How does this skill improve PostgreSQL performance?

It enforces specific indexing patterns, such as manual FK indexing and the use of GIN/GiST for complex data, while recommending performance-tuned settings like fillfactor for update-heavy tables.

Does it cover database security?

It provides guidance on implementing Row-Level Security (RLS) policies to handle access control directly at the database layer.

What data types does this skill recommend avoiding?

It explicitly advises against using serial, varchar(n), char(n), and timestamp without time zone, suggesting modern alternatives like generated identity columns and text/timestamptz.

Does it support the latest PostgreSQL features?

Yes, it includes modern patterns like 'NULLS NOT DISTINCT' (PG15+), identity columns, and pgvector support for AI applications.

Can it help with database partitioning?

Yes, it provides implementation patterns for Range, List, and Hash declarative partitioning to manage tables exceeding 100 million rows.

PostgreSQL Table Design

Name: PostgreSQL Table Design
Author: EricGrill

byEricGrill

•

数据库管理

Designs optimized, high-performance PostgreSQL schemas using industry-standard best practices for data integrity and scalability.

关于

This skill provides expert guidance for architecting PostgreSQL databases, focusing on performance-optimized schema design, efficient indexing strategies, and proper data type selection. It helps developers implement advanced features like Row-Level Security, GIN/GiST indexing, and declarative partitioning while avoiding common pitfalls such as silent coercions or improper primary key choices. Whether you are building a new application or refactoring an existing database, this skill ensures your PostgreSQL implementation is durable, maintainable, and adheres to the latest standards (PG15+ and beyond).

主要功能

2 GitHub stars
Comprehensive constraint management including EXCLUDE, UNIQUE, and CHECK constraints.
Modern scaling patterns for partitioning, Row-Level Security, and update-heavy workloads.
Strategic normalization (3NF) and performance-based denormalization patterns.
Advanced indexing strategies covering B-tree, GIN, GiST, BRIN, and Partial indexes.
Expert data type selection including TIMESTAMPTZ, BIGINT Identity, and JSONB.

使用场景

Optimizing existing database tables to resolve performance bottlenecks and bloat issues.
Designing a high-performance relational schema for a new enterprise SaaS application.
Implementing specialized storage for full-text search, geospatial data, or AI vector embeddings.

关于

主要功能

2 GitHub stars
Comprehensive constraint management including EXCLUDE, UNIQUE, and CHECK constraints.
Modern scaling patterns for partitioning, Row-Level Security, and update-heavy workloads.
Strategic normalization (3NF) and performance-based denormalization patterns.
Advanced indexing strategies covering B-tree, GIN, GiST, BRIN, and Partial indexes.
Expert data type selection including TIMESTAMPTZ, BIGINT Identity, and JSONB.

使用场景

Optimizing existing database tables to resolve performance bottlenecks and bloat issues.
Designing a high-performance relational schema for a new enterprise SaaS application.
Implementing specialized storage for full-text search, geospatial data, or AI vector embeddings.