data-sql-optimization

Name: data-sql-optimization
Rating: 4.05 (21 reviews)
Author: vasilyu1983

Production-grade SQL optimization with AI-assisted query analysis, EXPLAIN ANALYZE automation, balanced indexing strategies, performance tuning, schema design, and operations across PostgreSQL, MySQL, SQL Server, Oracle, SQLite.

TL;DR

Production-grade SQL optimization with AI-assisted analysis, indexing, and performance tuning across major databases.

What Is It

AI-powered query performance analysis
Automated EXPLAIN ANALYZE interpretation
Balanced indexing strategies avoiding over-indexing
Schema design and migration with version control

Key Features

Supports PostgreSQL, MySQL, SQL Server, Oracle, SQLite
Includes EXPLAIN ANALYZE automation and index health monitoring
Provides schema evolution, backup, and HA replication guidance
Offers operational templates and anti-pattern fixes
Enables performance tuning with memory, indexing, and auto-analyze
Includes slow query detection and index bloat analysis

How to Use

1.Identify slow queries using pg_stat_statements or slow query logs
2.Analyze execution plans with EXPLAIN ANALYZE or Performance Schema
3.Apply balanced indexing (e.g., B-tree, GIN, partial indexes)
4.Use Flyway or Liquibase for version-controlled schema changes
5.Implement backup/recovery and replication for high availability

Guardrails & Gotchas

Avoid over-indexing — index only when performance improves by 10x+
Verify selectivity <10% and table size >10k rows before indexing
Never skip index usage checks with pg_stat_user_indexes
Use version control (Flyway/Liquibase) for schema changes
Monitor index bloat and vacuum performance regularly

GitHub Stats

Author

@vasilyu1983

Repository

vasilyu1983/AI-Agents-public

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