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URL: https://www.cdata.com/kb/tech/sendgrid-cloud-heidisql.rst

⇱ Connect to SendGrid Data from HeidiSQL


Connect to SendGrid Data from HeidiSQL

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

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

Configure SendGrid Connectivity for HeidiSQL

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

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

    To make use of all the available features, provide the User and Password connection properties.

    To connect with limited features, you can set the APIKey connection property instead. See the "Getting Started" chapter of the help documentation for a guide to obtaining the API key.

    πŸ‘ Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab in the Add SendGrid Connection page and update the User-based permissions. πŸ‘ 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. πŸ‘ 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 SendGrid data from HeidiSQL.

Connect to SendGrid 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-SendGrid
  3. πŸ‘ 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 πŸ‘ Configuring a SQL Server connection to Connect AI

Query SendGrid from HeidiSQL

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

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