Adventures in Machine Learning

Mastering Data Integrity: The Distinct vs Unique Keywords in SQL

The Distinct Keyword in SQL

When working with SQL databases, we often find ourselves in situations where we need to retrieve data from tables. The SELECT statement is one of the most commonly used statements in SQL, and it enables us to retrieve data from one or more tables.

However, sometimes the result set contains duplicate rows, and in such cases, we need to use the DISTINCT keyword to eliminate duplicates.

Purpose of DISTINCT keyword

The DISTINCT keyword is used to eliminate duplicate rows from a result set. When used with the SELECT statement, it returns a unique set of values from a specified column or a set of columns.

The DISTINCT keyword only looks at the specified columns and eliminates duplicates based on those columns’ values. It does not consider other columns that are not part of the SELECT statement.

Example of DISTINCT in SQL

Let’s consider the Cars table, which contains columns for Brand and ProductionYear. Suppose we want to retrieve a list of distinct car brands.

We can use the following SQL statement:


Suppose the Cars table contains the following data:

| Brand | ProductionYear |


| Ford | 2010 |

| Chevrolet| 2009 |

| Ford | 2010 |

| Dodge | 2011 |

| Chevrolet| 2012 |

The result of the above SQL statement would be:

| Brand |


| Ford |

| Chevrolet|

| Dodge |

The DISTINCT keyword has eliminated the duplicate entries of “Ford” and “Chevrolet,” so we get a unique set of values from the Brand column.

The Unique Keyword in SQL

As we work with SQL databases, we want to ensure data integrity by preventing duplicate entries in columns where uniqueness is required. The UNIQUE keyword is used to enforce a constraint on a column and ensure that the values in that column are unique.

Purpose of UNIQUE keyword

The UNIQUE keyword is used to enforce a constraint on a column or a set of columns in a table. It ensures that each record’s values in that column or set of columns are unique and prevents duplicate entries.

The UNIQUE constraint can be applied to a single column or a set of columns. When we apply the UNIQUE constraint to a set of columns, it ensures that the combination of values in those columns is unique.

Example of UNIQUE in SQL

Let’s consider the Person table, which contains columns for SSN and Nationality. Suppose we want to ensure that the SSN column’s values are unique.

We can use the following SQL statement:



SSN varchar(11) UNIQUE,

Nationality varchar(255),



Suppose we want to insert a new person’s data with the following information:

INSERT INTO Person (SSN, Nationality) VALUES (‘123-45-6789’, ‘American’);

Suppose the Person table already contains a record with the same SSN number. In that case, we would get an error message indicating that the UNIQUE constraint has been violated:

Error: Duplicate entry ‘123-45-6789’ for key ‘SSN’

The UNIQUE keyword has prevented us from inserting a duplicate entry in the SSN column, ensuring data integrity.


Distinct and Unique keywords play a critical role in ensuring data accuracy and integrity in SQL databases. By using the DISTINCT keyword, we can eliminate duplicate rows from result sets, while the UNIQUE keyword ensures the uniqueness of columns and sets of columns.

Employing these techniques in our SQL queries and table designs will help us maintain high-quality data with fewer errors and ensure that we can make informed decisions based on the information stored in our databases. When it comes to data integrity in SQL databases, UNIQUE and DISTINCT are two crucial keywords that every SQL developer should know.

These two keywords help to establish the correctness of the data through ensuring that duplicate entries are avoided, and results are accurate. In this article, we discuss the differences between UNIQUE and DISTINCT keywords in SQL, their usage, and the importance of hands-on practice for SQL developers to master these database concepts.

Differences between UNIQUE and DISTINCT

Firstly, the DISTINCT keyword is used only in SQL SELECT statements, while the UNIQUE keyword is used with ALTER TABLE and CREATE TABLE statements. The two keywords serve different functions, and one cannot replace the other.

The DISTINCT keyword is used to filter out duplicate rows from the result set of a SELECT statement. It evaluates the specified column or columns’ distinct values and filters the duplicates out to return only a unique set of values.

The UNIQUE keyword, on the other hand, is used as a database constraint, either on a single column or a combination of columns. This keyword ensures that values in a column or a set of columns are unique, ensuring that the column(s) remain free of duplicates.

Another significant difference between the two keywords is that while DISTINCT eliminates duplicates from a result set, it does not modify the underlying data. It merely filters duplicates out temporarily to present it in a result set.

In contrast, a UNIQUE constraint modifies the underlying table structure to ensure the uniqueness of data in columns and sets of columns. Data must be modified or added considering the UNIQUE constraint’s specifications, which ensures future data remains free from duplicates and errors.


The UNIQUE keyword, as a database constraint, is used to prevent duplicates from being inserted or updated in a column or a set of columns while inserting or updating new records. It ensures that the data in the columns remain unique, enabling efficient and accurate data querying, analysis, and decision making.

The UNIQUE constraint is the primary method of ensuring data quality in SQL databases. For example, in a company’s employee database, the Social Security Number (SSN) or Employee ID column(s) would need a UNIQUE constraint to prevent duplicate creation of employees’ data.

On the other hand, the DISTINCT keyword modifies the query results within a SELECT statement. It is particularly useful when querying columns with repetitive data, such as names, dates, or country names.

For example, when you want to list the cities or countries where the company has branches, the DISTINCT keyword will eliminate the repeats of each city or country’s names to return a unique list of cities or countries.

Importance of hands-on practice for SQL developers

In order to become an expert in SQL and truly understand the differences between the UNIQUE and DISTINCT keywords, hands-on practice is essential. Technical theory and understanding data models is just the beginning; building and querying databases using SQL is a practical application that requires hands-on know-how.

Luckily, there are many SQL courses and tools available on the internet today that provide developers with the opportunity to practice real problems, test their knowledge, and build their understanding. One way to get hands-on experience is by using offers SQL-course and a SQL Practice Set that provides developers with real-world industry problems. The Practice Set includes a free SQL editor that allows you to test and practice writing SQL code without the need to set up an environment or database.

It incorporates different SQL concepts, which will challenge developers and provide them with the opportunity to improve their SQL writing abilities. In conclusion, SQL provides us with an effective and efficient method of storing and accessing data.

Distinct and Unique keywords, though different in use, are fundamental in maintaining data integrity and ensuring data accuracy within a database. By practicing SQL and using available resources such as those found at, SQL developers can master and use these keywords to build and manage efficient and productive databases.

In conclusion, the DISTINCT and UNIQUE keywords are fundamental in maintaining data accuracy and integrity in SQL databases. While the DISTINCT keyword filters out duplicates from a result set, the UNIQUE keyword, as a database constraint, ensures that values in a column or set of columns remain unique.

The two keywords play different functions and cannot replace each other. SQL developers must have hands-on practice on these keywords for database efficiency and productivity.

Using resources like enables developers to learn and apply these concepts effectively. As data becomes increasingly important in today’s world, understanding and applying these concepts will ensure accurate and quality data results.

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