Natural Join in SQL : Guide To Advanced SQL Join Techniques

Dealing with a database can be a bit messy, especially when trying to combine information from different tables. And if you are dealing with structured data, I’m sure that at some point, you’ve always had to bring together related data without writing a long and complicated query.

That’s where natural join in SQL steps in to make things easier.

We want to work as fast as possible, don’t we? SQL’s Natural Join was done exactly for that.

It eliminates the hassle of stating columns explicitly that are to be joined on. It auto-detects common columns in your tables and merges them. Ideally suited for situations when tables are said to share a relationship based upon columns that have the same names and data types.

Suppose we have two tables—Employee and Department. Both have a common column like Dept_ID. With a Natural Join, SQL automatically identifies that common column and merges data from both tables without you ever having to say a word about it.

Let’s get into the nitty-gritty details of just how it works, what makes it different, and how we can leverage it to our benefit.

Also read: SQL Tutorial for beginners

How Natural Join Works: Automatically Combining Tables Based on Common Columns

We all want to get the job done with as little fuss as possible, particularly when we are merging data from two or more tables. That is where the natural join in SQL shines.

Here is how it works:

• No need for the “ON” clause: Unlike some of the other SQL joins, natural join in SQL does the heavy lifting of actually automatically identifying columns that match by name and then by type.
• Matching rows: It fetches rows for which the values in those matching columns are identical.
• Unique columns: It removes any duplicate columns from the result, so we get a clean, unified view of the data.

Let’s consider our two tables: Employee and Department. Both have a column named Dept_ID.

When we use natural join, SQL already knows which column to match the two tables on.

We do not need to include Dept_ID anywhere in the query. SQL calculates it and joins the data where the Dept_ID is the same in both tables.

This saves you time and keeps your SQL queries clean and easy. Instead of this long-winded join condition, we have something that is much more meaningful: getting the data we want.

Also Read: Set Operators in SQL

Now that we know how natural join works, let’s take it all apart in its major attributes.

This is not another SQL JOIN- it has the peculiarities that make it both powerful and simple. Here is what distinguishes Natural Join:

• Automatic column matching: It will automatically look for the columns with the same name and type in the two tables.
• Unique columns in the result: You get only one copy of the common column in your result. Duplicate columns are eliminated.
• Acts like an inner join: It behaves like an INNER JOIN, meaning it only returns rows where there’s a match in both tables.
• Simpler syntax: There’s no need for the ON or USING SQL just knows what to do.

But beware—if the columns of the tables don’t have matched names and types, natural join in SQL won’t work either.

And if there are no columns in common, SQL may return something entirely unrelated: a Cartesian Product, which is just a fancy way of saying each row in one table gets matched up with every row in the other table.

It is not often what we want, so knowing the table structure before applying Natural Join is important.

Syntax for Writing Natural Join Queries in SQL

Alright, let’s get down to the real deal—how do we write a natural join in SQL?

The good news is the syntax is super simple. Here’s the basic structure of a Natural Join query:

Let’s say we have two tables:

Employee Table:

Department Table:

We want to join these tables based on the common column Dept_ID.

Here’s how we’d write the natural join:

Output:

Step-by-Step Example: Creating Tables and Performing a Natural Join in SQL

Getting SQL queries right is tough, especially when combining tables. So, let’s break down a clear, practical example of how to create tables and perform a natural join in SQL.

Let’s say we have two tables: Employee and Department.

Our goal is simple: We want to know which department each employee belongs to. Both tables share a common column: Dept_ID.

Here’s how to create these tables and perform a natural join in SQL:

Step 1: Creating the Employee and Department Tables

First, let’s create the Employee table:

Next, we’ll insert data into the Employee table:

Now, let’s create the Department table:

Finally, we’ll insert data into the Department table:

Now, we have our two tables. Here’s what they look like:

Employee Table:

Department Table:

Step 2: Writing the Natural Join Query in SQL

Now that we’ve got the tables, let’s perform a natural join in SQL to see which employee belongs to which department.

Here’s the query:

Output:

Common Use Cases for Natural Join in SQL

When do we really use natural join in SQL? Some scenarios where it surely makes sense:

• Employee and Department Data: As we saw in our example when, we have records of employees and names of departments in separate tables. Natural Join can easily link them to one another.
• Customer and Order Data: Suppose we have a Customer table and an Order table. If there is a common column, say Customer_ID, Natural Join will join both the tables based on that column.
• Product and Supplier Data: If you were working with product inventories and supplier details and there was a common column between two tables, like Supplier_ID. Natural Join would make it easy to join data.

Why use it in these cases?

Natural join makes things easier, so it saves time because we do not need to identify a join column. Syntax is cleaner with just the output we needed

Natural Join vs. Other SQL Joins (Inner, Left, Right Joins)

You might be asking what the difference is between natural join and other types of join in SQL.

