Technical Documentation : Connectors : Adding a Databricks Unity Catalog JDBC Connection
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Adding a Databricks Unity Catalog JDBC Connection
Prerequisites
  • A user with sufficient permissions is required to establish a connection with Databricks Unity Catalog.
  • Zeenea traffic flows towards the data source must be open.
Important: The Databricks JDBC driver is not provided with the connector. Download the Databricks JDBC driver for your Databricks instance and copy it to the /lib-ext folder of your scanner (only the .jar file). You can find the driver in the sources provided by the vendor on their website: https://www.databricks.com/spark/jdbc-drivers-download.

Note: You can find a link to the configuration template in Zeenea Connector Downloads.
Supported Versions
The Databricks Unity Catalog JDBC connector is compatible with Databricks on AWS, Azure, and Google Cloud platforms.
Our connector has been built and tested with Simba 2.7.3 driver on Databricks 16.4 LTS version.
Installing the Plugin
The Databricks Unity Catalog JDBC plugin can be downloaded here: Zeenea Connector Downloads.
For more information on how to install a plugin, please refer to the following article: Installing and Configuring Connectors as a Plugin.
Declaring the Connection
Creating and configuring connectors is done through a dedicated configuration file located in the /connections folder of the relevant scanner.
In order to establish a connection with a Databricks Unity Catalog instance, specifying the following parameters in the dedicated file is required:
Parameter
Expected Value
name
The name that will be displayed to catalog users for this connection
code
Unique identifier of the connection on the Zeenea platform. Once registered on the platform, this code must not be modified or the connection will be considered as new and the old one removed from the scanner.
connector_id
The type of connector to be used for the connection. Here, the value must be databricks-jdbc and this value must not be modified.
connection.url
JDBC URL (example: jdbc:databricks://<tenant>.cloud.databricks.com:443)
connection.oauth.endpoint
Databricks OAuth2 endpoint (Optional)

 Example: https://tenant.cloud.databricks.com/oidc/v1/token.
connection.oauth.client_id
Client identifier
connection.oauth.client_secret
Client secret
connection.http_path
Cluster HTTP path
filter
To filter datasets during the inventory
fingerprint.sampling_max_rows
Max sampling rows during fingerprinting (default 10,000)
lineage.enabled
Enable lineage (default true)
User Permissions
In order to collect metadata, the running user's permissions must have SELECT access to system tables that contains all information we have to retrieve. User must have SELECT permission on the following Databricks schema : system.information_schema
Rich Filters
Databricks connector benefits from the feature of rich filters in the configuration of the connector. Available filtering keys for Databricks Unity Catalog JDBC are the following:
  • catalog
  • schema
  • table
Read more: Filters
Data Extraction
To extract information, the connector is querying the following system tables :
  • system.information_schema.tables : To get available tables and retrieve metadata.
  • system.information_schema.views : To retrieve view's data
  • system.information_schema.columns : To retrieve table's schema
  • system.information_schema.table_constraints : To retrieve primary keys
  • system.information_schema.key_column_usage : To retrieve foreign keys
  • system.information_schema.constraint_column_usage : To retrieve foreign keys
Collected Metadata
Inventory
Will collect the list of tables and views accessible by the user.
Dataset
A dataset can be a table or a view.
  • Name
  • Source Description
  • Technical Data:
    • Catalog Name
    • Schema Name
    • Type
    • Data Source Format
    • Storage Location
    • Created at
    • Created by
    • Updated at
    • Updated by
    • View query definition
Field
Dataset field.
  • Name
  • Source Description
  • Type
  • Can be null: Depending on the field settings
  • Multivalued: Depending on field type
  • Primary Key: Depending on the "Primary Key" attribute
  • Technical Data:
    • Technical Name
    • Native type
Unique Identifier Keys
A key is associated with each item of the catalog. When the object comes from an external system, the key is built and provided by the connector.
More information about unique identification keys in this documentation: Identification Keys
Object
Identifier Key
Description
Dataset
code/catalog/schema/dataset name
- code: Unique identifier of the connection noted in the configuration file
- catalog: Object catalog
- schema: Object schema
- dataset name: Table or view name
Field
code/catalog/schema/dataset name/field name
- code: Unique identifier of the connection noted in the configuration file
- catalog: Object catalog
- schema: Object schema
- dataset name: Table or view name
- field name
Last modified date: 11/28/2025