Data warehouse vs data lake: what are the differences and use cases?

Warehouses store structured, curated data for analytics. Lakes store raw or semi-structured data cheaply. Warehouses optimize SQL analytics and governance. Lakes optimize flexibility and storage cost. Many teams build lakehouse architectures to combine both. Choose based on query patterns, governance, and cost constraints.