Kafka and RabbitMQ are two popular choices for message brokers, which are middleware applications that facilitate the exchange of data between different systems. But how do you decide which one is better suited for your needs? In this article, we will compare and contrast some key features and use cases of Kafka and RabbitMQ, and help you make an informed decision.
A message broker is a software that acts as an intermediary between producers and consumers of messages, which are units of data that carry information. A message broker allows different systems to communicate with each other without having to know the details of their protocols, formats, or locations. A message broker can also provide features such as routing, filtering, buffering, transformation, and delivery guarantees.
In my experience message broker use case mainly to introduce asynchrony in the distributed systems, so if a set of system sharing messages between them and one or multiple system goes offline; message brokers help to resume the processing of messages while the offline system are coming back or start to consume with there sweet time.
Kafka is a distributed streaming platform that can handle high volumes of data in real time. It is based on a publish-subscribe model, where producers publish messages to topics, and consumers subscribe to topics and consume messages. Kafka can store messages in a durable and scalable way, and also supports stream processing and analytics. Kafka is designed for high throughput, low latency, and fault tolerance.
Here to observe the how and where Kafka architecture differs with traditional messaging systems. The Kafka's main architecture differences are introducing partitions and keeping those partition data with in a replicated append only log systems per partitions, which gives Kafka subscribers to concurrently subscribe messages with different partitions point which introduce high throughput and low latency. But gives up order processing of messages. All the man made engineering system int this world has tradeoffs :).
RabbitMQ is a message broker that implements the Advanced Message Queuing Protocol (AMQP), which is a standard for messaging interoperability. It is based on a broker-queue model, where producers send messages to exchanges, and consumers receive messages from queues. RabbitMQ can route messages based on various criteria, such as routing keys, headers, or patterns. RabbitMQ is designed for flexibility, reliability, and ease of use.
The AMQP protocol has been evolved a lot from traditional messaging protocols like mq or jms. The traditional ones supported XA. Btw this kind of reliability still there in Rabbitmq with the same tradeoffs as traditional reliable messaging systems. But with the popularity of micro-services, multi-system extended architecture (XA) of transaction people started to avoid for high latency and low availability. So if the system requirement is between two micro-service communication (and services are following SAGA pattern) then two phase transaction is enough ( not XA) for reliability which RabbitMQ provides very nice way, and it also provides complete ordering of messages with trades offs to given up concurrency and latency requirements.
Kafka and RabbitMQ have distinct architectures, strengths, and weaknesses. Kafka is designed for high performance and scalability, while RabbitMQ is tailored for flexibility and reliability. Kafka utilizes a pull-based model, where consumers fetch messages from brokers at their own speed, while RabbitMQ uses a push-based model, where brokers deliver messages to consumers as they arrive. Additionally, Kafka retains messages until they are consumed or expired, whereas RabbitMQ discards messages once they are delivered or rejected. Furthermore, Kafka has a simpler and more consistent API compared to RabbitMQ's richer and more diverse API. Finally, Kafka supports stream processing and analytics, while RabbitMQ supports RPC and request-reply patterns.
Kafka combines elements of both push and pull models, while RabbitMQ primarily uses a push model. Kafka is often used for event streaming, while RabbitMQ is commonly used for traditional messaging scenarios.
When deciding between Kafka and RabbitMQ, it’s important to consider the amount of data you need to process and store, how fast you need to process and deliver data, how reliable and durable you need your data to be, the complexity of your routing and filtering rules, and your familiarity with the technologies and protocols involved.
reliability and message order is the choice in RabbitMQ and high concurrency and low latency is the choice in Kafka. I feel like choosing a messaging system is depends on what are the non functional requirement and performance number we want to go for.
Kafka and RabbitMQ both have their own use cases and scenarios where they excel. For example, Kafka is ideal for streaming data pipelines, like log aggregation, event sourcing, or IoT applications, as it can ingest, process, and analyze large amounts of data in real time. On the other hand, RabbitMQ is ideal for integration and orchestration of different systems and services, such as microservices, workflows, or messaging applications.