A Cheatsheet on Database Performance

Concise guide to optimize database performance with key strategies.

Database Performance Cheatsheet

Here’s a cheatsheet on database performance:

1. Indexing

• Purpose: Speed up data retrieval.
• Considerations:
  • Over-indexing can slow down writes.
  • Regularly review and optimize indexes.

2. Query Optimization

• Techniques:
  • UseEXPLAIN to analyze query plans.
  • AvoidSELECT *.
  • Write efficientWHERE clauses.

3. Connection Pooling

• Benefits:
  • Reduces overhead of establishing new connections.
  • Improves response times.

4. Caching

• Levels:
  • Application-level (e.g., Memcached, Redis).
  • Database-level (query cache).

5. Sharding

• Definition: Distribute data across multiple databases.
• Use Cases:
  • Handling large datasets.
  • Improving write performance.

6. Replication

• Types:
  • Master-slave.
  • Master-master.
• Purpose:
  • Read scaling.
  • High availability.

7. Hardware

• Considerations:
  • Sufficient RAM.
  • Fast storage (SSD).
  • Adequate CPU.

8. Monitoring

• Metrics:
  • Query response times.
  • CPU usage.
  • Disk I/O.

9. Normalization/Denormalization

• Normalization: Reduces redundancy.
• Denormalization: Improves read performance (trade-off with redundancy).

10. Partitioning

• Types:
  • Horizontal.
  • Vertical.
• Purpose:
  • Improve query performance.
  • Easier data management.