Data ScienceSQL

UNION vs UNION ALL - Key Differences Explained with Examples

Last Updated: 8th August, 2024

Arunav Goswami

Data Science Consultant at almaBetter

Explore the key differences between UNION and UNION ALL. Understand their use cases, performance impacts, error handling, and compatibility across SQL databases

When working with SQL databases, it's common to retrieve data from multiple tables using various techniques. One such technique involves combining the results of two or more queries. In SQL, there are two primary operators for this purpose: UNION and UNION ALL. Understanding what is the difference between UNION and UNION ALL is crucial for writing efficient and accurate SQL queries. This article delves into the distinctions, use cases, and performance considerations for each operator.

What is UNION?

In SQL, the UNION operator is used to combine the results of two or more SELECT statements. It removes duplicate rows between the various SELECT statements, ensuring that the final result set contains only unique rows. Each SELECT statement within the UNION must have the same number of columns in the result sets with similar data types in the corresponding columns.

Syntax:

SELECT column1, column2, ...
FROM table1
UNION
SELECT column1, column2, ...
FROM table2;

What is UNION ALL?

The UNION ALL operator, like UNION, is used to combine the result sets of two or more SELECT queries into a single result set. However, unlike UNION, UNION ALL does not remove duplicates. It includes all rows from the queries, including duplicates.

Syntax:

SELECT column1, column2, ...
FROM table1
UNION ALL
SELECT column1, column2, ...
FROM table2;

Difference Between UNION and UNION All in SQL

Duplicate Elimination

UNION: Automatically removes duplicate rows from the result set. This means that each row in the combined result set is unique.
UNION ALL: Does not remove duplicates. It includes every row from the input queries, even if there are duplicates.

Performance

UNION: Because it removes duplicates, UNION must perform additional work. This can involve sorting the result set or comparing each row with the others to ensure uniqueness. Consequently, UNION can be slower, especially with large datasets.
UNION ALL: As it does not remove duplicates, UNION ALL is generally faster than UNION. It simply concatenates the result sets, making it more efficient in terms of processing time.

Use Cases

UNION: Ideal when you need a combined result set with no duplicates. For instance, when combining lists of unique items from different sources where duplicate entries are not desired.
UNION ALL: Suitable when duplicates are acceptable or even desired. It's also useful when performance is a critical factor, and you must avoid the overhead of duplicate removal.

UNION ALL vs UNION: Practical Examples

Let's say we have two tables, Employees and Managers, and we want to create a list of all distinct names from both tables.

Employees Table:

EmployeeID	Name
1	Alice
2	Bob
3	Charlie

Managers Table:

ManagerID	Name
1	Bob
2	Dave
3	Eve

SQL Query Using UNION:

SELECT Name FROM Employees
UNION
SELECT Name FROM Managers;

Result:

Name
Alice
Bob
Charlie
Dave
Eve

This query will return a combined list of names from both tables without duplicates.

SQL Query Using UNION ALL:

SELECT Name FROM Employees
UNION ALL
SELECT Name FROM Managers;

Result:

Name
Alice
Bob
Charlie
Bob
Dave
Eve

Explanation:

The UNION ALL query combines the results from both Employees and Managers tables.
Unlike UNION, it does not remove the duplicate entry for "Bob". All entries from both tables are included in the result set.

Union vs Union All in SQL

Here's a tabular comparison of UNION and UNION ALL in SQL:

Feature	UNION	UNION ALL
Definition	Combines the results of two or more SELECT queries and removes duplicates.	Combines the results of two or more SELECT queries without removing duplicates.
Duplicates Handling	Removes duplicate rows from the result set.	Keeps all duplicate rows in the result set.
Performance	Slower due to the need to eliminate duplicates.	Faster because it does not need to check for duplicates.
Use Case	Use when you need a distinct list of records.	Use when you need all records, including duplicates.
Order of Results	Not guaranteed, as duplicates are removed; sorting may be needed.	Not guaranteed, but typically follows the order of the combined results.
Result Set Size	Potentially smaller due to duplicate elimination.	Can be larger because it includes all duplicates.
Memory Usage	Higher, as it needs to store and compare results to remove duplicates.	Lower, as it does not need additional memory for comparison.
Use with Aggregates	Often used when combining results of aggregate functions where distinct results are required.	Suitable for aggregations where all records, including duplicates, are needed.
Index Utilization	Can potentially use indexes less effectively due to the deduplication process.	Can leverage indexes more effectively as it simply appends results.
Execution Plan Complexity	More complex execution plan due to duplicate removal process.	Simpler execution plan as it just combines the results.
Data Integrity	Ensures data integrity by eliminating duplicates, which might be necessary for certain analytical tasks.	Maintains raw data integrity without alteration, suitable for raw data analysis.
Potential Use Cases	Merging lists of unique values (e.g., combining customer IDs)	Combining logs or records where all entries, including repeats, are needed

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Union vs Union All Performance Considerations

When deciding between UNION and UNION ALL, performance is a significant factor. UNION’s additional step of removing duplicates can lead to higher CPU and memory usage, particularly with large datasets. Conversely, UNION ALL's lack of this step means it can handle larger volumes of data more efficiently.

Benchmarking Performance

To illustrate the performance difference, consider a database with millions of rows. Running a UNION query on such a dataset will take considerably longer than a UNION ALL query due to the overhead of deduplication. For high-performance applications, especially where duplicate rows are acceptable, UNION ALL is typically the preferred choice.

Best Practices: Union vs Union All

Use UNION when data uniqueness is crucial: If your result set must have unique rows, opt for UNION. This ensures that your data integrity is maintained.
Prefer UNION ALL for performance: If you can tolerate duplicates or if performance is a primary concern, use UNION ALL. This is especially true for large datasets or time-sensitive queries.
Optimize query structure: Regardless of which operator you choose, ensure your queries are optimized. This includes indexing, minimizing subqueries, and selecting only the necessary columns.

Conclusion

Both UNION and UNION ALL are powerful tools for combining data from multiple queries. The choice between them depends on your specific needs—whether you prioritize data uniqueness or performance. By understanding their differences and use cases, you can write more efficient and effective SQL queries. Always consider the nature of your data and the requirements of your application when deciding which operator to use.

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