zlacker

"Low overhead"? Redis.

Reliable and durable? Emphatically not Redis, and at that point you probably want to just start looking at SQS.

(I've had good luck shipping products as docker-compose files, these days. Even to fairly backwards clients.)

>>eroppl+(OP)
I guess I didn't make it clear. Solution has to work in-house / in private cloud.

>>eroppl+(OP)
Can you explain why Redis is not durable? Looking into it for a project but this comment worries me.

>>tjanks+32
Intentionally so. It's not a deficiency or a footgun, it's a design decision to be aware of. Redis is an in-memory database first.

You can configure Redis for durability. The docs[1] page for persistence has a good examination of the pros and cons.

[1]: https://redis.io/topics/persistence

>>tjanks+32
In my experience Redis is plenty durable (especially in Elasticache with replicas + multi-region + backups). Redis _is_ an in-memory data store, so if the server crashes, you lose the data, but if you have replicas it'll fail over, if you have backups you can restore, and if you have multi-region you can failover to the other region. IMO, the idea that Redis is not durable enough is outdated.

It's something to be aware of and to have backup plans for, but we've been using Redis as our primary datastores for over a year with only one or two instance failures which were quickly resolved within minutes by failing over to replicas, with no data loss.

>>Jemacl+qe
Redis won't lose data from just a server crash. It has persistence with streaming AOF mode and snapshot RDB mode, and they can be combined. fsync is also configurable. It can be set to write every operation to disk but most set it to every 1 second which is safe enough with replicas.

>>chucks+xb
antirez put a lot of work in around Redis 3.0 (iirc) to make the persistence reliable and strong. As long as your server is configured and used correctly (obviously a large caveat, but you can only hold someone's hand so much), I don't think there is any reason to doubt Redis's persistence anymore.

It's important to make this distinction because there are commonly-used systems that offer a best-effort style persistence that usually works fine, but explicitly warn developers not to trust it, and developers rarely understand that.

We badly need to get better at distinguishing between true, production-level data integrity and "probably fine".