Databases are used for managing and retrieving data efficiently, with an emphasis on rapid transaction processing. Data warehouses store structured data in a centralized repository for analysis and reporting, focusing on historical data integration and complex queries. Data lakes hold large amounts of raw data in its native format, accommodating both structured and unstructured data without rigid organization, making them suitable for diverse datasets and flexible data processing. Selecting between these systems depends on specific business needs and data characteristics, with databases ideal for applications requiring quick data retrieval and updates, data warehouses best suited for businesses focusing on data-driven decision-making through historical analysis, and data lakes catering to those aiming for flexibility and insight in data science and analytics.