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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
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 TeamIf 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!
4 Replies
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.
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:
Best Regards,
Yang
Community Support TeamIf 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
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 TeamIf 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!
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.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/
