| Feature | Copy Activity | Mapping Data Flow | | :--- | :--- | :--- | | | ELT (Extract, Load, then Transform) | ETL (Transform in flight) or ELT | | Code Required | None. Configuration only. | Spark-based transformation logic (Visual). | | Compute | Uses ADF Integration Runtime. | Uses Apache Spark clusters (Databricks/ADF IR). | | Complexity | Best for moving data or simple flattening. | Best for joins, aggregations, row modifications, pivots. | | Cost | Low for data movement. | Higher due to Spark cluster spin-up time. |
A Linked Service is equivalent to a connection string. It defines the connection information needed for ADF to access external resources (Source or Sink). javatpoint azure data factory
To be fair, Javatpoint’s Azure Data Factory content is not without flaws. Experienced data engineers will notice several critical omissions. | Feature | Copy Activity | Mapping Data
“Outdated. The UI screenshots are from two years ago. I wasted 30 minutes looking for the ‘publish’ button.” — AzureNewbie, Reddit | | Compute | Uses ADF Integration Runtime
Go to the tab. View pipeline runs, activity-level errors, and duration. Drill into the Copy Activity to see rows read, written, and throughput.