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databases

Design and optimize MongoDB and PostgreSQL database schemas and queries.

Updated Jun 16, 2025
Search Tags:#design#database#postgresql#migration#sql#nosql#mongodb
One-click install
npx skills add https://github.com/Stonelukas/Mouse-on-Numpad --skill databases-stonelukas
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databases
Source: https://github.com/Stonelukas/Mouse-on-Numpad/tree/main/.opencode/skill/databases
Command: npx skills add https://github.com/Stonelukas/Mouse-on-Numpad --skill databases-stonelukas

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pymongo, psycopg2, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Database design and query optimization across MongoDB and PostgreSQL are complex and error-prone. This skill provides unified guidance for creating scalable schemas, writing efficient SQL and MongoDB queries, and planning migrations to improve performance and reliability.

Core Features & Use Cases

  • Schema Design: OLTP and OLAP modeling guidance, normalization concepts, and indexing strategies to support scalable data stores.
  • Query Crafting & Performance: SQL and MongoDB patterns, optimization tips, and performance best practices for common workloads.
  • Migrations & Tooling: Guidance on migrations, backups, and performance checks with example scripts and best practices for production deployments.
  • Reference Materials: Centralized references for MongoDB and PostgreSQL design and optimization topics.

Quick Start

Run the migration workflow on a sample schema to validate design correctness and performance.

Frequently Asked Questions about databases

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

FAQPage Schema
How do I design scalable database schemas for PostgreSQL and MongoDB?▼

Design scalable database schemas by applying OLTP and OLAP modeling guidance, normalization concepts, and targeted indexing strategies to support high-volume relational and document data stores.

What is the best way to optimize SQL and MongoDB queries for performance?▼

Optimize SQL and MongoDB queries by applying specific query patterns, optimization tips, and performance best practices tailored for common workloads across OLTP and analytics contexts.

How do I plan database migrations without losing data?▼

Plan database migrations using structured execution guides and practical scripts that enforce best practices for backups, schema changes, and performance validation in production deployments.

Does this database design approach work for both OLTP and analytics contexts?▼

Yes, this approach works for both OLTP and analytics contexts by providing centralized reference materials and structured execution guides to tune performance and enforce best practices across diverse workloads.

When should I use NoSQL query patterns instead of SQL for my database?▼

Use NoSQL query patterns instead of SQL when your database design requires flexible document structures, leveraging provided MongoDB design concepts and indexing strategies rather than traditional relational normalization.

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