Create Azure Data Lake Storage-Connected Enterprise Applications in OutSystems

OutSystems is a low-code platform which provides the tools for companies to developer, deploy, and manage omnichannel enterprise applications. When paired with CData Connect AI, you get instant, cloud-to-cloud access to Azure Data Lake Storage data for business applications. This article shows how to create a virtual database for Azure Data Lake Storage in Connect AI and build a simple app from Azure Data Lake Storage data in OutSystems.

The CData Connect AI provides a pure cloud-to-cloud interface for Azure Data Lake Storage, allowing you to build reports from live Azure Data Lake Storage data in OutSystems — without replicating the data to a natively supported database. As you create applications to work with data, OutSystems generates SQL queries to gather data. Using optimized data processing out of the box, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc.) directly to Azure Data Lake Storage, leveraging server-side processing to quickly return the requested Azure Data Lake Storage data.

Configure Azure Data Lake Storage Connectivity for OutSystems

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

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "Azure Data Lake Storage" from the Add Connection panel
👁 Selecting a data source

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 Entra ID (formerly 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 "Entra ID" (formerly Azure AD).
   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.
   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Azure Data Lake Storage Connection page and update the User-based permissions. 👁 Updating permissions
   

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create. 👁 Creating a new PAT
   
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Azure Data Lake Storage data from OutSystems.

Connect to Azure Data Lake Storage from OutSystems

The steps below outline connecting to CData Connect AI from OutSystems to create a new Azure Data Lake Storage database connection.

1. Open OutSystems Service Studio
2. Click the gear icon to open Environment Management in the Service Center 👁 Opening the Service Center
   
3. Click Administration and select "Database Connections"
4. Click "New Database Connection"
5. Configure the database connection:
   • Name: name the connection (e.g. CData Connect AI Azure Data Lake Storage)
   • DBMS: SQL Server / Azure SQL
   • Username: a Connect AI user (e.g. [email protected])
   • Password: the PAT for the Connect AI user
   • Server: tds.cdata.com,14333
   • Schema: the name of your Azure Data Lake Storage connection (e.g. ADLS1)
   👁 Connecting to the Connect AI
   
6. Click "Test Connection"
7. Click "Create"

Map Azure Data Lake Storage Tables or Views to Entities in an Extension Module

Once you create the database connection for Azure Data Lake Storage, you can create an extension that maps the tables or views to OutSystems entities. If you have not already done so, create an Application in Service Studio.

1. Open the Service Studio and open the existing Application
2. Click "Add Module," set the "Module Name" (e.g. adls_db_extension), set "Module Type" to "Extension," and click "Create Module" 👁 Creating a new extension module
   
3. In Integration Studio, connect to your environment
4. Right-click "Entities" in the extension tree and select "Connect to External Table or View..." 👁 Connecting to external tables or views
   
5. Follow the steps in the wizard, selecting the tables and views you wish to work with
6. In the Integration Studio, click "1-Click Publish"
7. In the "1-Click Publish" wizard, click "Configure" when the process completes
   • In the Service Center, associate the logical database name of the extension to the database connection that the extension will use and click "Apply" 👁 Configuring the external extension
     
8. In your application, click "Manage Dependencies..."
9. Add a dependency to the Extension and select the Entities that you will use in your application 👁 Adding a dependency to the extension
   

At this point, you can access and work with Azure Data Lake Storage data just like you would with the standard OutSystems entities.

Get CData Connect AI

With Connect AI and OutSystems, you can easily build Azure Data Lake Storage-connected applications. Request a free trial of Connect AI and start working with Azure Data Lake Storage data in OutSystems today.