DATABASE DESIGN: SQL VS. NOSQL AND WHEN TO USE EACH

The database question — SQL or NoSQL — is one of the most consequential early decisions in any project. Both have legitimate use cases, and understanding the tradeoffs prevents costly migrations later. SQL databases (PostgreSQL, MySQL): - Strong consistency and ACID transactions - Structured schemas enforce data integrity - Powerful query language for complex joins and aggregations - Best for: financial systems, e-commerce, CRM, any application requiring complex queries NoSQL databases: - Document stores (MongoDB): Flexible schemas, nested data, rapid prototyping - Key-value stores (Redis): Ultra-fast caching and session management - Wide-column (Cassandra): Massive write throughput for time-series and IoT data - Graph databases (Neo4j): Relationship-heavy data like social networks The modern reality: Most applications use multiple databases. PostgreSQL for transactional data, Redis for caching, Elasticsearch for full-text search. This is called polyglot persistence. Our advice: Start with PostgreSQL. It's versatile, battle-tested, and has excellent tooling. Add specialized databases only when you have specific requirements that PostgreSQL can't efficiently handle.