Start with Requirements and Entities
Good database design begins with understanding the information a system must store and the operations users need to perform. Identify the main entities, such as customers, orders, products, and payments, then list their attributes and business rules.
Draw a simple entity relationship diagram before writing migrations. Confirm which fields are required, which values must be unique, how records relate, and what should happen when a related record is deleted.
Choose Keys and Relationships
A primary key uniquely identifies a row. A foreign key links a row to a record in another table and helps enforce referential integrity. Use one-to-many relationships for examples such as one customer having many orders, and many-to-many relationships when records can be associated in both directions.
A many-to-many relationship is commonly represented by a junction table. Give the junction table appropriate foreign keys and a uniqueness rule where duplicate associations are not allowed.
Understand Normalization
Normalization organizes data to reduce duplication and update anomalies. First normal form generally means storing atomic values rather than repeating groups. Second and third normal forms further address dependencies on keys and non-key attributes.
Normalization is a design tool, not a goal to maximize blindly. Some systems intentionally duplicate or aggregate data for reporting and performance, but those choices should be deliberate and supported by a clear update strategy.
Use Data Types and Constraints Carefully
Choose data types that represent the data accurately. Use appropriate numeric types for quantities, dates and timestamps for time values, and decimal types for exact monetary values. Avoid storing structured values as free-form text when they need to be queried or constrained as relational data.
Use NOT NULL, UNIQUE, CHECK constraints where supported, and foreign keys to enforce important rules in the database. Application validation improves user feedback, while database constraints protect data integrity across all write paths.
Indexes and Query Performance
Indexes can speed up lookups, joins, and sorting when they match common query patterns. They also consume storage and add work to inserts, updates, and deletes. Add indexes based on actual queries and execution plans, not by indexing every column.
Review composite index column order, select only needed columns, paginate large result sets, and inspect slow queries with your database's explain tools. Test with realistic data volumes because a schema that performs well with ten rows may not scale.
Plan for Change and Backups
Use version-controlled migrations to evolve schemas consistently across environments. For large tables, plan potentially locking changes carefully and test migration time. Keep backup and restore procedures documented and periodically test that backups can actually be recovered.
Document important relationships, naming conventions, retention rules, and assumptions. A well-designed schema is understandable to the next developer and can evolve as business requirements change.
