Sort reads its input into memory, sorts it in memory, and then outputs the results. If the input does not completely fit into memory, then several sorted runs are created and then merged together. Sort does not return any rows until it has read all of the input rows. Sort locks its input rows.

If Sort executes in an environment where there is very little cache memory available, it may not be able to complete. In this case, Sort orders the remainder of the input using an indexed-based sort method. Input rows are read and inserted into a work table, and an index is built on the ordering columns of the work table. In this case, rows are read from the work table using a complex index scan. This indexed-based strategy is significantly slower. The optimizer avoids generating access plans using Sort if it detects that a low memory situation may occur during query execution. When the index-based strategy is needed due to low memory, a performance counter is incremented; you can read this monitor with the QueryLowMemoryStrategy property, or in the Query: Low Memory Strategies counter in the Windows Performance Monitor.

The amount of memory that can be used by a Sort operator is dependent upon the multiprogramming level of the server, and the number of active connections. See Threading in SQL Anywhere, and Setting the database server's multiprogramming level.

Sort performance is affected by the size of the sort key, the row size, and the total size of the input. For large rows, it may be cheaper to use a VALUES SENSITIVE cursor. In that case, columns in the SELECT-list are not copied into the work tables used by the sort. While Sort does not write output rows to a work table, the results of Sort must be materialized before rows are returned to the application. If necessary, the optimizer adds a work table to ensure this.