Guidance Needed on Push Dataset API Retirement

Hi Nagaraj_D,

Thanks for reaching fabric community, will happy to assist.

First The Actual Retirement Timeline

Creation of new streaming models (including push semantic models) remains enabled until October 31, 2027. After that date, creation of new real-time semantic models will no longer be supported. Your existing streaming semantic models will be unaffected. Microsoft Learn

So your current production solution is not breaking imminently you have time to plan.

Q1- Can you continue using Push Dataset REST APIs?

Yes, for now. Your existing push dataset and "PostRowsInGroup" calls will keep working until October 2027. However, creating brand new push datasets will eventually be blocked after that date. Plan migration before then, don't wait until the last minute.

Q2 - Exception via support ticket?

Honestly, based on community experience, exceptions are rarely granted for broad platform retirements like this. Microsoft's official stance is to migrate to Fabric Real-Time Intelligence. I wouldn't rely on an exception as a long-term strategy use the time until 2027 to plan a proper migration instead.

Q3 - Migration path that minimises rework

Here's the honest picture: the retirement of real-time streaming means Fabric Real-Time Intelligence using Eventstream and Eventhouse will replace it, and this requires upgrading to a Fabric capacity. Microsoft Fabric Community There is no way around this if you want the full replacement.

However, for your specific use case (pushing file metadata from a web app backend), the migration is actually simpler than a full streaming scenario:

Recommended Migration Path Minimum Rework:

Step-by-step:

• From your web app backend, instead of calling "PostRowsInGroup", write metadata to a Fabric Lakehouse table via the Fabric REST API or a simple Azure Function → Eventstream custom endpoint
• Build your Power BI reports on a Direct Lake Semantic Model on top of that Lakehouse table
• Reports refresh near-real-time without scheduled refresh cycles

This approach keeps your backend API pattern similar, avoids a full streaming architecture overhaul, and works well for file metadata (not high-frequency IoT data).

One Thing to Be Aware Of

Fabric Real-Time Intelligence is specifically built for time-based streaming events with features like auto-indexing and partitioning based on ingestion time. Microsoft Community Hub For your use case (file metadata, not millisecond-level streaming), the Lakehouse + Direct Lake path is likely simpler and cheaper than a full Eventhouse/Eventstream setup.

Summary

Start the migration planning now don't wait for 2027. Hope this helps!

Hi Nagaraj_D , Thank you for reaching out to the Microsoft Community Forum.

You’re not at immediate risk. Microsoft has deprecated real time streaming (which includes push datasets), but your existing push dataset and PostRowsInGroup calls will continue to work for now. The key point is that this pattern is no longer strategic and is expected to be retired.

On exceptions, I suggest you move to newer architectures rather than extend legacy ones. In practice, support tickets don’t give you a reliable long term path here, they may help short term, but they won’t change the direction of the platform.

There isn’t a true like for like replacement for push datasets. The shift is architectural, instead of pushing rows directly into a Power BI semantic model, I suggest you to land data in a storage layer first (for example, a Fabric Lakehouse or another database) and then build your semantic model on top of that. For your use case (file metadata, not high frequency streaming), you can keep your backend pattern but redirect it to write into a table and point your report to that table (Direct Lake in Fabric or DirectQuery/Import as an interim option).

If you want to minimize rework, a phased approach works best, continue using push datasets in the short term, introduce a proper storage layer in parallel and gradually move reports over. That way you avoid a big bang redesign while aligning with where Microsoft is heading.

Real-time streaming in Power BI - Power BI | Microsoft Learn

Load data in a Power BI streaming dataset and build a dataflows monitoring report with Power BI - Power Query | Microsoft Learn

Push Datasets - REST API (Power BI Power BI REST APIs) | Microsoft Learn

Power BI output from Azure Stream Analytics - Azure Stream Analytics | Microsoft Learn

Announcing the retirement of real-time streaming in Power BI - Power Community