SQL vs NoSQL: A Database Selection Guide
Database selection is one of the most critical architectural decisions in software projects. The wrong choice leads to serious performance and scaling issues down the road. SQL or NoSQL?
SQL Databases (Relational)
Store data in tables with predefined schemas, using the SQL query language.
CREATE TABLE users (
id SERIAL PRIMARY KEY,
name VARCHAR(100) NOT NULL,
email VARCHAR(255) UNIQUE NOT NULL
);
SELECT u.name, COUNT(o.id) as order_count
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
GROUP BY u.name;
ACID Guarantees: Atomicity, Consistency, Isolation, Durability
Popular: PostgreSQL, MySQL, SQLite, SQL Server
NoSQL Databases
Flexible schemas, horizontal scaling, and various data models.
Types
- Document Store (MongoDB, Firestore) — JSON-like documents
- Key-Value Store (Redis, DynamoDB) — Simple key→value pairs
- Column-Family (Cassandra, ScyllaDB) — Optimized for analytics
- Graph Database (Neo4j) — Relationship-heavy data
Comparison
| Feature | SQL | NoSQL | |---------|-----|-------| | Schema | Fixed (strict) | Flexible (schemaless) | | Scaling | Vertical (scale up) | Horizontal (scale out) | | Relationships | Strong (JOINs) | Embedded/denormalized | | Consistency | ACID (strong) | BASE (eventual) | | Query language | Standard SQL | Database-specific |
When to Choose
SQL — Complex relational data, transactions (finance), reporting, data consistency critical
NoSQL — Large data volumes, fast reads/writes, flexible schemas, horizontal scaling
Polyglot Persistence
Use the best database for each workload:
User profiles → PostgreSQL (relational)
Sessions → Redis (fast key-value)
Product catalog → MongoDB (flexible schema)
Search → Elasticsearch (full-text)
Analytics → ClickHouse (columnar)
Conclusion
The right answer to "SQL or NoSQL?" is "which do you need?" Use SQL for relational data and consistency. Use NoSQL for flexibility and scaling.
Learn about database design and data strategies in the Software Architecture 3.0 book.