Data Lakehouse to me is: > A Data Lakehouse open data management architecture that combines the flexibility, cost-efficiency, and scale of Data Lake with the data management and ACID transactions of Data Warehouse with Data Lake Table Formats (Delta Lake, Apache Iceberg & Apache Hudi) that enable Business Intelligence (BI) and Machine Learning (ML) on all data.

The initial concept was created by Databricks in the CIDR Paper (https://www.cidrdb.org/cidr2021/papers/cidr2021_paper17.pdf) in 2021.

Format is the same - parquet. Only the way metadata is stored is different.

>The root of the problem is using object storage improperly.

I don't see anything improper for any Parquet-with-metadata format.