Question

A retail analytics team already lands IoT sensor telemetry into a Delta table in a Fabric lakehouse using Spark Structured Streaming. The KQL analysts now need to run interactive, low-latency queries over the same telemetry from an Eventhouse (KQL database) without physically duplicating the data or maintaining a second ingestion pipeline. Data volume is high and the analysts are comfortable with slightly higher query latency than a native KQL table would provide. Which approach best meets these requirements?

Accepted Answer

Create a OneLake shortcut in the KQL database that points to the existing lakehouse Delta table

Answer

Add a new Eventstream destination that writes the telemetry into a native KQL table in the Eventhouse

Answer

Use a Data pipeline Copy activity to periodically copy the Delta table into a native KQL table

Answer

Enable database mirroring on the lakehouse to replicate the Delta table into the Eventhouse