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SuryaTejaK
Advocate II
Advocate II

Lakehouse and warehouse and onelake differences

Below are some of the differences

Feature/Aspect

Lakehouse

Warehouse

OneLake

Definition

A unified storage layer combining the flexibility of a data lake with the capabilities of a relational database.

A relational database optimized for large-scale analytics and structured data workloads.

A unified storage system in Fabric for managing and accessing data across all analytics workloads.

Primary Use Case

Managing unstructured, semi-structured (e.g., JSON, Parquet), and structured data in one place.

Running SQL-based analytical queries on highly structured data for reporting and dashboards.

Centralized storage for all Fabric workloads, offering a single data lake for seamless access.

Data Format

Supports files in formats like CSV, JSON, Parquet, Delta.

Stores data in structured, relational database format.

Stores data in a Delta Lake format, accessible by all Fabric engines.

Data Storage

Utilizes OneLake as its backend for file storage.

Built on top of OneLake but uses a SQL-based relational engine for structured storage.

The foundational storage layer for all Fabric workloads (Lakehouse, Warehouse, etc.).

Access Mechanism

Accessible through Data Science, Data Engineering, and Analytics workloads (e.g., Notebooks, Dataflows).

Primarily accessed through SQL tools like SSMS, T-SQL, and reporting tools like Power BI.

Accessed automatically by all workloads in Fabric, ensuring data consistency across tools.

Integration

Seamlessly integrates with Notebooks, Spark, and dataflows for data preparation and modeling.

Directly integrates with SQL tools and supports high-performance queries for analytics.

Serves as the underlying shared storage system for Lakehouse, Warehouse, and other services.

Performance

Optimized for data science and machine learning workloads requiring data transformation.

Optimized for structured queries, aggregations, and high-performance analytics.

Optimized for scalability and interoperability across Fabric workloads.

Security & Governance

Supports Fabric’s built-in security, compliance, and governance features.

Built-in row-level security, access control, and SQL-based security for structured data.

Centralized governance and compliance features for all data in Fabric.

Data Processing Tools

Works with Spark, Delta Lake, and Notebooks for processing large-scale datasets.

Uses T-SQL and supports query optimization for structured workloads.

Works with all Fabric services for data access, including Spark, SQL, and pipelines.

Ideal Scenarios

- Data preparation
- Machine learning
- Exploratory analytics
- Combining structured and unstructured data

- Data warehousing
- Business intelligence
- High-performance reporting

- Unified storage
- Cross-service data sharing
- Enterprise-scale data management

8 REPLIES 8
Anonymous
Not applicable

Thanks @SuryaTejaK , this is helpful

oliverjack941
New Member

It’s fascinating how these concepts compare! The differences between a Lakehouse, Warehouse, and OneLake highlight how diverse data solutions can be tailored for specific use cases. It's like crafting a subway sandwich dressing—you choose the right mix depending on the flavor or functionality you need. A Lakehouse is perfect for combining structured and unstructured data, a Warehouse excels in handling high-performance structured queries, while OneLake serves as a unified base for seamless integration across tools. Each plays its role in creating a complete data management ecosystem.

pallavi_r
Super User
Super User

Thanks for sharing this @SuryaTejaK , This is useful.

Thanks,

Pallavi

you are welcome @pallavi_r 

Anonymous
Not applicable

Hi @SuryaTejaK ,

 

Thanks for the reply from Srisakthi .

 

Thanks for sharing about the difference between Lakehouse and Warehouse and Onelake, it will be helpful for many people.

 

Best Regards,
Yang
Community Support Team

 

thank you @Anonymous 😊
any suggestion most welcome

 

Regards,

Suryateja K

Srisakthi
Super User
Super User

Hi @SuryaTejaK ,

 

Both Lakehouse and warehouse is build on top of Onelake. We can compare Onelake features with DataLake, Datawarehouse.

 

Regards,

Srisakthi

Hi @Srisakthi i think i have already post another one regrding onelake and datalake differences

 

Regards,

Suryateja K

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