Connect to PCA Sales Data from HeidiSQL



Use CData Connect Cloud to connect to and query live PCA Sales 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 PCA Sales data. This article demonstrates how to connect to PCA Sales using Connect Cloud and query PCA Sales data in HeidiSQL.

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

Configure PCA Sales Connectivity for HeidiSQL

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

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

    In order to authenticate using the OAuth, specify the following:

    • AuthScheme: Set to OAuth.

    In order to authenticate using the OAuth Password, specify the following:

    • AuthScheme: Set to OAuthPassword.
    • User: Enter the PCA Sales username.
    • Password: Enter the PCA Sales password.
    • ServiceId: Enter the Service ID used to connect tot he PCA API server.
    • ServicePassword: Enter the Service Password for the above Service ID.

    For both authentication methods, specify the following:

    • Data Center: Enter the name for the PCA API Server.
    • Default Data Area: Enter the data area to which you want to connect.
    • Product Code: Enter "Kon20" or "Acc20."

    For more information, refer to the Help documentation.

  4. Click Create & Test
  5. Navigate to the Permissions tab in the Add PCA Sales 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 PCA Sales 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-PCA Sales

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 PCA Sales from HeidiSQL

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