Redis in-memory store
Following are the key areas of differences between YugaByte DB and Redis in-memory store.
Persistent DB vs. in-memory cache
YugaByte DB’s Redis is a persistent database rather than an in-memory cache. [While Redis has a check-pointing feature for persistence, it is a highly inefficient operation that does a process fork. It is also not an incremental operation; the entire memory state is written to disk causing serious overall performance impact.]
Auto-sharded and clustered
YugaByte DB’s Redis is an auto-sharded, clustered with built-in support for strongly consistent replication and multi-DC deployment flexibility. Operations such as add node, remove node are simple, throttled and intent-based and leverage YugaByte’s core engine (YBase) and associated architectural benefits.
No explicit memory management
Unlike the normal Redis, the entire data set does not need to fit in memory. In YugaByte, the hot data lives in RAM, and colder data is automatically tiered to storage and on-demand paged in at block granularity from storage much like traditional database.
Consistent and transparent caching
Applications that use Redis only as a cache and use a separate backing database as the main system of record, and need to deal with dev pain points around keeping the cache and DB consistent and operational pain points at two levels of infrastructure (sharding, load-balancing, geo-redundancy) etc. can leverage YugaByte DB’s Redis as a unified cache + database offering.
Scan resistant block cache design ensures long scan (e.g., of older data) do not impact reads for recent data.