Clustered and non-clustered indexes are two essential types of indexing mechanisms used in databases to improve data retrieval speed. The primary difference between the two lies in how they organize and store data. A clustered index determines the physical order of data storage in a table based on the indexed column(s). This means that when you create a clustered index on a table, the rows are stored on disk in that particular order. There is only one clustered index per table since the data can be arranged in only one way.
On the other hand, a non-clustered index creates a separate structure from the actual data storage. This index contains pointers that reference the location of the data rows in the table. Non-clustered indexes can be created on multiple columns and can exist alongside the data rows, allowing for faster searches without altering the actual data layout. For instance, if you have a table storing customer information and you frequently query by last name, you could create a non-clustered index on that column, enabling quicker access to data sorted by last name without rearranging the entire table.
In practical terms, if you have a table with millions of records, a clustered index can drastically speed up the search for a specific row based on the indexed attribute, since it allows the database to navigate to the data directly. However, because of its structure, modifying or inserting data can be slower if it requires reorganizing the data to maintain the ordered structure. Non-clustered indexes, while slower for data modification operations, are particularly useful for read-heavy applications where queries are executed against various columns frequently. In summary, choosing between clustered and non-clustered indexes depends on the specific use case and access patterns within your application.