In Power BI, there are several connection modes that you can use to connect to your data sources. Please note that connection type is not data sources type.
Power BI supports a variety of data sources. Connection type determines how the connection is established with the data source. A single data source can support multiple connection types. For instance, connecting to a SQL Server database can be done through Import Data or DirectQuery. Despite being the same data source, different connection types offer varied methods of connectivity.
These are the approaches through which Power BI interacts with data and generates responses to visualization queries. Every visualization within a Power BI report relies on a dataset, which in turn utilizes one of the following connection types:
Import Mode:
In this mode, data from the source is imported into Power BI Desktop or Power BI Service. This mode is suitable for small to medium-sized datasets that do not frequently change. It provides fast performance as the data is stored within the Power BI file or dataset.
This type of connection imports the whole dataset into the memory. This memory will be the memory of the machine that hosts the Power BI dataset. If you have a Power BI dataset opened in Power BI Desktop, then it will be the memory of the machine that Power BI Desktop is running on it. When you publish your Power BI file on the Power BI Service, it will be the memory of that machine in the cloud.
Your question may be where the data is stored in the memory. Power BI models are always loaded into the Analysis Services engine. Even if you don’t have Analysis Services installed, it will be in your system, when you use Power BI with the Import Data connection type.
When you save and close your Power BI file, then that data will be persisted in a *.pbix file. The next time you open the file, data will be loaded again into Analysis Services in-memory engine.
Pros:
- Fast performance: Data is imported directly into Power BI, allowing for quick analysis and visualization.
- Offline access: Once data is imported, reports can be viewed offline without requiring a live connection to the data source.
- Data shaping: Enables extensive data transformation and modeling within Power BI, allowing for customized analysis.
Cons:
- Data freshness: Imported data may become stale if it's not regularly refreshed.
- Data volume limitations: Large datasets may exceed Power BI's memory capacity or performance capabilities.
- Data security: Imported data resides within Power BI, potentially raising concerns about data governance and compliance.
DirectQuery Mode:
With DirectQuery mode, Power BI sends queries directly to the data source each time a visualization or report is refreshed or interacted with. This mode is suitable for large datasets or scenarios where you need real-time or near real-time access to data. However, it's important to note that performance may be slower compared to Import mode, especially for complex queries or large datasets.
DirectQuery, as a connection type in Power BI, does not involve loading data into the Power BI model. DirectQuery means that Power BI establishes a direct connection to the data source. Whenever a visualization appears in a report, the data is sourced directly from a query sent to the data source. Learn more about DirectQuery
Pros:
- Real-time data access: DirectQuery allows querying data directly from the data source in real-time, ensuring data freshness.
- Scalability: Suitable for large datasets since it doesn't require importing data into Power BI.
- Data governance: Maintains a single source of truth as queries are executed directly against the data source.
Cons:
- Performance overhead: DirectQuery can introduce latency, especially for complex queries or large datasets.
- Limited data transformation: Power BI's data shaping capabilities are restricted compared to Import mode.
- Data source dependency: Relies heavily on the availability and performance of the data source, which can impact report responsiveness.
Live Connection Mode:
This mode allows you to connect directly to an Analysis Services model, either in Azure Analysis Services or SQL Server Analysis Services. With this mode, Power BI reports connect live to the underlying data model, enabling interactive analysis while leveraging the processing power and optimizations of Analysis Services. Learn more about Live Connection
Pros:
- Real-time data access: Similar to DirectQuery, provides real-time access to data without importing it into Power BI.
- Single source of truth: Ensures that reports always reflect the most up-to-date data from the data source.
- Data governance: Maintains data integrity and consistency by querying the original data source.
Cons:
- Performance dependency: Report performance depends on the performance and availability of the data source.
- Limited functionality: Similar to DirectQuery, certain Power BI features like data modeling and complex calculations are limited.
- Network latency: Relies heavily on network connectivity, potentially leading to slower report rendering times.
Composite Model:
In Power BI, a composite model entails having some parts of your model connected via DirectQuery to a data source (such as a SQL Server database), while other parts are linked via Import Data (such as an Excel file).
Introduced in later versions of Power BI, the composite model allows you to combine Import mode and DirectQuery mode within the same model. This enables you to import smaller tables for performance and connect larger or real-time data sources using DirectQuery. This mode is useful for scenarios where you need a balance between performance and real-time access to data.
Pros:
- Hybrid approach: Allows combining Import, DirectQuery, and Live Connection modes within a single model, offering flexibility.
- Scalability and performance: Ideal for scenarios where some data can be imported for performance reasons while maintaining real-time access to other data.
- Data flexibility: Enables leveraging the advantages of different connection modes for different data sources within the same report.
Cons:
- Complexity: Managing a composite model can be complex, requiring careful consideration of data relationships, refresh schedules, and performance optimizations.
- Resource utilization: May require more resources compared to simpler connection modes, especially when dealing with large datasets or multiple data sources.
- Data governance challenges: Requires a clear understanding of data sources and their respective refresh schedules to maintain data integrity and consistency.
DirectLake:
The data repository aspect of Microsoft Fabric is known as OneLake, where files are stored in the Parquet format. Microsoft introduced optimizations to the Parquet files within OneLake to greatly enhance their efficiency for VertiPaq querying. As a result, when a Power BI dataset accesses data from OneLake, it can directly query the Parquet files without the need to send SQL queries. This innovation yields outstanding performance akin to importing data, while simultaneously providing real-time access to live data without requiring refreshes. This novel approach to connecting Power BI is dubbed "Direct Lake."
When data is housed within a Lakehouse within OneLake, Power BI datasets can utilize a specialized connection known as Direct Lake. This connection type combines the speed of an import data connection with the real-time capabilities of a DirectQuery connection. The key lies in bypassing the translation of visual queries into SQL queries that typically run against the SQL endpoint of the Lakehouse; instead, these queries operate directly on Parquet files stored within OneLake.
These connection modes offer flexibility and cater to different data scenarios and requirements, allowing users to choose the most suitable option based on factors such as data size, performance, real-time needs, and data source type.
Thank you for reading!