Can it help me fix slow-running queries?

Yes, SQL Pro specializes in analyzing execution plans (EXPLAIN/ANALYZE) to identify bottlenecks and suggest specific indexing strategies to achieve sub-100ms response times.

Is this skill suitable for data warehousing tasks?

Yes, it includes specialized patterns for data warehousing, star schemas, slowly changing dimensions, and efficient ETL process design.

Does it support advanced SQL features like window functions?

Absolutely. It is designed to handle complex SQL patterns including Common Table Expressions (CTEs), window functions, recursive queries, and set-based operations.

Which database systems does SQL Pro support?

SQL Pro offers expert-level support for major database systems including PostgreSQL, MySQL, SQL Server, and Oracle, providing dialect-specific optimizations for each.

SQL Pro

Name: SQL Pro
Author: Jeffallan

byJeffallan

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Database Management

Optimizes complex database queries and designs scalable schemas across multiple SQL dialects for high-performance applications.

About

SQL Pro empowers Claude to act as a senior database administrator and developer, specializing in fine-tuning performance and architecting robust data structures. It provides expert guidance on advanced SQL features like window functions and CTEs, helps eliminate bottlenecks through execution plan analysis, and ensures database systems achieve sub-100ms response times across PostgreSQL, MySQL, SQL Server, and Oracle. Whether you are refactoring legacy queries or designing a data warehouse from scratch, this skill provides the specialized knowledge needed for production-grade database engineering.

Key Features

Detailed execution plan analysis and covering index strategies
Data warehousing, ETL patterns, and schema normalization
Deep support for PostgreSQL, MySQL, SQL Server, and Oracle dialects
7 GitHub stars
Implementation of complex patterns using CTEs and window functions
Advanced query optimization and performance tuning

Use Cases

Designing normalized database schemas for complex application architectures
Migrating and translating SQL logic between different database platforms
Refactoring slow-running legacy queries to meet sub-100ms performance targets

About

Key Features

Detailed execution plan analysis and covering index strategies
Data warehousing, ETL patterns, and schema normalization
Deep support for PostgreSQL, MySQL, SQL Server, and Oracle dialects
7 GitHub stars
Implementation of complex patterns using CTEs and window functions
Advanced query optimization and performance tuning

Use Cases

Designing normalized database schemas for complex application architectures
Migrating and translating SQL logic between different database platforms
Refactoring slow-running legacy queries to meet sub-100ms performance targets