RabbitMQ and Apache Kafka are both open-source distributed messaging systems, but they have different strengths and weaknesses. Kafka is a purely distributed log designed for efficient event streaming at a high scale, while RabbitMQ is a traditional messaging system designed for quick message publishing and deletion.
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The following table compares the performance of RabbitMQ and Kafka in terms of throughput, latency, and scalability:
|Millions of messages per second
|Billions of messages per second
|Horizontal scaling is possible but can be complex
|Horizontal scaling is easy and efficient
The following graph compares the throughput of RabbitMQ and Kafka under different workloads:
As you can see, Kafka has significantly higher throughput than RabbitMQ, especially under high load.
The following graph compares the latency of RabbitMQ and Kafka:
As you can see, RabbitMQ has slightly lower latency than Kafka. However, the difference in latency is very small, and it is unlikely to be noticeable in most applications.
While RabbitMQ and Apache Kafka may appear similar from a high level, they each have specific use cases where they excel. In some cases and circumstances companies end up using both for each of their strengths. That is one of the main reasons why there is an official RabbitMQ source connector for Kafka.
If you are looking for a system with low latency, supports complex routing, is relatively lightweight, and works well for microservice communication you want to go with RabbitMQ. However, if you are looking for real-time data streaming, integrating multiple sources, stream processing, large volumes of data, or permanent message storage you’d want to select Apache Kafka.