🔍 Indexing Strategies

  • Primary Keys: Use clustered indexes for frequently queried columns (e.g., user_id)
  • Composite Indexes: Combine multiple columns (e.g., order_date, customer_id) for complex filters
  • Covering Indexes: Include all fields from a query in the index to avoid disk I/O
  • Index Tuning: Regularly analyze query patterns with EXPLAIN or EXPLAIN ANALYZE

💡 Tip: Avoid over-indexing! Each index increases write overhead. Use tools like pgAdmin for PostgreSQL or MySQL Workbench for MySQL.

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🚀 Query Optimization

  • Reduce JOINs: Denormalize data or use materialized views
  • Limit Results: Use LIMIT with OFFSET for pagination
  • **Avoid SELECT ***: Specify only required columns
  • Use Query Caching: Enable Redis or Memcached for frequent queries

📌 Example: 

SELECT id, name FROM users WHERE status = 'active' AND created_at > NOW() - INTERVAL '1 year'
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📦 Partitioning & Sharding

  • Horizontal Partitioning: Split tables by date ranges or regions
  • Vertical Partitioning: Separate frequently accessed columns into different tables
  • Sharding: Distribute data across multiple servers (e.g., shard by user_region)
  • Use Case: Large e-commerce platforms often shard order tables by geographic regions

🌐 For more on partitioning techniques, see our database partitioning guide.

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⚙️ Caching Mechanisms

  • Application-Level Caching: Use Redis for session data or API responses
  • Database-Level Caching: Enable query cache in MySQL (deprecated in 8.0)
  • CDN Caching: Cache static assets to reduce database load
  • Cache Invalidation: Use time-to-live (TTL) policies for stale data

📈 Tools like Redis can reduce database latency by up to 70% in high-traffic scenarios.

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📊 Monitoring & Maintenance

  • Slow Query Logs: Analyze and optimize long-running queries
  • Connection Pooling: Use PgBouncer or HikariCP to manage database connections
  • Vacuuming: Regularly clean up PostgreSQL tables
  • Index Statistics: Update with ANALYZE to improve query planner accuracy

🛠️ For monitoring best practices, check our database performance guide.

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