When to Use a Cache (Redis, Memcached) and When Not To
🎯 What Caching Does
Caching stores frequently accessed data in fast memory (Redis, Memcached) instead of querying the database every time.
✅ When to Use a Cache
1. Expensive Queries
If a query is slow or expensive (joins, aggregations, complex calculations), cache the result.
2. Frequently Accessed Data
If the same data is requested many times (user profiles, settings, static content), cache it.
3. External API Calls
If you're calling external APIs, cache the responses. Don't hit their API on every request.
4. Session Data
Store sessions in Redis. Fast, and easy to expire.
❌ When Not to Use a Cache
1. Simple Queries
If your database query is fast (indexed, simple SELECT), caching adds complexity without benefit.
2. Frequently Changing Data
If data changes often, cache invalidation becomes a problem. Sometimes the database is simpler.
3. Small Scale
If you have low traffic, your database is probably fast enough. Don't add a cache until you need it.
4. Real-Time Requirements
If you need real-time data (live updates, current balances), caching can cause stale data issues.
💡 My Decision Process
- Is the query slow? → Optimize the query first
- Is it still slow after optimization? → Consider caching
- Is the data accessed frequently? → Cache it
- Does the data change often? → Maybe skip caching
🛠️ Simple Caching Strategy
Start with simple caching:
- Cache for 5–15 minutes
- Invalidate on updates
- Use Redis for structured data, Memcached for simple key-value
💭 My Take
Caching is a tool, not a requirement. Use it when you need it, not because it's trendy.
Start without a cache. Add one when you have a real performance problem. Most apps don't need caching at first.