Difference Between Clustered and Non-Clustered Index

By Priyanshu Vaish|Updated : June 5th, 2023

The key Difference between Clustered and Non-clustered Indexes is that clustered index is the primary key. If no clustered index exists in the database, a nonclustered index is specified when the PRIMARY KEY constraint is declared. A clustered index is preferred for one SELECT statement as it is faster. It is also one of the most frequently asked SQL Interview questions.

Difference between Clustered and Non-clustered Index PDF

The SQL Server database has two types of indexes: clustered and non-clustered. The difference between clustered and non-clustered indexes is extremely crucial for SQL performance. This article will learn more about both indexes and the difference between clustered and non-clustered indexes.

Difference Between Clustered and Non-Clustered Index

The difference between Clustered and a Non-clustered index is based on various factors such as speed, memory space required, storage, etc. When you use clustered indexing in a table, it only sorts within that table. In contrast, in a non-clustered index, data is kept in one location, while the index is kept in another.

Key Differences Between Clustered and Non-Clustered Index

Clustered Index

Non-clustered Index

The table's primary keys are clustered indexes by default.

When combined with the table's unique constraints, the composite key acts as a non-clustered index.

A Clustered index is a type of index that physically reorders table records to match the index.

A Non-Clustered index is a type of index in which the logical order of the index does not correspond to the physical stored order of the rows on the file.

The clustered index has a large size.

The non-clustered index has a smaller size.

Clustered indexes store pointers to blocks rather than data.

Non-clustered indexes store both the value and a pointer to the actual row containing the data.

The index is the primary data in a clustered index.

The index in a Non-Clustered index is a copy of the data.

A clustered index is more efficient.

The Unclustered index is slower.

For operations, a clustered index requires less memory.

For operations, a non-clustered index requires more memory.

Clustered and Non-Clustered Index

Clustered and Non-Clustered Index are the two types of indexes used in SQL Server databases to index tables. Out of the two, a clustered index is faster than a nonclustered index. Let us learn about them in detail.

What is Clustered Index?

The clustered index is only created if both of the following conditions are met. The data or file moved into secondary memory should be in sequential or sorted order, and there should be a key value, which means no repeated values.

Like a primary key, a clustered index can only be created once in a table. A clustered index is similar to a dictionary because the data is organized alphabetically.

What is a Non-Clustered Index?

The non-clustered Index is similar to a book's index. The book's index contains a chapter name and a page number; if you want to read a specific topic or chapter, you can go directly to that page by using the book's index. There is no need to read a book from cover to cover.

Because the data and non-clustered index are stored separately, a table can contain multiple non-clustered indexes.

When to Use a Clustered Index and a Non-Clustered Index

The table represents a comparison between clustered indexes and non-clustered indexes, specifically highlighting the scenarios or situations where each type of index is typically used:

SituationClustered IndexNon-Clustered Index
Primary KeyOften used on primary key columnsNot limited to primary key columns
Range QueriesEfficient for range-based operationsCan still be used for range queries, but not as efficient
Frequently AccessedSuitable for columns frequently accessed togetherCan improve performance for frequently accessed columns
Data ModificationEfficient for tables with frequent data modificationsDoes not significantly impact data modification efficiency
Non-Unique ColumnsCan be used on unique or non-unique columnsParticularly useful for non-unique columns
Join and Filter OpsMay not provide significant benefits for join and filteringCan improve performance for join and filtering operations

Choosing Between Clustered and Non-Clustered Index

When choosing the right index type for your database, consider the following guidelines:

Clustered Index:

  • Use for primary key columns.
  • Optimal for range queries.
  • Suitable for frequently accessed columns.
  • Efficient for tables with frequent data modifications.

Non-Clustered Index:

  • Use for non-unique columns.
  • Helpful for join and filter operations.
  • Can improve performance for frequently accessed columns.
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FAQs on Difference Between Clustered and Non-Clustered Index

  • The difference between clustered and non-clustered index is that a clustered index, like a dictionary, is used to define the order, sort the table, or arrange the data alphabetically. A non-clustered index collects data in one location and records it in another.

  • The difference between clustered and non-clustered index regarding the primary key is that clustered on the primary key. If no clustered index exists in the database, a non-clustered index is specified when the PRIMARY KEY constraint is declared.

  • The difference between Clustered and Non-clustered index regarding performance is that clustered index has faster data accessing speed. In contrast, the non-cluster index is slower because it needs extra space to search the record.

  • The difference between Clustered and Non-clustered index regarding storage is that Clustered indexes store pointers to blocks rather than data. In contrast, Non-clustered indexes store both the value and a pointer to the actual data row.

  • The difference between Clustered and Non-clustered index regarding the data and address is that a clustered index contains data, that is rows in their leaf node, as the Index is represented as BST. In contrast, a non-clustered index contains a pointer to data (address or rows) in their leaf node, requiring an additional step to obtain the data.

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