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The Azure Data Lake Storage ODBC Driver is a powerful tool that allows you to connect with live data from Azure Data Lake Storage, directly from any applications that support ODBC connectivity.

Access Azure Data Lake Storage data like you would a database - read, write, and update Azure Data Lake Storage ADLSData, etc. through a standard ODBC Driver interface.

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How to Query Azure Data Lake Storage Data in MySQL Workbench


Execute MySQL queries against live Azure Data Lake Storage data from MySQL Workbench.

You can use the SQL Gateway from the ODBC Driver for Azure Data Lake Storage to query Azure Data Lake Storage data through a MySQL interface. Follow the procedure below to start the MySQL remoting service of the SQL Gateway and work with live Azure Data Lake Storage data in MySQL Workbench.

Connect to Azure Data Lake Storage Data

If you have not already done so, provide values for the required connection properties in the data source name (DSN). You can use the built-in Microsoft ODBC Data Source Administrator to configure the DSN. This is also the last step of the driver installation. See the "Getting Started" chapter in the help documentation for a guide to using the Microsoft ODBC Data Source Administrator to create and configure a DSN.

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.

Configure the SQL Gateway

See the SQL Gateway Overview to set up connectivity to Azure Data Lake Storage data as a virtual MySQL database. You will configure a MySQL remoting service that listens for MySQL requests from clients. The service can be configured in the SQL Gateway UI.

Creating a MySQL Remoting Service in SQL Gateway (Salesforce is shown)

Query Azure Data Lake Storage from MySQL Workbench

The steps below outline connecting to the virtual Azure Data Lake Storage database created in the SQL Gateway from MySQL Workbench and issuing basic queries to work with live Azure Data Lake Storage data.

Connect to Azure Data Lake Storage through the SQL Gateway

  1. In MySQL Workbench, click to add a new MySQL connection.
  2. Name the connection (CData SQL Gateway for Azure Data Lake Storage).
  3. Set the Hostname, Port, and Username parameters to connect to the SQL Gateway.
  4. Click Store in Vault to set and store the password.
  5. Click Test Connection to ensure the connection is configured properly and click OK.

NOTE: When we refer to Username and Password, we mean the credentials for the user(s) created for the SQL Gateway.

Query Azure Data Lake Storage Data

  1. Open the connection you just created (CData SQL Gateway for Azure Data Lake Storage).
  2. Click File -> New Query Tab.
  3. Write a SQL query to retrieve Azure Data Lake Storage data, like SELECT * FROM `CData ADLS Sys`.Resources;

With access to live Azure Data Lake Storage data from MySQL Workbench, you can easily query and update Azure Data Lake Storage, just like you would a MySQL database. Get started now with a free, 30-day trial of the CData ODBC Driver for Azure Data Lake Storage and the CData SQL Gateway.