Exploring Power BI Storage Modes: Import, DirectQuery, and Dual

 In Power BI, Table Storage Mode refers to how data within individual tables is stored and queried, impacting how quickly Power BI can retrieve and display data in reports. There are three primary table storage modes, each serving different technical uses and scenarios:



 1. Import Mode

   - Use: Best for static or slowly changing data.

   - Scenario: Frequently used in reports that need fast access and low latency.

   - Impact: Queries data entirely from Power BI’s in-memory storage, providing faster performance but requiring more memory.

-Benefits:

  • Support all Power BI data source types, including databases, files, feeds, web pages, dataflows and more.
  • Can integrate source data.
  • Support all DAX and Power Query (M) functionality.
  • Support calculated tables
  • Deliver the best query performance

Limitations:

  • Power BI imposes dataset size restrictions, which limit the size of a model.
  • When we publish the model to a shared capacity, there's a 1-GB limit per dataset.
  • When the size limit is exceeded, the dataset will fail to refresh.
  • When we publish the model to a dedicated capacity, it can grow beyond 10 GB, providing us enable the Large dataset storage format setting for the capacity.
  • Imported data must be periodically refreshed.

 2. DirectQuery Mode

   - Use: Suitable for real-time data needs or very large datasets.

   - Scenario: Used when data volume is too large for Import Mode, or data freshness is critical.

   - Impact: Queries the underlying data source directly, which can impact performance based on source query time. Reduces Power BI’s memory requirements but is slower than Import.

Benefits:

  • DirectQuery tables don't require refresh.
  • A DirectQuery model can deliver near real time query result.
  • DirectQuery is also useful when the source database enforces row-level security (RLS).
  • If organization has security policies that restrict data leaving their premises, then it isn't possible to import data.

Limitations:

  • Not all data sources are supported.
  • All Power Query (M) transformations are not possible, because these queries must translate to native queries that are understood by source systems.
  • Analytic query performance can be slow

 3. Dual Mode

   - Use: Offers flexibility to use both Import and DirectQuery modes.

   - Scenario: Ideal when some data needs to be refreshed in real-time (DirectQuery) while other data remains static (Import).

   - Impact: Enables selective querying of tables, balancing performance and data freshness. 

Benefits:

  • Composite models provide us with design flexibility. 
  • This can choose to integrate data using different storage modes, striking the right balance between imported data and pass-through data.

Limitations:

  • An analytic query must combine imported and DirectQuery data, Power BI must consolidate source group query result which can impact performance.
  • When chaining models (DirectQuery to Power BI datasets), modifications made to upstream models can break downstream models. 
  • Relationships between tables from different source groups are known as limited relationships.

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