Celery vs RabbitMQ: What are the differences?
Celery: Distributed task queue. Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well; RabbitMQ: A messaging broker - an intermediary for messaging. RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
Celery and RabbitMQ belong to "Message Queue" category of the tech stack.
"Task queue" is the primary reason why developers consider Celery over the competitors, whereas "It's fast and it works with good metrics/monitoring" was stated as the key factor in picking RabbitMQ.
Celery and RabbitMQ are both open source tools. It seems that Celery with 12.9K GitHub stars and 3.33K forks on GitHub has more adoption than RabbitMQ with 5.94K GitHub stars and 1.78K GitHub forks.
reddit, 9GAG, and Rainist are some of the popular companies that use RabbitMQ, whereas Celery is used by Udemy, Robinhood, and Sentry. RabbitMQ has a broader approval, being mentioned in 940 company stacks & 548 developers stacks; compared to Celery, which is listed in 272 company stacks and 77 developer stacks.
What is Celery?
What is RabbitMQ?
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I developed one of the largest queue based medical results delivery systems in the world, 18,000+ queues and still growing over a decade later all using MQSeries, later called Websphere MQ. When I left that company I started using RabbitMQ after doing some research on free offerings.. it works brilliantly and is incredibly flexible from small scale single instance use to large scale multi-server - multi-site architectures.
If you can think in queues then RabbitMQ should be a viable solution for integrating disparate systems.
All of our background jobs (e.g., image resizing, file uploading, email and SMS sending) are done through Celery (using Redis as its broker). Celery's scheduling and retrying features are especially useful for error-prone tasks, such as email and SMS sending.
For orchestrating the creation of the correct number of instances, managing errors and retries, and finally managing the deallocation of resources we use RabbitMQ in conjunction with the Celery Project framework, along with a self-developed workflow engine.
We maintain a fork of Celery 3 that adds HTTPS support for Redis brokers. The Winning Model currently uses Celery 3 because Celery 4 dropped support for Windows.
We plan on migrating to Celery 4 once Azure ASE supports Linux apps
The poster child for scalable messaging systems, RabbitMQ has been used in countless large scale systems as the messaging backbone of any large cluster, and has proven itself time and again in many production settings.
Rabbit acts as our coordinator for all actions that happen during game time. All worker containers connect to rabbit in order to receive game events and emit their own events when applicable.
Used as central Message Broker; off-loading tasks to be executed asynchronous, used as communication tool between different microservices, used as tool to handle peaks in incoming data, etc.
RabbitMQ is the enterprise message bus for our platform, providing infrastructure for managing our ETL queues, real-time event notifications for applications, and audit logging.
RabbitMQ is an all purpose queuing service for our stack. We use it for user facing jobs as well as keeping track of behind the scenes jobs.
We used celery, in combination with RabbitMQ and celery-beat, to run periodic tasks, as well as some user-initiated long-running tasks on the server.