Connect and Query Live SingleStore Data in Databricks with CData Connect Cloud

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 Cloud gives organizations live, real-time access to SingleStore 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 SingleStore using CData Connect Cloud. Once configured, you'll be able to access SingleStore 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 Cloud, create a connection to your SingleStore 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 SingleStore data.

Prerequisites

Before you begin, make sure you have the following:

1. An active SingleStore account.
2. A CData Connect Cloud 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 SingleStore Connection in CData Connect Cloud

1.1 Add a Connection to SingleStore

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

1. Log into Connect Cloud, click Sources on the left, and then click Add Connection in the top-right.

2. Select "SingleStore" from the Add Connection panel.

3. Enter the necessary authentication properties to connect to SingleStore.

   The following connection properties are required in order to connect to data.

   • Server: The host name or IP of the server hosting the SingleStore database.
   • Port: The port of the server hosting the SingleStore database.
   • Database (Optional): The default database to connect to when connecting to the SingleStore Server. If this is not set, tables from all databases will be returned.

   Connect Using Standard Authentication

   To authenticate using standard authentication, set the following:

   • User: The user which will be used to authenticate with the SingleStore server.
   • Password: The password which will be used to authenticate with the SingleStore server.

   Connect Using Integrated Security

   As an alternative to providing the standard username and password, you can set IntegratedSecurity to True to authenticate trusted users to the server via Windows Authentication.

   Connect Using SSL Authentication

   You can leverage SSL authentication to connect to SingleStore 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.

   Connect Using SSH Authentication

   Using SSH, you can securely login to a remote machine. To access SingleStore data via SSH, configure the following connection properties:

   • SSHClientCert: Set this to the name of the certificate store for the client certificate.
   • SSHClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
   • SSHClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
   • SSHClientCertType: The certificate type of the client store.
   • SSHPassword: The password that you use to authenticate with the SSH server.
   • SSHPort: The port used for SSH operations.
   • SSHServer: The SSH authentication server you are trying to authenticate against.
   • SSHServerFingerPrint: The SSH Server fingerprint used for verification of the host you are connecting to.
   • SSHUser: Set this to the username that you use to authenticate with the SSH server.
   
4. Click Save & Test in the top-right.
5. Navigate to the Permissions tab on the SingleStore Connection page and update the user-based permissions based on your preferences.

1.2 Generate a Personal Access Token (PAT)

When connecting to Connect Cloud 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 Cloud. 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 Cloud 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. 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 SingleStore Data in Databricks

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

2.1 Install the CData JDBC Driver for Connect Cloud

1. In CData Connect Cloud, 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 Cloud\lib\cdata.jdbc.connect.jar

   • Mac/Linux:

     /Applications/CData/CData JDBC Driver for Connect Cloud/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.
2. Click on the running cluster, go to the Libraries tab, and click Install New at the top right.
3. In the Install Library dialog, select DBFS, and drag and drop the cdata.jdbc.connect.jar file. Click Install.

2.3 Query SingleStore 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;"

2. Replace:
   • your_username - With your CData Connect Cloud username
   • your_pat - With your CData Connect Cloud Personal Access Token (PAT)
   • Your_Connection_Name - With the name of your Connect Cloud data source, from the Sources page
3. Run the script.

Notebook Script 2 — Load DataFrame from SingleStore 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()

3. Replace:
   • your_username - With your CData Connect Cloud username
   • your_pat - With your CData Connect Cloud Personal Access Token (PAT)
   • Your_Connection_Name - With the name of your Connect Cloud data source, from the Sources page
   • YOUR_SCHEMA.YOUR_TABLE - With your schema and table, for example, SingleStore.Orders
4. 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"))

3. Replace ColumnName1 and ColumnName2 with the actual columns from your SingleStore structure (e.g. ShipName, ShipCity, etc.).
4. Run the script.

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

Try CData Connect Cloud Free for 14 Days

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

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