> ## Documentation Index
> Fetch the complete documentation index at: https://docs.getcollate.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Databricks Connector

> Connect Databricks to Collate effortlessly. Complete setup guide, configuration steps, and metadata extraction for your data lakehouse platform.

export const ConnectorDetailsHeader = ({name, icon, stage, availableFeatures, unavailableFeatures = [], availableFeaturesCollate = []}) => {
  const showSubHeading = availableFeatures?.length > 0 || unavailableFeatures?.length > 0 || availableFeaturesCollate?.length > 0;
  const totalAvailableFeatures = [...availableFeatures || [], ...availableFeaturesCollate || []];
  return <div className="container">
      <div className="Heading">
        <div className="flex items-center gap-3">
          {icon && <div className="IconContainer">
              <img src={icon} alt={name} noZoom className="ConnectorIcon" />
            </div>}
          <h1 className="ConnectorName">{name}</h1>
          <span className={`StageBadge ${stage === 'PROD' ? 'prod' : 'beta'}`}>
            {stage}
          </span>
        </div>
      </div>
      {showSubHeading && <div className="SubHeading">
          <div className="FeaturesHeading">Feature List</div>
          <div className="FeaturesList">
            {totalAvailableFeatures.map(feature => <div className="FeatureTag AvailableFeature" key={feature}>
                ✓ {feature}
              </div>)}
            {unavailableFeatures.map(feature => <div className="FeatureTag UnavailableFeature" key={feature}>
                ✕ {feature}
              </div>)}
          </div>
        </div>}
    </div>;
};

<ConnectorDetailsHeader icon="/public/images/connectors/databrick.webp" name="Databricks" stage="PROD" availableFeatures={["Metadata", "Query Usage", "Lineage", "Column-level Lineage", "Data Profiler", "Data Quality", "dbt", "Sample Data", "Reverse Metadata (Collate Only)", "Auto-Classification"]} unavailableFeatures={["Stored Procedures", "Tags", "Owners"]} />

<iframe width="800" height="450" src="https://www.youtube.com/embed/ASuCngUly80" title="Databricks connector setup video guide" frameBorder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowFullScreen />

<Tip>
  **Tip**: As per the [documentation](https://docs.databricks.com/en/data-governance/unity-catalog/tags.html#manage-tags-with-sql-commands), Collate only supports metadata `tag` extraction for Databricks version 13.3 and higher.
</Tip>

This section provides guides and references to use the Databricks connector.
Configure and schedule Databricks metadata and profiler workflows from the Collate UI:

* [Requirements](#requirements)
* [Iceberg tables](#iceberg-tables)
* [Unity Catalog](#unity-catalog)
* [Metadata Ingestion](#metadata-ingestion)
* [Query Usage](/ai-2-0/how-to-guides/guide-for-data-users/ingestion/workflows/usage)
* [Data Profiler](/ai-2-0/how-to-guides/data-quality-observability/profiler/profiler-workflow)
* [Data Quality](/ai-2-0/how-to-guides/data-quality-observability/quality)
* [Lineage](/ai-2-0/how-to-guides/data-lineage/workflow)
* [dbt Integration](/ai-2-0/connectors/database/dbt)
* [Troubleshooting](/ai-2-0/connectors/database/databricks/troubleshooting)
* [Reverse Metadata](#reverse-metadata)

## 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**.

<Columns cols={2}>
  <Card title="External Schedulers" href="https://docs.open-metadata.org/latest/deployment/ingestion">
    Get more information about running the Ingestion Framework Externally
  </Card>
</Columns>

## Requirements

Before ingesting metadata from Databricks, grant the following permissions to the user account Collate will use to connect.

### Permission Requirement

To enable full functionality of metadata extraction, profiling, usage, and lineage features in Collate, 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.

```sql theme={null}
GRANT USE CATALOG ON CATALOG <catalog_name> TO `<user>`;
GRANT USE SCHEMA ON SCHEMA <schema_name> TO `<user>`;
GRANT SELECT ON TABLE <table_name> TO `<user>`;
```

Ensure these grants are applied to all relevant tables for metadata ingestion and profiling operations.

### Usage and Lineage

These permissions enable Collate to extract query history and construct lineage information.

```sql theme={null}
GRANT SELECT ON SYSTEM.QUERY.HISTORY TO `<user>`;
GRANT USE SCHEMA ON SCHEMA system.query TO `<user>`;
```

These permissions allow access to Databricks system tables that track query activity, enabling lineage and usage statistics generation.

