UNION vs JOIN in SQL

The more you add to the databases, the more often SQL must combine data from multiple ta

bles within the database. There are two operators for this, SQL UNION Operator and SQL JOIN Operator. They do quite different jobs and could be confused with one another if you don’t know when you’re using one versus the other. Both are used in retrieving and making data available, but knowing how to differ between UNION and JOIN can save you a great deal of time in querying and manipulating your data. SQL UNION vs JOIN, their usage, and syntax, combined with when to prefer one over the other through clear examples and tables in this article.

Understanding SQL Joins and Unions

Both SQL UNION and SQL JOIN are used to combine data, but they do so in fundamentally different ways:

• SQL JOIN: Combines columns from two or more tables based on a related column between them. It allows combining data side-by-side, row by row, when certain conditions are met.
• SQL UNION: Combines the result sets of two or more SELECT queries into a single result set. It appends the rows from the second query to the first, making it useful for stacking results from different queries.

SQL JOIN Types

Before you get into a difference between UNION and JOIN, it’s necessary to have a basic understanding of the SQL JOIN types. Joins differ through combining rows from different tables, where some conditions are met.

• INNER JOIN: Pulls out only those rows with matches in both tables.
• LEFT JOIN: Returns all rows from the left table, and includes matched rows from the right table. If there are no matching rows, the result is NULL on the right side.
• RIGHT JOIN: This returns the rows of the right table and also corresponding rows from the left table with a NULL value for non-matching rows.
• FULL JOIN: Returns all rows from both tables. Where the rows do not match in the two tables, NULLS will be provided.

Example of SQL JOIN

Let’s take two tables, Customers and Orders, to demonstrate how JOIN works.

Customers Table

CustomerID	CustomerName
1	John
2	Lisa
3	Mike

Orders Table

OrderID	CustomerID	OrderDate
101	1	2024-10-10
102	2	2024-10-11
103	4	2024-10-12

SQL JOIN Example (INNER JOIN)

SELECT Customers.CustomerName, Orders.OrderDate
FROM Customers
INNER JOIN Orders
ON Customers.CustomerID = Orders.CustomerID;

Result of INNER JOIN:

CustomerName	OrderDate
John	2024-10-10
Lisa	2024-10-11

SQL UNION Operator

The SQL UNION operator combines the result sets of two or more SELECT statements. It eliminates duplicate rows unless the UNION ALL operator is used, which includes all duplicates.

SQL UNION Syntax

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

To use UNION, the SELECT statements must have the same number of columns and the corresponding columns must have compatible data types.

Example of SQL UNION

Let’s say we have two tables of customer information from different regions.

Customers_USA Table

CustomerID	CustomerName
1	John
2	Lisa

Customers_Canada Table

CustomerID	CustomerName
3	Mike
4	Emma

If we want to combine both tables into a single result set, we can use UNION:

SELECT CustomerID, CustomerName FROM Customers_USA
UNION
SELECT CustomerID, CustomerName FROM Customers_Canada;

Result of UNION:

CustomerID	CustomerName
1	John
2	Lisa
3	Mike
4	Emma

In this example, UNION combines the rows from both tables into one unified result.

Difference Between UNION vs JOIN in SQL

Though both UNION and JOIN are used to combine data, their purposes and mechanisms are different:

Feature	UNION	JOIN
Data Combination	Combines result sets vertically (appending rows).	Combines result sets horizontally (merging columns).
Number of Columns	SELECT statements must have the same number of columns.	Can combine tables with different column structures.
Duplicate Removal	UNION removes duplicates, UNION ALL includes duplicates.	No duplicate removal (unless specified).
Use Case	Used when combining data from separate result sets (e.g., different tables with the same structure).	Used to merge data from related tables based on a relationship.
Performance Consideration	UNION requires sorting to remove duplicates, which can slow performance.	Joins can be optimized with indexes on join conditions.

SQL UNION vs JOIN Examples

Let’s illustrate the difference between UNION and JOIN with practical examples using the same Customers_USA and Customers_Canada tables.

SQL UNION Example

SELECT CustomerID, CustomerName FROM Customers_USA
UNION
SELECT CustomerID, CustomerName FROM Customers_Canada;

Result of UNION:

CustomerID	CustomerName
1	John
2	Lisa
3	Mike
4	Emma

SQL JOIN Example (FULL OUTER JOIN)

Suppose now that we have two separate tables – Customers and Orders – where we want to join the customer names with their respective orders, making sure that all of our customers and orders come together. FULL OUTER JOIN will do it for us.

