Choosing between a data lake, lakehouse, and data mesh architecture
In a nutshell, data lake, lakehouse, and data mesh architectures are three different approaches to organizing and managing data in an organization.
A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. A data lake provides the raw data and is often used for data warehousing, big data processing, and analytics. A lakehouse is a modern data architecture that combines the scale and flexibility of a data lake with the governance and security of a traditional data warehouse. A lakehouse provides raw and curated data, making it easier for data warehousing and analytics.
A data mesh organizes and manages data that prioritizes decentralized data ownership and encourages cross-functional collaboration. In a data mesh architecture, each business unit is responsible for its own data and shares data with others as needed, creating a network of data products...