Celery vs Kafka

Celery
Celery

814
200
239
Kafka
Kafka

3.1K
4.5K
458
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Celery vs Kafka: What are the differences?

Developers describe Celery 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. On the other hand, Kafka is detailed as "Distributed, fault tolerant, high throughput pub-sub messaging system". Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

Celery and Kafka belong to "Message Queue" category of the tech stack.

"Task queue" is the top reason why over 84 developers like Celery, while over 95 developers mention "High-throughput" as the leading cause for choosing Kafka.

Celery and Kafka are both open source tools. Celery with 12.7K GitHub stars and 3.3K forks on GitHub appears to be more popular than Kafka with 12.5K GitHub stars and 6.7K GitHub forks.

According to the StackShare community, Kafka has a broader approval, being mentioned in 501 company stacks & 451 developers stacks; compared to Celery, which is listed in 271 company stacks and 77 developer stacks.

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.

Want advice about which of these to choose?Ask the StackShare community!

Why do developers choose Celery?
Why do developers choose Kafka?
What are the cons of using Celery?
What are the cons of using Kafka?
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What companies use Kafka?
What are some alternatives to 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.
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.
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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What tools integrate with Celery?
What tools integrate with Kafka?
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      How developers use 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 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.

      How much does Celery cost?
      How much does Kafka cost?
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