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URL: https://www.cdata.com/kb/tech/domino-cloud-databricks.rst

⇱ Connect and Query Live HCL Domino Data in Databricks with CData Connect AI

Connect and Query Live HCL Domino Data in Databricks with CData Connect AI

👁 Mohsin Turki
Mohsin Turki
Technical Marketing Engineer
Use CData Connect AI to integrate live HCL Domino data into Databricks and enable direct, live querying and analysis without replication.

Databricks is a leading AI cloud-native platform that unifies data engineering, machine learning, and analytics at scale. Its powerful data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes. Integrating Databricks with CData Connect AI gives organizations live, real-time access to HCL Domino data without the need for complex ETL pipelines or data duplication—streamlining operations and reducing time-to-insights.

In this article, we'll walk through how to configure a secure, live connection from Databricks to HCL Domino using CData Connect AI. Once configured, you'll be able to access HCL Domino data directly from Databricks notebooks using standard SQL—enabling unified, real-time analytics across your data ecosystem.

Overview

Here is an overview of the simple steps:

  1. Step 1 — Connect and Configure: In CData Connect AI, create a connection to your HCL Domino source, configure user permissions, and generate a Personal Access Token (PAT).
  2. Step 2 — Query from Databricks: Install the CData JDBC driver in Databricks, configure your notebook with the connection details, and run SQL queries to access live HCL Domino data.

Prerequisites

Before you begin, make sure you have the following:

  1. An active HCL Domino account.
  2. A CData Connect AI account. You can log in or sign up for a free trial here.
  3. A Databricks account. Sign up or log in here.

Step 1: Connect and Configure a HCL Domino Connection in CData Connect AI

1.1 Add a Connection to HCL Domino

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

  1. Log into Connect AI, click Sources on the left, and then click Add Connection in the top-right.
    2. 👁 Adding a Connection in CData Connect AI
  2. Select "HCL Domino" from the Add Connection panel.
    3. 👁 Selecting a data source
  3. Enter the necessary authentication properties to connect to HCL Domino.

    Connecting to Domino

    To connect to Domino data, set the following properties:

    • URL: The host name or IP of the server hosting the Domino database. Include the port of the server hosting the Domino database. For example: http://sampleserver:1234/
    • DatabaseScope: The name of a scope in the Domino Web UI. The driver exposes forms and views for the schema governed by the specified scope. In the Domino Admin UI, select the Scopes menu in the sidebar. Set this property to the name of an existing scope.

    Authenticating with Domino

    Domino supports authenticating via login credentials or an Entra ID (formerly Azure AD) OAuth application:

    Login Credentials

    To authenticate with login credentials, set the following properties:

    • AuthScheme: Set this to "OAuthPassword"
    • User: The username of the authenticating Domino user
    • Password: The password associated with the authenticating Domino user

    The driver uses the login credentials to automatically perform an OAuth token exchange.

    EntraID (formerly AzureAD)

    This authentication method uses Entra ID (formerly Azure AD) as an IdP to obtain a JWT token. You need to create a custom OAuth application in Entra ID (formerly Azure AD) and configure it as an IdP. To do so, follow the instructions in the Help documentation. Then set the following properties:

    • AuthScheme: Set this to "EntraID (formerly AzureAD)"
    • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
    • OAuthClientId: The Client ID obtained when setting up the custom OAuth application.
    • OAuthClientSecret: The Client secret obtained when setting up the custom OAuth application.
    • CallbackURL: The redirect URI defined when you registered your app. For example: https://localhost:33333
    • AzureTenant: The Microsoft Online tenant being used to access data. Supply either a value in the form companyname.microsoft.com or the tenant ID.

      The tenant ID is the same as the directory ID shown in the Azure Portal's Entra ID (formerly Azure AD) > Properties page.

