Does it include advanced scaling techniques?

Absolutely. The skill covers advanced topics such as table partitioning, materialized views for pre-computing expensive aggregates, and batch operation optimizations.

Can it help fix performance issues caused by ORMs?

Yes, it includes specific strategies for identifying and resolving common ORM-induced performance issues like the N+1 query problem and inefficient offset-based pagination.

How does this skill help with slow queries?

It provides systematic patterns for analyzing EXPLAIN plans to identify bottlenecks like full table scans and recommends specific indexing or query refactoring solutions to improve execution time.

Which database systems are covered by these patterns?

While the optimization concepts are universal, the skill provides specific syntax and advanced features for PostgreSQL and MySQL, including specialized index types and execution metrics.

Is this skill useful for database schema design?

Yes, it provides guidance on choosing appropriate data types and proactive indexing strategies to ensure your database is architected for performance from the start.

SQL Optimization Patterns

Name: SQL Optimization Patterns
Author: Microck

byMicrock

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データベース管理

Optimizes database performance through expert query refactoring, advanced indexing strategies, and detailed execution plan analysis.

概要

This Claude Code skill empowers developers to transform sluggish database operations into high-performance queries through systematic analysis and proven architectural patterns. It provides deep expertise in interpreting EXPLAIN plans, implementing advanced indexing strategies—such as covering and partial indexes—and resolving common performance bottlenecks like the N+1 query problem. Whether you are debugging production slowdowns, designing a scalable schema, or optimizing complex aggregations, this skill offers production-ready SQL snippets and best practices to reduce database load and improve application responsiveness.

主な機能

Advanced performance techniques like materialized views and table partitioning.
Advanced indexing patterns including GIN, JSONB, and functional indexes.
81 GitHub stars
Deep EXPLAIN and EXPLAIN ANALYZE plan interpretation for PostgreSQL and MySQL.
Cursor-based pagination strategies to replace slow OFFSET/LIMIT patterns.
Comprehensive solutions for resolving N+1 query anti-patterns and Cartesian products.

ユースケース

Diagnosing and fixing slow-running queries in high-traffic production environments.
Refactoring application-level data fetching logic to reduce database load and costs.
Designing performant database schemas that scale with large datasets.

概要

主な機能

Advanced performance techniques like materialized views and table partitioning.
Advanced indexing patterns including GIN, JSONB, and functional indexes.
81 GitHub stars
Deep EXPLAIN and EXPLAIN ANALYZE plan interpretation for PostgreSQL and MySQL.
Cursor-based pagination strategies to replace slow OFFSET/LIMIT patterns.
Comprehensive solutions for resolving N+1 query anti-patterns and Cartesian products.

ユースケース

Diagnosing and fixing slow-running queries in high-traffic production environments.
Refactoring application-level data fetching logic to reduce database load and costs.
Designing performant database schemas that scale with large datasets.