Data Lake vs Data Warehouse

Data Lake and Data warehouse (DWH) are different approaches to data storage. While unstructured (raw) data is stored in a lake, a DWH is filled with structured and processed data. In our article Data Lake vs Data Warehouse, we provide you with detailed information about the differences between the two technologies.

• Data warehouse or data lake

• Differences between DWH and Data Lake

• Which is better?

Data lake or data warehouse?

that Data warehouse (DWH) is a digital storage system that combines and harmonizes huge amounts of structured and formatted data from various sources.

With a Data Lake On the other hand, the data is also stored, but in its original, unedited form (raw data). They are neither structured nor formatted.

Differences between Data Lake and DWH

In the following, we show you a tabular comparison of Data Lake and Data warehouse. The most important differences include the data structure, the respective users, scalability and usage.

Do you need more information about the individual applications? You can find all relevant details on our website.

• Go to the Data Warehouse page
• Everything about Data Lake

DWH or lake — which is better?

Data Lakes and data warehouses have essential differences. The type of data storage you should choose depends on various factors, such as data structure and user requirements. A combination of the two is often the best solution to cover the full range of data storage requirements.

Alternatively, the “merged” solution is also used: the Data Lakehouse.

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