<Tip>
  **Tip**: Adjust \<user>, \<catalog\_name>, \<schema\_name>, and \<table\_name> according to your specific deployment and security requirements.
</Tip>

## Iceberg tables

Collate reads Databricks metadata through the standard catalog and table interfaces described on this page. If Databricks exposes an Iceberg-backed table through those interfaces, use the same Databricks connector workflow described here.

This page does not document separate Iceberg-specific configuration, classification, or profiling guarantees for the Databricks connector. Validate behavior in your environment if you rely on Databricks-specific Iceberg handling.

## Unity Catalog

If you use Unity Catalog in Databricks, see the [Unity Catalog](/ai-2-0/connectors/database/unity-catalog) connector.

## Metadata Ingestion

To ingest metadata from Databricks, you need to create a service connection. The service connects Databricks with Collate. Once you create a service, Collate automatically starts ingesting metadata.

### Step 1: Add New Service

1. In the left navigation, click **Connections**.
2. On the **Connections** page, click **Add New Service**.

<img src="https://mintcdn.com/collatedocs/bv5oe4uRjuorTJO1/public/images/ai-2.0/connectors/metadata-ingestion/add-new-service.png?fit=max&auto=format&n=bv5oe4uRjuorTJO1&q=85&s=733cef1141ef13d318634aa9f407eb2b" alt="Add New Service" width="2992" height="1256" data-path="public/images/ai-2.0/connectors/metadata-ingestion/add-new-service.png" />

### Step 2: Select a Service and Connector

From the service type dropdown, select **Database Services**, then click the **Databricks** connector tile.

<img src="https://mintcdn.com/collatedocs/kTp2dTyiNAX4Np5A/public/images/ai-2.0/connectors/metadata-ingestion/Database/select-service/databricks.png?fit=max&auto=format&n=kTp2dTyiNAX4Np5A&q=85&s=61556e5426ac54973abd05b2c73811d8" alt="Select Service" width="2164" height="1472" data-path="public/images/ai-2.0/connectors/metadata-ingestion/Database/select-service/databricks.png" />

### Step 3: Add Service Name and Description

* Enter a unique, descriptive **Service Name**. Collate identifies services by their service name. Enter a name that distinguishes this deployment from other Databricks services you are ingesting metadata from.
* Optional: Enter a **Description** for the service.

<img src="https://mintcdn.com/collatedocs/bWmb7UY94lEjxxg4/public/images/ai-2.0/connectors/metadata-ingestion/Database/service-name/databricks.png?fit=max&auto=format&n=bWmb7UY94lEjxxg4&q=85&s=e944feb1f11be4157df5f8402e488adb" alt="Add New Service Name" width="1500" height="858" data-path="public/images/ai-2.0/connectors/metadata-ingestion/Database/service-name/databricks.png" />

<Note>
  **Note**: The service name cannot be changed after it is set.
</Note>

### Step 4: Configure Connection Options

Specify where ingestion runs, provide your source credentials, and verify the connection.

#### Select Ingestion Runner

Select an **Ingestion Runner**: the runner where the ingestion pipeline will execute.

<img src="https://mintcdn.com/collatedocs/bv5oe4uRjuorTJO1/public/images/ai-2.0/connectors/metadata-ingestion/select-ingestion-runner.png?fit=max&auto=format&n=bv5oe4uRjuorTJO1&q=85&s=1249f828648614445e8a976ea1933487" alt="Add Name and Select Ingestion Runner" width="1444" height="506" data-path="public/images/ai-2.0/connectors/metadata-ingestion/select-ingestion-runner.png" />

#### Enter Connection Details

Enter the connection details for Databricks. The right-hand panel in the UI displays inline help for each field.

<img src="https://mintcdn.com/collatedocs/kTp2dTyiNAX4Np5A/public/images/ai-2.0/connectors/metadata-ingestion/Database/connection-details/databricks.png?fit=max&auto=format&n=kTp2dTyiNAX4Np5A&q=85&s=ebed3884539f9373d9039c893da563c8" alt="Configure Service Connection" width="1452" height="1182" data-path="public/images/ai-2.0/connectors/metadata-ingestion/Database/connection-details/databricks.png" />

* **Host and Port**: Enter the fully qualified hostname and port number for your Databricks deployment in the Host and Port field.
* **Token**: Generated Token to connect to Databricks.
* **HTTP Path**: Databricks compute resources URL.
* **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, Collate returns an error.
* **Catalog**: Catalog of the data source (for example, `hive_metastore`). This optional parameter restricts metadata reading to a single catalog. When left blank, Collate ingestion scans all catalogs.
* **DatabaseSchema**: The database schema of the data source. This optional parameter restricts metadata reading to a single schema. When left blank, Collate ingestion scans all schemas.

