Clustered Index vs. Non-Clustered Index — What's the Difference?
By Tayyaba Rehman — Published on January 2, 2024
A clustered index sorts and stores data rows in the table based on the index key, while a non-clustered index creates a separate structure to point to the actual table data without rearranging it.
Difference Between Clustered Index and Non-Clustered Index
Table of Contents
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Key Differences
A clustered index determines the physical order of data in a table, aligning the data storage with the index order. In contrast, a non-clustered index maintains a separate index structure linked to the table data without altering its physical order.
Only one clustered index can be created on a table since it defines the data’s physical sorting. However, multiple non-clustered indexes can be created on a table, as they do not affect the data's physical layout.
Clustered indexes are efficient for range queries and operations that retrieve large portions of data. Non-clustered indexes are more suitable for quick lookups and searches involving a small subset of data.
In a clustered index, the leaf nodes of the index structure are the actual data. In a non-clustered index, the leaf nodes contain pointers to the data residing in the table.
Updating a table with a clustered index may be slower due to the reordering of data. Updates in tables with non-clustered indexes are generally faster as they do not require reordering.
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Comparison Chart
Data Order
Aligns the physical order of data with the index.
Maintains a separate index without rearranging data.
Number Per Table
Only one per table.
Multiple indexes can be created per table.
Query Efficiency
Efficient for range queries and bulk data retrieval.
Better for specific data lookups and searches.
Structure
Leaf nodes are the actual data rows.
Leaf nodes contain pointers to data rows in the table.
Impact on Data Operations
Data operations may require reordering.
Operations do not change the physical order of data.
Compare with Definitions
Clustered Index
A clustered index sorts the database table's records in the same order as the index.
The database table's primary key was set as a clustered index to optimize range queries.
Non-Clustered Index
Non-clustered indexes are ideal for tables where insertions and deletions are frequent.
Due to frequent updates, we used a non-clustered index to avoid the overhead of data reorganization.
Clustered Index
Clustered indexes are optimal for accessing sequential records.
Our query performance improved after creating a clustered index on the sequential invoice numbers.
Non-Clustered Index
Non-clustered index speeds up data retrieval without reordering the actual data.
Creating a non-clustered index on the product category improved the query speed significantly.
Clustered Index
A clustered index rearranges the way records are stored in the database.
Creating a clustered index on the last name column changed the data storage order.
Non-Clustered Index
A non-clustered index creates a separate entity from the table data for indexing.
We added a non-clustered index on the customer name for faster search without altering data order.
Clustered Index
Clustered index dictates the physical storage order of data in the table.
We used a clustered index on the date column to efficiently retrieve records by date.
Non-Clustered Index
In a non-clustered index, the leaf nodes hold pointers to the data rows.
The non-clustered index on the order date column contains pointers to the rows in the sales table.
Clustered Index
Only one clustered index can be created per table.
The employee ID was chosen for the table’s single clustered index for quick access.
Non-Clustered Index
Non-clustered indexes can exist multiple times on a single table.
The table had multiple non-clustered indexes for various columns to optimize different queries.
Common Curiosities
Which index is faster for read operations?
Clustered indexes are generally faster for read operations, especially for range queries.
How does a clustered index affect data insertion?
Insertions might be slower in a clustered index as it may require data reordering.
Can a table have both clustered and non-clustered indexes?
Yes, a table can have one clustered and multiple non-clustered indexes.
Can non-clustered indexes improve update query performance?
Yes, they can improve update performance for specific data lookups.
Do non-clustered indexes consume additional storage?
Yes, they consume additional storage space for the index structure.
Does dropping a clustered index affect table data?
Dropping a clustered index does not affect the data, but it changes the physical data order.
Are clustered indexes always created on primary keys?
Often, but not necessarily. A clustered index can be created on any column.
Is a clustered index better for a table with frequent writes?
No, frequent writes can be slower due to the reordering of data.
Can a non-clustered index point to a clustered index?
Yes, a non-clustered index can point to the row location in a clustered index.
Is reindexing more frequent with non-clustered indexes?
It depends on the table usage patterns, but non-clustered indexes may require more frequent maintenance.
Can a non-clustered index be used to avoid full table scans?
Yes, it can help in avoiding full table scans for specific queries.
How does a clustered index affect backup time?
It can potentially reduce backup time due to the sequential nature of data storage.
How many clustered indexes can a table have?
A table can have only one clustered index.
Are non-clustered indexes beneficial for small tables?
They can be beneficial, but the impact is more significant in large tables.
Can both indexes be used in the same query?
Yes, both clustered and non-clustered indexes can be utilized in a single query for optimal performance.
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Written by
Tayyaba RehmanTayyaba Rehman is a distinguished writer, currently serving as a primary contributor to askdifference.com. As a researcher in semantics and etymology, Tayyaba's passion for the complexity of languages and their distinctions has found a perfect home on the platform. Tayyaba delves into the intricacies of language, distinguishing between commonly confused words and phrases, thereby providing clarity for readers worldwide.
