Data drives today’s digital-driven businesses and is considered as an asset to strengthening a data-driven decision-making process. Microsoft’s Power BI, a powerful business analytics tool, offers a platform to collect, analyze, and visualize data through attractive visualization and interactive reports, empowering businesses to boost profitability and uncover insights.
As you connect to data in Power BI, there are two primary modes that you can opt for – Import and DirectQuery. There is a constant comparison between Power BI Import vs Direct Query. The Import method captures a snapshot of data and caches it in the Power BI Desktop whereas the Direct Query method executes queries directly to the source at runtime.
The one that you choose depends on several factors like the amount of data that is to be handled, frequency of updates, organizational goals, etc. Based on these factors, a decision can be made. Before we investigate the difference between Power BI Direct Query vs Import, let us individually go through their features, pros, and cons.
Import mode is the most common mode used to develop datasets. This mode delivers fast performance thanks to in-memory querying. It also offers design flexibility to modelers, and support for specific Power BI service features (Q&A, Quick Insights, etc.). Because of these strengths, it’s the default mode when creating a new Power BI Desktop solution.
While using Power BI Import, data from disparate sources can be imported into the Power BI data file with a PBIX extension. It executes in the memory and is optimized by the ‘VertiPaq’ engine that creates reports and dashboards that are responsive. Once data is imported in the file and the model is created, the file is uploaded to the Power BI service for creating reports and dashboards.
The import mode of data storage empowers users to get the data easily into Power BI Desktop, by merely navigating t the data source, choosing the tables to be added, and clicking Import. It is recommended to be used when the data size is less than 1 GB and there is not much of change in the data. All the interactions and filters of data will be applied to the compressed source rather than the main one.
With Power BI Import, users can design complicated data models, and undergo advanced calculations with the Data Analysis Expressions (DAX) language for the creation of data visualizations. Data is loaded from different sources like CSV files, Excel files, databases, and cloud-driven services onto Power BI for further analysis.
DirectQuery mode is an alternative to Import mode. Models developed in DirectQuery mode don’t import data. Instead, they consist only of metadata defining the model structure. When the model is queried, native queries are used to retrieve data from the underlying data source.
Power BI Direct Query is a powerful deployment method that extracts data from different sources when the reports are executed so that the output is live. It directly connects to the data source and maintains that connectivity while executing reports. It reflects changes in real-time and hence refresh is not needed manually. It is recommended when data is getting updated frequently or when the volume of data is large.
Power BI sends queries to the data source on creating visual effects. The dashboard will query the data source at runtime and fetch the results in real time. All interaction with reports will result in a new query that will be directly executed.
Since no data is imported in Power BI, the data that is queried is available in the data source itself. Each query is limited to return less than or equal to 1 million rows. With Power BI Direct Query, users can build data models that can span across multiple data sources and tables to come up with real-time analytics of the data.
Pros of Power BI Import:
Cons of Power BI Import:
Pros of Direct Query:
Cons of Direct Query:
Parameters | Power BI Import | Power BI DirectQuery |
Performance | It has a high-performance query engine, and the data model is already cached with no latency but with more volume, it may degrade | Since queries are processed in real-time, it depends on the network connectivity. If indexes are well created, it performs well |
DAX Expressions and Transformations | Supports all DAX functions and advanced Power Query transformations for shaping the data prior to importing it | Restricted support for DAX functions and transformations since you can use limited data available in the data source |
Schedule Refresh | Hourly/daily programmed async jobs with maximum 8 schedules per day | Schedule at every 15-minute interval or at real-time |
Size | Approximately 1GB per dataset/model | No limit to storing data in an on-premises database |
Source of Data | Importing data from multiple sources | Importing data from a single source |
Data Modeling | No limitations | Some limitations |
In-built Hierarchy | Accessible | Not accessible |
Data Storage | Data is preserved in the Power BI Service since it is in the cloud | The cloud service will not store any data, it will be stored locally |
Data Availability | If data refresh doesn’t work, the last data available in the model is used | If data refresh doesn’t work, the report goes black since data is not stored |
Change in Data Connectivity Mode | Cannot change from Import to Direct Query | The mode can be changed from Direct Query to Import |
Target Groups | Small to Medium Datasets | Large Datasets (greater than 1 GB) |
Security | Users can create row-level security on the PBI dataset | Users can reuse on-premises row-level security for Analysis Services |
Clustering, Quick Insights, Calculated Tables | Available | Not available |
Flexibility and Control | There is more control over data and hence creation of complex data models is easier but may not be suitable for larger datasets | Since data is not stored in Power BI, it is not that flexible in terms of creating complex data models but can manage large datasets with ease |
Whenever there is a comparison between Direct Query vs Import Power BI, there are situations when one of them is recommended over the other. Here are certain suggestions:
Power BI Direct Query is suggested when:
Power BI Import is suggested when:
As we compare Direct vs Import Query in Power BI, we see that if needed, both these modes of connecting data can be combined. They can be combined in the same report, taking advantage of the features of both. This can happen using the Dual Storage mode, wherein some tables are imported while some are directly referred. This gives you a dual advantage of faster speed of import with Power BI Import and real-time access to data with Power BI DirectQuery.
The ongoing debate on Power BI Import vs DirectQuery is a long one. The above analysis can be of great help as you analyze. Both have their own set of characteristics to display as the situation arises. Finally, it depends on the organizational requirements and availability of skilled resources to conclude.
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