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Also known as: Direct Lake mode
A Power BI storage mode that reads Delta Lake tables in OneLake directly, combining import-like performance without data duplication or traditional DirectQuery latency.
DESCRIPTION
DirectLake is a Microsoft Fabric storage mode for Power BI models that enables the VertiPaq engine to read Delta Lake tables directly from OneLake. It avoids data import and reduces DirectQuery overhead by using cached columnar segments where possible. This approach yields near-import performance while keeping data fresh in place, aligning with lakehouse architectures. DirectLake works with Delta/Parquet files and supports enterprise scale scenarios. Proper file layouts, partitioning, and schema stability are key to good performance. It is particularly useful for large datasets and near-real-time reporting without heavy data movement.
ALTERNATIVE DEFINITIONS
Microsoft Learn
Direct Lake mode allows Power BI models to query data in OneLake directly, without importing the data or using DirectQuery.
Emphasizes direct access to OneLake without import or DirectQuery.
Microsoft Fabric Blog
Direct Lake brings cached performance to data over OneLake, combining the advantages of Import and DirectQuery for Power BI models.
Highlights performance benefits and hybrid nature of the mode.
Microsoft Learn
Power BI supports multiple storage modes for tables in a model, including Import, DirectQuery, and Direct Lake.
Positions Direct Lake among other storage modes for tabular models.
RELATED TERMS
Microsoft Fabric Power BI OneLake Delta Lake Data Lakehouse Tabular Model Composite Models Parquet
COMPETING TERMS
DirectQuery Import Mode
KNOWLEDGE AREAS
Data Warehousing & BI Platform & Tooling Cloud Data Engineering Data Services
TARGET AUDIENCE
BI Specialist Analytics Engineer Data Engineer Data Architect Data Governance Manager AI Product Manager
EXTERNAL SOURCES
- Microsoft Learn - Official overview of Direct Lake mode
- Microsoft Fabric Blog - Announcement and deep dive
- Microsoft Learn - Storage modes guidance
TOP QUESTIONS
Why is DirectLake relevant for Power BI in Microsoft Fabric?
DirectLake offers near-import performance without copying data, reducing latency and maintenance. It aligns with lakehouse architectures by querying Delta files directly in OneLake.
Category: Relevancy
How does DirectLake differ from DirectQuery?
DirectLake reads cached columnar segments from OneLake and avoids per-query roundtrips to external engines. DirectQuery sends queries to source systems at runtime, often with higher latency.
Category: Difference
What data formats does DirectLake support?
DirectLake targets Delta Lake tables stored as Parquet with transaction logs. Well-partitioned, columnar data yields the best performance.
Category: Requirements
When should I choose DirectLake over Import Mode?
Choose DirectLake when you need fresh data without scheduled refresh and want import-like performance. Import is suitable when static, in-memory snapshots suffice.
Category: Guidance
What are common mistakes with DirectLake?
Poor file layouts, tiny files, or excessive partitions degrade throughput. Changing schemas frequently or ignoring column encoding can also hurt performance.
Category: Mistakes
What is a key risk of using DirectLake incorrectly?
If underlying Delta tables are not optimized, queries may be slower than expected. Governance gaps may also expose raw lake data without appropriate controls.
Category: Risks
How do I optimize Delta tables for DirectLake?
Use compaction, Z-ordering (where applicable), partition pruning, and proper column types. Maintain statistics and avoid excessive small files.
Category: Best practices
Can DirectLake be used with composite models?
Yes. Composite models can mix DirectLake with Import or DirectQuery tables, enabling flexibility while retaining performance on lake-backed tables.
Category: Usage
What tools help monitor DirectLake performance?
Power BI performance analyzer, Fabric monitoring, and storage metrics in OneLake help diagnose bottlenecks, file sizes, and query behavior.
Category: Observability