A modern data architecture that combines the flexibility of data lakes with the structured querying and reliability of data warehouses. Like having one storage system that's both a giant filing cabinet and a searchable database.
A retail company uses a data lakehouse on Databricks to store raw clickstream data alongside structured sales reports, running analytics on both without moving data between systems.
A “lakehouse” is an architecture/pattern rather than a single native service on most clouds. Azure offers a first-party Lakehouse experience in Microsoft Fabric, and a widely used implementation via Azure Databricks with Delta Lake on ADLS. On AWS and GCP, similar outcomes are typically built by combining object storage with open table formats (e.g., Delta Lake/Iceberg/Hudi) plus query engines, but there isn’t one canonical, single-service equivalent.