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PostgreSQL - FULL OUTER JOIN

Last Updated : 12 Jul, 2025

In PostgreSQL, the FULL OUTER JOIN is a powerful feature that combines the effects of both LEFT JOIN and RIGHT JOIN. This join operation retrieves all rows from both tables involved in the join, including unmatched rows from each table. For any unmatched rows, PostgreSQL fills the result with NULL values for the columns of the table lacking a match.

In this article, we will explain the syntax and practical use cases of FULL OUTER JOIN, providing examples with detailed outputs. By the end, we will have a complete understanding of how to use FULL OUTER JOIN effectively in our PostgreSQL database queries to generate understanding and comprehensive reports.

This feature is essential for scenarios where both matching and non-matching data are required, such as in data integration, comparative analysis, or comprehensive reporting. FULL OUTER JOIN allows us to bring together data from two sources without losing any information, even if there are gaps in matching records.

Syntax

SELECT table1.column1, table1.column2, table2.column1, ....
FROM table1 
FULL JOIN table2 ON table1.matching_column = table2.matching_column;

Or alternatively:

SELECT table1.column1, table1.column2, table2.column1, ....
FROM table1 
FULL OUTER JOIN table2 ON table1.matching_column = table2.matching_column;

• table1: The first table in the join operation.
  
• table2: The second table in the join operation.
  
• matching_column: The column common to both tables used to match rows.

The Venn diagram for FULL OUTER JOIN is given below:

Let us take a look at some of the examples of FULL OUTER JOIN in PostgreSQL to better understand the concept. In this article, we will be using the sample DVD rental database, which is explained here and can be downloaded by clicking on this link in our examples.

In this example, we’ll fetch details of all films along with their actors. We’ll use the film table and actor table to retrieve data, including any records that don’t have a matching pair in the other table.

Query:

SELECT
    title,
    first_name,
        last_name
FROM
    film f
FULL OUTER JOIN actor a ON a.actor_id = f.film_id;

Output

Explanation:

• This query retrieves all films (film table) and all actors (actor table).
  
• If a film doesn’t have an actor associated, the actor_first_name and actor_last_name columns will contain NULL.
  
• Similarly, if an actor isn’t associated with any film, the film_title column will contain NULL.

Here we will make a query for all the films and the language of the movie using the "film" table and "language" table from our sample database.

Query:

SELECT
    title,
    name
FROM
    film f
FULL OUTER JOIN language l ON l.language_id = f.film_id;

Output

Explanation:

• This query retrieves all records from the film table with their respective languages from the language table.
  
• If a film does not have an associated language, language_name will be NULL.
  
• If a language does not have any films associated with it, film_title will be NULL.

• FULL OUTER JOIN in PostgreSQL combines the results of both LEFT JOIN and RIGHT JOIN.
  
• Since FULL OUTER JOIN includes unmatched rows with NULL values, it's essential to handle NULL values appropriately in subsequent data processing steps, such as using COALESCE() or CASE statements to manage NULL values based on specific requirements.
  
• FULL OUTER JOINs can be more resource-intensive compared to INNER JOINs or other types of joins, especially with large datasets.
• Common applications of FULL OUTER JOIN include data integration tasks, comparing datasets, and generating comprehensive reports.

In PostgreSQL, the FULL OUTER JOIN is an essential tool for cases where we need a complete view of two tables, including both matching and non-matching records. By using FULL OUTER JOIN, we ensure that no data is left out, which is particularly useful in data integration, report generation, and comparative analysis.

However, because FULL OUTER JOIN can be resource-intensive, it's crucial to use it selectively and optimize queries for large datasets. By handling NULLs effectively and monitoring performance, we can use FULL OUTER JOIN to create insightful and comprehensive reports that bring together diverse data sources in PostgreSQL.

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