What are the benefits and drawbacks of using a non-clustered index?

Non-clustered indexes improve query performance but can slow down data modification and consume additional storage space.

A non-clustered index is a type of database index that enhances the speed of data retrieval operations on a database table. It is beneficial in many ways. Firstly, it significantly improves the performance of queries by reducing the amount of data that needs to be read from the disk. This is because the index provides a shortcut to the data, allowing the database to bypass many disk reads that would otherwise be necessary.

Secondly, non-clustered indexes can be created on any column in a table, providing flexibility in optimising for different query patterns. This is particularly useful in large databases where different queries may need to optimise for different columns.

Thirdly, non-clustered indexes can include additional columns in the index, known as included columns, which can further improve query performance. This is especially beneficial for queries that select many columns from a table, as it can reduce the number of disk reads required.

However, non-clustered indexes also have several drawbacks. One of the main disadvantages is that they can slow down data modification operations such as inserts, updates, and deletes. This is because every time data is modified, the index also needs to be updated. This can lead to increased latency in data modification operations, which can be a significant issue in systems where data is frequently updated.

Another drawback is that non-clustered indexes consume additional storage space. Each index is stored separately from the table data, and so each additional index increases the total amount of storage required. This can be a significant issue in large databases where storage space may be at a premium.

Lastly, maintaining non-clustered indexes can increase the complexity of database management. This is because the optimal set of indexes for a given workload can change over time as the data and query patterns change. Therefore, database administrators need to regularly review and potentially adjust the set of indexes to ensure optimal performance.