Data Lake vs. Data Warehouse vs. Data Mart
What is what and how do they differ?
All three architectures are now established in enterprises and are part of a solid data platform, but how do they differ from one another? However, one can say that these concepts are not only competitors but rather build and depend on one another.
The Data Warehouse vs. The Data Lake
Here, I will only briefly define these two concepts in one single step, since I have already published an article on this subject matter, that can be found in the link below:
In a Data Lake, organizations can store large amounts of structured, semi structured and unstructured data and make it immediately available for real-time Analytics, Data Science, and Machine Learning use cases. With a Data Lake, data is ingested in its original form and without modification. While Data Warehouses use the classic ETL process in combination with structured data in a relational database, a Data Lake uses paradigms such as ELT and a schema on read as well as often unstructured data…
