Kafka vs RabbitMQ vs SQS vs Redis Streams

Side by side

Criterion	Kafka	RabbitMQ	SQS / SNS	Redis Streams
Model	Log	Queues + exchanges	Queue + pub/sub	Log in memory
Replay	Yes	Limited	No	Until trimmed
Ordering	Per partition	Per queue	FIFO per group (FIFO queues)	Per stream
Per-message ack/retry	Offsets (batch)	Yes	Yes (visibility timeout)	Yes (PEL)
Delays / priorities	No	Yes	Delay ≤ 15 min	Manual
Ops burden	High (unless managed)	Medium	None	Low
Throughput	Very high	High	Very high (standard)	High

When to choose each

Kafka

Partitioned, replicated, replayable log.

Choose when

Event streaming between many services
Replay and long retention
Very high throughput

Avoid when

Priority/delayed job queues
Small teams without managed Kafka

RabbitMQ

Broker with exchanges, queues, per-message acks.

Choose when

Task queues with routing
Priorities, TTLs, dead-letter exchanges

Avoid when

Replaying history
Massive fan-out streams

SQS / SNS

Fully managed queues and fan-out (AWS).

Choose when

Decoupling on AWS with zero ops
Background jobs at any scale

Avoid when

Replay
Strict ordering at high throughput (FIFO limits)

Redis Streams

Append-only streams in Redis with consumer groups.

Choose when

Lightweight streams where Redis already runs
Low latency

Avoid when

Large retained histories (memory)
Strong durability needs without AOF tuning

Use Kafka (managed if possible) for event streams and replay, RabbitMQ or SQS for job/task queues, and Redis Streams for lightweight cases when Redis is already core infrastructure. Many architectures combine a stream for events with queues per consumer.

Kafka vs RabbitMQ vs SQS vs Redis Streams

Side by side

When to choose each

Kafka

RabbitMQ

SQS / SNS

Redis Streams

Verdict

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Sources