It’s not. Imagine a web app that stores your user information in a session store, mapped by your cookie-provided session ID. Your web app searches redis 1 for the session id, but since that key is on redis 2, the lookup fails and the application thinks there is no such session, and rejects the request.
Now you could solve this specific case by sharding by prefix, or by querying all instances, but then you still do not have high availability: if the instance a specific session is on is down, these users cannot authenticate. At that point you’re better off with a single instance.
But that is his point.
If you cannot find the session id in redis, you login again.
If your Redis server crash, you start a new one and everyone just login again. No data is lost.
No two processes can guarantee data consistency unless using shared memory with some kind of locking on update. And given two servers don't share memory, two processes running on these servers can not guarantee consistency either.
To put the simple terms...
App writes to node-A, node-A (/process on node-A) crashes before change is synced from node-A to node-B, data is lost.
This is true for redis and true for postgresql/ mysql or any similar database. Difference between redis and a "database" is that database protects against this problem by writing change to durable storage before telling app that write is successful. Redis
First up, if I wanted to talk to a machine, I would've asked one myself.
Then, I don't understand your point really: Yes, the CAP theorem is a thing. There are compromise solutions available however to enable highly available data storage. Some of them for Redis too, but they are more complicated than those for other database engines. Which is the point of this discussion.
This discussion is a bit weird. We started off from, Redis should have better availability guarantees. Specifically to avoid the degradation of service you described.
But that requires running on multiple instances, which in turn requires to share the data across all replicas.
> The app would look up in both databases. If it exists in any, there would be a session.
And if you find the session with differing values in both databases, how do you know which one is up-to-date?
You need an algorithm to pick which data is right, such as electing a master instance.
And that brings us back to the original discussion: to manage sessions (unlike caches) in a highly available way, you need to setup HA (or reimplement it, which obviously is a bad idea). You can't read round robin from multiple non-HA instances.