Import DB2 Data Using Azure Data Factory

Microsoft Azure Data Factory (ADF) is a completely managed, serverless data integration service. When combined with CData Connect AI, ADF enables immediate cloud-to-cloud access to DB2 data within data flows. This article outlines the process of connecting to DB2 through Connect AI and accessing DB2 data within ADF.

CData Connect AI offers a cloud-to-cloud interface tailored for DB2, granting you the ability to access live data from DB2 data within Azure Data Factory without the need for data replication to a natively supported database. Equipped with optimized data processing capabilities by default, CData Connect AI seamlessly channels all supported SQL operations, including filters and JOINs, directly to DB2. This harnesses server-side processing to expedite the retrieval of the desired DB2 data.

Configure DB2 Connectivity for ADF

Connectivity to DB2 from Azure Data Factory is made possible through CData Connect AI. To work with DB2 data from Azure Data Factory, we start by creating and configuring a DB2 connection.

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. Select "DB2" from the Add Connection panel

3. Enter the necessary authentication properties to connect to DB2.

   Set the following properties to connect to DB2:

   • Server: Set this to the name of the server running DB2.
   • Port: Set this to the port the DB2 server is listening on.
   • Database: Set this to the name of the DB2 database.
   • User: Set this to the username of a user allowed to access the database.
   • Password: Set this to the password of a user allowed to access the database.

   You will also need to install the corresponding DB2 driver:

   • Windows: Install the IBM Data Server Provider for .NET.

     On Windows, installing the IBM Data Server Provider is sufficient, as the installation registers it in the machine.config.

   • Java: Install the IBM Data Server Driver for JDBC.

     In the Java version, place the IBM Data Server Driver JAR in the www\WEB-INF\lib\ folder for this application.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add DB2 Connection page and update the User-based 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.
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 DB2 data from Azure Data Factory.

Access Live DB2 Data in Azure Data Factory

To establish a connection from Azure Data Factory to the CData Connect AI Virtual SQL Server API, follow these steps.

1. Login to Azure Data Factory.

2. If you have not yet created a Data Factory, Click New -> Dataset.

3. In the search bar, enter SQL Server and select it when it appears. On the following screen, enter a name for the server. In the Linked service field, select New.

4. Enter the connection settings.
   • Name - enter a name of your choice.
   • Server name - enter the Virtual SQL Server endpoint and port separated by a comma: tds.cdata.com,14333
   • Database name - enter the Connection Name of the CData Connect AI data source you want to connect to (for example, DB21).
   • 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 - select Password (not Azure Key Vault) and enter the PAT you generated on the Settings page.
   • Click Create.

5. In Set properties, set the Name, choose the Linked service we just created, select a Table name from those available, and Import schema from connection/store. Click OK.

6. After creating the linked service, the following screen should appear:

7. Click preview data to see the imported DB2 table.
You can now use this dataset when creating data flows in Azure Data Factory.

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