Difference Between Primary Key and Unique Constraints in SQL

When designing a relational database, ensuring data integrity is crucial. SQL provides various constraints to enforce rules on the data stored in tables. Two commonly used constraints are the Primary Key and the Unique Constraint. While they both prevent duplicate values, they have key differences that impact database design and functionality.

What is a Primary Key?

A Primary Key (PK) is a column or a combination of columns that uniquely identifies each record in a table. It is a special constraint that ensures uniqueness and prevents NULL values.

Key Characteristics of a Primary Key:

• Uniqueness: No two rows in the table can have the same primary key value.
• Not Null: A primary key column cannot contain NULL values.
• Single Primary Key per Table: Each table can have only one primary key, though it can be composed of multiple columns (composite primary key).
• Used for Relationships: Primary keys are often used as foreign keys in other tables to establish relationships.
• Clustered Index: By default, a primary key is a clustered index in the table.
• Auto Increment: A primary key supports an auto-increment value.

Example of a Primary Key:

CREATE TABLE Employees (
    EmployeeID INT PRIMARY KEY,
    Name VARCHAR(100),
    Email VARCHAR(100)
);

In this example, EmployeeID is the primary key, ensuring that each employee has a unique ID and that the field cannot be left blank.

What is a Unique Constraint?

A Unique Constraint ensures that the values in a column (or a set of columns) are distinct across all rows in the table. Unlike a primary key, a unique constraint allows NULL values (but typically only one NULL per column).

Key Characteristics of a Unique Constraint:

• Ensures Uniqueness: Prevents duplicate values in the specified column(s).
• Allows NULL Values: A column with a unique constraint can contain NULL values (only one NULL value per column).
• Multiple Unique Constraints Per Table: A table can have multiple unique constraints applied to different columns.
• Non-Clustered Index: By default, a unique key is a unique non-clustered index.
• No Auto Increment: A unique key does not support auto-increment.

Example of a Unique Constraint:

CREATE TABLE Employees (
    EmployeeID INT PRIMARY KEY,
    Email VARCHAR(100) UNIQUE,
    PhoneNumber VARCHAR(15) UNIQUE
);

Here, both Email and PhoneNumber columns have unique constraints, ensuring no duplicate emails or phone numbers exist but still allowing the possibility of NULL values.

Key Differences Between Primary Key and Unique Constraint

When to Use Primary Key vs. Unique Constraint?

• Use a Primary Key when you need a unique identifier for each row that does not accept NULL values.
• Use a Unique Constraint when you want to ensure column values remain unique but still allow NULL values.

Frequently Asked Questions (FAQ) About Primary Key vs. Unique Key

1. Can a table have multiple primary keys?

No, a table can have only one primary key, but it can be composed of multiple columns (composite primary key).

2. Can a primary key contain NULL values?

No, a primary key column cannot have NULL values.

3. Can a unique key contain NULL values?

Yes, a unique key column can have NULL values, but usually only one NULL value per column.

4. How many unique keys can a table have?

A table can have multiple unique keys on different columns.

5. Does a primary key automatically create an index?

Yes, by default, a primary key creates a clustered index.

6. Does a unique key automatically create an index?

Yes, by default, a unique key creates a unique non-clustered index.

7. Can an auto-increment column be a unique key?

No, an auto-increment column must be a primary key.

Conclusion

Both Primary Keys and Unique Constraints play essential roles in database design by enforcing data integrity and preventing duplicates. The primary key is crucial for uniquely identifying records and establishing relationships, whereas unique constraints help maintain uniqueness in specific columns without making them mandatory fields.

Understanding these differences helps database administrators and developers structure their tables effectively to optimize performance and data consistency.