How does it help with query performance?

The skill offers detailed instructions on analyzing slow queries using tools like EXPLAIN ANALYZE and recommends optimal indexing strategies to improve speed.

Does this skill support both SQL and NoSQL?

Yes, it provides specialized guidance and implementation patterns for both MongoDB (document-oriented) and PostgreSQL (relational) databases.

Is it suitable for production administration?

Yes, it covers production-critical tasks including backup and restore strategies, user permission management, and high-availability configurations like sharding.

Can this skill help with database migrations?

Absolutely. It includes best practices for implementing migrations and provides Python utilities for generating and applying changes to your schema.

Unified Database Management

Name: Unified Database Management
Author: GGPrompts

byGGPrompts

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Database Management

Manages both MongoDB and PostgreSQL environments, from schema design and query optimization to production administration and migrations.

About

This skill provides a comprehensive toolkit for working with document-oriented MongoDB and relational PostgreSQL databases within the Claude Code environment. It guides users through critical tasks such as data modeling, writing complex aggregation pipelines, optimizing SQL queries, and managing database migrations. Whether you are choosing between NoSQL and SQL architectures or troubleshooting performance bottlenecks in a production environment, this skill offers the specific patterns, scripts, and best practices needed to build and maintain robust, high-performance data layers.

Key Features

Schema design and data modeling for both SQL and NoSQL systems
Comprehensive aggregation pipeline and complex SQL join management
Configuration for replication, sharding, and clustering high-availability
Advanced query optimization and performance analysis using EXPLAIN
Automated migration scripts and backup/restore strategies
1 GitHub stars

Use Cases

Evaluating and selecting the optimal database type for a new project architecture
Refactoring slow queries and implementing effective indexing strategies for scale
Managing database users, permissions, and migrations across environments

About

Key Features

Schema design and data modeling for both SQL and NoSQL systems
Comprehensive aggregation pipeline and complex SQL join management
Configuration for replication, sharding, and clustering high-availability
Advanced query optimization and performance analysis using EXPLAIN
Automated migration scripts and backup/restore strategies
1 GitHub stars

Use Cases

Evaluating and selecting the optimal database type for a new project architecture
Refactoring slow queries and implementing effective indexing strategies for scale
Managing database users, permissions, and migrations across environments