Because all data entering the warehouse must conform to a predefined schema when it is written, the system does not have to account for divergent schemas, unstructured data, or other complexities. This results from the structured nature of the data inside them. Data warehouse performance benefitsĭata warehouses are highly efficient, performing very well compared to other technologies. To answer these questions, let’s dig down a bit and see what made data warehouses beneficial to the businesses that used them. For the businesses adopting this new architecture it offers a powerful, hybrid benefit allowing for a best of both worlds scenario.īut what do those features achieve in a business sense? What are the traditional benefits of a data warehouse and how does a data lakehouse bring these benefits to the lake? Data warehouses: Benefits and impacts on the businessĭata lakehouses bring many of the features and benefits typically associated with data warehouses and apply them to data lakes. To do this, we’ll compare the differences between a data warehouse and data lake then discuss the hybrid advantage of a data lakehouse.
Let’s explore the business case for the adoption of a data lakehouse, also known as modern data lake, and see how it can improve versatility, maintain performance, and reduce costs. In fact, these differences are often the key reason that organizations make the transition from older technologies to modern ones.
Adopting a data lakehouse architecture over a traditional data warehouse comes with many business benefits.
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