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Introduction to Redis Caching Strategies

By TechLog Admin 1 min read
Redis

Redis Caching Strategies

Redis is an incredibly versatile cache store. Choosing the right caching strategy is crucial for application performance.

Common Strategies

Cache-Aside (Lazy Loading)

The application checks the cache first, then falls back to the database: 
def get_user(user_id):
    user = redis.get(f"user:{user_id}")
    if user:
        return user
    user = db.query(User).get(user_id)
    redis.setex(f"user:{user_id}", 3600, user)
    return user

Write-Through

Data is written to both cache and database simultaneously:

Cache Eviction Policies

  • LRU — Evict least recently used (most common)
  • TTL — Time-based expiration
  • LFU — Evict least frequently used

Performance Impact

Proper caching can reduce database load by 80-90% and cut API response times from 100ms to under 5ms.

Common Pitfalls

  • Cache stampede — Multiple requests simultaneously rebuilding cache
  • Stale data — Cache not invalidated on updates
  • Memory overuse — No TTL set on cached items
Redis caching, when done right, dramatically improves application performance and scalability.

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