What does a Data Lakehouse combine?

A Data Lakehouse combines the benefits of data lakes and data warehouses. This innovative architecture is designed to leverage the strengths of both systems, providing a unified platform to manage both structured and unstructured data.

Data lakes are known for their ability to store vast amounts of raw data in its native format, enabling data scientists and analysts to run complex data analytics and machine learning models without needing to prepare and transform this data extensively first. On the other hand, data warehouses are optimized for querying and reporting, with a focus on structured data and pre-defined schemas to provide fast access to this data for business intelligence purposes.

By integrating these two paradigms, a Data Lakehouse allows organizations to handle diverse data types and workloads in a single platform. It enables analytics on both historical and real-time data, supporting a range of modern data applications while simplifying management and reducing costs associated with maintaining separate systems. This combination empowers users to perform both exploratory data analysis and business intelligence tasks efficiently, catering to the needs of various stakeholders within an organization.