Databricks recommends using Unity Catalog and shared access mode for most workloads. This article outlines various limitations for each access mode with Unity Catalog. For details on access modes, see Access modes.
Databricks recommends using compute policies to simplify configuration options for most users. See Create and manage compute policies.
No-isolation shared is a legacy access mode that does not support Unity Catalog.
Init scripts and libraries have different support across access modes and Databricks Runtime versions. See Compute compatibility with libraries and init scripts.
Single user access mode on Unity Catalog has the following limitations. These are in addition to the general limitations for all Unity Catalog access mode. See General limitations for Unity Catalog.
Dynamic views are not supported.
To read from a view, you must have
SELECTon all referenced tables and views.
You cannot access a table that has a row filter or column mask.
The following limitations apply to all Unity Catalog-enabled access modes.
Apache Spark continuous processing mode is not supported. See Continuous Processing in the Spark Structured Streaming Programming Guide.
StreamingQueryListenercannot use credentials or interact with objects managed by Unity Catalog.
For more on streaming with Unity Catalog, see Using Unity Catalog with Structured Streaming.
You must use Unity Catalog-enabled compute to interact with Unity Catalog volumes. Volumes do not support all workloads. There is no support for Scala UDFs with volumes.
Support for accessing data in volumes using the
/Volumes/catalog/schema/volume path is limited to the following:
Volumes do not support
dbutils.fs commands distributed to executors.
For more volumes limitations, see Limitations.