What defines a managed table in Databricks?

A managed table in Databricks is characterized by the fact that Databricks handles both the storage and data retention of the table. When a managed table is created, the underlying data is stored in a system-controlled location, typically in a Databricks file system location that is tied to the workspace. This means that when a managed table is dropped, both the metadata and the actual data are removed from the system, allowing for easier data management as users do not need to manually handle data files and storage locations.

This automatic management enhances usability by relieving users of the burden of manually specifying where data resides or needing to manage its lifecycle, thus streamlining workflows. Overall, this characteristic of managed tables aligns with the principle of offering a higher level of abstraction for users concerning data operations.