How to Connect DBeaver to Azure Data Lake Storage via a JDBC Driver

The CData JDBC Driver for Azure Data Lake Storage implements JDBC standards that enable third-party tools to interoperate, from wizards in IDEs to business intelligence tools. This article shows how to connect to Azure Data Lake Storage data with wizards in DBeaver and browse data in the DBeaver GUI.

Create a JDBC Data Source for Azure Data Lake Storage Data

Follow the steps below to load the driver JAR in DBeaver.

1. Open the DBeaver application and, in the "Database" menu, select the "Driver Manager" option. Click "New" to open the "Create new driver" form.
2. In the Settings tab:
   • Set Driver Name to a user-friendly name for the driver (e.g. CData JDBC Driver for Azure Data Lake Storage).
   • Set Class Name to the class name for the JDBC driver: cdata.jdbc.adls.ADLSDriver.
   • Set URL Template to jdbc:adls:.
3. In the Libraries tab, click "Add File," navigate to the "lib" folder in the installation directory (C:\Program Files\CData[product_name] XXXX\) and select the JAR file (cdata.jdbc.ADLS.jar).

Create a Connection to Azure Data Lake Storage Data

Follow the steps below to add credentials and other required connection properties.

1. In the "Database" menu, click "New Database Connection."
2. In the "Connect to a database" wizard that results, select the driver you just created (e.g. CData JDBC Driver for Azure Data Lake Storage) and click "Next >."
3. On the Main tab of the configuration wizard, set the JDBC URL, using the required connection properties:

   Authenticating to a Gen 1 DataLakeStore Account

   Gen 1 uses OAuth 2.0 in Azure AD for authentication.

   For this, an Active Directory web application is required. You can create one as follows:

   1. Sign in to your Azure Account through the .
   2. Select "Azure Active Directory".
   3. Select "App registrations".
   4. Select "New application registration".
   5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
   6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
   7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

   To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen1.
   • Account: Set this to the name of the account.
   • OAuthClientId: Set this to the application Id of the app you created.
   • OAuthClientSecret: Set this to the key generated for the app you created.
   • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

   Authenticating to a Gen 2 DataLakeStore Account

   To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen2.
   • Account: Set this to the name of the account.
   • FileSystem: Set this to the file system which will be used for this account.
   • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Azure Data Lake Storage JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.adls.jar

   Fill in the connection properties and copy the connection string to the clipboard.

   Below is a typical connection string:

   jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH
4. Click "Test Connection ..." to ensure you have configured the connection properly.
5. Click "Finish."

Query Azure Data Lake Storage Data

You can now query information from the tables exposed by the connection: Right-click a Table and then click View Table. The data is available on the Data tab.

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