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URL: https://www.cdata.com/kb/tech/azuredatalake-cloud-jitterbit.rst

⇱ Integrate with live Azure Data Lake Storage Data in Jitterbit

Integrate with live Azure Data Lake Storage Data in Jitterbit

👁 Mohsin Turki
Mohsin Turki
Technical Marketing Engineer
Use CData Connect AI to connect to and integrate live Azure Data Lake Storage data in Jitterbit.

Jitterbit is an enterprise iPaaS (integration platform as a service) that lets you streamline your data workflows. When paired with CData Connect AI, Jitterbit gets access to live Azure Data Lake Storage data. This article demonstrates how to connect to Azure Data Lake Storage using Connect AI and integrate with live Azure Data Lake Storage data in Jitterbit.

CData Connect AI provides a pure OData 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 AI 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 Jitterbit

To work with Azure Data Lake Storage data from Jitterbit, we need to connect to Azure Data Lake Storage from Connect AI, provide user access to the connection, and create a Workspace for the Azure Data Lake Storage data.

Connect to Azure Data Lake Storage from Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

  1. Log into Connect AI, click Sources, and then click Add Connection
    2. 👁 Adding a Connection
  2. Select "Azure Data Lake Storage" from the Add Connection panel
    3. 👁 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.

Configure Azure Data Lake Storage Endpoints for Jitterbit

After connecting to Azure Data Lake Storage, create a workspace for your desired table(s).

  1. Navigate to the Workspaces page and click Add to create a new Workspace (or select an existing workspace). 👁 The Workspaces page.
    👁 Adding a new Workspace.
  2. Click Add to add new assets to the Workspace.
  3. Select the Azure Data Lake Storage connection (e.g. ADLS1) and click Next. 👁 Selecting an Asset (Salesforce is shown).
  4. Select the table(s) you wish to work with and click Confirm. 👁 Selecting Tables (Salesforce is shown).
  5. Make note of the OData Service URL for your workspace, e.g. https://cloud.cdata.com/api/odata/{workspace_name}

With the connection, PAT, and Workspace configured, you are ready to connect to Azure Data Lake Storage data from Jitterbit.

Connect to Azure Data Lake Storage from Jitterbit using Connect AI

To establish a connection from Jitterbit to CData Connect AI using the OData protocol, follow these steps.

  1. Log into Jitterbit.
  2. Create a project in Cloud Studio and provide a workspace environment for it. 👁 Creating a new project in Jitterbit.
  3. click Sources and enter OData in the search bar.
  4. Select the OData connector.
  5. Enter the OData connection properties.
    • Connection Name: enter a connection name.
    • OData Metadata URL: enter https://cloud.cdata.com/api/odata/{workspace_name}.
    • Authentication: select Basic Auth.
    • User Name: enter your CData Connect AI username. This is displayed in the top-right corner of the CData Connect AI interface. For example, [email protected].
    • Password: enter the PAT you generated on the Settings page.
    👁 Configuring connectivity to the Connect AI OData endpoint.
  6. Click Test to test the connection, and then click Save Changes.
  7. Choose the operation you want to perform and drag it to the workflow in your project. 👁 Selecting the operation for the workflow.
  8. Double-click the query operation to see all the tables and derived views available in your OData endpoint. 👁 Viewing the available endpoints.
  9. Select a table and configure the query.

You can now transform and integrate live Azure Data Lake Storage data in Jitterbit.

Get CData Connect AI

To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from Jitterbit, try CData Connect AI today!