Why were two message brokers used in the project — Kafka and RabbitMQ?

Using two message brokers — Kafka and RabbitMQ — in one project is often driven by different requirements for message processing and architectural tasks.

Kafka is well-suited for handling large data streams with high throughput and message history storage. It is an ideal choice for event-driven systems, analytics, logging, and microservices integration, where scalability and resilience are important.

RabbitMQ, on the other hand, handles queue tasks with delivery confirmation, message routing, and support for complex exchange patterns (e.g., RPC, pub/sub). It is convenient for synchronous or semi-synchronous processes where guaranteed delivery and flexible routing are crucial.

Thus, in a project, Kafka can be used for stream processing and event storage, while RabbitMQ manages tasks, queues, and interactions between services with more strict delivery requirements.

Example: an order processing system where Kafka collects and stores all order events, and RabbitMQ manages task queues for processing and confirmation.