Kafka vs RabbitMQ: What are the differences?
Kafka: 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; RabbitMQ: A messaging broker - an intermediary for messaging. RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
Kafka and RabbitMQ can be categorized as "Message Queue" tools.
Some of the features offered by Kafka are:
- Written at LinkedIn in Scala
- Used by LinkedIn to offload processing of all page and other views
- Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled)
On the other hand, RabbitMQ provides the following key features:
- Robust messaging for applications
- Easy to use
- Runs on all major operating systems
"High-throughput" is the top reason why over 95 developers like Kafka, while over 203 developers mention "It's fast and it works with good metrics/monitoring" as the leading cause for choosing RabbitMQ.
Kafka and RabbitMQ are both open source tools. It seems that Kafka with 12.7K GitHub stars and 6.81K forks on GitHub has more adoption than RabbitMQ with 5.94K GitHub stars and 1.78K GitHub forks.
reddit, 9GAG, and Rainist are some of the popular companies that use RabbitMQ, whereas Kafka is used by Uber Technologies, Spotify, and Slack. RabbitMQ has a broader approval, being mentioned in 940 company stacks & 548 developers stacks; compared to Kafka, which is listed in 509 company stacks and 470 developer stacks.
What is Kafka?
What is RabbitMQ?
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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.
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.
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.
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.
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.
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.
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.
Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.