Actively using KeyDB at work. I would normally agree with you; and for a long time after I initially heard about the project, we hesitated to use it. But the complexity and headaches of managing a
redis-cluster, uh, cluster (on a single machine — which is the idiomatic way to
vertically scale Redis on a single multicore machine...) eventually pushed us over the edge into a proof-of-concept KeyDB deployment.
Conveniently, we don't have to worry about the consistency properties of KeyDB, because we're not using KeyDB distributed, and never plan to do so. We were only using redis-cluster (again, on a single machine) to take advantage of all cores on a multicore machine, and to avoid long-running commands head-of-line blocking all other requests. KeyDB replaces that complex setup with one that's just a single process — and one that doesn't require clients to understand sharding, or create any barriers to using multi-key commands.
When you think about it, a single process on a single machine is a pretty "reliable backplane" as far as CAP theory goes. Its MVCC may very well break under Jepsen — hasn't been tested — but it'd be pretty hard to trigger that break, given the atomicity of the process. Whereas even if redis-cluster has a perfect Jepsen score, in practice the fact that it operates as many nodes communicating over sockets — and the fact that Redis is canonically a memory store, rather than canonically durable — means that redis-cluster can get into data-losing situations in practice for all sorts of silly reasons, like one node on the box getting OOMed, restarting, and finding that it now doesn't have enough memory to reload its AOF file.