When you first load a table into Power BI, one of the key decisions you’ll need to make is whether to use Import mode or DirectQuery mode. Both options have distinct advantages and drawbacks, and the best choice for your use case will depend on your specific requirements. In recent developments, a new option, Direct Lake, has been introduced, offering yet another approach to managing and querying data in Power BI. In this article, we’ll explore each of these modes in detail to help you better understand which might be the best fit for your data scenarios.

Import Mode

For most users, Import mode is the default and most widely used option when loading data into Power BI.

Pros of Import Mode

One of the main advantages of import mode is performance. Import mode is known for fast query performance because it queries data directly from memory. When you load data into Power BI using Import mode, the entire dataset is loaded into memory, which allows for faster querying and calculations. This in-memory approach enables Power BI to deliver results quickly, making it ideal for dashboards that need to be highly responsive.

Cons of Import Mode

However, this speed comes with trade-offs. Import mode requires all data to be loaded into memory before any queries can be executed. This can place considerable pressure on memory resources, especially as the size and number of datasets increase. As your data models grow, you may encounter performance issues related to capacity limits in Power BI.

Additionally, because data is loaded into memory, the model is only as current as the latest refresh. To keep data up to date, import models must be refreshed on a scheduled basis. This can be a resource-intensive process, particularly if you’re working with large datasets. A full refresh removes all data from all tables and reloads it from the data source, which can take significant time and resources.

DirectQuery Mode

DirectQuery mode is often used in situations where the dataset is too large to load into memory or when up-to-the-minute data is required.

Pros of DirectQuery Mode

One of the biggest benefits of DirectQuery is that it allows you to work with very large datasets without the need to pre-aggregate or import the data into Power BI. This mode sends queries directly to the source database, allowing you to work with data that is as fresh as possible without needing to refresh the model. Additionally, DirectQuery doesn’t have the 1-GB semantic model limitation that applies to Import mode.

Cons of DirectQuery Mode

However, DirectQuery comes with its own set of challenges. Not all features of Power BI Desktop are available in DirectQuery mode, and there are limitations on certain capabilities, such as quick insights. For instance, automatic date/time hierarchies aren’t supported, meaning you can’t easily drill down into date columns by year, quarter, month, or day.

Another major consideration is performance. Since DirectQuery sends all requests directly to the source database, the time required for visuals to refresh depends on how quickly the database can return results. Ideally, data should be returned in under five seconds for an acceptable user experience, but if the query takes longer than 30 seconds, users may experience significant delays. In the Power BI service, any query that takes more than four minutes will time out, resulting in an error message for the user.

Lastly, the load on the source database can become a concern, especially when row-level security (RLS) is in place. Refreshing a dashboard tile that uses RLS can generate one query per user, significantly increasing the number of queries sent to the database and potentially affecting overall performance.

Direct Lake Mode

A more recent addition to Power BI is Direct Lake mode, which offers a new way to handle large datasets, particularly those stored in Microsoft Fabric’s OneLake. Direct Lake is designed for situations where you need to quickly load and query large volumes of data from Delta tables, which store their data in Parquet files.

Pros of Direct Lake Mode

Direct Lake is optimized for fast querying of large datasets, with data being loaded into memory on-demand only as it is needed for queries. This process, known as transcoding, allows the Direct Lake semantic model to function similarly to an import model in terms of query performance without the need to pre-load all data into memory.

One of the standout features of Direct Lake is that it eliminates the need for costly and slow data imports. Instead of loading all the data into the model up front, columns from Delta tables are loaded into memory as they are queried, providing a more efficient use of resources.

In addition, refresh operations in Direct Lake are typically much faster and less resource-intensive compared to Import mode. A refresh in Direct Lake involves a process called framing, which analyzes the metadata of the Delta tables and updates the semantic model to reference the latest version of the data. This operation takes just a few seconds and ensures that data changes in OneLake are automatically reflected in the Direct Lake semantic model, without the need for a full data reload.

Cons of Direct Lake Mode

Despite its advantages, Direct Lake has some limitations. For example, if a Direct Lake semantic model table connects to a table in the SQL analytics endpoint that uses row-level security (RLS), the query will automatically fall back to DirectQuery mode. This can lead to slower query performance.

Additionally, Direct Lake doesn’t support composite modeling, calculated columns, or calculated tables. While features like calculation groups, what-if parameters, and field parameters are supported, these limitations could be a significant factor depending on your use case.

Which is Right?

The choice between Import, DirectQuery, and Direct Lake in Power BI depends largely on the nature of your data and your specific performance and update requirements. Import mode is the go-to for fast, in-memory querying but requires regular refreshes, which can be resource-intensive. DirectQuery allows for working with massive datasets and real-time data, but performance can suffer if the underlying database isn’t optimized. Finally, Direct Lake offers a new, flexible way to handle large volumes of data without the slow refresh times of Import mode or the potential performance pitfalls of DirectQuery, although it comes with its own set of limitations.

Understanding the pros and cons of each mode will help you make the best choice for your Power BI projects.