<aside> 📚 📁 Category: Backend

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Overview

Caching stores frequently accessed data in fast-access memory to reduce database load and improve response times. A well-designed caching strategy can improve performance by 10-100x.

<aside> ℹ️ Why It Matters: Understanding Caching Strategies is essential for building robust, scalable, and secure modern applications.

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Key Concepts

• [x] Cache-Aside (Lazy Loading) - Load on demand
• [x] Write-Through - Update cache when database updates
• [x] Write-Behind (Write-Back) - Async cache updates
• [x] Read-Through - Cache loads data automatically
• [x] Time-To-Live (TTL) - Auto-expiration strategy
• [x] Cache Invalidation - Keep cache fresh
• [x] Distributed Caching - Redis, Memcached
• [x] In-Memory Caching - Application-level cache

Common Use Cases

<aside> 💡 Where to Apply Caching Strategies

                        Database query results
                        API responses
                        Session data
                        User preferences and profiles
                        Product catalogs
                        Configuration data
                        Computed or aggregated data

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Best Practices

• [x] Cache only frequently accessed data
• [x] Set appropriate TTL based on data volatility
• [x] Implement cache warming for critical data
• [x] Monitor cache hit/miss ratios