What is Natural Join in SQL? Key Features, Implementation, and Best Practices

SQL JOIN functions combine data from multiple tables based on related columns. They include INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN, and NATURAL JOIN.

NATURAL JOIN automates table matching on common columns, reducing manual effort, eliminating duplicate data, and making queries more concise. It is especially useful in relational databases where frequent joins on common attributes are required for reporting and analytics.

In this blog, you’ll explore what is NATURAL JOIN in SQL, along with examples and best practices.

What Is a Natural Join in SQL? Key Features and Syntax

A NATURAL JOIN is a type of equijoin in SQL that automatically combines tables based on common column names, eliminating the need for an explicit ON condition.

It removes redundancy by excluding duplicate columns in the output, ensuring each common column appears only once. This simplifies queries by automatically joining tables on common column names, reducing redundancy.

NATURAL JOIN matches tables based on common column names, which can lead to unintended results if column names are shared but unrelated. 

Here are its key features.

• Automatic Column Matching

NATURAL JOIN automatically joins tables on columns with the same name and data type without the need for an explicit ON or USING clause.

Example: If an organization has an Employees table and a Departments table, both containing dept_id, the natural join will automatically match them.

• Default INNER JOIN Behavior

NATURAL JOIN works like an INNER JOIN, meaning it only gives rows where matching values exist in both tables. Rows without matches are removed.

Example:
If an employee belongs to a department (dept_id exists in both tables), they appear in the result. However, if an employee has a NULL or missing dept_id, they won’t be included.

• Removes Redundant Columns

Unlike other joins, a NATURAL JOIN removes redundant columns, ensuring only one instance of the common column is given in the output. It does not remove duplicate rows in the result.

Example: A company's Orders and Customers tables both contain customer_id. After a natural join, the final output will show only one customer_id column instead of two, avoiding redundancy.

• Does Not Include Unmatched Rows

NATURAL JOIN behaves like INNER JOINS, meaning unmatched rows are dropped. If you need unmatched records, you must use LEFT JOIN or FULL OUTER JOIN instead.

Example: A school has a Teachers table and a Subjects table, both containing subject_id. If a teacher is assigned to a subject, they appear in the result. However, if a subject has no assigned teacher, it will be excluded from the output.

• No Control Over Join Conditions

Since it automatically joins on all common columns, you cannot specify which column(s) to join on using ON or USING.

Example: A university has a Students table with student_id and date_of_birth, and a Registrations table with student_id and registration_date. A NATURAL JOIN would match on both student_id and date_of_birth = registration_date, which is incorrect and could give wrong results.

• Unintended Joins

If two unrelated columns have the same name but different meanings, the NATURAL JOIN might give incorrect results.

Example: A Sales table has an id column for sales transactions, while an Inventory table has an id column for stock items. A natural join would incorrectly link transactions to inventory items just because both have an id column.

To effectively use a NATURAL JOIN, it's crucial to understand its syntax. Let’s break down its structure and key considerations.

Understanding the Syntax of Natural Join in SQL

To use NATURAL JOIN effectively, it's necessary to understand its syntax and how it automatically determines the join condition. 

Here’s the common syntax for using NATURAL JOIN.

SELECT column_list  
FROM table1  
NATURAL JOIN table2;

The key components of the syntax include:

• SELECT column_list: This specifies the columns to be retrieved. You can also use * to select all columns or explicitly list the needed ones.
• table1 NATURAL JOIN table2: This joins table1 and table2 based on all common column names without the need for an ON or USING clause.

Let’s understand the working of NATURAL JOIN in brief:

• SQL automatically detects matching column names between both tables and joins them.
• The output will not include duplicate columns; only one instance of the matched column will be shown.
• Since NATURAL JOIN behaves like an INNER JOIN, it only includes rows where matching values exist in both tables.

Also Read: 20 Most Common SQL Query Interview Questions & Answers [For Freshers & Experienced]

Knowing the differences between NATURAL JOIN and INNER JOIN helps in selecting the appropriate join for a given dataset. Let’s explore their key differences and when to use each.

Difference Between NATURAL JOIN and INNER JOIN: Key Comparison

While both NATURAL JOIN and INNER JOIN combine rows based on matching values, they differ in how they determine join conditions and handle column selection. 

Here’s a key comparison to understand their differences.

Natural joins can be useful for reducing redundancy and simplifying queries. After understanding what is NATURAL JOIN in SQL, let’s understand how to implement natural join in the next section.

How to Implement a Natural Join in SQL? Step-by-Step Approach

The steps to implement a NATURAL JOIN include identifying common columns, writing the query correctly, and verifying the results after execution.

Here are the steps involved in implementing NATURAL JOIN.

Step 1: Identify common column names across tables

Before using NATURAL JOIN, inspect the tables to find common column names that will be used as the join condition. These columns must:

• Exist in both tables
• Have the same name
• Share the same data type

Note: If there are no common columns or they have different names, NATURAL JOIN will not work correctly.

Step 2: Write an SQL query using NATURAL JOIN

Once common columns are identified, construct the query using the NATURAL JOIN syntax:

SELECT column_list  
FROM table1  
NATURAL JOIN table2;

Key points:

• Replace column_list with specific column names or use * to retrieve all columns.
• Since NATURAL JOIN automatically matches common columns, you do not need to specify an ON or USING clause.

Step 3: Execute the query and retrieve the result

Run the query in your DBMS (MySQL, PostgreSQL, Oracle, etc.) and verify the output. Ensure:

• The output does not contain duplicate column names but may still have duplicate rows if the dataset contains them.
• The result only includes rows with matching values in the common column(s).
• If no matching values exist and columns do not allow NULLs, the result will be empty.

