Kafka Vs RabbitMQ
Kafka is more suitable for event streaming, pubsub whereas RabbitMQ is suitable for standard messaging work
Let's assume that both Kafka and RabbitMQ we setup 1 queue to evaluate how they can scale
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As we can see that with only 1 queue, RabbitMQ only can have 1 worker at a time process the message since they will delete afterwards. If we want to scale multiple worker, we need multiple queue.
| Feature | RabbitMQ | Apache Kafka |
|---|---|---|
| Best For | Background tasks & simple microservices. | High-speed data streams & event history. |
| Data Retention | Ephemeral: Deleted after it is read. | Durable: Stored on disk for days or years. |
| Throughput | ~4k – 10k messages per second. | 1 Million+ messages per second. |
| Message Replay | No (Except for modern "Stream Queues"). | Yes: Native "rewind and replay" ability. |
| Routing | Complex: High flexibility (headers, keys). | Simple: Based on Topics/Partitions. |
| Model | Push: Broker sends data to you. | Pull: You ask the broker for data. |
| Scalability | Vertical & Horizontal (moderate). | Extreme: Massively horizontal via partitions. |
Scaling
RabbitMQ scale by adding more node/cluster
Kafka scaling by adding more partition