Connect to SQL Analysis Services Data from HeidiSQL

Mohsin Turki
Mohsin Turki
Technical Marketing Engineer
Use CData Connect AI to connect to and query live SQL Analysis Services 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 SQL Analysis Services data. This article demonstrates how to connect to SQL Analysis Services using Connect AI and query SQL Analysis Services data in HeidiSQL.

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

Configure SQL Analysis Services Connectivity for HeidiSQL

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a Connection
  3. Select "SQL Analysis Services" from the Add Connection panel
  4. Selecting a data source
  5. Enter the necessary authentication properties to connect to SQL Analysis Services.

    To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

    To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

    • HTTP Authentication

      Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

    • Windows (NTLM)

      Set the Windows User and Password and set AuthScheme to "NTLM".

    • Kerberos and Kerberos Delegation

      To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

    • SSL/TLS:

      By default, the data provider attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.

    You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

    See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab in the Add SQL Analysis Services Connection page and update the User-based permissions. Updating 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. Creating a new PAT
  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 SQL Analysis Services data from HeidiSQL.

Connect to SQL Analysis Services 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-SQL Analysis Services
  3. Creating a new session in HeidiSQL.

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 Configuring a SQL Server connection to Connect AI

Query SQL Analysis Services from HeidiSQL

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

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