An access mode for classic compute in which multiple users can share a cluster and run work at once, kept apart by Lakeguard and governed by Unity Catalog. It is the recommended mode unless a needed feature isn't supported.
Also called formerly shared access mode, Shared access mode.
Read more: Microsoft Learn
In the Ultra Transcenders books
Each book explains Standard access mode in context, with comparison tables and the common traps.
Terms in this definition
- Access mode
Set on each compute resource, this controls which people can attach and what data they reach. Dedicated (once called single user) belongs to a single user or group, standard (once called shared) keeps many users apart from each other, and Auto leaves the choice to the runtime.
- Classic compute
All-purpose, jobs and pipeline compute running in your own Azure subscription, which you set up and manage yourself. Its counterpart is serverless compute, which Azure Databricks runs for you.
- Share
In OpenSharing, the container you fill with tables, views, volumes, models and notebooks for recipients. You need
CREATE SHAREon the metastore to make one; add a schema and all its assets, including later ones, go with history. - Unity Catalog
Azure Databricks' governance solution covering both data and AI in one place, with centralised permissions, auditing, data discovery and lineage.
Related terms
- Allowlist
Held at metastore level, it records which JAR files, Maven libraries and init scripts may run on compute using the standard access mode. It begins with no entries, and only holders of
MANAGE ALLOWLISTmay change it. - CRAN
The R package repository, one of the places compute-scoped libraries can come from. Packages from CRAN can't be used on compute in standard access mode.
- JAR
Java or Scala code, compiled and packaged as a single archive. In Lakeflow Jobs, a JAR task invokes the archive's main class; on standard access mode compute the JAR must first be allowlisted.
- RDD
Short for Resilient Distributed Dataset, the older low-level Spark interface for working with distributed collections. Serverless compute and standard access mode don't allow it, so code relying on RDDs needs dedicated compute.