ActiveMQ
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Celery

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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?

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.

What is Celery?

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.

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    What tools integrate with ActiveMQ?
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    What are some alternatives to ActiveMQ and Celery?
    RabbitMQ
    RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
    Kafka
    Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
    Apollo
    Build a universal GraphQL API on top of your existing REST APIs, so you can ship new application features fast without waiting on backend changes.
    Amazon SQS
    Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.
    ZeroMQ
    The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.
    See all alternatives
    Decisions about ActiveMQ and Celery
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    How developers use ActiveMQ and Celery
    Avatar of Kalibrr
    Kalibrr uses CeleryCelery

    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.

    Avatar of Cloudify
    Cloudify uses CeleryCelery

    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.

    Avatar of MOKA Analytics
    MOKA Analytics uses CeleryCelery

    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

    Avatar of Yaakov Gesher
    Yaakov Gesher uses CeleryCelery

    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.

    Avatar of Dieter Adriaenssens
    Dieter Adriaenssens uses CeleryCelery

    Using Celery, the web service creates tasks that are executed by a background worker. Celery uses a RabbitMQ instance as a task queue.

    Avatar of Casey Smith
    Casey Smith uses ActiveMQActiveMQ

    Remote broker and local client for incoming data feeds. Local broker for republishing data feeds to other systems.

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