ActiveMQ vs Celery: What are the differences?
Developers describe ActiveMQ as "A message broker written in Java together with a full JMS client". Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License. On the other hand, Celery is detailed as "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.
ActiveMQ and Celery belong to "Message Queue" category of the tech stack.
"Open source" is the primary reason why developers consider ActiveMQ over the competitors, whereas "Task queue" was stated as the key factor in picking Celery.
ActiveMQ and Celery are both open source tools. It seems that Celery with 12.9K GitHub stars and 3.33K forks on GitHub has more adoption than ActiveMQ with 1.5K GitHub stars and 1.05K GitHub forks.
According to the StackShare community, Celery has a broader approval, being mentioned in 272 company stacks & 77 developers stacks; compared to ActiveMQ, which is listed in 33 company stacks and 17 developer stacks.
What is ActiveMQ?
What is Celery?
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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
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.
Using Celery, the web service creates tasks that are executed by a background worker. Celery uses a RabbitMQ instance as a task queue.