[datalopers]

Keep in mind the context of this thread. It's some shitty blog suggesting you do every fuck thing on postgres. Myself and the other guy are simply suggesting that running a single-node instance of redis is an infinitely better and simpler choice than implementing a cache or a job queue on a rdbms.

I don't feel designing for a guaranteed high-availability application was part of the discussion at all.

[maxbond]

If you don't find it applicable, feel free to discard what I'm saying, I take no offense. But I just don't quite understand your perspective. Maybe I have oncall firefighter brain rot, but a distributed job queue is exactly the sort of thing I'd want to be available, and a cache is something I regard as being very dangerous and requiring utmost care.

[tekknik]

You use SQS, couple clicks and you’re done. You shouldn’t be using a cache for a queue. You use a queue for a queue.

[julik]

Yes, mostly. There are a few things to take into account though:

- No multiple queues - No priorities - Practically no scheduling (the delay is very limited) - Creating and tearing down a queue takes a lot of time and the number of queues is subject to AWS account limits - The FIFO/LIFO semantics (remember about no priorities?) will bite you when you least expect

It does have great durability unlike Redis though and will scale to much, much larger queues in an easier way.

[maxbond]

Not disagreeing, but purely for interest, Redis contains a queue-like primitive.

https://redis.io/docs/data-types/streams/

You can make good job queues out of this, combined with sharding or consistent hashing, for low(ish) latency applications. Each shard has a stream, they operate on data stored in Redis, and you pass them the key to this data over their stream.

But SQS is great, and a great rebuttal to the article. Totally easier to prototype a job queue that way than with pg, and you probably won't need to move off of it.

[julik]

I have used both SQS and PG-based queues and for the smaller workloads/smaller systems (read: "not very very large systems") I now prefer the latter. There is also a non-trivial amount of stuff that we turned out to need for operating SQS at scale on the application side, basically to compensate for the things SQS does not have. It is great it doesn't have those things, but if you have a smaller application you might want to have those things instead and sacrifice a bit of scalability.

[maxbond]

The advantage being that you could sort things to implement priorities and such? Did you use listen()/notify() at all?

ETA: seeing your list of missing features now, that all makes a lot of sense. In my mind the biggest advantage of SQS is that it glues together all the other AWS offerings, so you can go AWS -> Lambda for an instant job queue (with concurrency limits, etc. so you don't blow your hand off - perhaps undermining the simplicity argument). But everything you're saying makes sense if your job queue needs any degree of sophistication.

[tekknik]

Sure, but you still need to run redis vs click a couple of buttons and create a queue, offloading the entire management to AWS staff.

[datalopers]

Redis isn’t just a cache. That’s memcached. Also SQS absolutely sucks for a job queue as soon as you want to do anything like control concurrency or have job priorities, but if your needs are simply “I need a background job queue” then SQS is likely a great choice.