go-cache-caching

Type-safe caching in Go uses generic Cache[T] APIs to unify memory, Redis, SQLite, and PostgreSQL backends. This enforces compile-time type safety while allowing pluggable codecs and multi-layer backfill chaining to reduce latency and database load.

The cache loader pattern in Go reduces database load by using cache-aside semantics for on-demand loading. When a cache miss occurs, the loader automatically fetches data from the backend, populates the cache, and returns the result without manual get-set logic.

Yes, batch operations for Redis and SQLite are supported to minimize network round-trips. The library enables bulk reads and writes across all configured stores, while SQLite and PostgreSQL also offer iterable store support for processing large datasets efficiently.

Yes, Go generics enable a type-safe Cache[T] API where you can plug in JSON, MessagePack, or Gob codecs. This zero-dependency approach serializes and deserializes cached objects cleanly across memory, Redis, SQLite, and PostgreSQL backends.

Multi-layer caching in Go handles background cleanup through automated store maintenance tasks and achieves safe concurrency using MVCC-like benefits. This ensures predictable cache performance and prevents race conditions during high-volume reads and writes.

Use PostgreSQL or SQLite for caching when you need iterable stores and persistent disk-backed storage, whereas Redis or memory stores suit ultra-fast, volatile workloads. Multi-layer backfill chaining allows combining them for predictable latency and reduced database load.