Integrates directly with GitHub and Azure DevOps for version control. Step-by-Step Guide: Creating Your First ADF Pipeline
A logical grouping of activities that perform a specific unit of work.
: New projects in greenfield environments should consider Microsoft Fabric as the long‑term platform. However, Azure Data Factory remains fully supported and will continue to serve millions of existing pipelines. Many organizations will run both in parallel during a multi‑year migration.
Out-of-the-box support for over 100+ native connectors, including AWS S3, Google BigQuery, Salesforce, SAP, Oracle, and Azure services. javatpoint azure data factory
: The execution layer responsible for moving and transforming data. Activities run on Integration Runtimes, which provide the compute resources.
Always use Azure DevOps integration with ADF to manage your pipeline code (JSON) in Git. This enables version control, collaboration, and CI/CD deployment across development, test, and production environments.
Whether you are building your first data pipeline or designing an enterprise‑grade data integration platform, Azure Data Factory provides the tools and flexibility to succeed. Integrates directly with GitHub and Azure DevOps for
Whether your data sits behind an requiring a Self-hosted IR. Share public link
: Logical groupings of activities that perform a specific task together. Activities
For existing ADF users, Microsoft has published migration guidance to transition pipelines to Fabric. The Mapping Data Flows engine, for instance, is being updated to use Spark 3.4. However, Azure Data Factory remains fully supported and
At the highest level, ADF consists of four interconnected components:
A represents the structure of the data you want to work with. If the linked service defines how to connect to a data store, the dataset defines what data to read or write.