Connect to FTP 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 FTP data. This article demonstrates how to connect to FTP using Connect AI and query FTP data in HeidiSQL.

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

Configure FTP Connectivity for HeidiSQL

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

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "FTP" from the Add Connection panel

3. Enter the necessary authentication properties to connect to FTP.

   To connect to FTP or SFTP servers, specify at least RemoteHost and FileProtocol. Specify the port with RemotePort.

   Set User and Password to perform Basic authentication. Set SSHAuthMode to use SSH authentication. See the Getting Started section of the data provider help documentation for more information on authenticating via SSH.

   Set SSLMode and SSLServerCert to secure connections with SSL.

   The data provider lists the tables based on the available folders in your FTP server. Set the following connection properties to control the relational view of the file system:

   • RemotePath: Set this to the current working directory.
   • TableDepth: Set this to control the depth of folders to list as views.
   • FileRetrievalDepth: Set this to retrieve and list files recursively from the root table.

   Stored Procedures are available to download files, upload files, and send protocol commands. See the Data Model chapter of the FTP data provider documentation for more information.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add FTP Connection page and update the User-based 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.
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 FTP data from HeidiSQL.

Connect to FTP 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-FTP

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

Query FTP from HeidiSQL

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