Does this skill support both SQL and NoSQL databases?

Yes, it provides comprehensive support and specialized guidance for PostgreSQL (relational) and MongoDB (document-oriented) databases.

Can I use this for production database performance tuning?

Absolutely. It includes guidance on using EXPLAIN ANALYZE for PostgreSQL and aggregation profiling for MongoDB, alongside indexing best practices.

Does it provide automation scripts for database tasks?

Yes, the skill includes Python utilities for managing migrations, running automated backups, and performing threshold-based performance checks.

How does it help in choosing the right database?

The skill features a selection guide comparing MongoDB and PostgreSQL based on schema flexibility, consistency requirements, scaling needs, and specific use cases.

Database Management & Optimization

Name: Database Management & Optimization
Author: rafaelcalleja

byrafaelcalleja

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Database Management

Simplifies database schema design, query optimization, and administration for MongoDB and PostgreSQL environments.

About

This skill provides a unified workflow for managing both relational (PostgreSQL) and document-oriented (MongoDB) databases within Claude Code. It guides developers through critical tasks such as choosing the right architecture for their use case, writing complex aggregation pipelines or SQL joins, performing safe migrations, and optimizing production performance. Whether you are configuring a new MongoDB Atlas cluster, troubleshooting slow PostgreSQL queries, or implementing robust backup strategies, this skill offers specialized domain knowledge and Python utility scripts to streamline your database operations and ensure data integrity.

Key Features

Production-ready configurations for replication, sharding, and security
Comprehensive guides for indexing strategies and schema design
Automated migration and backup utility scripts in Python
1 GitHub stars
Unified support for MongoDB (BSON) and PostgreSQL (SQL) workflows
Advanced performance profiling and slow-query analysis tools

Use Cases

Automating database maintenance tasks like backups, restores, and performance health checks
Optimizing complex relational joins and ACID transactions in PostgreSQL for financial systems
Designing a scalable data model for real-time applications using MongoDB document structures

About

Key Features

Production-ready configurations for replication, sharding, and security
Comprehensive guides for indexing strategies and schema design
Automated migration and backup utility scripts in Python
1 GitHub stars
Unified support for MongoDB (BSON) and PostgreSQL (SQL) workflows
Advanced performance profiling and slow-query analysis tools

Use Cases

Automating database maintenance tasks like backups, restores, and performance health checks
Optimizing complex relational joins and ACID transactions in PostgreSQL for financial systems
Designing a scalable data model for real-time applications using MongoDB document structures