If your result is different from expectations, check the following:

• A common column is missing or mistyped.
• The data contains NULL values, which will exclude rows.
• A different join type (e.g., LEFT JOIN) might be more suitable for your use case.

Learn how to optimize SQL queries, boost performance, and extract deeper insights from data. Join the free course on Advanced SQL: Functions and Formulas.

After exploring the steps to implement NATURAL JOIN in SQL, let’s now understand the workings of NATURAL JOIN in SQL with examples.

Natural Join in SQL with Example: How It Works?

Consider an example where you have two tables: Student (containing student details) and Fee (containing fee payment records). Using NATURAL JOIN in SQL, you retrieve only the students who have a corresponding fee entry, ensuring no duplicate columns.

1. Successful Implementation

Student Table:

Fee Table:

Here’s the query to implement NATURAL JOIn for this case:

SELECT *  
FROM Student  
NATURAL JOIN Fee;

Expected Output:

Explanation:

• NATURAL JOIN automatically joins the tables based on the common column student_id.
• Only students who have a matching entry in both tables appear in the result (Neha is excluded as she has no fee record).
• The output eliminates duplicate student_id columns, keeping only one instance.

While this example successfully works as the student_id column exists in both tables, let’s check out a condition where NATURAL JOIN fails to implement.

2. Failure

Considering the Student and Fee tables do not have any common column names, NATURAL JOIN in SQL will fail or return a Cartesian product.

Student Table:

Fee Table:

SQL query to implement NATURAL JOIN:

SELECT *  
FROM Student  
NATURAL JOIN Fee;

Output:

• Since student_id and student_ref are different column names, NATURAL JOIN will not work.
• If no common column exists, SQL may return an error or a Cartesian product, which results in incorrect and unintended output.

After exploring NATURAL JOIN in SQL with examples, let’s now look at the best practices for using it effectively.

Best Practices and Challenges of Using Natural Joins

Best practices for using NATURAL JOIN include ensuring correct column names, avoiding column name changes, and considering explicit joins for better control.

Here are the best practices to use NATURAL JOIN.

• Give Meaningful Column Names

NATURAL JOIN automatically matches columns with the same name. Make sure these columns actually represent the same data.

Example: If a Projects table and a Teams table both have a column named id, a NATURAL JOIN may create incorrect matches, assuming they represent the same entity.

• Avoid NATURAL JOIN when Column Names Change

If a column name changes in one table but not the other, NATURAL JOIN may break or produce incorrect results.

Example: If the customer_id column in Orders is later renamed to cust_id, the NATURAL JOIN will no longer work, requiring code updates.

• Use Only to Remove Redundant Columns

NATURAL JOIN automatically removes redundant columns, which may cause data loss if those columns contain different values.

Example: If an Invoices table and a Payments table both have amount, but they represent different values, a NATURAL JOIN could incorrectly merge them, leading to confusion.

• Verify Data to Avoid Losses

Since NATURAL JOIN acts like an INNER JOIN, it removes unmatched rows, potentially avoiding important data. Always validate output to ensure NATURAL JOIN is matching the intended columns correctly.

Example: In a School database, if Students and Fee Payments tables are joined using NATURAL JOIN, only students who have paid their fees will appear in the result. Students who are yet to pay fees will be completely excluded.

• Use Explicit Join for Better Control

Using INNER JOIN with ON gives more flexibility by allowing explicit conditions, reducing the risk of unintended joins.

Example: If an Orders table and a Products table share a common column product_id, an INNER JOIN ensures that only valid product orders are retrieved.

Having explored the best practices, let’s look at the potential challenges you may face in implementing NATURAL JOIN.

Challenges of Using NATURAL JOIN in SQL

Common challenges in using NATURAL JOIN include mismatched results due to incorrect join conditions, data loss from non-matching rows, and issues with handling NULL values.

Here are some challenges faced while using NATURAL JOIN.

• Data Loss Due to Unmatched Records

INNER JOIN only returns rows when there is a match in both tables. If there are missing references, important data might be omitted.

Example: A Students table is joined with an Attendance table using student_id. If a student has never attended a class, their record will be missing from the result, even though they exist in the Students table.

• Performance for Large Datasets

INNER JOIN requires scanning and matching rows from both tables, which can slow down performance while handling millions of records.

Example: An e-commerce platform joins an Orders table with a Customers table on customer_id. If both tables have millions of records, the join operation can be slow.

• Misinterpretation of Data

If multiple matching records exist in one or both tables, INNER JOIN can produce duplicate rows, leading to unrelated results.

Example: A Sales table is joined with a Customers table using customer_id. If a customer has placed multiple orders, the result will have multiple rows for the same customer.

• Unexpected Results

Using the wrong column or an incorrect condition can cause irrelevant or incomplete results.

Example: A Products table is joined with an Inventory table, but the join is mistakenly done on product_name instead of product_id. It will incorrectly link inventory data, leading to mismatched stock levels.

• NULL Values

INNER JOIN does not include rows where the joining column contains NULL, which can lead to missing data.

Example: A Job Applicants table is joined with a Job Openings table using job_id. If some applicants haven’t been assigned a job_id yet (NULL values), they won’t appear in the result.

Being aware of NATURAL JOIN's limitations helps avoid unintended results and performance issues. Now, let’s explore ways to deepen your knowledge in this field.

How Can upGrad Help You Learn SQL and Database Management?

SQL operations like JOIN, GROUP BY, DELETE, and more are essential for manipulating data in relational databases like SQL. These skills are crucial for roles such as Database Administrator, Database Developer, and Data Analyst, where managing, optimizing, and analyzing data is key.

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