Query scale-out is a feature in Power BI Premium that allows you to distribute query processing across multiple read-only replicas of a dataset. This can significantly improve the performance of your reports, especially when you have a large number of users or when your dataset is very complex.
Here are some of the benefits of using query scale-out:
- Reduced query latency: When multiple users are querying a dataset, the replicas can share the load, which can significantly reduce the latency of each query.
- Increased throughput: With more replicas, you can handle more queries at the same time, which can improve the overall throughput of your Power BI solution.
- Improved data freshness: Refresh isolation ensures that data refresh operations do not impact query performance, so users can always see up-to-date data.
- Automated scaling: Power BI Premium can automatically scale the number of replicas based on usage, so you don't have to worry about manually adding or removing replicas.
Here are some of the limitations of using query scale-out:
- Increased storage requirements: Each replica of a dataset needs to store the entire dataset, so you will need to have enough storage space to accommodate the replicas.
- Increased network traffic: When users query a dataset, the request must be sent to all of the replicas, so there may be an increase in network traffic.
- Potential for conflicts: If multiple replicas are updating the dataset at the same time, there is a potential for conflicts. Power BI Premium uses a conflict-resolution mechanism to resolve these conflicts, but this can add some overhead.
Overall, query scale-out is a powerful feature that can significantly improve the performance of your Power BI solutions. However, it is important to weigh the benefits and limitations carefully before deciding whether or not to use it.
