Orchestration- Databricks Workflow VS Azure Data Factory

Ideally, Databricks Workflow orchestrates and schedules Databricks notebooks within the Databricks environment, whereas Azure Data Factory orchestrates and automates larger data integration workflows with numerous data sources and destinations.

What is Databricks Workflows?

Databricks Workflows is an orchestration tool that integrates with the Databricks environment, allowing users to construct, plan, and monitor complicated data pipelines right within Databricks. It is ideal for advanced analytics and machine learning jobs.

📌Key features of Databricks Workflow📌

🔍Integrates seamlessly with Databricks notebooks, jobs, and clusters.
🔍Helps you create and orchestrate data pipelines with Databricks notebooks and Spark tasks.
🔍Designed for complicated machine learning workflows and advanced analytics.
🔍Offers robust support for Delta Lake, improving data dependability and performance.
🔍Integration with Git provides built-in version control and collaboration tools.
Easily scales with the Databricks infrastructure.

🔔Use cases- When to use Databricks Workflow🔔

📌Machine learning model development and deployment.
📌Advanced analytics and ETL (extract, transform, and…