Connect to Kintone 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 Kintone data. This article demonstrates how to connect to Kintone using Connect Cloud and query Kintone data in HeidiSQL.

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

Configure Kintone Connectivity for HeidiSQL

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

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

   In addition to the authentication values, set the following parameters to connect to and retrieve data from Kintone:

   • Url: The URL of your account.
   • GuestSpaceId: Optional. Set this when using a guest space.

   Authenticating with Kintone

   Kintone supports the following authentication methods.

   Using Password Authentication

   You must set the following to authenticate:

   • User: The username of your account.
   • Password: The password of your account.

   Using Basic Authentication

   If the basic authentication security feature is set on the domain, supply the additional login credentials with BasicAuthUser and BasicAuthPassword. Basic authentication requires these credentials in addition to User and Password.

   Using Client SSL

   Instead of basic authentication, you can specify a client certificate to authenticate. Set SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword. Additionally, set User and Password to your login credentials.

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

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 Kintone from HeidiSQL

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