What type of database is designed to store large amounts of data in multiple linked tables?

The answer is a relational database because it is specifically structured to store large amounts of data organized across multiple linked tables. In a relational database, data is stored in tables, which can be related to one another through common fields known as keys. This design allows for complex queries and efficient data retrieval by enabling users to join information from different tables based on the relationships established between them.

Relational databases also enforce data integrity and normalization, minimizing redundancy and ensuring consistency across the dataset. The ability to handle large datasets with interrelated information is a fundamental characteristic of relational databases, making them widely used in applications that require structured data management.

In comparison, a flat file database stores data in a singular table-like structure, making it less suitable for managing complex relationships between data points. Hierarchical databases arrange data in a tree-like structure, which can limit flexibility in querying data compared to the more versatile relationship capabilities of relational databases. Object-oriented databases store data as objects and are more aligned with object-oriented programming practices rather than the tabular format of relational databases. Each type has its own use cases, but when dealing with large datasets that require multiple linked tables, relational databases are the preferred solution.