What is the primary purpose of a database in a typical system design?

To store, manage, and retrieve persistent data efficiently.

To execute application logic and business rules.

To handle user interface rendering and client-side interactions.

To manage network communication between different services.

What is the primary advantage of using a NoSQL database (e.g., a document store) over a relational database for storing user profiles with highly variable and evolving attributes?

Horizontal scalability and flexible schema for diverse data structures.

Strong transactional consistency across multiple tables.

Strict schema enforcement for data integrity.

Efficient joining of data from multiple related tables.

Denormalization in database design is often performed to improve which aspect of system performance?

Read performance by minimizing joins.

Write performance by reducing data redundancy.

Data integrity by enforcing stricter constraints.

Storage efficiency by eliminating duplicate data.

In a globally distributed system, why is eventual consistency often chosen over strong consistency for certain types of data?

To improve system availability and partition tolerance, especially under network latency.

To guarantee immediate data accuracy across all distributed nodes.

To simplify database backups and disaster recovery processes.

To reduce the overall storage footprint of the database.

For a microservices architecture, why might 'polyglot persistence' be considered a beneficial approach?

It allows each microservice to choose the database technology best suited for its specific data storage and access patterns.

It forces all microservices to use the same database technology for standardization.

It eliminates the need for any database in a microservice architecture.

It ensures strong ACID compliance across all services automatically.

Consider a system with a single relational database experiencing extreme load. What is the primary trade-off when deciding between vertical scaling (upgrading server hardware) and horizontal scaling (sharding data across multiple servers)?

Vertical scaling is generally simpler to manage but has finite limits, while horizontal scaling provides higher scalability but adds significant architectural complexity.

Vertical scaling offers infinite capacity, while horizontal scaling has severe limits.

Horizontal scaling guarantees stronger ACID properties, whereas vertical scaling compromises them.

Vertical scaling is only applicable to NoSQL databases, while horizontal scaling is only for relational databases.

Concepts of Databases in System Design — Free MCQ Practice Test

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