Which Fabric tool is primarily used for streaming data ingestion?

• A. Data Pipeline
• B. Dataflow Gen2
• C. Notebook
• D. Eventstream

Answer: (D)

Streaming data ingestion is about capturing data as events as soon as they’re produced and delivering it with low latency for real-time analysis. In Fabric, the tool built for that role is Eventstream. It’s designed to handle high-velocity, continuous data from sources such as application logs, sensors, and messaging systems, and move it into your lakehouse or data warehouse with minimal delay so you can wake up dashboards, trigger alerts, and run near‑real-time queries.

Other options serve different purposes. Data Pipeline is oriented toward designing and orchestrating ETL/ELT workflows, usually batch-oriented or scheduled rather than continuous streaming. Dataflow Gen2 is a processing engine that runs transformations on data, whether batch or streaming, but it’s about computing and shaping data after ingestion rather than the ingestion itself. Notebooks are for interactive exploration and analysis, not for bringing in streaming data. That’s why streaming ingestion is best accomplished with the streaming-specific tool.