Connect to Bitbucket 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 Bitbucket data. This article demonstrates how to connect to Bitbucket using Connect AI and query Bitbucket data in HeidiSQL.

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

Configure Bitbucket Connectivity for HeidiSQL

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

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

2. Select "Bitbucket" from the Add Connection panel

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

   For most queries, you must set the Workspace. The only exception to this is the Workspaces table, which does not require this property to be set, as querying it provides a list of workspace slugs that can be used to set Workspace. To query this table, you must set Schema to 'Information' and execute the query SELECT * FROM Workspaces>.

   Setting Schema to 'Information' displays general information. To connect to Bitbucket, set these parameters:

   • Schema: To show general information about a workspace, such as its users, repositories, and projects, set this to Information. Otherwise, set this to the schema of the repository or project you are querying. To get a full set of available schemas, query the sys_schemas table.
   • Workspace: Required if you are not querying the Workspaces table. This property is not required for querying the Workspaces table, as that query only returns a list of workspace slugs that can be used to set Workspace.

   Authenticating to Bitbucket

   Bitbucket supports OAuth authentication only. To enable this authentication from all OAuth flows, you must create a custom OAuth application, and set AuthScheme to OAuth.

   Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

   Creating a custom OAuth application

   From your Bitbucket account:

   1. Go to Settings (the gear icon) and select Workspace Settings.
   2. In the Apps and Features section, select OAuth Consumers.
   3. Click Add Consumer.
   4. Enter a name and description for your custom application.
   5. Set the callback URL:
      • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the CallbackURL property.
      • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
   6. If you plan to use client credentials to authenticate, you must select This is a private consumer. In the driver, you must set AuthScheme to client.
   7. Select which permissions to give your OAuth application. These determine what data you can read and write with it.
   8. To save the new custom application, click Save.
   9. After the application has been saved, you can select it to view its settings. The application's Key and Secret are displayed. Record these for future use. You will use the Key to set the OAuthClientId and the Secret to set the OAuthClientSecret.
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Bitbucket 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 Bitbucket data from HeidiSQL.

Connect to Bitbucket 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-Bitbucket

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

Query Bitbucket from HeidiSQL

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