Database Design Decisions

About

Provides a structured framework for making critical database architecture decisions based on specific data access patterns and requirements. This skill helps developers navigate the complex trade-offs between SQL and NoSQL, implement efficient schema designs, and apply advanced optimization techniques like indexing and caching. From managing ACID transactions in PostgreSQL to implementing single-table design in DynamoDB, it offers the patterns and best practices needed to build scalable, maintainable, and high-performing data layers for any application.

Key Features

• 3 GitHub stars
• Query optimization techniques to prevent N+1 problems and improve indexing
• Advanced transaction management patterns including optimistic locking
• Schema design patterns for RDBMS, Document, and Key-Value databases
• Scalable caching strategies using Redis and write-through patterns
• SQL vs NoSQL selection frameworks based on CAP theorem trade-offs

Use Cases

• Choosing the right database technology for a new software project
• Designing and normalizing schemas for complex relational data
• Optimizing existing database performance through indexing and caching