[sbellware]

Or managed Postgres on AWS Aurora, AWS RDS, Google Cloud SQL, Heroku, etc :)

SNS, Kenesis (Kafka), Google Pub/Sub are awesome. Not the same problem/solution fit as an event store, but awesome for the scenarios and architectures they're targeted at.

[ziftface]

Is there a difference from a programming perspective between, say Kafka, and the event store linked in this post?

I understand that Kafka can scale horizontally and can handle crazy throughput, but I mean from a programming point of view, the idea of a unified log as a data model applies to both, correct?

[ethangarofolo]

There are some similarities, and there are definitely worse technologies you could choose for a message store than Kafka. It's worth calling out the difference between event-sourced and event-based. The former is necessarily the latter, but that doesn't go in the opposite direction.

Event-based just means that communication happens over events. Event-sourced means that the authoritative state of the system is sourced from events. If the events are literally the state, then how those are retrieved begins to matter.

Kafka breaks down as a message store in 2 key ways that I mentioned elsewhere in all these threads.

> The first is that one generally has a separate stream for each entity in an event-sourced system. Streams are sort of like topics in Kafka, but it would be quite challenging to, say, make a topic per user in Kafka. The second is Kafka's lack of optimistic concurrency support (see https://issues.apache.org/jira/browse/KAFKA-2260). The decision to not support expected offsets makes perfect sense for what Kafka is, but it does make it unsuitable for event sourcing.

If my only tool were Kafka, then I wouldn't be able to use the messages in the same way that I can with something like Message DB. And that's okay, different tools for different jobs.