Kafka, on the other hand, is a queuing system that was first developed by LinkedIn for its own internal purposes. It is written in Scala and is designed from the ground up for horizontal scalability and the best performance possible.

Focusing on performance is a key differentiator for Apache Kafka, but it means that in order to achieve performance, we need to sacrifice something. Messages in Kafka don't hold unique IDs, but are addressed by their offset in the log. Apache Kafka consumers are not tracked by the system; it is the responsibility of the application design to do so. Message ordering is implemented at the partition level and it is the responsibility of the consumer to identify if a message has been delivered already.

Semantics were introduced in version 0.11 and are part of the latest 1.0 release so that messages can now be both strictly ordered within a partition and always arrive exactly once for each consumer: