Does this skill support both SQL and NoSQL databases?

Yes, it provides comprehensive patterns for relational databases like PostgreSQL as well as NoSQL document stores like MongoDB and key-value stores like Redis.

How does it handle complex data relationships?

It provides standardized implementations for 1:1, 1:N, and M:N relationships, including junction tables and foreign key constraints to ensure referential integrity.

Does it include security-related data patterns?

Yes, it covers critical security and governance patterns such as Row-Level Security (RLS) for multi-tenancy and automated audit logging for data changes.

Does it assist with data migration strategy?

Yes, it outlines safe migration patterns for schema evolution, such as adding non-null columns and renaming fields without causing downtime or data loss.

Can it help me with database performance optimization?

Absolutely. The skill includes specific guidance on when and how to denormalize data, use materialized views, and structure indexes for read-heavy or write-heavy workloads.

Data Design & Architecture

Name: Data Design & Architecture
Author: miles990

bymiles990

•

データベース管理

Designs efficient, scalable, and maintainable data structures and schemas using industry-best practices for SQL and NoSQL databases.

概要

This skill provides Claude with expert-level guidance for creating robust data architectures and schemas. It covers essential modeling principles including entity-relationship diagrams, normalization (1NF-3NF), and strategic denormalization for performance. Beyond basic tables, it offers advanced patterns for real-world requirements such as multi-tenancy, audit logging, soft deletes, and temporal versioning. Whether you are architecting a new system or refactoring a legacy database, this skill ensures your data layer is optimized for both integrity and performance across relational and non-relational environments.

主な機能

Safe schema evolution and migration patterns to maintain data integrity
Advanced patterns for multi-tenancy, row-level security, and audit trails
Data pipeline architecture guidance for ETL, ELT, and Event Sourcing
1 GitHub stars
Comprehensive SQL schema design including normalization and junction tables
NoSQL modeling strategies for Document (MongoDB) and Key-Value (Redis) stores

ユースケース

Optimizing read-heavy workloads through strategic denormalization and materialized views
Implementing versioning and historical tracking for sensitive domain entities
Designing a complex relational database for a multi-tenant SaaS application

概要

主な機能

Safe schema evolution and migration patterns to maintain data integrity
Advanced patterns for multi-tenancy, row-level security, and audit trails
Data pipeline architecture guidance for ETL, ELT, and Event Sourcing
1 GitHub stars
Comprehensive SQL schema design including normalization and junction tables
NoSQL modeling strategies for Document (MongoDB) and Key-Value (Redis) stores

ユースケース

Optimizing read-heavy workloads through strategic denormalization and materialized views
Implementing versioning and historical tracking for sensitive domain entities
Designing a complex relational database for a multi-tenant SaaS application