What is a lakehouse in Microsoft Fabric?

Microsoft Fabric Lakehouse is a data architecture platform for storing, managing, and analyzing structured and unstructured data in a single location. It's a flexible and scalable solution that allows organizations to handle large volumes of data using various tools and frameworks to process and analyze that data. It integrates with other data management and analytics tools to provide a comprehensive solution for data engineering and analytics.

Gif of overall lakehouse experience.


Microsoft Fabric is in preview.

Lakehouse SQL endpoint

The Lakehouse creates a serving layer by automatically generating a SQL endpoint and a default dataset during creation. This new see-through functionality allows user to work directly on top of the Delta tables in the lake to provide a frictionless and performant experience all the way from data ingestion to reporting.

An important distinction between default warehouse is that it's a read-only experience and doesn't support the full T-SQL surface area of a transactional data warehouse. Note that only the tables in Delta format are available in the SQL endpoint. Parquet, CSV, and other formats can't be queried using the SQL endpoint. If you don't see your table, convert it to Delta format.

Automatic table discovery and registration

The automatic table discovery and registration is a feature of Lakehouse that provides a fully managed file to table experience for data engineers and data scientists. You can drop a file into the managed area of the Lakehouse and the system automatically validates it for supported structured formats, and registers it into the metastore with the necessary metadata such as column names, formats, compression, and more. (Currently the only supported format is Delta table.) You can then reference the file as a table and use SparkSQL syntax to interact with the data.

Interacting with the Lakehouse item

A data engineer can interact with the lakehouse and the data within the lakehouse in several ways:

Learn more about the different ways to load data into your lakehouse: Options to get data into the Fabric Lakehouse.

Next steps

In this overview, you get a basic understanding of a lakehouse. Advance to the next article to learn how to create and use your own lakehouse: