A data lakehouse is a modern data architecture that blends the storage flexibility of a data lake with the data management and performance features of a traditional data warehouse. It allows organizations to store raw data and run analytics and business intelligence workloads on the same platform, thanks to capabilities such as ACID transactions, schema enforcement, and built-in governance and optimization.
What distinguishes a data lakehouse from a data lake is its ability to provide both reliability and usability without requiring separate systems. While a data lake focuses on cost-effective storage and schema-on-read, a lakehouse integrates data quality, performance, and structure directly into the platform. This makes it well-suited for unified data operations across analytics, data science, and reporting teams.