Let’s break it down:

Natural Join vs. Inner Join:

• Inner Join requires us to explicitly declare which columns to join on. This offers a bit more control.
• Natural Join commonly finds common columns for us and automatically matches them.
• A natural join avoids duplicate columns, as we pointed out, while an inner join shows us varieties of the same column.

Natural Join vs. Left Join:

• Left Join includes all rows from the left-hand table, even if there aren’t matching rows in the right-hand table.
• Natural Join returns only those rows where there is a match­ing occurrence of a row in both tables.

Natural Join vs. Right Join:

• Right Join is the opposite of Left Join. It returns all the rows from the right table, even if there isn’t a match on the
• Once again, Natural Join returns only matching rows.

When to choose one over the other?

If you are sure that your joining tables have matching rows based on common columns, then Natural Join is your choice.

If you need more control or want to include non-matching rows- Inner Join, Left Join or Right Join might be preferable.

Minimising Common Errors and Issues While Using Natural Join in SQL

Natural Join in SQL is very useful, but it has some challenges that we should be aware of. Here’s where things can go wrong and how to sidestep them.

Non-Matching Column Names

If the column names don’t match in both tables, SQL will have no idea where to join them. This makes no join happen.

Solution:

Always check for Natural Join before it is used whether the columns which you think would be joining are in the same name and datatype.

Unintentional Joins on Columns with Same Names But Different Data

There could also be two tables where the column name is the same, but the data inside the column is utterly different. This will lead to a wrong or unexpected join.

Solution:

When you’re dealing with larger or more complicated databases, it’s better to err on the side of caution. Use INNER JOIN, or specify the columns you wish to match so there can’t be any accidental mismatches.

Cartesian Product When There Are No Common Columns

If there are no common columns, SQL creates a Cartesian Product. This can be awful—rather dreadful, in fact. They will join every row from one table with all rows from the other table—which is probably going to create bloated results you may not even have wanted.

Solution:

If you are not sure if your tables share common columns, then use Inner Join instead. That way, you control much better.

Performance Issues on Big Data

When doing huge datasets, natural join in SQL can be terribly slow because it has to scan for matching columns. This can be very taxing on your database.

Solution:

For much performance on big data, use Inner Join with explicit conditions.

Advanced SQL Join Techniques: Combining Natural Join with Left, Right, and Full Outer Joins

Sometimes, a natural join in SQL isn’t enough on its own.

What if we need more data flexibility, like showing all rows from one table even if there isn’t a match in the other?

That’s where advanced join techniques come into play.

By combining Natural Join with Left Join, Right Join, or Full Outer Join, we can handle more complex data scenarios.

Natural Left Join in SQL

With a left join, we want to see every row from the left table and whether or not there’s a matching row in the right table.

In this case, if an employee doesn’t belong to a department, they’ll still show up in the result. The Department column will just be NULL.

Let’s say we add another employee to our Employee table who doesn’t belong to any department.

Updated Employee Table:

The result from our Natural Left Join would look like this:

Output:

Notice that Reema doesn’t have a department, but she still appears in the result.

Natural Right Join in SQL

With a Right Join, we flip things around.

We show every row from the right table, whether or not there’s a matching row in the left table.

If we had a department with no employees, that department would still show up, with the Employee columns showing as NULL.

Let’s imagine we add a new department that doesn’t have any employees yet.

Updated Department Table:

Output:

Marketing shows up, even though no employees are assigned to it yet.

Natural Full Outer Join in SQL

If we want the best of both worlds, we use a Full Outer Join. This will include every row from both tables, whether there’s a match or not.

With this, both employees without departments and departments without employees will show up.

Output:

This join gives a complete picture; no matter what data is missing.

Working with Multiple Tables Using Natural Join in SQL

Working with two tables is simple enough. But what happens when we need to join three or more tables?

Let’s say we want to add another layer to our example by including a Location table. Here’s how we do it:

Step 1: Create the Location Table

Step 2: Perform the Natural Join Across Three Tables

Now we can join all three tables together:

Output:

This result shows us which employees work in which department and their department’s location.

The natural join in SQL makes it easy to pull related data from multiple tables as long as the columns match.

Also Read: Constraints in SQL

Conclusion

The natural join in SQL is powerful because it makes data merging between two tables much easier when the columns have the same name and datatype. Of course, though, this lessens the amount of emphasis on explicit conditions, which leads to cluttered querying and thus less efficient database operations.

Whether it is dealing with the employees and department relations or customer orders, it keeps queries clean and nice. The freedom to combine Natural Join with Left, Right, or Full Outer Joins adds flexibility and makes it possible for both matched and unmatched rows to be handled effectively.

Knowing how and when to use it and its limitations can help efficiently and accurately manage the data, whether small projects or big databases exist.