Kafka versus traditional message brokers.

Official answer

Compare specific products and modes rather than treating every “traditional broker” as one design.

Kafka's usual model is a retained partition log with consumer-controlled positions and independent consumer groups. Reading does not delete a record. It fits replayable event streams, data integration and multiple downstream projections. Ordering is per partition, and retention/compaction determine which history remains.

A queue-oriented RabbitMQ or ActiveMQ design commonly focuses on routing work to consumers with individual acknowledgement/redelivery and queue lifecycle controls. This can fit task dispatch, routing patterns and workflows needing broker-specific priority or expiry features. The exact capabilities depend on the selected queue type and product/version. RabbitMQ also has replicated streams and partitioned super streams, so retained logs and replay are not exclusive to Kafka.

Neither category automatically makes an external payment or database update exactly once. Acknowledgement, redelivery, transactions and idempotency must be evaluated at the application-effect boundary. Strict order, competing consumers and retries can also conflict unless the design defines the ordering domain.

Benchmark representative payloads, fan-out, backlog, durability settings, replication and failure/recovery. Kafka is not universally faster, nor is another broker universally lower latency or more reliable. Include operating cost, client support, routing needs and replay requirements. Choose the mode whose semantics solve the workflow with manageable complexity.

Kafka consumer contract, RabbitMQ streams, RabbitMQ acknowledgements, ActiveMQ Artemis address model