What is the difference between clustered and non-clustered indexes in a database?

Understanding Clustered vs. Non-Clustered Indexes in Databases

In a database, clustered and non-clustered indexes serve different purposes in optimizing data retrieval. The focus keyword difference between clustered and non-clustered indexes lies in the way they physically store and organize data:

Clustered Index:

A clustered index determines the actual order in which data is physically stored in a table. When a clustered index is created on a table, the data rows are rearranged to match the order of the index key columns. As a result, a table can have only one clustered index, and it enforces the sorting and storage of data based on this index.

Non-Clustered Index:

On the other hand, a non-clustered index does not alter the physical order of the table records. Instead, it creates a separate structure that points to the physical location of the data. This allows for multiple non-clustered indexes to be created on a single table, providing flexibility in optimizing different queries.

It is essential to consider the focus keyword differences between clustered and non-clustered indexes when designing and optimizing database performance. Clustered indexes directly impact the organization of data on disk, while non-clustered indexes create additional data structures for efficient data retrieval.

Overall, understanding the distinction between clustered and non-clustered indexes is crucial for improving query performance and enhancing the overall efficiency of a database system.