Data lakes and data warehouses serve different purposes. Data lakes are used for storing and processing raw data, while data warehouses are used for storing processed data that is ready for analysis. Data lakes are more flexible than data warehouses and can handle a wider variety of data types, but data warehouses provide better performance and reliability for analytical workloads.
