Skip to main content
cancel
Showing results for 
Search instead for 
Did you mean: 

Join us at FabCon Vienna from September 15-18, 2025, for the ultimate Fabric, Power BI, SQL, and AI community-led learning event. Save €200 with code FABCOMM. Get registered

Reply
pmscorca
Advocate V
Advocate V

Comparison between data warehouse, data lake and data lakehouse

Hi,

I'm searching a good and synthetic article that talk about a comparison between data warehouse, data lake and data lakehouse.

I haven't found any good articles.

Any suggests to me, please? Thanks

1 ACCEPTED SOLUTION
Anonymous
Not applicable

Hi @pmscorca ,

 

Okay, that's more at a glance.

 

Feature

Data Warehouse

Data Lake

Data Lakehouse

Data Structure

Highly structured

Structured and unstructured

Combines both

Use Case

Business intelligence and reporting

Big data analytics, machine learning

BI, reporting, and advanced analytics

Data Type

Primarily structured data

Raw and semi-structured data

Handles all data types

Query Performance

Fast querying

Slower querying

Advanced querying capabilities

Cost

Generally higher

More cost-effective for large volumes

Balances cost efficiency with performance

 

If you have any other questions please feel free to contact me.

 

Best Regards,
Yang
Community Support Team

 

If there is any post helps, then please consider Accept it as the solution  to help the other members find it more quickly.
If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!

View solution in original post

4 REPLIES 4
Anonymous
Not applicable

Hi @pmscorca ,

 

Thanks for the reply from @frithjof_v , your reply worked like a charm.

 

This table summarizes the differences between the data warehouse vs. data lake vs. data lakehouse.

vhuijieymsft_0-1722215687905.png

 

A data warehouse is a good choice for companies seeking a mature, structured data solution that focuses on business intelligence and data analytics use cases. However, data lakes are suitable for organizations seeking a flexible, low-cost, big-data solution to drive machine learning and data science workloads on unstructured data.

 

Suppose the data warehouse and data lake approaches aren’t meeting your company’s data demands, or you’re looking for ways to implement both advanced analytics and machine learning workloads on your data. In that case, a data lakehouse is a reasonable choice.

 

More information can be found in this document:

Data Warehouse vs. Data Lake vs. Data Lakehouse: An Overview of Three Cloud Data Storage Patterns - ...

 

Best Regards,
Yang
Community Support Team

 

If there is any post helps, then please consider Accept it as the solution  to help the other members find it more quickly.
If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!

Hi, thanks for you reply.

I'm preparing a training course and so I need to search a synthetic feature comparison at a glance between data warehouse, data lake and data lakehouse, not too articles to read.

Other features to match in a synthetic manner? Thanks

Anonymous
Not applicable

Hi @pmscorca ,

 

Okay, that's more at a glance.

 

Feature

Data Warehouse

Data Lake

Data Lakehouse

Data Structure

Highly structured

Structured and unstructured

Combines both

Use Case

Business intelligence and reporting

Big data analytics, machine learning

BI, reporting, and advanced analytics

Data Type

Primarily structured data

Raw and semi-structured data

Handles all data types

Query Performance

Fast querying

Slower querying

Advanced querying capabilities

Cost

Generally higher

More cost-effective for large volumes

Balances cost efficiency with performance

 

If you have any other questions please feel free to contact me.

 

Best Regards,
Yang
Community Support Team

 

If there is any post helps, then please consider Accept it as the solution  to help the other members find it more quickly.
If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!

frithjof_v
Super User
Super User

In general, a Lakehouse is a ("virtual") Data Warehouse built on top of a Datalake storage.

 

Warehouse brings structure, schemas and other relational database features, whereas the Datalake storage is flexible (can store unstructured, semi-structured and structured data) and can store large amounts of data, and compute and storage is decoupled so it is highly scalable. The data lake is common for data science and machine learning purposes.

 

The data lakehouse is a warehouse which is using a data lake as data storage.

 

The specific details and definitions will differ between different vendors or products (Microsoft Fabric, Databricks, Google, Amazon, Oracle, etc.)

 

Each of these articles has their own approaches to explaining these concepts:

 

https://www.montecarlodata.com/blog-data-warehouse-vs-data-lake-vs-data-lakehouse-definitions-simila...

 

https://www.forbes.com/sites/bernardmarr/2022/01/18/what-is-a-data-lakehouse-a-super-simple-explanat...

 

https://www.databricks.com/blog/2020/01/30/what-is-a-data-lakehouse.html

 

https://docs.databricks.com/en/lakehouse/index.html#lakehouse-vs-data-lake-vs-data-warehouse

 

https://azure.microsoft.com/en-us/resources/cloud-computing-dictionary/what-is-a-data-lake

 

https://cloud.google.com/discover/what-is-a-data-lakehouse

 

 

P.S.: The Fabric Data Warehouse is actually a lakehouse, however it has different features than the Fabric Lakehouse: https://debruyn.dev/2023/fabric-lakehouse-or-data-warehouse/

Helpful resources

Announcements
Join our Fabric User Panel

Join our Fabric User Panel

This is your chance to engage directly with the engineering team behind Fabric and Power BI. Share your experiences and shape the future.

June FBC25 Carousel

Fabric Monthly Update - June 2025

Check out the June 2025 Fabric update to learn about new features.

June 2025 community update carousel

Fabric Community Update - June 2025

Find out what's new and trending in the Fabric community.