ActiveMQ
ActiveMQ

177
200
39
Celery
Celery

837
494
239
Kafka
Kafka

3.2K
2.5K
459

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.

What is Kafka?

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

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    What are some alternatives to ActiveMQ, Celery, and Kafka?
    RabbitMQ
    RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
    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.
    NSQ
    NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.
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    How developers use ActiveMQ, Celery, and Kafka
    Avatar of Pinterest
    Pinterest uses KafkaKafka

    http://media.tumblr.com/d319bd2624d20c8a81f77127d3c878d0/tumblr_inline_nanyv6GCKl1s1gqll.png

    Front-end messages are logged to Kafka by our API and application servers. We have batch processing (on the middle-left) and real-time processing (on the middle-right) pipelines to process the experiment data. For batch processing, after daily raw log get to s3, we start our nightly experiment workflow to figure out experiment users groups and experiment metrics. We use our in-house workflow management system Pinball to manage the dependencies of all these MapReduce jobs.

    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 Coolfront Technologies
    Coolfront Technologies uses KafkaKafka

    Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.

    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.

    Avatar of ShareThis
    ShareThis uses KafkaKafka

    We are using Kafka as a message queue to process our widget logs.

    Avatar of Christopher Davison
    Christopher Davison uses KafkaKafka

    Used for communications and triggering jobs across ETL systems

    Avatar of theskyinflames
    theskyinflames uses KafkaKafka

    Used as a integration middleware by messaging interchanging.

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