Which of the statements are incorrect when choosing between lakehouse and Datawarehouse?

Which of the statements are incorrect when choosing between lakehouse and Datawarehouse?
A . Lakehouse can have special indexes and caching which are optimized for Machine learning
B . Lakehouse cannot serve low query latency with high reliability for BI workloads, only suitable for batch workloads.
C . Lakehouse can be accessed through various API’s including but not limited to Python/R/SQL
D . Traditional Data warehouses have storage and compute are coupled.
E . Lakehouse uses standard data formats like Parquet.

Answer: B

Explanation:

The answer is Lakehouse cannot serve low query latency with high reliability for BI workloads, only suitable for batch workloads.

Lakehouse can replace traditional warehouses by leveraging storage and compute optimizations like caching to serve them with low query latency with high reliability.

Focus on comparisons between Spark Cache vs Delta Cache.

https://docs.databricks.com/delta/optimizations/delta-cache.html

What Is a Lakehouse? – The Databricks Blog