How did the semantic cache work in Redis?

Semantic cache in Redis is an approach to caching where keys and values are organized considering the semantic context of the data, rather than just by direct key matching.

For example, if we have database queries with parameters (such as filters or ranges), instead of caching each specific query separately, a semantic cache stores data in a way that allows for partial matches or combining results.

In Redis, this can be implemented through data structures such as hashes, sets, or sorted sets, where keys reflect query parameters, and values are the results. When a new query comes in, the system checks whether it can use already cached data with similar parameters, reducing the number of database accesses.

Example: if a result for the filter "age > 30" is cached, and a request comes in for "age > 35", part of the data from the cache can be used to speed up the response.

Thus, semantic caching increases efficiency by understanding the meaning and structure of data, not just their exact match.