How does schema-on-read differ from schema-on-write?

The correct answer highlights a fundamental difference between how data schemas are applied in different contexts. Schema-on-read refers to the process where the structure of the data is determined when the data is read or queried, not at the moment the data is stored. This approach is commonly used in big data environments where the data may be unstructured or semi-structured. Users can apply different schemas as needed when they pull data from storage, allowing for greater flexibility in data analysis.

On the other hand, schema-on-write requires that the schema is defined and enforced at the time of data entry. This means that data must conform to a predefined structure before it can be stored in a database. This method is typical of traditional relational database systems, where strict data validation rules are applied to ensure data integrity upon writing it to the database.

Understanding this distinction is crucial for database design, as it impacts how data is stored, analyzed, and retrieved in various applications.