Connect and Query Live EnterpriseDB Data in Databricks with CData Connect AI
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 EnterpriseDB 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 EnterpriseDB using CData Connect AI. Once configured, you'll be able to access EnterpriseDB 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:
- Step 1 — Connect and Configure: In CData Connect AI, create a connection to your EnterpriseDB source, configure user permissions, and generate a Personal Access Token (PAT).
- 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 EnterpriseDB data.
Prerequisites
Before you begin, make sure you have the following:
- An active EnterpriseDB account.
- A CData Connect AI account. You can log in or sign up for a free trial here.
- A Databricks account. Sign up or log in here.
Step 1: Connect and Configure a EnterpriseDB Connection in CData Connect AI
1.1 Add a Connection to EnterpriseDB
CData Connect AI uses a straightforward, point-and-click interface to connect to available data sources.
- Log into Connect AI, click Sources on the left, and then click Add Connection in the top-right.
- Select "EnterpriseDB" from the Add Connection panel.
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Enter the necessary authentication properties to connect to EnterpriseDB.
The following connection properties are required in order to connect to data.
- Server: The host name or IP of the server hosting the EnterpriseDB database.
- Port: The port of the server hosting the EnterpriseDB database.
You can also optionally set the following:
- Database: The default database to connect to when connecting to the EnterpriseDB Server. If this is not set, the user's default database will be used.
Connect Using Standard Authentication
To authenticate using standard authentication, set the following:
- User: The user which will be used to authenticate with the EnterpriseDB server.
- Password: The password which will be used to authenticate with the EnterpriseDB server.
Connect Using SSL Authentication
You can leverage SSL authentication to connect to EnterpriseDB data via a secure session. Configure the following connection properties to connect to data:
- SSLClientCert: Set this to the name of the certificate store for the client certificate. Used in the case of 2-way SSL, where truststore and keystore are kept on both the client and server machines.
- SSLClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
- SSLClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
- SSLClientCertType: The certificate type of the client store.
- SSLServerCert: The certificate to be accepted from the server.
- Click Save & Test in the top-right.
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Navigate to the Permissions tab on the EnterpriseDB Connection page
and update the user-based permissions based on your preferences.
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.
- Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
- 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 EnterpriseDB Data in Databricks
Follow these steps to establish a connection from Databricks to EnterpriseDB. 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 EnterpriseDB data data.
2.1 Install the CData JDBC Driver for Connect AI
- 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.
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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.
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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
- Windows:
2.2 Install the JAR File on Databricks
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Log in to Databricks. In the navigation pane, click Compute on the left. Start or create a compute cluster.
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Click on the running cluster, go to the Libraries tab, and click Install New at the top right.
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In the Install Library dialog, select DBFS, and drag and drop the
cdata.jdbc.connect.jar file. Click Install.
2.3 Query EnterpriseDB Data in a Databricks Notebook
Notebook Script 1 — Define JDBC Connection:
- 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;"
- 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
- Run the script.
Notebook Script 2 — Load DataFrame from EnterpriseDB data:
- Add a new cell for this second script. From the menu on the right side of your notebook, click Add cell below.
- 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()
- 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, EnterpriseDB.Orders
- Run the script.
Notebook Script 3 — Preview Columns:
- Similarly, add a new cell for this third script.
- Paste the following script into the new cell:
display(remote_table.select("ColumnName1", "ColumnName2"))
- Replace ColumnName1 and ColumnName2 with the actual columns from your EnterpriseDB structure (e.g. ShipName, ShipCity, etc.).
- Run the script.
You can now explore, join, and analyze live EnterpriseDB data directly within Databricks notebooks—without needing to know the complexities of the back-end API and without replicating EnterpriseDB data.
Try CData Connect AI Free for 14 Days
Ready to simplify real-time access to EnterpriseDB data? Start your free 14-day trial of CData Connect AI today and experience seamless, live connectivity from Databricks to EnterpriseDB.
Low code, zero infrastructure, zero replication — just seamless, secure access to your most critical data and insights.