Key details at a glance
Data Warehouses use schema-on-write (structured data only), are SQL-first for fast BI queries, but become expensive and inflexible at scale. Data Lakehouses use schema-on-read (any data type), support both ML and BI from the same storage layer, and offer lower storage cost at the price of added complexity. Warehouses best fit BI teams, finance, and reporting use cases; lakehouses best fit AI/ML teams working with both raw and structured data. The same five-stage ingestion pipeline (Sources → Extract → Transform → Load → Analyse) underlies both architecture choices.
