Build Lakebase-Connected Visualizations in datapine

datapine is a browser-based business intelligence platform. When paired with the CData Connect AI, you get access to your Lakebase data directly from your datapine visualizations and dashboards. This article describes connecting to Lakebase in CData Connect AI and building a simple Lakebase-connected visualization in datapine.

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

Configure Lakebase Connectivity for datapine

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

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

2. Select "Lakebase" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Lakebase. To connect to Databricks Lakebase, start by setting the following properties:
   • DatabricksInstance: The Databricks instance or server hostname, provided in the format instance-abcdef12-3456-7890-abcd-abcdef123456.database.cloud.databricks.com.
   • Server: The host name or IP address of the server hosting the Lakebase database.
   • Port (optional): The port of the server hosting the Lakebase database, set to 5432 by default.
   • Database (optional): The database to connect to after authenticating to the Lakebase Server, set to the authenticating user's default database by default.

   OAuth Client Authentication

   To authenicate using OAuth client credentials, you need to configure an OAuth client in your service principal. In short, you need to do the following:

   1. Create and configure a new service principal
   2. Assign permissions to the service principal
   3. Create an OAuth secret for the service principal

   For more information, refer to the Setting Up OAuthClient Authentication section in the Help documentation.

   OAuth PKCE Authentication

   To authenticate using the OAuth code type with PKCE (Proof Key for Code Exchange), set the following properties:

   • AuthScheme: OAuthPKCE.
   • User: The authenticating user's user ID.

   For more information, refer to the Help documentation.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Lakebase 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 Lakebase data from datapine.

Connecting to Lakebase from datapine

Once you configure your connection to Lakebase in Connect AI, you are ready to connect to Lakebase from datapine.

1. Log into datapine
2. Click Connect to navigate to the "Connect" page
3. Select MS SQL Server as the data source
4. In the Integration step, fill in the connection properties and click "Save and Proceed"
   • Set the Internal Name
   • Set Database Name to the name of the connection we just configured (e.g. Lakebase1)
   • Set Host / IP to "tds.cdata.com"
   • Set Username to your Connect AI username (e.g. [email protected])
   • Set Password to the corresponding PAT
   • Set Database Port to "14333"
   
5. In the Data Schema step, select the tables and fields to visualize and click "Save and Proceed"
6. In the References step, define any relationships between your selected tables and click "Save and Proceed"
7. In the Data Transfer step, click "Go to Analyzer"

Visualize Lakebase Data in datapine

After connecting to CData Connect AI, you are ready to visualize your Lakebase data in datapine. Simply select the dimensions and measures you wish to visualize!

Having connect to Lakebase from datapine, you are now able to visualize and analyze real-time Lakebase data no matter where you are. To get live data access to 300+ SaaS, Big Data, and NoSQL sources directly from datapine, try CData Connect AI today!