Why Unity Catalouge ?Fine-grained permissions: Unity Catalog can enforce permissions for data at the row, column or view level instead of the file lev...

Data Engineering

Join discussions on data engineering best practices, architectures, and optimization strategies within the Databricks Community. Exchange insights and solutions with fellow data engineers.

Why Unity Catalouge ?

Fine-grained permissions: Unity Catalog can enforce permissions for data at the row, column or view level instead of the file level, so that you can always share just part of your data with a new user without copying it.
An open, standard interface: Unity Catalog’s permission model is based on ANSI SQL, making it instantly familiar to any database professional. We’ve also built a UI to make governance easy for data stewards, and we’ve extended the SQL model to support attribute-based access control, allowing you to tag many objects with the same attribute (e.g., “PII data”) and apply one policy to all of them. Finally, the same SQL based interface can be used to manage ML models and external data sources.
Central control: Unity Catalog can work across multiple Databricks workspaces, geographic regions and clouds, allowing you to manage all enterprise data centrally. This central position also enables it to track lineage and audit all accesses.
Secure access from any platform: Although we love the Databricks platform, we know that many customers will also access the data from other platforms and that they’d like their governance rules to work across them. Unity Catalog enforces security permissions from any client that connects through JDBC/ODBC or through Delta Sharing, the open protocol we’ve launched to exchange large datasets between a wide range of platforms.