks at regular intervals for available workers. Documented transports include RabbitMQ, Redis, Amazon SQS, Kafka and Google Pub/Sub, with different capability labels: RabbitMQ and Redis are stable, SQS is stable without monitoring or remote control, and Kafka is experimental without those features. Integrations are documented for Django, Pyramid, Pylons, Flask, web2py, Tornado and FastAPI. Commands inspect and manage workers, while Flower and event utilities provide monitoring options. Celery 5.6 supports Python 3.9 through 3.13 and PyPy 3.9 or newer. It is self-hosted, installable via PyPI or source, and licensed under the New BSD License.

Gearman is a free, self-hosted application framework for distributing work across machines or processes. A client submits jobs, a job server routes them, and a worker performs them, allowing parallel processing and load balancing. Jobs can run asynchronously in the background or receive priorities. Clients and workers may use different language interfaces when they understand the workload; listed interfaces include C, C#/.NET, Go, Java, Node.js, PHP, Perl, Python, Ruby, Rust, and Lisp. Messages can reach 4 GB, with chunking for larger messages. Clients and workers can connect to multiple job servers and fail over when one dies. The C job server supports persistent queues. MySQL and PostgreSQL functions expose client calls to queries, triggers, and stored procedures, while the pure Perl API supports SSL. Gearman runs on Linux and Windows, offers API access, and is licensed under BSD. GearmanSharp is incomplete.