Connect to MessageBird Data from HeidiSQL

Mohsin Turki
Mohsin Turki
Technical Marketing Engineer
Use CData Connect AI to connect to and query live MessageBird 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 MessageBird data. This article demonstrates how to connect to MessageBird using Connect AI and query MessageBird data in HeidiSQL.

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

Configure MessageBird Connectivity for HeidiSQL

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a Connection
  3. Select "MessageBird" from the Add Connection panel
  4. Selecting a data source
  5. Enter the necessary authentication properties to connect to MessageBird.

    Start by setting the Profile connection property to the location of the MessageBird Profile on disk (e.g. C:\profiles\MessageBird.apip). Next, set the ProfileSettings connection property to the connection string for MessageBird (see below).

    MessageBird API Profile Settings

    Retrieve your private API Key from the MessageBird dashboard under Developers > API Access.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab in the Add MessageBird 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 MessageBird data from HeidiSQL.

Connect to MessageBird 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-MessageBird
  3. 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 MessageBird from HeidiSQL

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