Define PostgreSQL and MongoDB schemas with migrations, indexes, and RLS.
npx skills add https://github.com/neuron-one/GODMODE --skill database-neuron-one
Please help me install this Agent Skill. Skill: database Source: https://github.com/neuron-one/GODMODE/tree/main/skills/development/database Command: npx skills add https://github.com/neuron-one/GODMODE --skill database-neuron-one
PostgreSQL and MongoDB design, migrations, and indexing guidance to ensure data integrity and scalable performance across applications.
Create a normalized PostgreSQL schema with UUID primary keys, created_at/updated_at timestamps, and indexes for common queries in a multi-tenant SaaS environment.
High-intent search queries and answers about installing and using this skill.
To design a multi-tenant PostgreSQL schema, you normalize tables to 3NF using UUID primary keys and foreign-key constraints. You then apply row-level security (RLS) policies to isolate tenant data and ensure scalable, secure access across the application.
Database schema migrations with rollback are handled by defining forward upgrade scripts and corresponding reverse scripts. This ensures safe schema evolution, maintains data integrity during updates, and allows immediate reversion if constraints or indexing changes cause issues.
An indexing strategy for PostgreSQL and MongoDB is created by analyzing common query patterns and adding targeted indexes. This ensures scalable performance by accelerating data retrieval while maintaining robust schema constraints and data integrity.
MongoDB schema design typically prioritizes flexible, embedded documents over strict 3NF normalization and foreign-key constraints used in PostgreSQL. However, you can enforce data integrity through validation rules and indexed references to structure relationships effectively.
You need created_at and updated_at timestamps in a database schema design to track record lifecycle events accurately. They are standard requirements for robust PostgreSQL schemas, supporting auditing, data synchronization, and temporal query filtering.
Adding row-level security to a multi-tenant database requires specific constraints to prevent data leakage between tenants. Establishing strict foreign-key constraints and normalized schemas ensures the RLS policies function correctly without compromising data integrity.
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