SELECT Customers.CustomerName, Orders.OrderID
FROM Customers
FULL JOIN Orders
ON Customers.CustomerID = Orders.CustomerID;

Result of FULL OUTER JOIN:

CustomerName	OrderID
John	101
Lisa	102
Mike	NULL
NULL	103

When to Use UNION in SQL

The SQL UNION operator is used when you need to combine the results of two or more SELECT statements into a single result set while ensuring that duplicate rows are eliminated. This operator is particularly useful in scenarios where data is stored across multiple tables and you want to create a cohesive dataset for analysis or reporting. For instance, if you have customer information spread across different regional tables, you can use UNION to merge these datasets into one comprehensive list. It’s essential that the SELECT statements being combined have the same number of columns with compatible data types, as this ensures the integrity of the resulting dataset. Additionally, UNION is ideal for creating distinct lists from similar datasets, making it a powerful tool for data consolidation and reporting in SQL applications.

• Combining separate datasets: Use the UNION when you have the need to combine the result of two SELECT statements but where the tables involved have no direct link but do share the same column structure.
• Stacking query results : Suitable for appending results from different regions or different time periods to one unified list.

Example: Combining Sales from Different Years

SELECT SaleID, SaleAmount FROM Sales_2023
UNION
SELECT SaleID, SaleAmount FROM Sales_2024;

When to Use JOIN in SQL

• Merging related tables: Include correlated tables Merging related tables use JOIN when you need to access joined information from more than one table based on a common key, CustomerID or ProductID.
• Data enrichment: JOIN works great when one wants to enrich the data by introducing columns that exist in another table related to the first one.

Example: Joining Orders with Customer Data

SELECT Orders.OrderID, Customers.CustomerName
FROM Orders
JOIN Customers
ON Orders.CustomerID = Customers.CustomerID;

SQL UNION ALL vs UNION

The UNION ALL operator is like UNION except that it includes all rows, even if they are duplicates. This could be useful when the duplicates in the result set have meaning and improves performance because it avoids the overhead of eliminating duplicates.

Example: SQL UNION ALL

SELECT CustomerID, CustomerName FROM Customers_USA
UNION ALL
SELECT CustomerID, CustomerName FROM Customers_Canada;

Result of UNION ALL:

CustomerID	CustomerName
1	John
2	Lisa
3	Mike
4	Emma
1	John
2	Lisa

Here, the same customers might appear multiple times if they exist in both tables.

UNION and JOIN Performance Considerations

Both UNION and JOIN can, hence be very performance-intensive if applied in the right manner.

• UNION operations are slower than JOIN because JOIN doesn’t require removing duplicates unless UNION ALL is used.
• JOIN operations can also be optimized by indexing the columns used for the joining, which improves speed of execution of queries.
• JOIN can return a larger result set because it combines data horizontally, while UNION combines it vertically.

Advantages of UNION vs JOIN in SQL

UNION and JOIN operators are used in SQL to combine data from two or more tables. They have different purposes. Knowing the differences in advantages of UNION and JOIN will set where best to use each of them depending on a use case. Here are some of the advantages of each:

Benefits of UNION Over JOIN

1. Combine Data That Originates from Different Sources

Union of Results: UNION is useful if you have two or more independent queries that return the same number of columns and whose data types can be combined. Stacks rows- it adds one result to another.

2. DOES NOT eliminate duplicates by default

Duplicates Removed: The default UNION removes duplicate rows from the result set. You would avoid repetitions there as well. This is helpful when merging data where you only want to get a distinct number of rows in the end.

3. Combines Data Without Relationships

No Join Condition Required: UNION is very useful when the tables to be merged are not directly related through keys or any join conditions. It enables merging data across different sources even when there is no common field connecting the two data sets.

4. Facilitates Easier Queries in Specific Situations

Less Complex than JOIN: UNION makes the query less complex while you want to combine data from two or more queries where you are querying different tables or conditions. It doesn’t make any sense to use a lot of JOINs; instead you use independent queries, each one gets run and then results merged.

5. From Vertically Different Tables

Better for Similar Structures: UNION is easier to use when you need to join together data coming from tables with similar structures but not necessarily part of a normalized database schema. For example, it would be more convenient with UNION if you needed to join together two customer data bases from two different systems that have the same types of fields.

Advantages of JOIN Over UNION

1. Combines Data Horizontally (Across Columns)

JOINs merge horizontally (across columns). This means that JOINs are designed specifically for combining rows of two or more tables based on a related column, often in a primary key-foreign key relationship. Use this type of merge to join data of related things, such as customers and their orders, into a result set that spans multiple columns.

