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4.2.3. Lakehouse Architecture
💡 First Principle: A Lakehouse combines the flexibility of a data lake (store any format) with the structure of a data warehouse (schema, ACID transactions, SQL queries).
Traditional Trade-off:
- Data Lake: Cheap storage, any format, but no transactions, poor query performance
- Data Warehouse: Fast queries, ACID transactions, but expensive, only structured data
Lakehouse Solution:
- Store data in open Delta format on cheap object storage
- Delta Lake provides ACID transactions, schema enforcement, time travel
- Query with both Spark and SQL engines
⚠️ Exam Tip: If a question mentions combining "lake flexibility with warehouse reliability" or "Delta Lake format," think Lakehouse architecture.