Supported Authentication Types:
- Personal Access Token — Generated token from your Databricks workspace (User Settings > Developer > Access Tokens).
- Databricks OAuth — OAuth2 Machine-to-Machine authentication using Service Principal credentials.
- Azure AD Setup — Azure Active Directory authentication using Service Principal for Azure Databricks workspaces.
How to Run the Connector Externally
To run the Ingestion via the UI you’ll need to use the OpenMetadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment. If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.External Schedulers
Get more information about running the Ingestion Framework Externally
Requirements
Before configuring the Unity Catalog connector, make sure the following requirements are in place.Permission Requirement
To enable full functionality of metadata extraction, profiling, usage, and lineage features in OpenMetadata, the following permissions must be granted to the relevant users in your Databricks environment.Metadata and Profiling Permissions
These permissions are required on the catalogs, schemas, and tables from which metadata and profiling information will be ingested.Usage
These permissions enable OpenMetadata to extract query history for usage statistics.Lineage
These permissions enable OpenMetadata to extract table and column-level lineage from Databricks system tables.Tags
These permissions enable OpenMetadata to extract Unity Catalog tags from catalogs, schemas, tables, and columns.Metadata Ingestion
To ingest metadata from Unity Catalog, you need to create a service connection. The service connects Unity Catalog with OpenMetadata. Once you create a service, OpenMetadata automatically starts ingesting metadata.Step 1: Add New Service
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Navigate to Settings > Services.

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Click Add New Service.

Step 2: Select a Service and Connector
From the service type dropdown, select Database Services, then click the Unity Catalog connector tile.
Step 3: Add Service Name and Description
- Enter a unique, descriptive Service Name. OpenMetadata identifies services by their service name. Enter a name that distinguishes this deployment from other Unity Catalog services you are ingesting metadata from.
- Optional: Enter a Description for the service.

Note: The service name cannot be changed after it is set.
Step 4: Configure Connection Options
Specify your source credentials and verify the connection.Enter Connection Details
Enter the connection details for Unity Catalog. The right-hand panel in the UI displays inline help for each field.
- Host and Port: Enter the fully qualified hostname and port number for your Databricks deployment in the Host and Port field.
- HTTP Path: Databricks compute resources URL.
- Personal Access Token: Provide the token generated from your Databricks workspace (User Settings > Developer > Access Tokens).
- Databricks OAuth: Provide the Service Principal
Client IDandClient Secretcreated in your Databricks Account Console. - Azure AD Setup: Provide the
Azure Client ID,Azure Client Secret, andAzure Tenant IDfrom your Azure Active Directory Service Principal.
- connectionTimeout: The maximum amount of time (in seconds) to wait for a successful connection to the data source. If the connection attempt takes longer than this timeout period, an error is returned.
- Catalog: Catalog of the data source (for example,
hive_metastore). This is an optional parameter, if you would like to restrict the metadata reading to a single catalog. When left blank, OpenMetadata attempts to scan all catalogs. - Database Schema: Database schema of the data source. This is an optional parameter, if you would like to restrict the metadata reading to a single database schema. When left blank, OpenMetadata attempts to scan all database schemas.
Test Connection
Once the credentials have been added, click on Test Connection and Save the changes.
Step 5: Configure Ingestion Options
In the What to Ingest step, use filter patterns to control which assets OpenMetadata ingests from your database service. Filter patterns use regular expressions applied to asset names.How Filter Patterns Work
- Include: Add one or more comma-separated regular expressions. OpenMetadata ingests only assets whose names match at least one expression. Leave blank to include all assets.
- Exclude: Add one or more comma-separated regular expressions. OpenMetadata skips any asset whose name matches an expression. Leave blank to exclude nothing.
- contains: matches any name containing the value. For example,
salesmatchesmy_sales_dataandsales_2024. - starts with: matches names beginning with the value. For example,
prod_matchesprod_dbandprod_schema. - ends with: matches names ending with the value. For example,
_rawmatchesevents_rawandlogs_raw. - is exactly: matches the exact name only. For example,
analyticsmatches onlyanalytics. - matches regex: matches names using a regular expression. For example,
^prod_.*_v\d+$matchesprod_events_v1.
- Database: Controls which databases OpenMetadata ingests from the source.
- Schema: Controls which schemas within the ingested databases are included.
- Table: Controls which tables and views within the ingested schemas are included.
- Scan Mode: You can choose between the following scan modes:
- Scan all: Ingests every asset of that type the connector can access. This is the default.
- Only specific: Enables include rules so only assets matching at least one rule are ingested.
- Exclude system toggle: Use this toggle to automatically filter out system-reserved names defined by the connector, for example, Exclude system databases for the Databases section.
- Always exclude: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules.
- Preview: Shows a real-time summary of what will be in scope based on your current rules.
- Include rules (available only in Only specific mode): Click + Add to define a rule. Added rules appear as chips; an asset is included if it matches any rule.
Step 6: Create & Deploy
Click Create & Deploy to deploy the agent and start the first metadata ingestion run. OpenMetadata saves the service configuration and immediately begins pulling metadata from the source. To monitor ingestion progress or view the service you just added, go to Settings > Services and select your service.Configure Metadata Agent and Schedule Ingestion
The Metadata Agent extracts schemas, tables, columns, and other structural metadata from your source and keeps your OpenMetadata catalog in sync. It powers discovery, lineage, and governance across your data assets. When you click Create & Deploy, OpenMetadata automatically deploys a Metadata Agent for this service and triggers the first ingestion run. View its status and run history from the Agents tab on the service detail page. To configure the additional Metadata Agent and schedule ingestion, follow these steps:-
Navigate to Settings > Services and select the service type.

- Click the service you have added.
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Select the Agents tab and click Add Agent > Metadata.
For some services, the dropdown is not available and clicking Add Agent takes you directly to the agent configuration page.
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On the Configure Ingestion page, do the following and click Next.
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Name this Ingestion: Enter a unique recognizable name for this ingestion pipeline.

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Agent Setup: Configure core parameters for metadata extraction. The following fields are available:

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Filter Patterns: Apply include or exclude rules to scope which databases, schemas, tables, and stored procedures this agent ingests. For more information about various filter options, see Step 6: Configure Ingestion Options.

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Scope & Behaviour: Control how the agent handles metadata during ingestion. Toggle each option on or off based on your needs:
Available toggles vary by connector. Stored procedure options only appear for connectors that support stored procedures.

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Advanced Config: Optional connector-specific settings such as Include Views and Extract JSON Schema.

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Name this Ingestion: Enter a unique recognizable name for this ingestion pipeline.
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On the Schedule Interval page, set when the agent runs:
- Schedule: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression.
- On-Demand: No automatic schedule; trigger the agent manually when needed.

- Click Add to deploy the agent.
Related
Usage Workflow
Learn more about how to configure the Usage Workflow to ingest Query information from the UI.
Lineage Workflow
Learn more about how to configure the Lineage from the UI.
Profiler Workflow
Learn more about how to configure the Data Profiler from the UI.
Data Quality Workflow
Learn more about how to configure the Data Quality tests from the UI.
dbt Integration
Learn more about how to ingest dbt models’ definitions and their lineage.