10 Database Design Best Practices Every Developer Should Know

Database design is one of the most critical aspects of application development. A well-designed database can make your app fast, scalable, and maintainable. A poorly designed one? You'll be drowning in technical debt before you know it.

Whether you're building a startup MVP or an enterprise system, these 10 best practices will help you create robust database schemas that stand the test of time.

1. Follow Naming Conventions Religiously

Consistency is key. Choose a naming convention and stick to it across your entire schema. Here's what works:

• Tables: Plural nouns (e.g., users, orders, products)
• Columns: snake_case (e.g., created_at, user_id)
• Primary Keys: Simple id or descriptive like user_id
• Foreign Keys: table_name_id (e.g., author_id references users.id)

2. Normalize to Third Normal Form (3NF)... Usually

Database normalization eliminates data redundancy and ensures data integrity. Aim for Third Normal Form (3NF) in most cases:

• 1NF: Atomic values (no arrays or lists in cells)
• 2NF: No partial dependencies (all columns depend on the entire primary key)
• 3NF: No transitive dependencies (no column depends on another non-key column)

When to denormalize: For read-heavy applications or analytics, strategic denormalization can boost performance. But always normalize first, then denormalize deliberately.

3. Use the Right Data Types

Choosing the correct data type saves storage space and improves query performance:

• Integers: Use INT for IDs, not VARCHAR
• Booleans: Use BOOLEAN, not TINYINT or strings
• Dates: Use TIMESTAMP or DATE, not strings
• Text: Use VARCHAR(n) with appropriate length, or TEXT for large content
• JSON: Use native JSON or JSONB (Postgres) for flexible data

4. Always Define Primary Keys

Every table needs a primary key. No exceptions. Use auto-incrementing integers (SERIAL in Postgres, AUTO_INCREMENT in MySQL) or UUIDs for distributed systems. Primary keys ensure uniqueness and are essential for relationships.

5. Index Wisely, Not Wildly

Indexes speed up reads but slow down writes. Index columns you frequently query:

• Foreign keys (for JOIN operations)
• Columns in WHERE clauses
• Columns in ORDER BY clauses
• Frequently searched fields (email, username)

Don't index: Small tables (<1000 rows), columns that change frequently, or low-cardinality columns (like boolean flags).

6. Use Foreign Keys for Referential Integrity

Foreign key constraints prevent orphaned records and maintain data consistency. Always define them, and specify the appropriate ON DELETE and ON UPDATE actions (CASCADE, SET NULL, RESTRICT) based on your business logic.

7. Add NOT NULL Constraints Where Appropriate

If a column should always have a value, make it NOT NULL. This prevents bugs and makes your data more reliable. Common examples: created_at, user_id, status.

8. Include Timestamp Columns

Always add created_at and updated_at to every table. You'll thank yourself later when debugging or analyzing user behavior. Set created_at to DEFAULT CURRENT_TIMESTAMP and use triggers or application logic for updated_at.

9. Plan for Soft Deletes

Instead of permanently deleting records, add a deleted_at column. This allows data recovery, maintains audit trails, and preserves referential integrity. Filter soft-deleted records in your queries with WHERE deleted_at IS NULL.

10. Document Your Schema

Use database comments to document tables and columns. Future you (and your teammates) will appreciate it:

COMMENT ON TABLE users IS 'User accounts and authentication data';
COMMENT ON COLUMN users.email IS 'Primary contact email, must be unique';

Even better: Use tools like Structa to visually design and auto-generate documented schemas from natural language descriptions.

Bonus: Use Migration Files

Never modify your production database schema manually. Always use migration files (with tools like Prisma, Flyway, or Liquibase) to track changes, enable rollbacks, and keep your development and production environments in sync.

Try It Yourself

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