Database caching is a critical technique to optimize application performance by reducing direct database access. Here are common strategies:
1. In-Memory Caching
Use tools like Redis or Memcached to store frequently accessed data in memory.
Example:
import redis
cache = redis.Redis(host='localhost', port=6379, db=0)
data = cache.get('user:1001') or None
2. Query Caching
Cache the results of database queries to avoid repeated execution.
Best Practice:
- Cache queries with stable results (e.g.,
SELECT * FROM users WHERE status = 'active') - Invalidate cache when data changes
3. Object Caching
Store serialized objects in cache to minimize database roundtrips.
Tools:
- Redis (supports TTL and data structures)
- APC (PHP-specific)
4. Connection Pooling
Reuse database connections instead of creating new ones for each request.
Benefits:
- Reduces overhead
- Improves scalability
5. Read-Write Splitting
Route read operations to cache and write operations to the database.
Use Case:
- High-traffic applications with frequent read requests
For advanced techniques, see our guide on Best Practices for Caching.