Question

A retail analytics team ingests clickstream events into a Fabric Eventhouse using an Eventstream. Analysts run frequent, low-latency KQL queries that filter and aggregate the last 24 hours of events. The team wants the fastest possible query performance and full indexing/caching benefits on this hot data. When configuring the Eventstream destination into the Eventhouse, which approach should they choose?

Accepted Answer

Land the data as a native KQL table (direct ingestion) in the Eventhouse

Answer

Create a OneLake shortcut in the Eventhouse pointing to a lakehouse Delta table populated by the Eventstream

Answer

Write the events to a lakehouse table via Spark structured streaming, then query it from the Eventhouse over a shortcut

Answer

Store the events as Parquet files in OneLake and query them through an external table