Build a caching system that stores frequently accessed data in memory or Redis, reducing database queries and improving application performance.

Project Checklist

• Implement in-memory cache with TTL (time-to-live)
• Create cache get, set, and delete operations
• Add cache key generation strategy
• Implement cache invalidation on data updates
• Add cache statistics tracking
• Handle cache misses gracefully

Bonus Project Checklist Items

• Integrate Redis for distributed caching
• Implement cache warming strategies
• Add cache compression for large values
• Create cache hit/miss metrics
• Implement cache versioning
• Add cache preloading for critical data

Inspiration (Any companies/libraries similar)

• Redis
• Memcached
• Varnish

Hint/Code snippet to start

const cache = new Map();

function getCacheKey(key) {
  return `cache:${key}`;
}

async function get(key) {
  const cacheKey = getCacheKey(key);
  const cached = cache.get(cacheKey);
  if (cached && cached.expires > Date.now()) {
    return cached.value;
  }
  cache.delete(cacheKey);
  return null;
}

async function set(key, value, ttl = 3600) {
  const cacheKey = getCacheKey(key);
  cache.set(cacheKey, {
    value,
    expires: Date.now() + ttl * 1000
  });
}