Best Practices for Caching
- Learn the data access pattern and cache based on it.
- Choose a caching product that suits your requirements, not just by name.
- Harness cache at all layers (from CPU to CDN).
- Warm the cache periodically or at specific times using schedulers. The intensity of warming should be based on how hot the data is.
Types of Caching Strategies
Cache-Aside (Lazy Loading)
The most common caching strategy. When data is requested:
- Check the cache first.
- If data is available (cache hit), return it.
- If data is not available (cache miss), query the database, populate the cache, then return the data.
Advantages: Cost-effective cache size, immediate performance gains.
Disadvantage: Initial response time overhead due to cache misses.
Read-Through
Fetches data from the database and stores it in the cache when a cache miss occurs. Beneficial for complex data retrieval scenarios.
Write-Through
Writes data to both the cache and the database simultaneously. The cache is proactively updated immediately following the primary database update.
Advantages: Up-to-date cache, better overall performance, optimal database performance.
Disadvantage: Larger and more expensive cache due to storing infrequently-requested data.
Write-Around
Writes data to the cache but not immediately to the database. Suitable for write-once, read-less-frequently scenarios.
Write-Back
Writes data to the cache and updates the database periodically. Beneficial for write-heavy workloads.
Least Recently Used (LRU)
Evicts the least recently accessed data from the cache when it reaches capacity.
Least Frequently Used (LFU)
Evicts the data with the lowest access frequency from the cache when it reaches capacity.
Conclusion
A proper caching strategy often includes a combination of write-through and lazy loading approaches, along with setting appropriate expiration times for data to keep it relevant and lean. The choice of strategy depends on your specific use case and performance requirements.