Starburst Pre-Configuration Details
Audience: System Administrators, Data Owners, and Data Users
Content Summary: This page describes the configuration options, features, and limitations of the Starburst integration.
See the Starburst integration page for a tutorial on enabling Starburst and these features through the App Settings page.
|Project Workspaces||Starburst Tag Ingestion||User Impersonation||Native Query Audit||Multiple Integrations|
A valid Starburst Enterprise license
The Starburst integration supports the following authentication methods to create data sources in Immuta:
- Username and password: You can authenticate with your Starburst username and password.
- OAuth 2.0: You can authenticate with OAuth 2.0. Immuta's OAuth authentication method uses the Client Credentials Flow; when you register a data source, Immuta reaches out to your OAuth server to generate a JSON web token (JWT) and then passes that token to the Starburst cluster.
Configure JWT authentication method in Starburst
When using OAuth authentication to create data sources in Immuta, configure your Starburst (Trino) cluster to use JWT authentication, not OpenID Connect or OAuth.
The Immuta Starburst integration cannot ingest tags from Starburst, but you can connect any of these supported external catalogs to work with your integration.
Native impersonation allows users to natively query data as another Immuta user. To enable native user impersonation, see the Integration User Impersonation page.
Native Query Audit
Immuta translates Starburst events into comprehensive audit logs for users with the Immuta
AUDIT permission to view. For more information about what is included in those audit logs, see the
Starburst Audit Logs page.
Multiple Starburst Instances
You can configure multiple integrations of Starburst with a single Immuta instance and use them dynamically. Only configure the integration once in Immuta to use it in multiple Starburst instances.
Limit your masked joins to columns with matching column types. Starburst truncates the result of the masking expression to conform to the native column type when performing the join, so joining two masked columns with different data types produces invalid results when one of the columns' lengths is less than the length of the masked value.
For example, if the value of a hashed column is 64 characters, joining a hashed varchar(50) and a hashed varchar(255) column will not be joined correctly, since the varchar(50) value is truncated and doesn’t match the varchar(255) value.
Certain interpolation functions can block the creation of a native view, specifically