The Core Concept

A cache is a fast, temporary storage layer that serves repeated requests without hitting the slow origin. The origin might be a database, an external API, or a computation-heavy function. Caching trades storage for speed.

Cache Hit vs Cache Miss

A cache hit occurs when requested data is in the cache — response time is microseconds. A cache miss occurs when it is not — the system fetches from origin, stores the result, then responds. Your goal is maximizing the hit ratio.

# Redis cache-aside example
const cached = await redis.get(`user:${id}`);
if (cached) return JSON.parse(cached);

const user = await db.query('SELECT * FROM users WHERE id = $1', [id]);
await redis.setex(`user:${id}`, 3600, JSON.stringify(user));
return user;

When Not to Cache

Caching adds complexity: stale data, invalidation bugs, and cold-start problems. Avoid caching when data changes on every request, when accuracy is critical (financial balances, inventory counts), or when the fetch is already fast. Cache read-heavy, slow-to-compute, or expensive-to-fetch data. The 80/20 rule applies: 20% of your data is requested 80% of the time — those are your cache candidates.