Redis vs RocksDB

They have nothing in common. You are trying to compare apples and oranges here.

Redis is a remote in-memory data store (similar to memcached). It is a server. A single Redis instance is very efficient, but totally non scalable (regarding CPU). A Redis cluster is scalable (regarding CPU).

RocksDB is an embedded key/value store (similar to BerkeleyDB or more exactly LevelDB). It is a library, supporting multi-threading and a persistence based on log-structured merge trees.

While Didier Spezia's answer is correct in his distinction between the two projects, they are linked by a project called LedisDB. LedisDB is an abstraction layer written in Go that implements much of the Redis API on top of storage engines like RocksDB. In many cases you can use the same Redis client library directly with LedisDB, making it almost a drop in replacement for Redis in certain situations. Redis is obviously faster, but as OP mentioned in his question, the main benefit of using RocksDB is that your dataset is not limited to the amount of available memory. I find that useful not because I'm processing super large datasets, but because RAM is expensive and you can get more milage out of smaller virtual servers.