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NipawanV
Helper I
Helper I

What is the best option to choose between Lakehouse and SQL Analytic Endpoint from OneLake data hub

Previously there is no SQL Analytic Endpoint when Í get the data from OneLake data hub in Power BI Desktop.  I used Lakehouse to get the data.  Now this option is available, so I need to know which one to choose for Power BI Report and why. 

 

 

 

 

1 ACCEPTED SOLUTION
rajendraongole1
Super User
Super User

Hi @NipawanV - Lakehouse provides direct access to data stored in files within OneLake (such as Delta Lake tables), allowing you to build reports directly on top of this data without needing to transform it into a structured relational format.

  • Performance: It uses Direct Lake mode, which bypasses the need for data import or a query engine, allowing Power BI to access the data with high-speed retrieval directly from OneLake storage. This is ideal for large datasets that need to be updated frequently without refreshing or importing.
  • When to Use:
    • If your data is in a file format (e.g., Parquet or Delta Lake).
    • If you need real-time or near-real-time access to large datasets without importing the data.
    • If you want to leverage Power BI’s visualization capabilities directly on top of OneLake data files.

SQL ENDPOINT: The SQL Analytics Endpoint provides a SQL interface to data in the Lakehouse, allowing you to run T-SQL queries on structured datasets in OneLake. It essentially acts as a relational layer on top of your Lakehouse data.

 

  • Performance: By using SQL Analytics Endpoint, Power BI can query data in a relational format, which supports optimizations like indexing and faster query performance for complex calculations, aggregations, and joins.
  • When to Use:
    • If you need structured, relational data queries for complex reports or aggregations.
    • If your data model requires advanced filtering, joins, or complex DAX measures.
    • For scenarios where you need to leverage SQL-based security, control, and governance.

 

In many cases, SQL Analytics Endpoint is preferable for complex business reporting, while Lakehouse is ideal for direct, fast access to recent data with simpler transformations.

Hope the above details helps.

 

 

 





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2 REPLIES 2
rajendraongole1
Super User
Super User

Hi @NipawanV - Lakehouse provides direct access to data stored in files within OneLake (such as Delta Lake tables), allowing you to build reports directly on top of this data without needing to transform it into a structured relational format.

  • Performance: It uses Direct Lake mode, which bypasses the need for data import or a query engine, allowing Power BI to access the data with high-speed retrieval directly from OneLake storage. This is ideal for large datasets that need to be updated frequently without refreshing or importing.
  • When to Use:
    • If your data is in a file format (e.g., Parquet or Delta Lake).
    • If you need real-time or near-real-time access to large datasets without importing the data.
    • If you want to leverage Power BI’s visualization capabilities directly on top of OneLake data files.

SQL ENDPOINT: The SQL Analytics Endpoint provides a SQL interface to data in the Lakehouse, allowing you to run T-SQL queries on structured datasets in OneLake. It essentially acts as a relational layer on top of your Lakehouse data.

 

  • Performance: By using SQL Analytics Endpoint, Power BI can query data in a relational format, which supports optimizations like indexing and faster query performance for complex calculations, aggregations, and joins.
  • When to Use:
    • If you need structured, relational data queries for complex reports or aggregations.
    • If your data model requires advanced filtering, joins, or complex DAX measures.
    • For scenarios where you need to leverage SQL-based security, control, and governance.

 

In many cases, SQL Analytics Endpoint is preferable for complex business reporting, while Lakehouse is ideal for direct, fast access to recent data with simpler transformations.

Hope the above details helps.

 

 

 





Did I answer your question? Mark my post as a solution!

Proud to be a Super User!





Hi @rajendraongole1 many thanks for your valuable feedback. 

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