Connect to Live SQL Analysis Services Data in PostGresSQL Interface through CData Connect AI

There are a vast number of PostgreSQL clients available on the Internet. PostgreSQL is a popular interface for data access. When you pair PostgreSQL with CData Connect AI, you gain database-like access to live SQL Analysis Services data from PostgreSQL. In this article, we walk through the process of connecting to SQL Analysis Services data in Connect AI and establishing a connection between Connect AI and PostgreSQL using a TDS foreign data wrapper (FDW).

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.

Connect to SQL Analysis Services in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

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

2. Select "SQL Analysis Services" from the Add Connection panel

3. 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.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add SQL Analysis Services 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 SQL Analysis Services data from PostgreSQL.

Build the TDS Foreign Data Wrapper

The Foreign Data Wrapper can be installed as an extension to PostgreSQL, without recompiling PostgreSQL. The tds_fdw extension is used as an example (https://github.com/tds-fdw/tds_fdw).

1. You can clone and build the git repository via something like the following view source:

   sudo apt-get install git
   git clone https://github.com/tds-fdw/tds_fdw.git
   cd tds_fdw
   make USE_PGXS=1
   sudo make USE_PGXS=1 install
   

   Note: If you have several PostgreSQL versions and you do not want to build for the default one, first locate where the binary for pg_config is, take note of the full path, and then append PG_CONFIG= after USE_PGXS=1 at the make commands.
2. After you finish the installation, then start the server:

   sudo service postgresql start
   

3. Then go inside the Postgres database

   psql -h localhost -U postgres -d postgres
   

   Note: Instead of localhost you can put the IP where your PostgreSQL is hosted.

Connect to SQL Analysis Services data as a PostgreSQL Database and query the data!

After you have installed the extension, follow the steps below to start executing queries to SQL Analysis Services data:

1. Log into your database.
2. Load the extension for the database:

   CREATE EXTENSION tds_fdw;
   

3. Create a server object for SQL Analysis Services data:

   CREATE SERVER "SSAS1" FOREIGN DATA WRAPPER tds_fdw OPTIONS (servername'tds.cdata.com', port '14333', database 'SSAS1');
   

4. Configure user mapping with your email and Personal Access Token from your Connect AI account:

   CREATE USER MAPPING for postgres SERVER "SSAS1" OPTIONS (username '[email protected]', password 'your_personal_access_token' );
   

5. Create the local schema:

   CREATE SCHEMA "SSAS1";
   

6. Create a foreign table in your local database:

   #Using a table_name definition:
   
   CREATE FOREIGN TABLE "SSAS1".Adventure_Works  (      
   id varchar,      
   Sales_Amount varchar)      
   SERVER "SSAS1"
   OPTIONS(table_name 'SSAS.Adventure_Works', row_estimate_method 'showplan_all');
   
   #Or using a schema_name and table_name definition:
   
   CREATE FOREIGN TABLE "SSAS1".Adventure_Works (      
   id varchar,      
   Sales_Amount varchar)      
   SERVER "SSAS1"
   OPTIONS (schema_name 'SSAS', table_name 'Adventure_Works', row_estimate_method 'showplan_all');
   
   #Or using a query definition:
   
   CREATE FOREIGN TABLE  "SSAS1".Adventure_Works (
   id varchar,      
   Sales_Amount varchar)      
   SERVER "SSAS1"
   OPTIONS (query 'SELECT * FROM SSAS.Adventure_Works', row_estimate_method 'showplan_all');
   
   #Or setting a remote column name:
   
   CREATE FOREIGN TABLE "SSAS1".Adventure_Works (
   id varchar,
   col2 varchar OPTIONS (column_name 'Sales_Amount'))
   SERVER "SSAS1"
   OPTIONS (schema_name 'SSAS', table_name 'Adventure_Works', row_estimate_method 'showplan_all');
   

7. You can now execute read/write commands to SQL Analysis Services:

   SELECT id, Sales_Amount
   FROM "SSAS1".Adventure_Works;
   

More Information & Free Trial

Now, you have created a simple query from live SQL Analysis Services data. For more information on connecting to SQL Analysis Services (and more than 200 other data sources), visit the Connect AI page. Sign up for a free trial and start working with live SQL Analysis Services data in PostgreSQL.