What is one disadvantage of using flat-file databases?

One significant disadvantage of using flat-file databases is their inefficiency in handling large amounts of data. Flat-file databases structure data in a single table, typically without the ability to relate or link to other tables, which can lead to complications as the dataset grows.

When the volume of data increases, operations such as searching, filtering, and updating become slower and more cumbersome because the entire dataset is stored as one entity. Unlike relational databases, which can manage large datasets through structured organization in multiple related tables, flat-file databases lack indexing and efficient querying capabilities, making them less suitable for applications requiring performance as data scales up. This limitation is particularly noticeable in scenarios where data needs to be manipulated or accessed in a complex manner.

The other options highlight attributes that don’t align with the characteristics of flat-file databases, such as their inability to effectively manage complex relationships or utilize advanced data types, which further underscores the efficiency concerns when dealing with significant amounts of data.