Lakehouse vs. Warehouse in Microsoft Fabric: when to use each

João Barros 12 de December de 2024 2 min read

Microsoft Fabric offers two analytical storage artifacts: the Lakehouse and the Warehouse. The right choice depends on the data, the teams and the performance requirements.

Lakehouse

The Lakehouse combines the flexibility of a data lake with SQL analytical capabilities. Data is stored in Delta Parquet on OneLake and exposed through two endpoints:

SQL Analytics Endpoint — allows read-only SQL queries over the Delta tables.
Spark — full read/write processing with PySpark notebooks or Spark SQL.

Ideal for: large-scale data ingestion, complex Spark transformations, semi-structured data (JSON, CSV, Parquet).

Warehouse

The Warehouse is a fully managed relational warehouse with full T-SQL support (DDL + DML). Data is also stored on OneLake in Delta Parquet, but management is done through SQL.

-- Create a table in the Warehouse
CREATE TABLE dbo.FactSales (
    SalesKey   INT           NOT NULL,
    DateKey    INT           NOT NULL,
    ProductKey INT           NOT NULL,
    Revenue    DECIMAL(18,2) NOT NULL
)
WITH (CLUSTERED COLUMNSTORE INDEX, DISTRIBUTION = HASH(SalesKey))

Ideal for: BI teams with strong SQL background, structured data, business-critical reports with performance SLAs.

Typical combination

Lakehouse Bronze  → raw ingestion
Lakehouse Silver  → Spark transformations
Warehouse Gold    → analytical SQL queries + Power BI

Conclusion

It is not an exclusive decision — most mature architectures use both in different layers. The Lakehouse for flexible transformations, the Warehouse to serve SQL consumers and business reports.