Connect to Airtable Data from HeidiSQL



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

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

Configure Airtable Connectivity for HeidiSQL

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

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

    APIKey, BaseId and TableNames parameters are required to connect to Airtable. ViewNames is an optional parameter where views of the tables may be specified.

    • APIKey : API Key of your account. To obtain this value, after logging in go to Account. In API section click Generate API key.
    • BaseId : Id of your base. To obtain this value, it is in the same section as the APIKey. Click on Airtable API, or navigate to https://airtable.com/api and select a base. In the introduction section you can find "The ID of this base is appxxN2ftedc0nEG7."
    • TableNames : A comma separated list of table names for the selected base. These are the same names of tables as found in the UI.
    • ViewNames : A comma separated list of views in the format of (table.view) names. These are the same names of the views as found in the UI.
  4. Click Create & Test
  5. Navigate to the Permissions tab in the Add Airtable 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 Airtable 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-Airtable

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 Airtable from HeidiSQL

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