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Also known as: Microsoft Fabric Lakehouse
A Microsoft Fabric item that combines open-format lake storage with SQL and Spark engines to deliver lakehouse analytics.
DESCRIPTION
Fabric Lakehouse brings the lakehouse paradigm to Microsoft Fabric, storing data in OneLake using open formats like Delta/Parquet. It exposes both Spark-based processing and SQL endpoints for analytics and BI. Typical use includes ELT, curated layers, and direct Power BI access. It blends flexibility of lakes with performance and governance closer to warehouses.
ALTERNATIVE DEFINITIONS
Microsoft Learn
A lakehouse in Microsoft Fabric is a data architecture that combines the flexibility of data lakes with the manageability and performance of data warehouses.
Defines lakehouse by combining lake flexibility and warehouse performance.
Databricks
A lakehouse is a new architecture that combines the best elements of data lakes and data warehouses, delivering data management and ACID transactions on open data formats.
Introduces lakehouse concept emphasizing open formats and ACID.
Microsoft Azure
Microsoft Fabric delivers a lake-centric architecture with OneLake and integrated engines, enabling lakehouse experiences across analytics workloads.
Product framing of lakehouse within Fabric ecosystem.
RELATED TERMS
Microsoft Fabric OneLake Delta Lake Parquet Apache Spark SQL Endpoint Power BI Medallion Architecture Databricks Lakehouse
COMPETING TERMS
KNOWLEDGE AREAS
Data Architecture Data Warehousing & BI Cloud Data Services
TARGET AUDIENCE
Data Engineer Analytics Engineer Data Architect BI Specialist Data Scientist
EXTERNAL SOURCES
- Wikipedia - Data lake
- Microsoft Learn - Fabric lakehouse overview
- Databricks - Definitive lakehouse article
- Microsoft Learn - How to create a lakehouse
TOP QUESTIONS
What is Fabric Lakehouse used for?
Curating data in open formats with both Spark and SQL access, supporting ELT, analytics, and direct Power BI connectivity via SQL endpoints.
Category: Example
How does Fabric Lakehouse differ from a traditional warehouse?
It stores data in open lake formats while offering SQL access, blending schema flexibility with governance and performance features.
Category: Alternatives
What file formats are typical in Fabric Lakehouse?
Parquet and Delta Lake are common, enabling columnar storage, ACID transactions, and interoperability across engines.
Category: Requirements
Can Fabric Lakehouse integrate with Power BI?
Yes, via SQL endpoints or Direct Lake integration, enabling fast, governed analytics.
Category: Example
What are common modeling patterns in Fabric Lakehouse?
Medallion architecture (bronze/silver/gold), dimensional modeling in curated layers, and semantic models for BI.
Category: Example
What are common mistakes in lakehouse design?
Poor partitioning, mixed schemas, missing governance, and overuse of row-based formats reduce performance and maintainability.
Category: Mistakes
Is Fabric Lakehouse suitable for ML workflows?
Yes, Spark enables feature engineering and model training on curated datasets stored in OneLake.
Category: Opinion
How is security handled in Fabric Lakehouse?
Use Fabric access controls, OneLake security, item-level permissions, and data masking or row-level security where applicable.
Category: Requirements
How does Fabric Lakehouse relate to OneLake?
Lakehouse is an item built on OneLake, leveraging unified storage and governance across Fabric.
Category: Definition