What type of index is best suited for a data warehouse fact table?

A clustered columnstore index is the best choice for a data warehouse fact table due to its ability to efficiently handle large volumes of data and optimize query performance, particularly for analytical queries that involve aggregation, filtering, and large scans. In a data warehouse environment, fact tables typically have a high cardinality and contain a significant number of rows.

Clustered columnstore indexes store data in a columnar format rather than a traditional row-based format, which leads to improved compression and reduced storage requirements. This format is particularly beneficial for read-heavy workloads common in data warehousing, where queries often examine large datasets. The columnar storage also allows for operations on individual columns, enhancing performance when executing queries that only require access to specific data fields.

Moreover, the clustered columnstore index can facilitate advanced analytics, as it is designed to work well with batch processing, making it suitable for periodic reports and analyses characteristic of data warehouse operations. This index type also benefits from parallel processing capabilities, which can significantly speed up query execution times, particularly for large-scale aggregations and analytics typical in a data warehousing context.