While a data lake and a database both contain information, each is built to serve different purposes. While databases contain structured and organized data with pre-defined schema, data lake allows storing any type of structured, semi-structured, or unstructured data in raw format. Data lakes are best suited for large-scale analysis, machine learning, research, and exploration of the data. One of the key ideas behind data lake definition and its architecture is that it is possible to store the data without understanding the particular purpose of analysis. There is no single answer to whether data lake or database should be used because much depends on the type of data, workloads, and business needs.
