What caching strategies should a backend engineer know?

A cache trades freshness and complexity for latency and load reduction. The right strategy depends on read and write patterns, how stale data can be and whether a miss storm would overwhelm the origin.

The common patterns

• Cache-aside: the application reads the cache, loads on a miss and writes the result back
• Read-through: the cache layer loads from the origin on a miss
• Write-through: writes go to the cache and the origin together, favoring consistency
• Write-behind: writes go to the cache and are flushed to the origin later, risking data loss
• Layered caches: browser, CDN, application memory and a shared store such as Redis
• Negative caching: store not-found results briefly to stop repeated misses

async function getUser(id) {
  const key = "user:" + id;
  const cached = await redis.get(key);
  if (cached) return JSON.parse(cached);

  const user = await db.user.findUnique({ where: { id } });
  if (user) {
    await redis.set(key, JSON.stringify(user), { EX: 300 });
  }

  return user;
}

Every cache needs a policy for misses. If many requests miss the same key at once, they all hit the database. Add a short lock, a single-flight mechanism or TTL jitter to prevent a stampede. Also decide what happens when the cache is unavailable: serving from the origin is often better than failing the request.