Which feature distinguishes hashed internal tables from others?

Hashed internal tables are specifically designed for efficient data retrieval based on unique keys, which makes them distinct in their functionality. When accessing an entry in a hashed internal table, the system uses a hash algorithm to compute the address of the row that corresponds to a given key. This leads to significantly faster access times for unique keys compared to other types of internal tables where access may involve sequential search or more complex indexing strategies.

This feature is particularly beneficial when working with large datasets, as it allows for quick lookups and improves performance in scenarios where the uniqueness of keys is a critical factor. The structure of a hashed table inherently supports constant time complexity for operations like reading and writing entries, as long as the hash function distributes the keys uniformly.

The features that other types of internal tables offer, such as maintaining the order of rows, allowing duplicate entries, or consuming less memory, do not apply to hashed internal tables in the same way. For example, hashed internal tables do not maintain order, can only contain unique keys, and may consume more memory than standard tables due to the overhead from hash indexing.