database-design

Evaluate schema design, indexing strategy, and ORM options for scalable databases.

Updated Jan 27, 2026

Search Tags:#design #indexing #database #postgresql #schema #orm #normalization

Ready to run

npx skills add https://github.com/BrunoSantanaDeveloper/flyeelab-agent-kit --skill database-design-brunosantanadeveloper

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: database-design
Source: https://github.com/BrunoSantanaDeveloper/flyeelab-agent-kit/tree/main/skills/database-design
Command: npx skills add https://github.com/BrunoSantanaDeveloper/flyeelab-agent-kit --skill database-design-brunosantanadeveloper

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Database design decisions unlock scalable, maintainable data models for evolving applications. This skill guides normalization, indexing, PK strategies, and ORM choices to prevent costly migrations and performance bottlenecks.

Core Features & Use Cases

Schema design guidance: normalization vs denormalization, primary key strategies, and timestamp conventions for consistent data integrity.
Indexing & performance: guidance on when and what indexes to create, and how to optimize queries with appropriate FK handling and partitioning patterns.
ORM selection & deployment: recommendations for Drizzle, Prisma, or raw SQL approaches across serverless to traditional deployments. Use cases include multi-tenant SaaS schemas, analytics workloads, and edge-ready databases.

Quick Start

Analyze your project’s data requirements and I will propose a scalable schema plan in one pass.

Frequently Asked Questions about database-design

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

FAQPage Schema

How do I design a scalable database schema for a multi-tenant platform?▼

To design a scalable database schema for multi-tenant platforms, apply normalization rules, choose appropriate primary key strategies, and implement safe migration patterns to maintain data integrity and prevent performance bottlenecks.

What is the best way to choose between Drizzle, Prisma, and raw SQL for PostgreSQL?▼

Choosing between Drizzle, Prisma, or raw SQL involves evaluating your deployment target, ranging from serverless databases to edge deployments, to ensure the ORM aligns with your specific workload and scalability requirements.

When do I need database indexing and partitioning for query optimization?▼

You need database indexing and partitioning when optimizing queries with foreign key handling, ensuring appropriate indexes are created to prevent performance bottlenecks in analytics workloads and evolving applications.

How do I handle database normalization versus denormalization for data integrity?▼

Handling database normalization versus denormalization requires evaluating schema design alongside timestamp conventions and primary key strategies to balance consistent data integrity with query performance.

Does this schema design guidance work for serverless databases and edge deployments?▼

Yes, this schema design guidance works for serverless databases and edge deployments by recommending ORM options and scalable database designs tailored for these specific environments and workloads.