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moai-domain-database

Design and optimize PostgreSQL, MongoDB, Redis, and Oracle database schemas and queries.

Updated Nov 20, 2025
Search Tags:#database#postgresql#data modeling#sql#nosql#performance tuning#mongodb
One-click install
npx skills add https://github.com/soo-kate-yeon/shadowoo --skill moai-domain-database-soo-kate-yeon
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: moai-domain-database
Source: https://github.com/soo-kate-yeon/shadowoo/tree/main/.agents/skills/moai-domain-database
Command: npx skills add https://github.com/soo-kate-yeon/shadowoo --skill moai-domain-database-soo-kate-yeon

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and modules (resource) components.

What problem does it solve?

This Skill provides expert guidance on designing, optimizing, and managing diverse database systems, ensuring data integrity and high performance for complex applications.

Core Features & Use Cases

  • Database Design: Expert advice on relational (PostgreSQL, Oracle) and NoSQL (MongoDB) schema design, data modeling, and advanced patterns.
  • Performance Tuning: Strategies for query optimization, indexing, connection pooling, and scaling across multiple database technologies.
  • Use Case: You need to design a scalable database schema for a new e-commerce platform that handles both structured product data and flexible user profiles, while ensuring fast query responses.

Quick Start

Use the moai-domain-database skill to design a PostgreSQL schema for a blog with posts, users, and comments.

Frequently Asked Questions about moai-domain-database

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design a PostgreSQL schema for an application with both structured data and flexible user profiles?▼

Schema design for PostgreSQL involves modeling relational tables for structured data while leveraging JSONB columns for flexible user profiles, ensuring data integrity and fast query responses across complex application architectures.

What's the best way to optimize slow PostgreSQL and MongoDB queries in a multi-database architecture?▼

Query optimization in multi-database architectures requires analyzing execution plans, implementing targeted indexing strategies, and configuring connection pooling to improve response times across PostgreSQL, MongoDB, Redis, and Oracle systems.

How do I model data for a scalable e-commerce platform using a mix of SQL and NoSQL databases?▼

Data modeling for scalable e-commerce platforms combines relational schemas for structured product data with NoSQL patterns for flexible user profiles, utilizing advanced data patterns to maintain high performance.

When should I use NoSQL data modeling patterns instead of traditional relational schemas?▼

NoSQL data modeling patterns are necessary when applications require flexible schemas, high-volume unstructured data ingestion, or horizontal scaling, whereas relational schemas suit structured data with strict integrity constraints.

Can I manage database migrations and ORM configuration across multiple database technologies?▼

Managing database migrations and ORM configurations across multiple technologies is supported, providing strategies to maintain schema consistency and handle complex data transitions across PostgreSQL, MongoDB, Redis, and Oracle implementations.

What indexing strategies should I use for performance tuning in enterprise-grade database implementations?▼

Performance tuning indexing strategies include selecting appropriate B-tree, GiST, or GIN indexes for PostgreSQL and compound indexes for MongoDB, directly impacting complex query optimization and enterprise-grade scalability.

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