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Connect to Salesforce Pardot Data from HeidiSQL



Use CData Connect Cloud to connect to and query live Salesforce Pardot 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 Cloud, HediSQL reach extends to include access to live Salesforce Pardot data. This article demonstrates how to connect to Salesforce Pardot using Connect Cloud and query Salesforce Pardot data in HeidiSQL.

CData Connect Cloud provides a pure SQL Server interface for Salesforce Pardot, allowing you to query data from Salesforce Pardot without replicating the data to a natively supported database. Using optimized data processing out of the box, CData Connect Cloud pushes all supported SQL operations (filters, JOINs, etc.) directly to Salesforce Pardot, leveraging server-side processing to return the requested Salesforce Pardot data quickly.

Configure Salesforce Pardot Connectivity for HeidiSQL

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

  1. Log into Connect Cloud, click Connections and click Add Connection
  2. Select "Salesforce Pardot" from the Add Connection panel
  3. Enter the necessary authentication properties to connect to Salesforce Pardot.

    Salesforce Pardot supports connecting through API Version, Username, Password and User Key.

    • ApiVersion: The Salesforce Pardot API version which the provided account can access. Defaults to 4.
    • User: The Username of the Salesforce Pardot account.
    • Password: The Password of the Salesforce Pardot account.
    • UserKey: The unique User Key for the Salesforce Pardot account. This key does not expire.
    • IsDemoAccount (optional): Set to TRUE to connect to a demo account.

    Accessing the Pardot User Key

    The User Key of the current account may be accessed by going to Settings -> My Profile, under the API User Key row.

  4. Click Create & Test
  5. Navigate to the Permissions tab in the Add Salesforce Pardot Connection page and update the User-based permissions.

Add a Personal Access Token

If you are connecting from a service, application, platform, or framework that does not support OAuth authentication, you can create a Personal Access Token (PAT) to use for authentication. Best practices would dictate that you create a separate PAT for each service, to maintain granularity of access.

  1. Click on your username at the top right of the Connect Cloud app and click User Profile.
  2. On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
  3. Give your 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.

Connect to Salesforce Pardot from HeidiSQL using Connect Cloud

To establish a connection from HeidiSQL to the CData Connect Cloud 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-Salesforce Pardot

Configure a SQL Server Connection to Connect Cloud

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

Query Salesforce Pardot from HeidiSQL

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