Redis provides fast in-memory caching for applications. Different caching patterns suit different scenarios. Understanding patterns enables effective cache utilization for performance gains.
Caching Strategies
Cache-aside reads from cache, falling back to database. Write-through updates cache on writes. Write-behind batches writes for efficiency. Refresh-ahead proactively refreshes expiring entries.
- Cache-aside works well for read-heavy workloads
- Set appropriate TTLs based on data freshness needs
- Use cache invalidation on data updates
- Implement cache warming for predictable access patterns
- Monitor cache hit rates identifying optimization opportunities
Data Structures
Strings store simple key-value pairs. Hashes group related fields. Lists maintain ordered collections. Sets store unique members. Choose structures matching your access patterns.