1. Index Optimization 🔍

  • Use selective indexes: Only create indexes on columns frequently used in WHERE, JOIN, or ORDER BY clauses.
    database_index
  • Avoid over-indexing: Excessive indexes slow down write operations. Monitor index usage with EXPLAIN queries.
  • Composite indexes: Combine related columns into a single index (e.g., (user_id, created_at)).

2. Query Efficiency 🚀

  • Optimize SQL queries by:
    • Reducing subqueries with JOIN operations
    • Limiting result sets with LIMIT or WHERE filters
    • Avoiding SELECT * and specifying needed columns
  • Use caching for frequent queries (e.g., Redis or Memcached).
    query_optimization

3. Schema Design 📁

  • Normalize data to reduce redundancy but balance with denormalization for performance.
  • Choose appropriate data types (e.g., INT instead of VARCHAR for numeric fields).
  • Partition tables by time or region for faster data retrieval.

4. Connection Pooling 🔄

  • Reuse database connections via connection pooling to minimize overhead.
  • Configure pool size based on application load and database capacity.

5. Monitoring & Tools 📊

  • Use tools like pg_stat_statements (PostgreSQL) or SHOW ENGINE INNODB STATUS (MySQL) to analyze performance.
  • Regularly check slow query logs and optimize accordingly.
    database_monitoring

For advanced techniques, check our Best Practices section.
For performance tuning in specific databases, visit MySQL Optimization or PostgreSQL Optimization.