2. Preserves All Data by Default

Retains All Matching Rows: JOIN does not delete the duplicate unless you specifically instruct it to do so. It works based on the relationship specified, which can be INNER JOIN, LEFT JOIN, etc. and ensures that the result contains all rows from all tables.

3. Handles Complex Relationships

Better for complex queries when multiple tables are related through keys and you need to fetch related information. For example, using JOIN is more suited for querying customers, orders, and order details in a single query than using UNION.

4. More suited for relational databases

Optimized for Key Relations: JOIN happens to be relatively much faster and better in its performance when dealing with the relational databases which connect tables together through keys. Because it taps into indexes and keys for merging related information, it would be more preferable over normalized database structures.

5. Combines Data from Multiple Tables in a Single Query

Multiple Table Relationships: JOIN allows multiple tables to be joined into a single query based on relationships, an important aspect of relational databases. UNION cannot be used because it simply combines result sets and not related data across tables.

Key Differences in Advantages

1. Data Structure Compatibility
   • UNION: Requires the same number of columns and compatible data types in both queries.
   • JOIN: Combines data from multiple tables with no restrictions on the number of columns or types, as long as there’s a relationship between tables.
2. Duplication Handling
   • UNION: Automatically removes duplicates unless UNION ALL is used.
   • JOIN: Does not remove duplicates unless specified, making it suitable for relational data where duplicates are meaningful.
3. Query Complexity
   • UNION: Simpler for combining independent datasets.
   • JOIN: More appropriate for querying related data spread across multiple tables.

Disadvantages of UNION vs JOIN in SQL

Both UNION and JOIN have their specific use cases and limitations. Understanding the disadvantages of each can help developers decide when to use one over the other.

UNION Disadvantages Compared to JOIN

1. Performance Impact

Slower Performance: UNION can be slower than JOINs, especially when dealing with a large amount of data. That is because UNION must first execute both result sets and then take an extra step to remove any duplicates (unless it uses UNION ALL). That extra step can make the query performance much slower.

2. Same Number of Columns

Strict Column Matching: When applying UNION, the two queries must yield an equal number of columns with compatible data types. If your queries are not already aligned, such limitation necessitates a change or transformation of your data that makes the former less adaptable than JOIN, which allows for combining data even when different tables have structures that are dissimilar.

3. Limited to Vertical Data Combination

Combines Vertically Not Horizontally: UNION combines result sets vertically, that is stacking rows. It does not support merging rows from related tables horizontally like JOIN. If you need to combine related rows across several tables, then using UNION would not be the right approach and JOIN would be the better solution .

4. Cannot Combine Data on Relationships

No Table-Level Relationship: UNION doesn’t employ table-level relationships such as primary and foreign keys to combine data. If you needed to join two tables into a single resulting set based on a related column, you would use JOIN rather than UNION.

5. Handling of Duplicates Can Be Expensive

Automatic Duplicates Elimination (With UNION): UNION, by its nature, removes duplicates automatically. This can be considered overhead if you don’t care about duplicates. You could use UNION ALL to avoid this overhead, but then pay for it with more processing time if your data sets are large.

Disadvantages of JOIN Over UNION

1. More Complex Queries

Complex Syntax and Logic: JOINs, especially those that use multiple tables, can be quite arduous and difficult to write, read, and maintain. Taken syntactically, it could also get very complex, not least because of distinct join types such as INNER, LEFT, RIGHT, FULL or when one must work with a considerable number of tables, which may make it more error-prone than the simple UNION structure.

2. Relationship-Dependent

Must have Join Condition: JOINs must have a defined relationship between tables that might be represented by a foreign key or common column. If there is no such relationship between tables, then JOIN is not applicable and you might need to rephrase your query. However UNION can stitch together two distinct datasets without any commonality and with no defined relationship.

3. Data Duplication

Duplicates Not Removed: JOIN does not remove duplicates unless this is stated like UNION, sometimes resulting in duplicate rows where data from two tables is joined together, specially when using many-to-many relationships that would also need distinct clauses or further filtering.

4. Can be slower with complex joins

Performance under Big Data and Complex JOINs. JOINs that involve more than one table or have complex conditions, such as conditions on non-indexed columns, slow down the performance of the application. The complexity and the number of potential bottlenecks may increase dramatically with the addition of more tables, especially for large databases.

5. Risk for Unexpected Data Growth

Cartesian Products with Improper Joins: JOINs without proper join conditions may produce Cartesian products-all rows of one table combined with every row of another-resulting in what you might find surprising as an unexpectedly large result set that, if it shows up at the wrong time, can adversely affect the performance and readability of your output. This is particularly so if there are CROSS JOINs or a failure to specify a join condition.