caching

What problem does it solve?

Caching reduces latency and database load by storing frequently accessed data in fast storage, enabling apps to serve responses faster and scale more effectively.

Core Features & Use Cases

• Cache-aside patterns for databases and API responses to minimize database load.
• Write-through and write-behind caching to keep caches in sync with storage.
• HTTP cache headers and CDN caching to improve API/CDN performance.
• In-memory memoization and TTL-based caches for quick repeated computations.

Quick Start

To begin, configure a Redis-backed cache or an in-memory cache, choose a TTL strategy, and integrate cache lookups around data fetches. Example: run a Redis instance locally and point your application to the REDIS_URL environment variable.