What is a key feature of a temporary view in Databricks?

A key feature of a temporary view in Databricks is that it is session-specific and not stored. This means that temporary views exist only for the duration of the session in which they are created. Once the session ends, the temporary view is automatically dropped and not available for future sessions. This characteristic makes temporary views particularly useful for quick analysis or transformations without cluttering the workspace with permanent views or tables.

In contrast, the persistence aspect is not applicable as temporary views do not store their data on disk; they simply act as a reference to the data but do not retain it beyond the session. This functionality allows users to utilize the same data multiple times within the session while ensuring that no residual data or definitions are left behind when the session concludes. Temporary views can also restrict access since they exist only within a specific session scope, which contrasts with regular views that can be shared and accessed by multiple users. Enhanced performance isn't specifically attributed to temporary views either, as performance can vary based on numerous factors beyond view type.