Cache Fundamentals
Storing frequently accessed lookup results in memory blocks (RAM) to bypass slow disks.
What you'll learn
- Cache Aside (Lazy Loading)
- Write Through
- Write Behind (Write Back)
- Cache Eviction
TL;DR
Storing frequently accessed lookup results in memory blocks (RAM) to bypass slow disks.
Visual System Topology
Cache Aside Pattern
Concept Overview
Caching stores frequently accessed data in fast storage (usually memory) to avoid expensive operations like database queries or API calls. It's one of the most effective ways to improve performance and reduce load.
Different caching strategies (Cache Aside, Write Through, Write Behind) offer different trade-offs between consistency and performance.
Key Architectural Pillars
Cache Aside (Lazy Loading)
Application checks cache first. On miss, loads from database and updates cache. Most common pattern.
Write Through
Write to cache and database simultaneously. Slower writes but cache always up-to-date.
Write Behind (Write Back)
Write to cache immediately, database asynchronously. Fast writes but risk of data loss.
Cache Eviction
How to remove items when cache is full: LRU (Least Recently Used), LFU (Least Frequently Used), TTL (Time To Live).