{"active":true,"blog_title":"Fast copy in Dataflows Gen2","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/fast-copy-in-dataflows-gen-2","feature_description":"Partitioned Compute is a capability of Dataflow Gen2 that enables parts of a dataflow to run in parallel, reducing the time to finish its evaluations.Partitioned compute targets scenarios where the Dataflow engine can efficiently fold operations that can partition the data source and process each partition in parallel. For example, in a scenario where you're connecting to multiple files stored in an Azure Data Lake Storage Gen2, you can partition the list of files from your source, efficiently retrieve the partitioned list of files using query folding, use the combine files experience, and process all files in parallel.By moving to GA, Partitioned Compute becomes a stable, supported foundation for performant and highly scalable data transformation in Fabric.","feature_name":"Dataflows - Dataflows Gen2 Partitioned Compute","last_modified":"2026-04-16","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q2 2026","release_item_id":"385260b0-5b07-ef11-9f89-000d3a34b75c","release_status":"Planned","release_type":"General availability"}