Redis is best known as a high performance, in-memory, key-value database used for distributed caching. However, data structure databases like Redis, Valkey, and Key DB can do so much more than just operate on string values! With over a dozen different data types like hashes, lists, sets, sorted sets, bloom filters, and streams, these databases provide a number of tools that can help solve common problems.

We’ll explore these basic data structures in Redis and Valkey, with real world examples of using them to solve problems like rate limiting, distributed resource locking, and efficiently checking membership in massive sets of data.

We'll also discuss some of the newer functionality designed for AI and LLM applications, like vector similarity searches and vector sets.