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What is the difference between res.set('Cache-Control', 'no-cache') and 'no-store' in an Express response? What is the difference between in-memory caching (like a Map or node-cache) and a distributed cache (like Redis)? What HTTP caching headers (Cache-Control, ETag) can a Node.js/Express API use to let clients and CDNs cache responses? How would you implement a Least Recently Used (LRU) cache in Node.js, and why is eviction necessary for an in-memory cache? What is memoization, and how does it differ from a general-purpose external cache like Redis? How would you cache the result of a database query in Node.js while ensuring the cache is properly invalidated when the underlying data changes? What is the risk of caching sensitive or user-specific data with a shared cache key, and how do you avoid it? What is negative caching, and why might you deliberately cache the fact that a lookup returned 'not found'? What are the main cache invalidation strategies (TTL, write-through, cache-aside), and when is each appropriate? What is cache stampede (thundering herd), and how do you prevent it in a high-traffic Node.js service?
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Node.js › Caching

What is caching, and why is it commonly used to improve the performance of a Node.js application?

Beginner

Answer

Caching stores the result of an expensive operation (a database query, an API call, a computed value) temporarily, so subsequent requests for the same data can be served from the fast cache instead of repeating the expensive work -- reducing latency for end users and reducing load on downstream systems like databases, which is especially valuable for data that's read far more often than it changes.
const cache = new Map();

async function getUser(id) {
  if (cache.has(id)) return cache.get(id);
  const user = await db.users.findById(id);
  cache.set(id, user);
  return user;
}
Real-world example A product-catalog API that previously queried the database on every request starts serving the vast majority of requests from an in-memory cache instead, since product data changes only a few times a day but is read thousands of times per minute.

Common follow-ups: What's the risk of caching data that changes frequently, and how do you decide what's safe to cache?;What is cache invalidation, and why is it often called one of the two hardest problems in computer science?

Databases & ORMs (MongoDB/Mongoose SQL/Sequelize);Performance Optimization & Profiling
All 15 Caching questions