Clustered vs Nonclustered Index: What’s the Difference?

Posted on by Ian

Indexes can play a crucial role in optimizing SQL query performance. A well designed index can help a query perform much faster than it otherwise might. While there are many types of indexes, two common index types are clustered and nonclustered indexes.

Understanding the difference between clustered and nonclustered indexes can have a significant impact on our database design and query optimization strategies.

In this article, we’ll take a look at clustered and nonclustered indexes as implemented in SQL Server, explore their characteristics, and examine when to use each type.

What is an Index?

Before we delve into the specifics of clustered and nonclustered indexes, let’s briefly review what an index is. In database terms, an index is a data structure that improves the speed of data retrieval operations on a database table.

It’s similar to an index in a book, allowing us to quickly locate specific information without scanning every page. Similarly, having an index on a table or view can help SQL Server locate specific information much more quickly than it otherwise might.

See my Introduction to Indexing in SQL for a more detailed description of indexes in general.

The Difference

First, here’s a quick overview of the difference between clustered and nonclustered indexes:

  • A clustered index determines the physical order of data in a table. There can be only one clustered index per table.
  • A nonclustered index is a separate structure from the data rows. It holds a copy of selected columns and a pointer to the data row containing the full record. There can be multiple nonclustered indexes on a table.

Let’s explore this a bit further, starting with the clustered index, followed by the nonclustered index.

Clustered Index

A clustered index determines the physical order of data in a table. It sorts and stores the data rows in the table based on their key values. Here are some key points about clustered indexes:

  • One per table: There can be only one clustered index per table because the data rows themselves can be sorted in only one order.
  • Physical ordering: The clustered index dictates the physical order of the data in the table. This means the table data is stored on disk in the same order as the clustered index.
  • Automatic creation: In some database management systems, a clustered index is automatically created when we define a primary key for the table. This is the case in SQL Server for example, unless there’s already a clustered index on the table or we specify a nonclustered index for the primary key.
  • Faster retrieval for range queries: Clustered indexes are particularly efficient for queries that retrieve a range of data.

As mentioned, tables often get a clustered index automatically when we define the primary key. However, it’s certainly possible to have a table without a clustered index. A table that doesn’t have a clustered index is called a heap. In this case, the rows are stored and sorted in no particular order.

In most cases we are better off having a clustered index on our tables. That said, there can be specific scenarios where not having a clustered index (i.e. making the table a heap) could be beneficial (such as when bulk loading, or in tables that are subject to a lot of truncations and reloading, etc).

Example of a Clustered Index

Let’s consider a table named Employees with columns EmployeeID, FirstName, LastName, and Department. If we create a clustered index on EmployeeID, the data in the table will be physically ordered based on EmployeeID.

CREATE CLUSTERED INDEX IX_Employees_EmployeeID
ON Employees (EmployeeID);

Now, the data pages of the Employees table will be sorted by EmployeeID. This means queries that search for ranges of EmployeeID values will be particularly fast.

As mentioned, some DBMSs create a clustered index by default whenever we create a primary key. If this is the case, then there would be no need to run the above code. For example, if we’d created the table like this:

CREATE TABLE Employees (
    EmployeeID INT PRIMARY KEY,
    FirstName NVARCHAR(50),
    LastName NVARCHAR(50),
    Department NVARCHAR(50)
);

Then a clustered index would have been automatically created for the EmployeeID column.

Nonclustered Index

A nonclustered index is a separate structure from the data rows. It holds a copy of selected columns and a pointer to the data row containing the full record. Here are the key characteristics of nonclustered indexes:

  • Multiple per table: We can have multiple nonclustered indexes per table.
  • Separate structure: Nonclustered indexes are stored separately from the table data, with pointers to the actual data rows.
  • No effect on physical order: Creating a nonclustered index doesn’t change the physical order of the table.
  • Best for selective queries: Nonclustered indexes are most effective for queries that return a small percentage of rows.

Example of a Nonclustered Index

Using the same Employees table, let’s create a nonclustered index on the LastName column:

CREATE NONCLUSTERED INDEX IX_Employees_LastName
ON Employees (LastName);

This index will create a separate structure that stores LastName values along with pointers to the corresponding data rows. It doesn’t change the physical order of the data in the Employees table.

We can create multiple nonclustered indexes on a given table, each serving their own distinct purpose. We could also create a composite index, which is an index on multiple columns:

CREATE NONCLUSTERED INDEX IX_Employees_Name
ON Employees (FirstName, LastName);

This would be helpful for when we search for both first name and last name.

Clustered vs Nonclustered: Key Differences

Now that we’ve explored both types of indexes, let’s summarize the key differences:

  • Number per table: Only one clustered index per table, but multiple nonclustered indexes are allowed.
  • Data storage: A clustered index determines the storage order of data in the table, while nonclustered indexes are stored separately with pointers to the data rows.
  • Speed: Clustered indexes are generally faster for retrieving a range of data, while nonclustered indexes are faster for selective queries.

When to Use Each Type

Choosing between clustered and nonclustered indexes depends on our specific use case:

  • Use a clustered index for columns that are frequently used to sort the data or retrieve ranges of data.
  • Use nonclustered indexes for columns often used in WHERE clauses or JOIN conditions, especially when the queries are highly selective.

In practice, a combination of both types often yields the best performance. We might have a clustered index on the primary key and several nonclustered indexes on columns used frequently in our queries.

Conclusion

Understanding the difference between clustered and nonclustered indexes is crucial for optimizing our database performance. By choosing the right type of index for our specific needs, we can significantly improve query speed and overall database efficiency.

Remember, the key is to balance the benefits of faster data retrieval with the overhead of maintaining the indexes.