How much latency could you really be saving versus introducing complexity?
But I am not a storage/backend engineer, so maybe I don't understand the target use of Redis.
We use it to broadcast messages across horizontally scaled services.
Works fine, probably a better tool out there for the job with better delivery guarantees, but the decision was taken many years ago, and no point in changing something that just works.
It's also language agnostic, which really helps.
We use ElasticCache (Valkey i suppose), so most of the articles points are moot for our use.
Were we to implement it from scratch today, we might look for better delivery guarantees, or we might just use what we already know works.
Redis also scales horizontally much, much easier because of the lack of relational schemas. Keys can be owned by a node without any consensus within the cluster beyond which node owns the key. Distributed SQL needs consensus around things like "does the record this foreign key references exist?", which also has to take into account other updates occurring simultaneously.
It's why you see something like Redis caching DB queries pretty often. It's way, way easier to make your Redis cluster 100x as fast than it is to make your DB 100x as fast. I think it's also cheaper in terms of hardware, but I haven't done much beyond napkin math to validate that.
If you've got to store 5 GB videos, maybe reach for object store instead of postgres. But for most uses postgres is a solid choice.