What statement best describes the trade-offs between relational and document-oriented approaches for address data?

What statement best describes the trade-offs between relational and document-oriented approaches for address data?

• A. Relational databases offer strong consistency and normalized data, while document databases provide a flexible schema and easier history storage, with faster writes but potential duplication
• B. Relational databases offer strong consistency and easy joins; Document databases offer a flexible schema and easier history storage, with faster writes but potential data duplication
• C. Relational has no consistency; Document has never history
• D. There is no difference between the two approaches

Answer: (A)

This question tests how relational systems and document stores handle data structure, consistency, and history for addresses. Relational databases emphasize normalized data and strong consistency; changes are coordinated through constraints and ACID transactions, which minimizes duplication and keeps updates reliable across related records. For addresses, this means you store components in separate, linked tables and use history or audit tables if you need to track changes, but you may need joins and multiple writes to keep everything in sync. Document databases prioritize a flexible schema and the ability to store related data together (denormalization). You can embed address data and its history in a single document, which makes writes faster and often simplifies retrieval of a full address record. The trade-off is the risk of duplicating data across documents, so updates can become inconsistent if the same address appears in many places and isn’t updated uniformly. Option A captures these realities: relational databases offer strong consistency and normalized data; document databases offer a flexible schema and easier history storage, with faster writes but potential duplication. The other options introduce inaccuracies—relational systems do provide strong consistency and joins aren’t the decisive differentiator here, and saying there is no difference or that history can never exist in either approach is misleading.

This question tests how relational systems and document stores handle data structure, consistency, and history for addresses. Relational databases emphasize normalized data and strong consistency; changes are coordinated through constraints and ACID transactions, which minimizes duplication and keeps updates reliable across related records. For addresses, this means you store components in separate, linked tables and use history or audit tables if you need to track changes, but you may need joins and multiple writes to keep everything in sync.

Document databases prioritize a flexible schema and the ability to store related data together (denormalization). You can embed address data and its history in a single document, which makes writes faster and often simplifies retrieval of a full address record. The trade-off is the risk of duplicating data across documents, so updates can become inconsistent if the same address appears in many places and isn’t updated uniformly.

Option A captures these realities: relational databases offer strong consistency and normalized data; document databases offer a flexible schema and easier history storage, with faster writes but potential duplication. The other options introduce inaccuracies—relational systems do provide strong consistency and joins aren’t the decisive differentiator here, and saying there is no difference or that history can never exist in either approach is misleading.