I am new to lakehouse details in power BI. I read few articles about connecting Power BI to Azure data lake. But recently I came to the term " Lakehouse in microsoft" I went throught microsoft articles about it.
I am confused about the below points:
- What is the difference between azure data lake and microsoft lakehouse ?
- If azure data lake is already there then why microsoft lakehouse has come?
- Which one is better to use?
I went through below links:
https://learn.microsoft.com/en-us/fabric/data-engineering/tutorial-lakehouse-introduction
https://www.youtube.com/watch?v=8BAeLUywEMM&list=PLMXQvYI7QV6dn8eYXtlZT9Jc_p67_CfJR
and many more similar to this. But still did not get my answer.
after going some of the articles on the internet i have following to say.
for gist understanding
microsoft lakehouse is a design pattern that combines data lakes and data warehouses, while Azure Lakehouse is a specific implementation of this pattern within the Azure ecosystem. Azure Lakehouse provides a unified and scalable platform for data storage and analytics, leveraging Azure Data Lake Storage and Azure Synapse Analytics.
for detailed explanation
Microsoft Lakehouse is a concept that refers to the integration of data lakes and data warehouses into a unified architecture. It combines the scalability and flexibility of data lakes with the structured querying and performance optimizations of data warehouses. Microsoft Lakehouse is not a specific product, but rather a design pattern that can be implemented using various technologies, including Azure Data Lake Storage and Azure Synapse Analytics.
On the other hand, Azure Lakehouse is a specific implementation of the Microsoft Lakehouse concept within the Azure ecosystem. Azure Lakehouse leverages Azure Data Lake Storage Gen2 as the data lake and Azure Synapse Analytics as the data warehouse. It provides a unified and scalable platform for storing, processing, and analyzing both structured and unstructured data.
Azure Lakehouse offers several advantages, including the ability to handle large volumes of data, support for various data formats, and integration with other Azure services. It also provides features like data governance, security, and advanced analytics capabilities.