Are you the one looking out for the best messaging tools? Have you heard about RabbitMQ and Apache Kafka? Confused about what to choose? Ksolves can make it easier for you. How? Let us see.
Apache Kafka and RabbitMQ come with different architectures and approaches. Apache Kafka is the most popular event streaming system and known to be fast, but when we compare it with traditional message brokers like RabbitMQ, there are many aspects that make it a really hard choice. While choosing the wrong option will only add to your problems. So what to do? Sit back and read this article.
Here, we will look at the evaluation criteria and provide you with a decision so that you can choose the best option for your unique solutions.
What is Apache Kafka and RabbitMQ?
Apache Kafka and RabbitMQ are open-source pub-sub systems That are adopted by many big enterprises.
Apache Kafka is an open-source distributed event streaming platform written in Java and Scala. It is a message bus developed for high-ingress data streams. It is a durable message broker that helps applications to process, store and re-process streamed data. Kafka has a routing key to send messages to a topic.
RabbitMQ is an open-source distributed message broker that efficiently delivers messages in complex routing scenarios. It is a general-purpose message broker and supports protocols like MQTT, AMQP, and STOMP. It usually deals with high throughput use cases and acts as a message broker for microservices.
Apache Kafka vs RabbitMQ: Architecture
- General-purpose message broker- It uses request/reply variations, offers point-to-point and pub-sub communication patterns.
- Smart broker/dumb consumer model- It offers consistent message delivery to consumers at almost the same speed at which the broker monitors the consumer state.
- A mature platform- It has a well-supported mature platform that is available for Java, client libraries, .NET, Ruby, etc, and offers many plugins.
- Communication- It offers synchronous as well as asynchronous communication.
- Deployment- It offers a distributed deployment scenario.
- Multi-node cluster- It does not rely on external services.
Apache Kafka Architecture
- High-volume Pub-sub message and streaming platform- It is durable, fast, and scalable.
- Message store- Messages are stored like a log and run in a server cluster.
- Messages- They are made of a value, a key, and a timestamp.
- Dumb broker/smart consumer model- It does not track the read messages of the consumers and keeps unread messages. It stores messages for a period of time.
- Require external services- Sometimes it uses Apache Zookeeper.
Apache Kafka vs RabbitMQ Approach
Apache Kafka’s pull approach
Kafka works on a pull model where consumers request batches of messages from an offset. Kafka allows long pooling and prevents tight loops when there is no message.
Kafka has partitions and that is why the pull model is perfect. It also allows users to leverage the batching of messages to get higher-throughput.
RabbitMQ’s push approach
RabbitMQ on the other hand uses a push-based model and can be used for low latency messaging. The goal of the push model here is to distribute messaging quickly. It also ensures that the work is parallelized and messages are processed in the same order in which they arrive.
Apache Kafka vs RabbitMQ: Handling messaging
Kafka and RabbitMQ both have different ways of handling messages. Let’s have a look-
Kafka offers message ordering due to its partitions. On the other hand, Message ordering is not supported in RabbitMQ.
Kafka is a log and hence all the messages are always there. One can manage this by a message retention policy. RabbitMQ is a queue and once messages are consumed, they are no longer there.
In partition, Apache Kafka guarantees that the complete batch of processes either fails or passes. RabbitMQ, on the other hand, does not guarantee atomicity.
Apache Kafka vs RabbitMQ: Performance
Apache Kafka’s performance
When it comes to performance, Apache Kafka is way ahead of any message brokers like RabbitMQ. Since it uses sequential disk I/O for boosting performance, it is a suitable option for implementing queues. Kafka can process millions and trillions of messages per second with less resources and that is why it is the favorite for big data use cases.
Like Kafka, RabbitMQ can also process millions of messages per second but with much more resources. RabbitMQ can be used for use cases similar to Kafka but you will have to combine it with other tools like Apache Cassandra.
Requirements and use cases
Apache Kafka is designed for stream processing. Recently, Kafka has added Kafka streams, client library and microservices. There are many use cases handled by Kafka such as- activity tracking, stream processing, log aggregation, metrics, event sourcing, and many more.
RabbitMQ is usually used when web servers need to respond quickly to requests. This also allows you to eliminate the need to perform resource-intensive activities. Through RabbitMQ you can convey a message to various recipients to share the load or for consumption.
Apache Kafka vs RabbitMQ: What should you choose?
In this article, we have tried to cover all the differences between Kafka and RabbitMQ so that it becomes easier to choose. Although both can consume several messages per second, Kafka is a better choice. It is fast, scalable, and demands less hardware as compared to RabbitMQ. Also, as stated earlier, Kafka’s performance is much better than RabbitMQ and is a good choice for big data applications and many other real-time applications.
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