How do SQL and NoSQL database models differ, and which scenario is typical for each?

• A. SQL databases have rigid schemas and ACID guarantees, while NoSQL offers flexible schemas and eventual consistency; use SQL for accounting, NoSQL for real-time analytics or content stores.
• B. SQL databases are unstructured; NoSQL are structured.
• C. NoSQL databases always guarantee stronger consistency than SQL.
• D. NoSQL databases can only be used for document storage.

Answer: (A)

The key idea is how data models balance schema rigidity and transaction guarantees, and how that guides when to use each type. SQL databases rely on predefined schemas and ACID transactions, which enforce strong consistency, reliability, and structured data organization—perfect for tightly controlled domains like accounting where exactness and auditability matter. NoSQL databases, by contrast, offer flexible or dynamic schemas and tend to emphasize scalability and performance with large, varied datasets, often using eventual or tunable consistency. This makes them well-suited for scenarios like real-time analytics, content stores, or large-scale web applications where data shapes can evolve rapidly.

So, the statement reflects the usual distinction: SQL = rigid schemas + ACID; NoSQL = flexible schemas + eventual consistency; run SQL for accounting and similar strict data domains, and NoSQL for real-time analytics or content stores. The other claims—SQL being unstructured, NoSQL always being more consistent, or NoSQL only for document storage—don’t hold broadly across the different database families.