NoSQL vs SQL
Understand when to use SQL vs NoSQL — relational databases, document stores, key-value stores, graph databases, and polyglot persistence.
55 min•By Priygop Team•Last updated: Feb 2026
Database Types
- Relational (SQL): PostgreSQL, MySQL, SQL Server — structured data with relationships. ACID transactions guarantee consistency. Best for: financial data, user accounts, inventory, anything with relationships
- Document (NoSQL): MongoDB, CouchDB — store JSON-like documents. Flexible schema (fields can vary per document). Best for: content management, user profiles, product catalogs with varying attributes
- Key-Value: Redis, DynamoDB — simple get/set by key. Fastest for lookups. Best for: caching, session storage, real-time leaderboards, rate limiting
- Column-Family: Cassandra, HBase — optimized for writes and wide rows. Best for: time-series data, IoT sensor data, event logging at massive scale
- Graph: Neo4j, Amazon Neptune — nodes and relationships are first-class. Best for: social networks, recommendation engines, fraud detection, knowledge graphs
- When SQL: Data has clear relationships, need ACID transactions, complex queries with JOINs, data integrity is critical. When NoSQL: Schema varies, horizontal scaling needed, simple access patterns, high write throughput