What are primary keys in a relational database?

A primary key in a relational database is a column or a set of columns that uniquely identifies each row in a table. Every table must have one primary key, which enforces data integrity by ensuring no two rows have the same key value. The primary key also cannot contain NULL values, meaning every row must have a valid identifier. For example, in a users table, a column like user_id could serve as the primary key, ensuring each user has a distinct identifier. This uniqueness and non-null constraint makes primary keys essential for accurately referencing and managing data across relationships in the database.

Primary keys are critical for establishing relationships between tables. When a primary key from one table is referenced in another table, it becomes a foreign key, linking the two tables. For instance, an orders table might include a user_id column as a foreign key to associate each order with a specific user in the users table. This connection enables efficient querying across related data. Additionally, primary keys are often used by the database to create indexes, which improve query performance by allowing faster lookups. For example, searching for a user by their user_id is quicker because the primary key index organizes the data for optimal access.

While a single column is often sufficient, primary keys can also be composite, combining multiple columns. For example, in an order_items table, the combination of order_id and product_id might form a composite key to uniquely identify each item within an order. When designing primary keys, developers often choose between natural keys (existing data like email addresses) and surrogate keys (system-generated values like auto-incrementing integers). Surrogate keys are common because they avoid dependencies on business logic that might change. For instance, using an auto-incremented employee_id instead of a Social Security number ensures stability even if business rules evolve. Properly chosen primary keys simplify data management and maintain consistency in relational databases.