Kafka is a write-ahead log, not a queue per se. It handles transactions to the disk. Not across the network.

RabbitMQ is neat out of the box. But I went with ZeroMQ at the time.

ZeroMQ is cool but during current year I'd only use it to learn from their excellent documentation. Coming from Python, it taught me about Berkeley sockets and the process of building cross-language messaging patterns. After a few projects, it's like realizing I didn't need ZeroMQ to begin with I could make my own! If ZeroMQ's Hintjens were still with us I'd still be using it.

It's like the documented incremental process of designing a messaging queue to fit your problem domain, plus a thin wrapper easing some of lower level socket nastiness. At least that's my experience using it over the years. Me talking about it won't do it enough justice.

NATS does the lower level socket wrapper part very nicely. It's a but more modern too. Golang's designed to be like a slightly nicer C syntax, so it would make sense that it's high performance and sturdy. So it's similar to ZeroMQ there.

I'm not sure if either persist to disk out of the box. So either of these are going to be simpler and faster than Kafka.

The DB people are probably trying too hard to cater to the queues. Ideally I'd have normalized the data and modeled the relations such transactions don't lock up the whole table. Then I started questioning why I needed a queue at all when databases (sans SQLite which is fast enough as is) are made for pooling access to a database.

Kafka supports pipelining to a relational database but this part is where you kind of have to be experienced to not footgun and I'm not at that level. I think using it as a queue in that you're short-circuiting it from the relational database pipeline is non-standard for Kafka. I suspect that's where a lot of the Kafka hate is from. I could understand if the distributed transactions part is hell but at that point it's like why'd you skip the database then? Trying to get that free lunch I assume.

I have an alternative. Try inserting everything into a SQLite file. Running into concurrency issues? Use a second SQLite file. Two computers? send it over the network. More issues? Since it's SQL just switch to a real database that will pool the clients. Or switch to five of them. SQL is sorta cool that way. I assume that would avoid the reimplementing half of the JVM to sync across computers where you get Oracle Java showing up to sell you their database halfway into making your galactic scale software or the whatever.

I must be stressed today. Thanks for asking.