Database Selection for Web Applications: SQL vs NoSQL and Beyond

Database selection is one of the most impactful architectural decisions. Changing databases later is expensive. Understand the tradeoffs before committing.

PostgreSQL: the default choice for most web applications. Relational with excellent JSON support, full-text search, geospatial queries, and rock-solid reliability. Handles most use cases without specialized databases.

MongoDB: document database for flexible, schema-less data. Best for content management, catalogs with variable attributes, and rapid prototyping where the schema is evolving. Not ideal for transactions or complex joins.

Redis: in-memory key-value store for caching, sessions, real-time leaderboards, and pub/sub messaging. Extremely fast (sub-millisecond reads). Use alongside your primary database, not as a replacement.

When to use SQL (PostgreSQL, MySQL): structured data with relationships, complex queries, transactions requiring ACID compliance, and data integrity guarantees. The answer for 90% of web applications.

When to use NoSQL (MongoDB, DynamoDB): flexible schemas, document-oriented data, massive write throughput, and horizontal scaling requirements. Evaluate honestly whether you genuinely need these capabilities.

Managed databases: use managed services (AWS RDS, Supabase, PlanetScale, MongoDB Atlas) instead of self-managing databases. Managed services handle backups, updates, scaling, and high availability.

ORM selection: Prisma (modern, type-safe), Drizzle (lightweight, SQL-first), or TypeORM (mature, decorator-based) for TypeScript applications. ORMs accelerate development but can hide performance issues.

Database scaling strategies: optimize queries first (add indexes, fix N+1 queries), add read replicas for read-heavy workloads, implement caching for frequently accessed data, and consider sharding only at extreme scale.

Multi-database architectures: use PostgreSQL for primary data, Redis for caching, and Elasticsearch for search. Multi-database complexity is justified only when a single database genuinely cannot serve all needs.