DataForge vs. Databricks Delta Live Tables for Change Data Capture
We are excited to announce the release of our latest video, where Vadim Orlov, CTO and co-founder of DataForge, walks us through the automation of Change Data Capture (CDC) processes using DataForge Cloud in comparison to Databricks Delta Live Tables.
Key Highlights of the Video:
Introduction to DataForge: Vadim explains how DataForge, a platform designed by data engineers, simplifies and automates the complex aspects of data engineering. He begins by addressing the frequent question from customers—why choose DataForge when Databricks already offers a powerful data platform?
Exploring Change Data Capture (CDC): The video focuses on a critical data engineering pattern—CDC—where Vadim compares and contrasts its implementation using Databricks’ Delta Live Table (DLT) library and DataForge Cloud. He highlights the nuances of configuring CDC pipelines in Databricks while showing how DataForge automates this traditionally tedious process.
Manual CDC in Databricks Delta Live Tables: Vadim reviews how Databricks handles CDC, including setting up pipeline snapshots and applying changes to source tables using DLT. He explains the steps involved in accumulating snapshots and the extensive boilerplate code needed to make it work, emphasizing the use of Python for this process.
Automating with DataForge Cloud: Vadim then shifts focus to DataForge Cloud and demonstrates how the platform automates the entire CDC process—from ingesting source data and configuring connections to storing and processing data in bronze, silver, and gold layers of a Delta Lake. With just a few clicks, DataForge Cloud handles tasks that typically take hours with DLT.
Real-time Demonstration: The video features a live demo where Vadim shows how to set up and manage CDC pipelines in both Databricks and DataForge Cloud. He performs key operations such as pulling data from a SQL server, tracking changes using DataForge’s built-in observability tools, and handling Slowly Changing Dimensions (SCD) types 1 and 2.
Advanced Features of DataForge Cloud: Vadim also covers advanced features such as exporting configuration settings into YAML files for easy management, making the platform even more flexible for complex projects. This feature helps users manage, track, and share configurations in source control systems.
Why You Should Watch This Video:
Time-Saving Automation: See firsthand how DataForge Cloud automates repetitive and complex data tasks, cutting down hours of manual configuration into just minutes.
Detailed Comparison: Gain insights into the strengths and limitations of using Databricks Delta Live Tables versus DataForge Cloud for CDC.
Live Demo: Follow along with Vadim as he walks through a real-world example, showcasing the simplicity and efficiency of DataForge Cloud.
Whether you're a data engineer looking to streamline your workflows or a business interested in automating your data pipelines, this video is packed with valuable insights.
The video is also available on YouTube with chapters to quickly navigate between sections.
Make sure to check out our website for additional resources, demos, and a 30-day free trial of DataForge Cloud!
