What is a data lakehouse? How does it compare to the data lake or a traditional data warehouse? In the final video in our series on Delta Lake, Austin goes through the basics of explaining what a data lakehouse is, how to store data in the data lake using delta format, keeping your traditional data warehouse architecture but saving on storage by utilizing the data lake as the storage layer instead of a traditional database.
The Data Lakehouse is a powerful and modern data architecture that combines the data lake and data warehouse technologies to provide enhanced insights. It is a single, unified platform for ingesting, preparing, managing, and analyzing large volumes of structured and unstructured data. The Data Lakehouse is designed to provide a single source of truth for all data, and to enable organizations to unlock the full potential of their data, regardless of its source. It creates a single source of truth, enabling a unified approach to data processing and analytics. The Data Lakehouse also enables organizations to take advantage of the scalability and cost-effectiveness of the cloud while maintaining the security and compliance requirements of their data. The Data Lakehouse can be used for a variety of use cases such as fraud detection, customer segmentation, and predictive maintenance.
Data lakes and data warehouses are both widely used for storing big data, but they are not interchangeable terms. A data lake is a vast pool of raw data, the purpose for which is not yet defined. A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose.
Data lakehouses came into existence because of the need to offer data lake-style benefits while leveraging warehouse-style features, such as SQL functionality and schema. This kind of need was first identified by cloud warehouse providers. Some examples of data lakehouses include Amazon Redshift Spectrum or Delta Lake.
A lakehouse provides a one-size-fits-all approach. It is not merely an integration of a warehouse with a data lake but a combination of it, warehouse, and purpose-built store enabling easy, unified governance and movement.
Data lakehouses usually start as data lakes containing all data types; the data is then converted to Delta Lake format (an open-source storage layer that brings reliability to data lakes). Delta lakes enable ACID transactional processes from traditional data warehouses on data lakes.