Basically the same types of uses cases as Kafka and similar systems: event sourcing, CQRS, stream processing (e.g. processing click stream events), data pipelines (e.g. log or metric aggregation used to feed multiple backends), or as a replicated transaction commit log (e.g. use it to create materialized views, populate caches or indexes, etc.). Log compaction means it can do this efficiently by just retaining the current state and discarding older transactions.

https://kafka.apache.org/uses