What are the main differences between SQL and NoSQL databases in the context of AIS?

What are the main differences between SQL and NoSQL databases in the context of AIS?

• A. SQL uses structured tables with ACID transactions; NoSQL uses flexible schemas and scalable storage, often with eventual consistency.
• B. NoSQL is always more secure than SQL.
• C. SQL does not support transactions.
• D. NoSQL uses fixed schemas and strong consistency always.

Answer: (A)

In AIS contexts, the key distinction rests on how data is modeled, how integrity is guaranteed, and how the system scales. SQL databases organize data into structured tables with predefined schemas, enforcing data types and relationships. They prioritize reliable, transaction-based operations using ACID properties—Atomicity, Consistency, Isolation, and Durability—so financial records stay accurate and auditable even in concurrent access scenarios. This makes SQL a solid choice when precise, consistent updates and complex reporting are essential. NoSQL databases, on the other hand, use more flexible schemas and a variety of data models (document, key-value, column-family, graph). They are designed to scale out across many servers and handle large, evolving datasets more readily. Because of this emphasis on performance and distribution, they often operate under eventual or other relaxed consistency models rather than strict ACID guarantees. That trade-off can be advantageous for certain types of data or workloads in an AIS, provided you design the system to maintain necessary integrity where it matters. The statement about NoSQL being always more secure is not accurate—the security of a database depends on implementation, configuration, and controls, not just the data model. Also, SQL does support transactions, so saying it doesn’t is incorrect. And NoSQL does not inherently use fixed schemas with strong, universal consistency; it commonly uses flexible schemas with varying consistency guarantees, not a blanket rule.

In AIS contexts, the key distinction rests on how data is modeled, how integrity is guaranteed, and how the system scales. SQL databases organize data into structured tables with predefined schemas, enforcing data types and relationships. They prioritize reliable, transaction-based operations using ACID properties—Atomicity, Consistency, Isolation, and Durability—so financial records stay accurate and auditable even in concurrent access scenarios. This makes SQL a solid choice when precise, consistent updates and complex reporting are essential.

NoSQL databases, on the other hand, use more flexible schemas and a variety of data models (document, key-value, column-family, graph). They are designed to scale out across many servers and handle large, evolving datasets more readily. Because of this emphasis on performance and distribution, they often operate under eventual or other relaxed consistency models rather than strict ACID guarantees. That trade-off can be advantageous for certain types of data or workloads in an AIS, provided you design the system to maintain necessary integrity where it matters.

The statement about NoSQL being always more secure is not accurate—the security of a database depends on implementation, configuration, and controls, not just the data model. Also, SQL does support transactions, so saying it doesn’t is incorrect. And NoSQL does not inherently use fixed schemas with strong, universal consistency; it commonly uses flexible schemas with varying consistency guarantees, not a blanket rule.