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In Kafka, topics are partitioned into multiple logs which are then replicated across a number of servers for fault tolerance, making it a distributed commit log.

Outliers aside, we see that the brokered queues have fairly uniform throughputs.

Nanomsg is written by one of the ZeroMQ authors, and as I , works in a very similar way to that library.

- Eventing from other applications to notify a pinpoint refresh is needed for some data into the denormalized store for example, a user updated a setting in their store, which causes a JSON model to update.

Unlike its predecessor, the library also offers a true API which greatly improves performance by allowing memory to be copied from machine to machine while completely bypassing the CPU.

If you are used to random-access data systems, like a database or key-value store, you will generally expect maximum throughput around 5,000 to 50,000 queries-per-second, as this is close to the speed that a good RPC layer can do remote requests.

Fundamental to the notion of a log is a way to globally order events.