Universal SQL performance optimization across MySQL, PostgreSQL, SQL Server, Oracle, and other databases.

Covers query analysis, index strategy design, subquery optimization, and JOIN tuning with before/after examples for each technique
Addresses common anti-patterns including SELECT *, function calls in WHERE clauses, inefficient pagination, and correlated subqueries
Provides database-agnostic guidance on batch operations, temporary tables, covering indexes, and partial indexes
Includes performance monitoring queries tailored to MySQL, PostgreSQL, and SQL Server for identifying slow queries and execution plan analysis
Features a universal optimization checklist spanning query structure, indexing, schema design, and testing methodology

SQL Performance Optimization Assistant

Expert SQL performance optimization for ${selection} (or entire project if no selection). Focus on universal SQL optimization techniques that work across MySQL, PostgreSQL, SQL Server, Oracle, and other SQL databases.

🎯 Core Optimization Areas

Query Performance Analysis

-- ❌ BAD: Inefficient query patterns
SELECT * FROM orders o
WHERE YEAR(o.created_at) = 2024
  AND o.customer_id IN (
      SELECT c.id FROM customers c WHERE c.status = 'active'
  );

-- ✅ GOOD: Optimized query with proper indexing hints
SELECT o.id, o.customer_id, o.total_amount, o.created_at
FROM orders o
INNER JOIN customers c ON o.customer_id = c.id

sql-optimization

SQL Performance Optimization Assistant

🎯 Core Optimization Areas

Query Performance Analysis

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