Introduction

Database performance is crucial for web application success. This guide covers optimization techniques for both PostgreSQL and MongoDB, helping you achieve better performance and scalability.

PostgreSQL Optimization

Query Optimization

Understanding and optimizing your queries is the first step to better performance:

-- Use EXPLAIN ANALYZE to understand query performance
EXPLAIN ANALYZE SELECT u.name, COUNT(p.id) as post_count
FROM users u
LEFT JOIN posts p ON u.id = p.user_id
WHERE u.created_at > '2023-01-01'
GROUP BY u.id, u.name
ORDER BY post_count DESC;

Index Strategies

Proper indexing can dramatically improve query performance:

-- Composite index for common query patterns
CREATE INDEX idx_posts_user_published 
ON posts(user_id, published_at) 
WHERE status = 'published';

-- Partial index for specific conditions
CREATE INDEX idx_active_users 
ON users(email) 
WHERE status = 'active';

MongoDB Optimization

Document Structure

Design your document structure for optimal query performance:

// Optimized document structure
{
  "_id": ObjectId("..."),
  "user_id": ObjectId("..."),
  "title": "Blog Post Title",
  "content": "...",
  "tags": ["javascript", "mongodb", "optimization"],
  "metadata": {
    "created_at": ISODate("..."),
    "updated_at": ISODate("..."),
    "view_count": 150
  }
}

Aggregation Pipeline Optimization

// Optimized aggregation pipeline
db.posts.aggregate([
  { $match: { "metadata.created_at": { $gte: new Date("2023-01-01") } } },
  { $group: { 
      _id: "$user_id", 
      post_count: { $sum: 1 },
      total_views: { $sum: "$metadata.view_count" }
    }
  },
  { $sort: { post_count: -1 } },
  { $limit: 10 }
])

Connection Pooling

Implement proper connection pooling to manage database connections efficiently:

# PostgreSQL with Rails
# config/database.yml
production:
  adapter: postgresql
  pool: 25
  timeout: 5000
  checkout_timeout: 5

Monitoring and Alerting

Set up comprehensive monitoring to track database performance:

Query execution time monitoring
Connection pool utilization
Slow query logging
Resource utilization alerts

Caching Strategies

Implement multiple layers of caching:

Application-level caching with Redis
Query result caching
Database-level caching

Conclusion

Database optimization is an ongoing process that requires continuous monitoring and adjustment. By implementing these techniques, you can significantly improve your application's performance and user experience.

Database Optimization Techniques for Web Applications