Databases 101: SQL vs NoSQL

Overview

Relational (SQL) databases store structured data in tables with relationships. NoSQL databases optimize for flexible schemas, scale, or specific access patterns.

When to choose which

SQL: strong consistency, complex queries, transactions (Postgres, MySQL)
NoSQL: flexible schema, high write scale, document or key-value data (MongoDB, DynamoDB)

Key concepts

Normalization vs denormalization
ACID vs eventual consistency
Indexes and query plans
ORMs (Prisma, Sequelize, SQLAlchemy) vs query builders (Knex)

Example schema (SQL)

Tables: users, projects, tasks (FK from tasks->projects)

Checklist

Write a simple ER diagram
Define indexes for frequent queries
Add migrations (Prisma, Alembic, Django migrations)
Seed development data

Resources

postgres.ai learning hub
MongoDB University basics
Prisma data modeling guide