#### Advanced Configuration

Database Services have an Advanced Configuration section, where you can pass extra arguments to the connector and, if needed, change the connection scheme. This is required only for advanced connectivity scenarios or customizations.

* **Connection Options (Optional)**: Enter the details for any additional connection options that can be sent to the database during the connection. These details must be added as key-value pairs.
* **Connection Arguments (Optional)**: Enter the details for any additional connection arguments such as security or protocol configs that can be sent during the connection. These details must be added as key-value pairs.

#### Test Connection

After adding the credentials, click on **Test Connection** and **Save** the changes.

<img src="https://mintcdn.com/collatedocs/bv5oe4uRjuorTJO1/public/images/ai-2.0/connectors/metadata-ingestion/test-connection.png?fit=max&auto=format&n=bv5oe4uRjuorTJO1&q=85&s=3365cff7bb9d82c85a2ff9ab559d6f11" alt="Test Connection" width="1446" height="188" data-path="public/images/ai-2.0/connectors/metadata-ingestion/test-connection.png" />

### Step 5: Configure Ingestion Options

In the **What to Ingest** step, use filter patterns to control which assets Collate 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. Collate 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. Collate skips any asset whose name matches an expression. Leave blank to exclude nothing.

Rules match asset names using one of five expressions:

* **contains**: matches any name containing the value. For example, `sales` matches `my_sales_data` and `sales_2024`.
* **starts with**: matches names beginning with the value. For example, `prod_` matches `prod_db` and `prod_schema`.
* **ends with**: matches names ending with the value. For example, `_raw` matches `events_raw` and `logs_raw`.
* **is exactly**: matches the exact name only. For example, `analytics` matches only `analytics`.
* **matches regex**: matches names using a regular expression. For example, `^prod_.*_v\d+$` matches `prod_events_v1`.

When both Include and Exclude are set, Exclude takes priority.

<Tip>
  **Tip**: Leave all filter patterns empty to ingest all databases, schemas, and tables available in the source.
</Tip>

**Filter Options**

The Database, Schema, Table, and Stored Procedure sections each include the following filter options:

* **Database**: Controls which databases Collate 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.
* **Stored Procedure**: Controls which stored procedures are included in metadata ingestion.

Each section provides the following controls:

* **Scan Mode**: 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.

<Tip>
  **Tip**: If [AutoPilot](/ai-2-0/admin-guide/applications/autopilot) is enabled, usage tracking, data lineage, and other downstream workflows start automatically after the first metadata ingestion completes.
</Tip>

### Step 6: Create & Deploy

Click **Create & Deploy** to deploy the agent and start the first metadata ingestion run. Collate 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 **Connections** in the left navigation 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 Collate catalog in sync. It powers discovery, lineage, and governance across your data assets.

When you click **Create & Deploy**, Collate 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:

1. In the left navigation, click **Connections** and select your service.

2. Click the **Agents** tab.

3. Click **Add Agent** and select **Metadata** from the dropdown.
   <img src="https://mintcdn.com/collatedocs/bv5oe4uRjuorTJO1/public/images/ai-2.0/connectors/metadata-ingestion/add-metadata-agent.png?fit=max&auto=format&n=bv5oe4uRjuorTJO1&q=85&s=accad7d1c4ddf209781bff851d51d464" alt="Add Metadata Agent" width="2398" height="1144" data-path="public/images/ai-2.0/connectors/metadata-ingestion/add-metadata-agent.png" />
   For some services, the dropdown is not available and clicking **Add Agent** takes you directly to the agent configuration page.

4. On the **Configure Ingestion** page, do the following and click **Next**.

   * **Name this Ingestion**: Enter a unique recognizable name for this ingestion pipeline.

