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Sparkdata's avatar
Sparkdata
New Member
20 days ago
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Direct Lake vS Direct Query

Came across this, has some deep insights. i personally find Direct Query more flexible, what do you all prefer ?   https://medium.com/@rishabh.gulati_94109/microsoft-fabric-direct-lake-is-fast-goo...
  • EduardoCastro's avatar
    13 days ago

    Hi,

    I understand why you prefer DirectQuery is very flexible, especially when you need live data or can't move everything into OneLake.

    But here's the key difference I've noticed:

    - Direct Lake reads directly from Delta tables in OneLake. Then all the transformations, aggregations and joins happens before the report runs, so Power BI just uses pre-optimized data. The report is fast, but requires more ETL work upfront.

    - DirectQuery queries the source every single time – warehouse, SQL Server, etc. It's flexible, but the performance depends entirely on how complex your queries and DAX are.

    The catch with DirectQuery? If you have:

    • Complex joins
    • Heavy aggregations
    • Lots of concurrent users

    Then your warehouse becomes the bottleneck. I've seen reports that were perfectly fine with DirectQuery suddenly to a loading failure when the data grew or more users are using it.

    So for me, it comes down to:

    • Direct Lake = more engineering work upfront, but better performance and scalability
    • DirectQuery = faster to set up, but can hit performance walls if your queries get complex

    Both have their place. I use DirectQuery for quick simple and operational dashboards, but for enterprise reporting with lots of users, the Direct Lake approach (with a good Gold-layer star schema) has been more reliable with precalculated columns.