Connect to Azure DevOps 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 AI, HediSQL reach extends to include access to live Azure DevOps data. This article demonstrates how to connect to Azure DevOps using Connect AI and query Azure DevOps data in HeidiSQL.

CData Connect AI provides a pure SQL Server interface for Azure DevOps, allowing you to query data from Azure DevOps 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 DevOps, leveraging server-side processing to return the requested Azure DevOps data quickly.

Configure Azure DevOps Connectivity for HeidiSQL

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

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

2. Select "Azure DevOps" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to Azure DevOps. You can connect to your Azure DevOps account by providing the Organization and PersonalAccessToken.

   Obtaining a Personal Access Token

   A PersonalAccessToken is necessary for account authentication.

   To generate one, log in to your Azure DevOps Organization account and navigate to Profile -> Personal Access Tokens -> New Token. The generated token will be displayed.

   If you wish to authenticate to Azure DevOps using OAuth refer to the online Help documentation for an authentication guide.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Azure DevOps 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 DevOps data from HeidiSQL.

Connect to Azure DevOps from HeidiSQL using Connect AI

To establish a connection from HeidiSQL to the CData Connect AI 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 DevOps
👁 Creating a new session in HeidiSQL.

Configure a SQL Server Connection to Connect AI

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 AI username. This is displayed in the top-right corner of the CData Connect AI interface. For example, [email protected]
5. Set the Password to your PAT created in Connect AI in the previous section.
6. Set the Port to 14333 👁 Configuring a SQL Server connection to Connect AI
   

Query Azure DevOps from HeidiSQL

1. In the database listing on the left, find your connection to Azure DevOps configured earlier.
2. Expand this connection to view individual tables or data objects present within Azure DevOps.
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 👁 Querying within HeidiSQL.
   

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