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What is a Clustered Index? Boosting Database Query Performance

What is a Clustered Index?

A Clustered Index determines how data is physically stored on disk. The table's rows are arranged in the same order as the clustered index key, so the index's leaf nodes contain the actual data. Because of this, a table can have only one clustered index.

By default, many databases use the primary key as the clustered index (e.g., SQL Server, InnoDB). But you can choose another column if it better fits your query patterns.

Why Use a Clustered Index?

Clustered indexes make:

  • Range queries and sorting lightning fast, since data is stored sequentially on disk
  • Queries like fetching all records between two dates very efficient
  • Grouping and ordered retrieval faster without extra sorting
  • Better disk read performance due to data locality (adjacent rows stored close)

Performance Trade-offs

  • Inserting rows can be slower if new data needs to fit in the middle of existing sorted data (causing page splits)
  • Updating clustered keys is costly because rows might move to keep order
  • Only one clustered index allowed per table, so choose carefully based on common queries
  • Non-clustered indexes reference data through the clustered key, adding some overhead

When to Use?

Ideal for columns frequently used in range queries or sorting, such as:

  • Date or timestamp columns (e.g., logs, history tables)
  • Customer last names if often queried in sorted order
  • Auto-incrementing primary keys to optimize insert speed

For small tables, clustered indexing matters less, but for large tables, it significantly improves performance on ordered queries.

Example

In SQL Server, create a clustered index like this:

CREATE CLUSTERED INDEX idx_cust_name ON Customers(LastName ASC, FirstName ASC);

This stores the Customers table physically sorted by LastName and FirstName. Queries ordering by these columns or searching ranges like LastName BETWEEN 'A' and 'C' run very efficiently.