Forum Discussion
Does Power BI Process Refresh Partitions Sequentially or in Parallel?
Hi Team,
I would like to understand the expected Power BI refresh behavior from a SQL Server perspective.
During both Incremental Refresh and Full Refresh operations, our DBA observed multiple SQL queries running simultaneously against the source database.
For example, during Incremental Refresh, queries for multiple date ranges/partitions appear to run at the same time:
DATE_TIME >= '2026-06-11' AND DATE_TIME < '2026-06-12' DATE_TIME >= '2026-06-12' AND DATE_TIME < '2026-06-13' DATE_TIME >= '2026-06-13' AND DATE_TIME < '2026-06-14' DATE_TIME >= '2026-06-14' AND DATE_TIME < '2026-06-15'
Could you please confirm:
During Incremental Refresh, does Power BI process partitions sequentially or can multiple partitions be processed in parallel?
During a Full Refresh, does Power BI process tables/partitions sequentially or can multiple queries run concurrently against the source database?
Is there any Microsoft documentation that describes this behavior?
Is there any Power BI setting that controls or limits refresh parallelism?
We are trying to understand whether seeing multiple concurrent SQL queries during a Power BI refresh is expected behavior or not.
Thanks.
Hi manoj_0911,
Incremental Refresh -
Power BI creates multiple partitions and processes them during refresh. These partitions are not processed strictly one after another, multiple partitions can be processed in parallel (subject to engine limits and capacity).
Microsoft explains the partitioning behavior here - https://learn.microsoft.com/power-bi/connect-data/incremental-refresh-overviewFull Refresh -
Similarly, during a full refresh, Power BI does not process all tables or partitions sequentially. Multiple tables and/or partitions can be refreshed concurrently, which means multiple queries can hit the SQL Server source at the same time.Control over Refresh parallelism -
There’s no direct setting to control partition-level parallelism in Power BI. However, with Premium/PPU and the XMLA endpoint, you can explicitly control how partitions are processed.Microsoft explains Advanced incremental refresh and real-time data with the XMLA endpoint - https://learn.microsoft.com/power-bi/connect-data/incremental-refresh-xmla
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Best regards,
Rupasree Achari | BI & Fabric Analytics Engineer
5 Replies
- Rupa01
Solution Sage
Hi manoj_0911,
Incremental Refresh -
Power BI creates multiple partitions and processes them during refresh. These partitions are not processed strictly one after another, multiple partitions can be processed in parallel (subject to engine limits and capacity).
Microsoft explains the partitioning behavior here - https://learn.microsoft.com/power-bi/connect-data/incremental-refresh-overviewFull Refresh -
Similarly, during a full refresh, Power BI does not process all tables or partitions sequentially. Multiple tables and/or partitions can be refreshed concurrently, which means multiple queries can hit the SQL Server source at the same time.Control over Refresh parallelism -
There’s no direct setting to control partition-level parallelism in Power BI. However, with Premium/PPU and the XMLA endpoint, you can explicitly control how partitions are processed.Microsoft explains Advanced incremental refresh and real-time data with the XMLA endpoint - https://learn.microsoft.com/power-bi/connect-data/incremental-refresh-xmla
💡 Helpful? Give a Kudos 👍 — keep the community growing
✅ Solved your issue? Mark as Solution ✔️ — help others find it faster
Best regards,
Rupasree Achari | BI & Fabric Analytics Engineer - Parchitect
Solution Sage
Just to add a bit more context from the engine perspective, and not add same information as other correct replies in the post.The behavior you’re seeing (multiple SQL queries running at the same time) is expected and comes from how the Tabular engine processes data.Each partition (in incremental refresh) is processed independently, and the engine can process partitions in parallel to maximize throughput. That’s why you see multiple date-range queries executing concurrently against the source.The same applies to full refresh:- multiple tables and partitions can be processed in parallel- Power BI uses a limited number of processing slots (typically around 6 concurrent operations by default), so some queries run simultaneously while others queueMicrosoft documentation confirms that partitions in tabular models can be processed either sequentially or in parallel depending on available resources:https://learn.microsoft.com/en-us/analysis-services/tabular-models/partitions-ssas-tabularSo from a SQL Server / DBA perspective, seeing concurrent queries during refresh is completely normal and by design.Best regards,
Solutions Architect - Microsoft Fabric Specialist - Parchitect
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✔️Did I answer your question? Please mark my post as a Solution, it helps others find the answer faster. - krishnakanth240
Super User
Hi manoj_0911
Incremental Refresh = Power BI processes multiple partitions in parallel and might not be strictly sequential.
Full Refresh = Tables and partitions can also be refreshed concurrently and multiple queries against SQL Server are expected.
Documentation Links
https://learn.microsoft.com/en-us/power-bi/connect-data/incremental-refresh-xmla
Settings = No simple toggle in Power BI Desktop/Service. Parallelism is managed automatically by the engine and Premium capacity offers more control via XMLA.
Expected behavior = Yes, seeing multiple concurrent SQL queries during refresh is
normal.
- v-sgandrathi
Community Support
Hi manoj_0911,
Thank you krishnakanth240 Parchitect Rupa01 for your response to the query.
Following up to check whether you got a chance to review the suggestions given. If the issue still persists please let us know. Glad to help.Thank you.
- v-csrikanth
Community Support
Hi manoj_0911
We would like to inquire whether have you got the chance to check the solutions provided by other users in commiunity to resolve the issue. We hope the information provided helps to clear the query. Should you have any further queries, kindly feel free to contact the Microsoft Fabric community.
Thanks.