Connect to Azure Data Lake Storage Data from HeidiSQL

HeidiSQL is an open-source database administration tool that natively supports MariaDB, MySQL, SQL Server, and PostgreSQL. When paired with CData Connect Cloud, HediSQL reach extends to include access to live Azure Data Lake Storage data. This article demonstrates how to connect to Azure Data Lake Storage using Connect Cloud and query Azure Data Lake Storage data in HeidiSQL.

CData Connect Cloud provides a pure SQL Server interface for Azure Data Lake Storage, allowing you to query data from Azure Data Lake Storage without replicating the data to a natively supported database. Using optimized data processing out of the box, CData Connect Cloud pushes all supported SQL operations (filters, JOINs, etc.) directly to Azure Data Lake Storage, leveraging server-side processing to return the requested Azure Data Lake Storage data quickly.

Configure Azure Data Lake Storage Connectivity for HeidiSQL

Connectivity to Azure Data Lake Storage from HeidiSQL is made possible through CData Connect Cloud. To work with Azure Data Lake Storage data from HeidiSQL, we start by creating and configuring a Azure Data Lake Storage connection.

1. Log into Connect Cloud, click Connections and click Add Connection
2. Select "Azure Data Lake Storage" from the Add Connection panel
3. Enter the necessary authentication properties to connect to Azure Data Lake Storage.

   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.
4. Click Create & Test
5. Navigate to the Permissions tab in the Add Azure Data Lake Storage Connection page and update the User-based permissions.

Add a Personal Access Token

If you are connecting from a service, application, platform, or framework that does not support OAuth authentication, you can create a Personal Access Token (PAT) to use for authentication. Best practices would dictate that you create a separate PAT for each service, to maintain granularity of access.

1. Click on your username at the top right of the Connect Cloud app and click User Profile.
2. On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
3. Give your PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

Connect to Azure Data Lake Storage from HeidiSQL using Connect Cloud

To establish a connection from HeidiSQL to the CData Connect Cloud Virtual SQL Server API, follow these steps.

Create a new HeidiSQL Session

1. In the Session Manager, select New in the bottom-left
2. Give the new session a descriptive name, e.g. Connect-Cloud-Azure Data Lake Storage

Configure a SQL Server Connection to Connect Cloud

1. In the session settings, set the Network type to Microsoft SQL Server (TCP/IP)
2. The Library DLL should automatically update to MSOLEDBSQL
3. Set the Hostname/IP to tds.cdata.com
4. Set the User to your CData Connect Cloud username. This is displayed in the top-right corner of the CData Connect Cloud interface. For example, [email protected]
5. Set the Password to your PAT created in Connect Cloud in the previous section.
6. Set the Port to 14333

Query Azure Data Lake Storage from HeidiSQL

1. In the database listing on the left, find your connection to Azure Data Lake Storage configured earlier.
2. Expand this connection to view individual tables or data objects present within Azure Data Lake Storage.
3. Write custom SQL queries targeting these tables, treating the data source like any SQL Server database, or visually explore each tabular data set by selecting the relevant tables

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