    👁 Configuring a connection (Salesforce is shown)
  4. Click Save & Test in the top-right.
  5. Navigate to the Permissions tab on the HCL Domino Connection page and update the user-based permissions based on your preferences. 👁 Updating permissions

1.2 Generate a Personal Access Token (PAT)

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. PAT functions as an alternative to your login credentials for secure, token-based authentication. It is a 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. Note: The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

Step 2: Connect and Query HCL Domino Data in Databricks

Follow these steps to establish a connection from Databricks to HCL Domino. You'll install the CData JDBC Driver for Connect AI, add the JAR file to your cluster, configure your notebooks, and run SQL queries to access live HCL Domino data data.

2.1 Install the CData JDBC Driver for Connect AI

  1. In CData Connect AI, click the Integrations page on the left. Search for JDBC or Databricks, click Download, and select the installer for your operating system.
  2. Once downloaded, run the installer and follow the instructions:
    • For Windows: Run the setup file and follow the installation wizard.
    • For Mac/Linux: Unpack the archive and move the folder to /opt or /Applications. Make sure you have execute permissions.
  3. After installation, locate the JAR file in the installation directory:
    • Windows: 
      C:\Program Files\CData\CData JDBC Driver for Connect AI\lib\cdata.jdbc.connect.jar
    • Mac/Linux: 
      /Applications/CData/CData JDBC Driver for Connect AI/lib/cdata.jdbc.connect.jar

2.2 Install the JAR File on Databricks

  1. Log in to Databricks. In the navigation pane, click Compute on the left. Start or create a compute cluster. 👁 Launching a compute cluster in Databricks
  2. Click on the running cluster, go to the Libraries tab, and click Install New at the top right. 👁 Accessing the Libraries tab in Databricks
  3. In the Install Library dialog, select DBFS, and drag and drop the cdata.jdbc.connect.jar file. Click Install. 👁 Uploading the JDBC driver JAR to DBFS

2.3 Query HCL Domino Data in a Databricks Notebook

Notebook Script 1 — Define JDBC Connection:

  1. Paste the following script into the notebook cell:
driver = "cdata.jdbc.connect.ConnectDriver"
url = "jdbc:connect:AuthScheme=Basic;User=your_username;Password=your_pat;URL=https://cloud.cdata.com/api/;DefaultCatalog=Your_Connection_Name;"
  1. Replace:
    • your_username - With your CData Connect AI username
    • your_pat - With your CData Connect AI Personal Access Token (PAT)
    • Your_Connection_Name - With the name of your Connect AI data source, from the Sources page
  2. Run the script.

Notebook Script 2 — Load DataFrame from HCL Domino data:

  1. Add a new cell for this second script. From the menu on the right side of your notebook, click Add cell below.
  2. Paste the following script into the new cell:
remote_table = spark.read.format("jdbc") \
 .option("driver", "cdata.jdbc.connect.ConnectDriver") \
 .option("url", "jdbc:connect:AuthScheme=Basic;User=your_username;Password=your_pat;URL=https://cloud.cdata.com/api/;DefaultCatalog=Your_Connection_Name;") \
 .option("dbtable", "YOUR_SCHEMA.YOUR_TABLE") \
 .load()
  1. Replace:
    • your_username - With your CData Connect AI username
    • your_pat - With your CData Connect AI Personal Access Token (PAT)
    • Your_Connection_Name - With the name of your Connect AI data source, from the Sources page
    • YOUR_SCHEMA.YOUR_TABLE - With your schema and table, for example, Domino.ByName
  2. Run the script.

Notebook Script 3 — Preview Columns:

  1. Similarly, add a new cell for this third script.
  2. Paste the following script into the new cell:
display(remote_table.select("ColumnName1", "ColumnName2"))
  1. Replace ColumnName1 and ColumnName2 with the actual columns from your HCL Domino structure (e.g. Name, Address, etc.).
  2. Run the script.
👁 Previewing HCL Domino data data in Databricks notebook

You can now explore, join, and analyze live HCL Domino data directly within Databricks notebooks—without needing to know the complexities of the back-end API and without replicating HCL Domino data.

Try CData Connect AI Free for 14 Days

Ready to simplify real-time access to HCL Domino data? Start your free 14-day trial of CData Connect AI today and experience seamless, live connectivity from Databricks to HCL Domino.

Low code, zero infrastructure, zero replication — just seamless, secure access to your most critical data and insights.