When and how do you use Kafka and RabbitMQ — what is the difference?

Kafka and RabbitMQ are message exchange systems, but they are designed for different scenarios and have different architectural features.

Kafka:

• Suitable for processing large data streams (event streaming).
• Uses a publish-subscribe model with message storage in topics on disk.
• Allows consumers to read messages from a specific position, supports re-reading.
• High performance and scalability.
• Used for analytics, logging, and integrating microservices with large data volumes.

RabbitMQ:

• Traditional message broker supporting various exchange models (queues, topics, routing).
• Messages are deleted after delivery (by default).
• Supports complex routing schemes and delivery guarantees.
• Good for tasks with guaranteed delivery, task queues, load distribution.

When to use:

• If you need to process large volumes of events with re-reading and scaling capabilities — Kafka.
• If you need a reliable message queue with flexible routing and delivery confirmation — RabbitMQ.

Example usage in Python with the kafka-python library for Kafka and pika for RabbitMQ.