     <img src="https://mintcdn.com/collatedocs/bv5oe4uRjuorTJO1/public/images/ai-2.0/connectors/metadata-ingestion/metadata-agent-name.png?fit=max&auto=format&n=bv5oe4uRjuorTJO1&q=85&s=d5ec1f0f3742cadab8cd54c602c97239" alt="Name this Ingestion" width="1578" height="644" data-path="public/images/ai-2.0/connectors/metadata-ingestion/metadata-agent-name.png" />

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

     | Field                                 | Default | Description                                                                                                              |
     | ------------------------------------- | ------- | ------------------------------------------------------------------------------------------------------------------------ |
     | Default Owner                         | —       | Owner applied to all entities when no specific level owner is configured. Accepts a user or team name/email.             |
     | Service Owner                         | —       | Owner assigned to the service entity.                                                                                    |
     | Database Owner                        | —       | Owner assigned to all ingested databases. Accepts a single owner or a per-database name mapping.                         |
     | Database Schema Owner                 | —       | Owner assigned to all ingested schemas. Accepts a single owner or a per-schema name mapping.                             |
     | Table Owner                           | —       | Owner assigned to all ingested tables. Accepts a single owner or a per-table name mapping.                               |
     | Enable Inheritance                    | On      | When on, child entities inherit the owner from their parent when they have no owner configured.                          |
     | Query Log Duration                    | 1       | Number of days to look back in query logs when processing stored procedure results.                                      |
     | Query Parsing Timeout Limit           | 300     | Timeout in seconds for parsing a single query.                                                                           |
     | Number of Threads                     | 1       | Number of threads to use for parallel table ingestion.                                                                   |
     | Incremental Extraction                | Off     | When enabled, subsequent runs only extract entities changed since the last successful run.                               |
     | Successful Pipeline Run Lookback Days | 7       | Number of days to search back for a prior successful run to use as a baseline for incremental extraction.                |
     | Safety Margin Days                    | 1       | Additional days added to the baseline timestamp as a buffer for incremental extraction.                                  |
     | JSON Schema Sample Size               | 10      | Number of rows sampled to infer JSON column schema. Only applies when Extract JSON Schema is enabled in Advanced Config. |

     <img src="https://mintcdn.com/collatedocs/kTp2dTyiNAX4Np5A/public/images/ai-2.0/connectors/metadata-ingestion/Database/database-agent-setup.png?fit=max&auto=format&n=kTp2dTyiNAX4Np5A&q=85&s=429839e5b479082a6909dd2a7734513d" alt="Agent Setup" width="1570" height="1396" data-path="public/images/ai-2.0/connectors/metadata-ingestion/Database/database-agent-setup.png" />

   * **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 5: Configure Ingestion Options**.

     <img src="https://mintcdn.com/collatedocs/kTp2dTyiNAX4Np5A/public/images/ai-2.0/connectors/metadata-ingestion/Database/database-filter-pattern.png?fit=max&auto=format&n=kTp2dTyiNAX4Np5A&q=85&s=8a0c5fcc3475acf8acc94e6eecb55a11" alt="Filter Patterns" width="1560" height="1030" data-path="public/images/ai-2.0/connectors/metadata-ingestion/Database/database-filter-pattern.png" />

   * **Scope & Behaviour**: Control how the agent handles metadata during ingestion. Toggle each option on or off based on your needs:

     | Toggle                         | Default | Description                                                                                                                                                            |
     | ------------------------------ | ------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
     | Include Tables                 | On      | Ingest table metadata from the source. Turn off to skip tables entirely.                                                                                               |
     | Include Tags                   | On      | Ingest tags from the source.                                                                                                                                           |
     | Include Stored Procedures      | On      | Ingest stored procedure metadata.                                                                                                                                      |
     | Include DDL Statements         | Off     | Ingest DDL statements alongside table metadata.                                                                                                                        |
     | Include Owners                 | Off     | Assign owners to ingested entities when the source owner's email matches a user in Collate. Does not overwrite an existing owner.                                      |
     | Include Custom Properties      | Off     | Ingest connector-specific custom properties onto entities.                                                                                                             |
     | Mark Deleted Tables            | On      | Soft-delete tables in Collate when they are removed from the source. Applies only within the currently ingested schema.                                                |
     | Mark Deleted Stored Procedures | On      | Soft-delete stored procedures in Collate when they are removed from the source.                                                                                        |
     | Mark Deleted Schemas           | Off     | Soft-delete schemas and all their child assets when removed from the source.                                                                                           |
     | Mark Deleted Databases         | Off     | Soft-delete databases and all their child assets when removed from the source.                                                                                         |
     | Override Metadata              | Off     | When on, source values overwrite existing descriptions, tags, owners, and display names in Collate. When off, Collate only updates fields that have no existing value. |
     | Enable Debug Log               | Off     | Sets the ingestion log level to DEBUG. Useful for troubleshooting.                                                                                                     |

