SQL databases enforce structure and relationships; NoSQL databases trade some structure for flexibility and horizontal scale. Modern data teams routinely use both — the skill is matching the tool to the data.
Key Points
- SQL (MySQL, PostgreSQL): tables, joins, ACID transactions, mature tooling
- NoSQL families: document (MongoDB), key-value (Redis), column (Cassandra), graph (Neo4j)
- SQL scales vertically + replicas; NoSQL scales horizontally by sharding
- Strong consistency vs eventual consistency trade-offs (CAP theorem)
- Analytics and reporting overwhelmingly speak SQL
- Interview-ready line: structured relational data → SQL; massive flexible-scale data → NoSQL
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