# Non-Clustered Index: A Definition > [!Note] > A Non-Clustered Index provides a logical ordering of key values separate from the data rows, using pointers to quickly locate records without affecting the table’s physical layout. A **Non-Clustered Index** builds its own **B-tree** structure alongside the base table, with leaf-level entries containing index keys and **row locators** that point to the actual data rows. Unlike a clustered index, it does not dictate the physical sequence of table pages, allowing multiple non-clustered indexes per table to support diverse query patterns. When a query filter matches the index key, SQL Server performs an **index seek** within this auxiliary structure, swiftly retrieving the relevant locators before fetching the complete rows. Because non-clustered indexes store only the indexed columns and locators, they are typically smaller than the full table, reducing **I/O** during lookups. However, when queries request additional columns not included in the index, a **Key Lookup**—either a **RID Lookup** for heaps or a **Clustered Index Lookup** for tables with a clustered index—is required, which incurs extra reads. To avoid these lookups, one can design [[Covering Index]] by adding included columns to the leaf level, thus satisfying query requirements directly from the index itself. > [!Tip] > When creating non-clustered indexes, balance the number of indexes against update overhead—each index must be maintained on INSERT, UPDATE, and DELETE operations, which can slow write-heavy workloads. Regular **index maintenance**, including rebuilding or reorganizing fragmented indexes and updating **statistics**, ensures that non-clustered indexes remain efficient. By aligning index design with common filtering, sorting, and grouping operations, and by monitoring their usage through execution plans, one can leverage non-clustered indexes to dramatically accelerate targeted data retrieval without restructuring the underlying table. --- ## References - Korotkevitch, D. (2022). _SQL Server advanced troubleshooting and performance tuning: Best practices and techniques_. O’Reilly Media. - Nevarez, B. (2022). _SQL Server query tuning and optimization: Optimize Microsoft SQL Server 2022 queries and applications_. Packt Publishing.