     <Note>
       **Note**: Available toggles vary by connector. Stored procedure options only appear for connectors that support stored procedures.
     </Note>

     <img src="https://mintcdn.com/collatedocs/kTp2dTyiNAX4Np5A/public/images/ai-2.0/connectors/metadata-ingestion/Database/database-scope-behaviour.png?fit=max&auto=format&n=kTp2dTyiNAX4Np5A&q=85&s=6ada5b2870c990f494d1dac400e73459" alt="Scope & Behaviour" width="1566" height="1436" data-path="public/images/ai-2.0/connectors/metadata-ingestion/Database/database-scope-behaviour.png" />

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

     <img src="https://mintcdn.com/collatedocs/kTp2dTyiNAX4Np5A/public/images/ai-2.0/connectors/metadata-ingestion/Database/database-advance.png?fit=max&auto=format&n=kTp2dTyiNAX4Np5A&q=85&s=63ef86d9e746b6d31f0571b599792357" alt="Advanced Config" width="1564" height="352" data-path="public/images/ai-2.0/connectors/metadata-ingestion/Database/database-advance.png" />

5. 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.

   <img src="https://mintcdn.com/collatedocs/bv5oe4uRjuorTJO1/public/images/ai-2.0/connectors/metadata-ingestion/schedule.png?fit=max&auto=format&n=bv5oe4uRjuorTJO1&q=85&s=25cc1d78f6f2a8bd115830d034d1d8d1" alt="Schedule Interval" width="1588" height="1044" data-path="public/images/ai-2.0/connectors/metadata-ingestion/schedule.png" />

6. Click **Add** to deploy the agent.

## Reverse Metadata

* **Description Management**: Databricks supports description updates at all levels:
  * Database level
  * Schema level
  * Table level
  * Column level

* **Owner Management**: Databricks supports owner management at the following levels:

  * Database level
  * Schema level
  * Table level

  <Tip>
    **Tip**: Databricks does not support to set `null` as owner.
  </Tip>

  <Note>
    **Note**: Databricks identifies user principals by email, not by username. When reverse ingestion updates a user owner, Collate uses the assigned user's email address when available and falls back to the Collate username otherwise. Collate resolves teams by team name—the team must match a Databricks account-level group.
  </Note>

* **Tag Management**: Databricks supports tag management at all levels:
  * Database level
  * Schema level
  * Table level
  * Column level

* **Custom SQL Template**: Databricks supports custom SQL templates for metadata changes. The template is interpreted using python f-strings.

  Here are examples of custom SQL queries for metadata changes:

  ```sql theme={null}
  -- Set table tags
  ALTER TABLE {database}.{schema}.{table} SET TAGS {tags};
  ```

  The list of variables for custom SQL can be found [here](/ai-2-0/admin-guide/applications/reverse-metadata#custom-sql-templates).

* **Requirements for Reverse Metadata**: In addition to the basic ingestion requirements, for reverse metadata ingestion the user needs:

  ```sql theme={null}
  -- Catalog grants
  GRANT USE CATALOG ON CATALOG `<catalog>` TO `<principal>`;
  GRANT MANAGE ON CATALOG `<catalog>` TO `<principal>`;

  -- Schema grants
  GRANT USE SCHEMA ON SCHEMA `<catalog>`.`<schema>` TO `<principal>`;
  GRANT MANAGE ON SCHEMA `<catalog>`.`<schema>` TO `<principal>`;
  GRANT APPLY TAG ON SCHEMA `<catalog>`.`<schema>` TO `<principal>`;

  -- Table grants
  GRANT MANAGE ON TABLE `<catalog>`.`<schema>`.`<table>` TO `<principal>`;
  GRANT APPLY TAG ON TABLE `<catalog>`.`<schema>`.`<table>` TO `<principal>`;
  ```

For more information about reverse metadata ingestion, see [Reverse Metadata Application](/ai-2-0/admin-guide/applications/reverse-metadata).

## Troubleshooting

<Columns cols={2}>
  <Card title="Databricks Troubleshooting" href="/ai-2-0/connectors/database/databricks/troubleshooting">
    Learn more about how to troubleshoot common Databricks connector issues and resolve configuration or ingestion errors.
  </Card>
</Columns>