Process & Analyze Webflow Data in Databricks (AWS)

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Use CData, AWS, and Databricks to perform data engineering and data science on live Webflow Data.

Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live Webflow data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live Webflow data in Databricks.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Webflow data. When you issue complex SQL queries to Webflow, the driver pushes supported SQL operations, like filters and aggregations, directly to Webflow and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Webflow data using native data types.

Install the CData JDBC Driver in Databricks

To work with live Webflow data in Databricks, install the driver on your Databricks cluster.

  1. Navigate to your Databricks administration screen and select the target cluster.
  2. On the Libraries tab, click "Install New."
  3. Select "Upload" as the Library Source and "Jar" as the Library Type.
  4. Upload the JDBC JAR file (cdata.jdbc.api.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Access Webflow Data in your Notebook: Python

With the JAR file installed, we are ready to work with live Webflow data in Databricks. Start by creating a new notebook in your workspace. Name the notebook, select Python as the language (though Scala is available as well), and choose the cluster where you installed the JDBC driver. When the notebook launches, we can configure the connection, query Webflow, and create a basic report.

Configure the Connection to Webflow

Connect to Webflow by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the RTK property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.

Step 1: Connection Information

driver = "cdata.jdbc.api.APIDriver"
url = "jdbc:api:RTK=5246...;Profile=C:\profiles\Webflow.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;"

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Webflow JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.api.jar

Fill in the connection properties and copy the connection string to the clipboard.

Authentication

Webflow uses OAuth 2.0 authentication to ensure secure access to sites, CMS collections, e-commerce data, and other resources. This authentication method allows you to securely connect to your Webflow workspace and manage resources with proper authorization.

OAuth 2.0 Setup and Configuration

Step 1: Create a Webflow OAuth Application

To set up OAuth authentication:

  1. Visit the Webflow Developer Portal
  2. Navigate to "Apps & Integrations" in your Webflow account
  3. Click "Register an App" to create a new OAuth application
  4. Configure the application name, description, and redirect URI (CallbackURL)
  5. Copy the Client ID and Client Secret for use in your connection

Required Connection Properties

  • AuthScheme: Set this to OAuth (required)
  • OAuthClientId: Client ID from your Webflow OAuth application (required)
  • OAuthClientSecret: Client secret from your Webflow OAuth application (required)
  • CallbackURL: Redirect URI specified in your OAuth application (required)
  • InitiateOAuth: Set to GETANDREFRESH for automatic token management (recommended)

Required OAuth Scopes

The Webflow API Profile requires the following OAuth scopes:

  • sites:read - Read access to site information and configuration
  • pages:read - Read access to site pages
  • cms:read - Read access to CMS collections and items
  • forms:read - Read access to forms and form submissions
  • assets:read - Read access to media assets and folders
  • ecommerce:read - Read access to products, orders, and inventory
  • authorized_user:read - Read access to the authorized user

Load Webflow Data

Once you configure the connection, you can load Webflow data as a dataframe using the CData JDBC Driver and the connection information.

Step 2: Reading the data

remote_table = spark.read.format ( "jdbc" ) \
	.option ( "driver" , driver) \
	.option ( "url" , url) \
	.option ( "dbtable" , "Sites") \
	.load ()

Display Webflow Data

Check the loaded Webflow data by calling the display function.

Step 3: Checking the result

display (remote_table.select (""))

Analyze Webflow Data in Databricks

If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.

Step 4: Create a view or table

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

With the Temp View created, you can use SparkSQL to retrieve the Webflow data for reporting, visualization, and analysis.

% sql

SELECT ,  FROM SAMPLE_VIEW ORDER BY  DESC LIMIT 5

The data from Webflow is only available in the target notebook. If you want to use it with other users, save it as a table.

remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )

Download a free, 30-day trial of the CData API Driver for JDBC and start working with your live Webflow data in Databricks. Reach out to our Support Team if you have any questions.

Ready to get started?

Connect to live data from Webflow with the API Driver

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