Async Processing: Kafka & RabbitMQ
Quick Reference: Pub/Sub Model
Quick Reference
| Feature | Kafka | RabbitMQ |
|---|---|---|
| Type | Distributed log | Message broker |
| Throughput | Very high (millions/sec) | High (thousands/sec) |
| Latency | Higher (batch) | Lower (real-time) |
| Durability | Persistent log | Optional |
| Use Case | Event streaming, logs | Task queues, routing |
Clear Definition
Kafka is a distributed event streaming platform optimized for high throughput. RabbitMQ is a message broker optimized for routing and reliability. Both enable asynchronous processing and decouple system components.
š” Key Insight: Kafka for high-throughput event streaming, RabbitMQ for reliable message routing and task queues.
Core Concepts
Kafka
- Topics: Streams of records
- Partitions: Topics split into partitions for parallelism
- Producers: Write to topics
- Consumers: Read from topics
- Brokers: Kafka servers
RabbitMQ
- Exchanges: Route messages to queues
- Queues: Hold messages
- Bindings: Connect exchanges to queues
- Routing: Direct, topic, fanout, headers
Use Cases
Kafka
- Event Streaming: User activity, logs
- Data Pipeline: ETL processes
- Real-time Analytics: Stream processing
RabbitMQ
- Task Queues: Background jobs
- Message Routing: Complex routing needs
- Reliable Delivery: Guaranteed delivery
Best Practices
- Choose Based on Needs: Kafka for streaming, RabbitMQ for queues
- Handle Failures: Implement retries and dead letter queues
- Monitor: Track message rates and lag
Quick Reference Summary
Kafka: High-throughput event streaming platform.
RabbitMQ: Reliable message broker for task queues and routing.
Key: Kafka for streaming, RabbitMQ for queues.
Next Topic: Pub/Sub Model ā
Back to: Step 7 Overview | Main Index