How does a data lakehouse differ from a data lake and a data warehouse?

How does a data lakehouse differ from a data lake and a data warehouse?

• A. It stores only structured data.
• B. It uses graph databases to accelerate queries.
• C. It enforces ACID transactions but limits data formats.
• D. It combines lake flexibility with warehouse-style ACID transactions and fast queries.

Answer: (D)

A data lakehouse tests the idea of unifying the best parts of a data lake and a data warehouse. It keeps the lake’s flexibility and scalable storage for all data types—raw, semi-structured, and structured—while adding the warehouse-style guarantees and speed you need for analytics. The key is combining the open, cost-effective storage and broad data repertoire with strong transactional support (ACID) and fast query performance, so you can ingest, modify, and query data reliably in one place without moving data between separate systems. That’s why the statement is best: you get lake-like flexibility plus warehouse-like ACID transactions and accelerated queries. In contrast, storing only structured data isn’t accurate for a lakehouse, graph databases aren’t central to its defining feature, and enforcing ACID while limiting data formats would contradict the lakehouse’s goal of handling diverse data types with robust transactions.

A data lakehouse tests the idea of unifying the best parts of a data lake and a data warehouse. It keeps the lake’s flexibility and scalable storage for all data types—raw, semi-structured, and structured—while adding the warehouse-style guarantees and speed you need for analytics. The key is combining the open, cost-effective storage and broad data repertoire with strong transactional support (ACID) and fast query performance, so you can ingest, modify, and query data reliably in one place without moving data between separate systems.

That’s why the statement is best: you get lake-like flexibility plus warehouse-like ACID transactions and accelerated queries. In contrast, storing only structured data isn’t accurate for a lakehouse, graph databases aren’t central to its defining feature, and enforcing ACID while limiting data formats would contradict the lakehouse’s goal of handling diverse data types with robust transactions.