Redshift DB views Incremental Refresh Solution In ...

Koritala · ‎11-25-2025

Hi All,

I have redshift database views as source for my semantic model.

many views are having huge volume of data (morethan 1000000 rows). when I tried to import views it is exceeding the maximum limit and saying Import mode doesn't support.

Then I use the Direct Query mode. After that when I try to implement the Incremental refresh approach my creating parameters, view native SQL is not enabling in applied steps.

Can anyone help in this, how to setup incremental approach with Redshift data base views. Whether Power BI support this feature with Resdshift db or not.

I need to refresh data on incremental approach only on daily basis.

Thanks,

Sri.

Shubham_rai955

Power BI cannot do incremental refresh on a pure DirectQuery model, and that is why it fails for your Redshift views.

What Power BI supports

Incremental refresh works for Import or Hybrid (Import + DirectQuery) tables, not for tables that are 100% DirectQuery.
For Redshift, the table or view used for incremental refresh must support query folding (View Native Query enabled) so Power BI can push the RangeStart/RangeEnd filters back to Redshift.

Practical options for your case

Switch back to Import with incremental refresh
- Ask the Redshift team to expose your data as a table or materialized view with a date column you can filter on.
- In Power BI, set the connection to Import, define RangeStart / RangeEnd parameters and an incremental refresh policy on that table. This bypasses the 1‑million‑row per‑query DirectQuery limit because historical data is stored in the model and only new partitions refresh.
Use a Hybrid model (Premium/Fabric capacity)
- Import historical partitions with incremental refresh, and optionally enable the “Get the latest data in real time with DirectQuery” option so only the most recent slice hits Redshift in DirectQuery.
- Ensure the M query still folds when RangeStart/RangeEnd filters are applied; otherwise that DirectQuery option will be disabled.
If you must stay pure DirectQuery
- You cannot use Power BI incremental refresh; instead, handle incrementality in Redshift itself (for example, with materialized views that Redshift refreshes incrementally) and let Power BI query those objects directly.

In short: to get daily incremental loads from Redshift into Power BI, move the model to Import or Hybrid mode on a foldable table/materialized view, then configure incremental refresh on that table.

Koritala

Hi Shubham,

May I how what does it mean of Hybrid (Import + DirectQuery) tables?

I am not clear on this.

Thanks,

Sri

v-tejrama

Hi @Koritala ,

In Power BI, a Hybrid table is a single table that combines both Import mode and DirectQuery for different parts of its data. Usually, historical data is imported and stored in memory, while the most recent data is kept in DirectQuery mode, allowing Power BI to access the latest records directly from the source. This setup is automatically created when incremental refresh is enabled on a Premium or Fabric capacity, together with real-time data access.

As a result, most of the table is imported, and only a small, recent section stays in DirectQuery, giving users the benefits of both Import performance and DirectQuery freshness in one table. This is referred to as a Hybrid table in Power BI.

I'm also providing the Microsoft links for your reference--https://learn.microsoft.com/en-us/power-bi/connect-data/incremental-refresh-overview?utm_source.

Thank you.

v-tejrama · ‎11-26-2025

Hi @Koritala ,

It looks like everything you are running into is caused by how Power BI handles DirectQuery and query folding rather than anything specific to Redshift. Import mode is the only mode that supports incremental refresh, so once your dataset switched to DirectQuery to handle the size of your views, incremental refresh became unavailable. Even if the view allowed folding, incremental refresh still would not work because DirectQuery models simply do not support that feature.

Redshift views add another complication because they often cannot fold, especially if they include joins or aggregations, which is why you are seeing the native query option disabled in Power Query. To use incremental refresh with Redshift, the data has to be in Import or Hybrid mode, and the source has to support folding so Power BI can push the date filters back to the source. The typical solution is to replace the view with a table or a materialized view in Redshift so the model can be set back to Import mode. Once the data is coming from a foldable, date-filtered table and the model is using Import or Hybrid mode, incremental refresh will work as expected.

Thank you.

Koritala · ‎11-29-2025

Hi Tejrama,

After I read your commnets my understanding is if Redshift views definetions are having joins, incremental refresh will not work. To make it happen we need to change the views either into tables or Materialized views to enable the query folding option.

Please correct me if my understanding is correct or not?

Thanks,

Sri

v-tejrama · ‎12-02-2025

Hi @Koritala ,

You’re very close, but there is an important detail to clarify so you have the full picture. Incremental refresh does not work in DirectQuery mode at all, regardless of whether a Redshift view has joins or folds correctly. As long as the model is in DirectQuery, incremental refresh will remain unavailable. The reason people often move from a view to a table or a materialized view in Redshift is that those objects typically fold cleanly, which then allows the model to be switched back to Import or Hybrid mode. Once the data is coming from a foldable table and the model is no longer DirectQuery, Power BI can push the date filters back to the source and incremental refresh can finally work.

So it isn’t just the joins in the view that cause the issue. The real requirement is having a foldable source and using Import or Hybrid mode. Converting the view into a table or materialized view is the right approach, and once you do that and reload the model in Import mode, incremental refresh will behave as expected.

Thank you.

Koritala · ‎12-02-2025

Hi Tejrama,

Thanks for your response.

I just want to clarify onething that as you are saying instead of Redshift views, convert those to either to redshiaft tables or Materilized views. then connect those tables or materialized views connect with Import mode. then Foldinf will be enabled.

Here my problem is we are using PPU license and most of the base tables/views pulling more than 10 MB data that is the maximum limit support from power bi. So no way I can use Import mode of tables or Materilized views.

What are your suggestions in this scenario.

Appriciate if you can provide any solution.

Thanks,

Sri

v-tejrama

Hello again @Koritala ,

The 10 MB warning you are seeing is specific to Power Query’s preview and Desktop query limits, and does not restrict your Import model. For production, model size is determined by your license: Pro allows up to 1 GB per dataset, Premium Per User (PPU) supports up to 100 GB, and Premium capacities can be increased further with Large semantic model storage.

Converting complex Redshift views to tables or materialized views that support query folding enables loading via Import or Hybrid tables on PPU/Premium, and you can set up incremental refresh for efficient updates. Essentially, the preview warning does not prevent Import; ensure your workspace license and query folding capabilities align with your required model size and performance.

Thank you.

Koritala

Hi Tejrama,

Thanks for your response.

Thing is like, when I try to import the redshift view to power bi desktop using getdata option and selected the view and clickon load option, after few seconds or a minutes it is throwing a message saying that view has a maximum row limit in size and connect in direct query mode. selected view is not loading into power bi memory if i choose Import mode.

Please sugest in this case how to takle the situation.

Thanks,

Sri

v-tejrama

Hi @Koritala ,

Thank you @Shubham_rai955 for the helpful input!

Were you able to resolve the issue? If the response addressed your query, kindly confirm. This helps keep the community informed and improves solution visibility.

Thank you for your support!

v-tejrama

Hi @Koritala ,

I wanted to follow up and see if you had a chance to review the information shared. If you have any further questions or need additional assistance, feel free to reach out.

Thank you.