In which circumstances would you create a column store table?

Creating a column store table is optimal in scenarios where calculations primarily involve a small number of columns. This aligns with the way column-oriented databases function, as they store data in columns rather than rows, which allows for highly efficient querying and analytical operations on those specific columns.

In analytical workloads, it is common to perform operations such as aggregations and calculations over selected columns while reading significantly fewer rows than the total number of rows available. By organizing data in a columnar format, the database minimizes the amount of data that needs to be scanned and read for such queries, resulting in improved performance.

Having a small number of columns involved in calculations also enhances the compression capabilities of column stores, as similar data types are stored together, resulting in better overall resource utilization.

Other choices don't align as closely with the strengths of a column store. For instance, if a table has very few columns, the benefits of the column-oriented approach are less pronounced since the overhead of having a column store may not be justified compared to a row-oriented table. Additionally, if only insert operations are required, a column store doesn't provide inherent advantages over a traditional row-based table since the benefits manifest primarily during query operations. Finally, when data integrity is the primary concern, relational databases can maintain integrity