Learn how Fabric receives streaming events, stores them for fast operational analysis, and turns conditions in live data into actions.
Eventstreams move and shape events, Eventhouse stores them, KQL queries them, dashboards show the current state, and Activator responds when a rule is satisfied.
Use Eventstreams to capture events from sources such as Event Hubs, IoT Hub, Kafka, or Fabric events. Filter, project, aggregate, join, and window events before sending them to an Eventhouse, Lakehouse, Activator, or another destination.
Choose Eventstreams when data needs transformation or routing while it is in motion.
An Eventhouse contains KQL databases designed for append-heavy, time-series and operational workloads. Data is queried with Kusto Query Language (KQL), and the same data can feed dashboards, Power BI, and automated actions.
Choose an Eventhouse for high-volume event data that is queried by time, entity, or operational state.
Apply restrictive where filters early, especially time filters. Use project to return only the columns needed, put the smaller input on the left side of a join, and use limit while exploring large results.
Reduce the amount of data scanned before expensive joins, projections, or aggregations.
Real-Time Dashboards display refreshed KQL query results. Activator follows a Connect, Monitor, Act pattern: it watches properties of real-world objects and triggers actions when a rule condition is met.
Use Activator when a condition should cause an action, not merely appear in a report.
| Requirement | Best fit |
|---|---|
| Transform or route events before storage | Eventstream |
| Store and query high-volume time-series data | Eventhouse with a KQL database |
| Create reusable query logic | Stored KQL function |
| Precompute recurring aggregations | Materialized view |
| Trigger a notification or workflow from a condition | Activator |