Is Azure Data Factory different from Azure Databricks?

Yes, Azure Data Factory (ADF) and Azure Databricks serve different purposes in the Azure data ecosystem. ADF is a cloud-based data integration service that orchestrates data movement and transformation using pipelines, connectors, and data flows. It excels at ETL/ELT workflows, scheduling, and managing data pipelines across various sources. Azure Databricks, on the other hand, is an Apache Spark-based analytics platform that provides a collaborative workspace for data engineering, data science, and machine learning. It is used for large-scale data processing, complex transformations, and running notebooks. In practice, you might use ADF to orchestrate a pipeline that triggers a Databricks notebook for heavy processing, then writes results back to storage. Thus, ADF handles orchestration, while Databricks handles compute-intensive transformations.