How does it help with performance optimization?

The skill provides guidance on using EXPLAIN for SQL, analyzing aggregation pipelines in MongoDB, and implementing strategic indexing.

Is it suitable for production database administration?

Yes, it covers production-critical topics like backup/restore strategies, user permissions, and high-availability configuration.

Does this skill support both SQL and NoSQL?

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

Can it help with database migrations?

Absolutely, it includes patterns and utility scripts for generating and applying migrations for both supported database types.

Databases & Data Modeling

Name: Databases & Data Modeling
Author: Activer007

byActiver007

Database Management

Streamlines database management by providing optimized workflows and best practices for both MongoDB and PostgreSQL systems.

About

This skill equips Claude with specialized knowledge to handle both relational (PostgreSQL) and document-oriented (MongoDB) database environments, offering a unified interface for schema design, query optimization, and production administration. It serves as a comprehensive guide for developers to choose the right database architecture, implement complex aggregation pipelines or SQL joins, and maintain high-performance deployments through automated migrations and advanced indexing strategies.

Key Features

Performance optimization through query analysis and indexing recommendations
0 GitHub stars
Dual-support for PostgreSQL (Relational) and MongoDB (NoSQL) workflows
Automated migration generation and backup utility scripts
Best practices for data modeling, security, and schema evolution
Detailed guidance on replication, sharding, and high-availability setups

Use Cases

Refactoring and optimizing slow SQL queries or MongoDB aggregation pipelines
Automating database administration tasks like backups and user permission management
Architecting scalable data models and schemas for new applications

About

Key Features

Performance optimization through query analysis and indexing recommendations
0 GitHub stars
Dual-support for PostgreSQL (Relational) and MongoDB (NoSQL) workflows
Automated migration generation and backup utility scripts
Best practices for data modeling, security, and schema evolution
Detailed guidance on replication, sharding, and high-availability setups

Use Cases

Refactoring and optimizing slow SQL queries or MongoDB aggregation pipelines
Automating database administration tasks like backups and user permission management
Architecting scalable data models and schemas for new applications