Can it help with production performance issues?

Yes, it provides strategies for query optimization, index selection, and interpreting EXPLAIN ANALYZE output to resolve performance bottlenecks.

How does it handle database migrations?

It outlines safe migration patterns, such as adding nullable columns before backfilling, to ensure schema changes don't cause application downtime or data loss.

Is this skill useful for ORM users?

Yes. Even when using an ORM, understanding underlying database patterns like indexing and N+1 query avoidance is critical for building efficient applications.

Does this skill support NoSQL databases?

While it focuses primarily on relational SQL patterns, it includes guidance for document-style storage like JSONB and general data modeling principles applicable to many systems.

Database Design Patterns

Name: Database Design Patterns
Author: Zate

byZate

Gestión de Bases de Datos

Implements industry-standard database design patterns, indexing strategies, and migration best practices for optimized data persistence.

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This skill provides Claude with expert-level guidance on architecting robust database schemas, optimizing query performance, and managing data migrations safely. It covers essential areas such as normalization levels, naming conventions, composite index ordering, and query anti-patterns. Whether you are designing a new data model from scratch or troubleshooting a legacy database with performance bottlenecks, this skill ensures your architecture is scalable, maintainable, and follows modern best practices for SQL and high-performance data environments.

Características Principales

Advanced indexing strategies including B-tree, GIN, and composite indexes
Standardized naming conventions for tables, columns, and constraints
Query optimization techniques and interpretation of execution plans
Schema design and normalization guidance (1NF to BCNF)
Safe migration patterns for zero-downtime database updates
0 GitHub stars

Casos de Uso

Identifying and refactoring slow queries through indexing and anti-pattern removal
Architecting a scalable relational schema for a complex new application feature
Planning and executing high-risk data migrations without table-locking or data loss

Acerca de

Características Principales

Advanced indexing strategies including B-tree, GIN, and composite indexes
Standardized naming conventions for tables, columns, and constraints
Query optimization techniques and interpretation of execution plans
Schema design and normalization guidance (1NF to BCNF)
Safe migration patterns for zero-downtime database updates
0 GitHub stars

Casos de Uso

Identifying and refactoring slow queries through indexing and anti-pattern removal
Architecting a scalable relational schema for a complex new application feature
Planning and executing high-risk data migrations without table-locking or data loss