Celery vs Gearman vs RabbitMQ

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Celery
Celery

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+ 1
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Gearman
Gearman

63
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+ 1
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RabbitMQ
RabbitMQ

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3.8K
+ 1
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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 Gearman?

Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.

What is RabbitMQ?

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
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Why do developers choose Celery?
Why do developers choose Gearman?
Why do developers choose RabbitMQ?

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    What tools integrate with Celery?
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    What are some alternatives to Celery, Gearman, and RabbitMQ?
    Kafka
    Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
    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.
    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.
    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.
    MQTT
    It was designed as an extremely lightweight publish/subscribe messaging transport. It is useful for connections with remote locations where a small code footprint is required and/or network bandwidth is at a premium.
    See all alternatives
    Decisions about Celery, Gearman, and RabbitMQ
    James Cunningham
    James Cunningham
    Operations Engineer at Sentry · | 18 upvotes · 214.9K views
    atSentrySentry
    Celery
    Celery
    RabbitMQ
    RabbitMQ
    #MessageQueue

    As Sentry runs throughout the day, there are about 50 different offline tasks that we execute—anything from “process this event, pretty please” to “send all of these cool people some emails.” There are some that we execute once a day and some that execute thousands per second.

    Managing this variety requires a reliably high-throughput message-passing technology. We use Celery's RabbitMQ implementation, and we stumbled upon a great feature called Federation that allows us to partition our task queue across any number of RabbitMQ servers and gives us the confidence that, if any single server gets backlogged, others will pitch in and distribute some of the backlogged tasks to their consumers.

    #MessageQueue

    See more
    Kafka
    Kafka
    RabbitMQ
    RabbitMQ

    The question for which Message Queue to use mentioned "availability, distributed, scalability, and monitoring". I don't think that this excludes many options already. I does not sound like you would take advantage of Kafka's strengths (replayability, based on an even sourcing architecture). You could pick one of the AMQP options.

    I would recommend the RabbitMQ message broker, which not only implements the AMQP standard 0.9.1 (it can support 1.x or other protocols as well) but has also several very useful extensions built in. It ticks the boxes you mentioned and on top you will get a very flexible system, that allows you to build the architecture, pick the options and trade-offs that suite your case best.

    For more information about RabbitMQ, please have a look at the linked markdown I assembled. The second half explains many configuration options. It also contains links to managed hosting and to libraries (though it is missing Python's - which should be Puka, I assume).

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    Frédéric MARAND
    Frédéric MARAND
    Core Developer at OSInet · | 2 upvotes · 103.2K views
    atOSInetOSInet
    Beanstalkd
    Beanstalkd
    RabbitMQ
    RabbitMQ
    Kafka
    Kafka

    I used Kafka originally because it was mandated as part of the top-level IT requirements at a Fortune 500 client. What I found was that it was orders of magnitude more complex ...and powerful than my daily Beanstalkd , and far more flexible, resilient, and manageable than RabbitMQ.

    So for any case where utmost flexibility and resilience are part of the deal, I would use Kafka again. But due to the complexities involved, for any time where this level of scalability is not required, I would probably just use Beanstalkd for its simplicity.

    I tend to find RabbitMQ to be in an uncomfortable middle place between these two extremities.

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    Michael Mota
    Michael Mota
    CEO & Founder at AlterEstate · | 4 upvotes · 51.6K views
    atAlterEstateAlterEstate
    Celery
    Celery
    RabbitMQ
    RabbitMQ
    Django
    Django

    Automations are what makes a CRM powerful. With Celery and RabbitMQ we've been able to make powerful automations that truly works for our clients. Such as for example, automatic daily reports, reminders for their activities, important notifications regarding their client activities and actions on the website and more.

    We use Celery basically for everything that needs to be scheduled for the future, and using RabbitMQ as our Queue-broker is amazing since it fully integrates with Django and Celery storing on our database results of the tasks done so we can see if anything fails immediately.

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    Interest over time
    Reviews of Celery, Gearman, and RabbitMQ
    Review ofRabbitMQRabbitMQ

    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.

    How developers use Celery, Gearman, and RabbitMQ
    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 Cloudify
    Cloudify uses RabbitMQRabbitMQ

    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.

    Avatar of Chris Saylor
    Chris Saylor uses RabbitMQRabbitMQ

    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.

    Avatar of Clarabridge Engage
    Clarabridge Engage uses RabbitMQRabbitMQ

    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.

    Avatar of Analytical Informatics
    Analytical Informatics uses RabbitMQRabbitMQ

    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.

    Avatar of Packet
    Packet uses RabbitMQRabbitMQ

    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.

    Avatar of opening.io
    opening.io uses GearmanGearman

    Internal, distributed message queue. Main communication happens via port 4730 and consists of simple json messages. Completely independent of the main website back-end.

    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.

    How much does Celery cost?
    How much does Gearman cost?
    How much does RabbitMQ cost?
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