Comparing the benefits of a data warehouse vs data lake vs data lakehouse

The text provides an in-depth comparison of data warehouses, data lakes, and data lakehouses, explaining the benefits and limitations of each architecture. Data warehouses are highlighted for their structured data storage, high performance, reliability, and use of SQL, but they can be costly and require complex ETL processes. Data lakes offer a modern, versatile, and cost-effective alternative, capable of storing diverse data structures and supporting large-scale data science and machine learning applications. Data lakehouses combine the strengths of both data lakes and data warehouses, offering improved performance, reduced costs, and enhanced functionality such as ACID compliance and schema evolution. They provide a democratized access to data across organizations while maintaining the agility and low-cost benefits of cloud object storage. The text emphasizes that data lakehouses represent an evolution in data architecture, allowing businesses to reduce reliance on traditional data warehouses while optimizing data management and analytics capabilities.