This time we’re going bigger than ever. Fabric, Power BI, SQL, AI and more. We're covering it all. You won't want to miss it.
Learn moreDid you hear? There's a new SQL AI Developer certification (DP-800). Start preparing now and be one of the first to get certified. Register now
Categories: Real-Time Intelligence, Eventstreams
Tags: SQL operator, streaming, transformations, routing, code-first, multi-destination, event-time processing, testing
The SQL operator was first introduced in preview to give customers an early look at a code‑first transformation experience in Fabric Eventstreams. During preview, customers used the SQL operator to simplify real-time pipelines, consolidate transformation logic, and unlock advanced scenarios using familiar SQL semantics. Feedback from this phase directly shaped the GA release—driving improvements across multi‑destination support, event‑time processing, testing capabilities, and overall production readiness.
Building on this preview momentum, we’ve reached the next milestone for SQL operator in Fabric Eventstreams, a powerful, code‑first way to transform and route data across Fabric’s Real-Time Intelligence experiences. This complements Eventstream’s no-code capabilities, giving engineers the flexibility to choose the right abstraction for their scenarios.
With this release, you can define transformation and routing logic once using familiar SQL semantics and seamlessly deliver streaming results to multiple destinations in parallel—all from a single operator.
Multiple destinations from a single SQL operator - Fan out processed events simultaneously to Eventhouse, Lakehouse, Activator, or downstream Eventstreams—without duplicating pipelines.
Screenshot_of_an_eventstream_toplogy_depicting_a_EcommerceOrderEvents_custom_end
Figure: Eventstream topology using SQL operator writing to multiple outputs.
Built‑in testing experience - Validate transformations for individual outputs before publishing, making it easier to author and debug complex streaming logic.
Screenshot_of_a_code_editor_displaying_a_SQL_query_designed_to_read_and_analyze
Figure: An updated explorer and test results design for multiple outputs.
Event‑time processing - Process events based on event timestamps in the payload, with built‑in controls for handling late and out‑of‑order data.
Screenshot_of_an_eventstream_in_edit_mode_that_has_a_customer_endpoint_source_an
Figure: New advanced settings to configure late arrival and out of order threshold.
With the SQL operator in Fabric Eventstreams, you can:
You decide what data each destination receives, while Fabric handles the parallel delivery at scale.
We would love to hear what real-time scenarios you’re exploring and what topics you’d like us to cover in future posts. Drop us a comment or reach out to us at askeventstreams@microsoft.com
Have new feature ideas? Submit them at Fabric Ideas – Microsoft Fabric Community