An open protocol and platform from Azure Databricks for sharing data and AI assets securely, whether with another metastore (Databricks-to-Databricks) or with recipients who don't use Databricks (open sharing).
Also called formerly Delta Sharing, Delta Sharing.
Read more: Microsoft Learn
In the Ultra Transcenders books
Each book explains OpenSharing in context, with comparison tables and the common traps.
Terms in this definition
- Databricks
Analytics platform built on Apache Spark where data is processed in notebooks; Unity Catalog is the governance model it recommends.
- Metastore
The highest-level Unity Catalog container, holding metadata and permissions for a single cloud region. Each region has only one, which every workspace in that region shares, and it is not meant to be the usual boundary for isolating data.
Related terms
- IP access list
Only connections from the IPv4 addresses or CIDR ranges entered here are allowed. An OpenSharing open recipient accepts at most 100 entries, set up separately from the lists that protect a workspace.
- Provider
The organisation that shares data in OpenSharing. Recipients also see a provider as a Unity Catalog securable, from which shares can be mounted as catalogs.
- Recipient
The Unity Catalog object for an individual or organisation that is given access to OpenSharing shares. Properties set on it can be checked with
CURRENT_RECIPIENT()to filter what that party sees. - 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.