Data Lakes and Data Warehouses: Architecture Essentials
Data Lakes and Data Warehouses: Architecture Essentials Data teams often face a choice between data lakes and data warehouses. A practical platform uses both, and sometimes a blended pattern called a lakehouse. A data lake provides scalable storage for raw data, while a data warehouse applies structure and optimized queries. The lakehouse idea aims to combine these strengths in a single system. Understanding the roles Understanding the roles helps avoid wasted effort. A data lake stores raw, diverse data: logs, images, sensor streams. It is cost-effective and flexible, but the data may need processing before analysis. A data warehouse stores curated, structured data. It enforces a schema-on-write, supports fast SQL, and is easier for business users to trust. A lakehouse sits between them, using strong metadata and governance to enable fast queries over a unified store. ...