Some example projects in which it can be utilized include business intelligence (BI), data science, machine learning (ML), AI and SQL analytics. What to use data lakehouses for: Key featuresīecause it has the capabilities of both a data lake and a data warehouse, a data lakehouse can be used for several projects. In a data lakehouse, you also get data management, governance, ACID transactions and data quality-the primary offerings of data warehouses. Data lakehouses add in what data lakes lack.That means it is a cost-effective and flexible data storage solution, just as any data like is. This all-in-one platform enables storing data in raw formats, just like a data lake: in unstructured, semi-structured and structured ways.It addresses the limitations of data lakes and data warehouses when utilizing them separately. This article explains data lakehouses, including how they emerged, how they shape up versus data lakes and data warehouses, their architecture, and finally, the pros and cons of using a data lakehouse.Ī data lakehouse is a data management solution that leverages the best features of a data lake and a data warehouse into a single, unified platform. The features of a data lakehouse make it ideal for a range of data analytics use cases. It is popular among many organizations that incorporate the features of both data lakes and data warehouses. A data lakehouse is a modern data architecture.
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