Splendid Distributed Databases Test - 79+ MCQs: Distributed Databases test: Assess Your Knowledge with Challenging Questions and Answers

1. Why is maintaining data consistency challenging in distributed databases?

Maintaining data consistency is not challenging in distributed databases.

Maintaining data consistency is only a concern in centralized databases.

Maintaining data consistency is challenging due to the distributed nature of data and the potential for network failures.

Maintaining data consistency is the sole responsibility of database administrators.

2. Examine the impact of node failures on the consistency and availability of distributed databases, and propose strategies for fault detection and recovery.

Data Replication

Query Optimization

Load Balancing

Handling Network Failures

3. Which data storage model is commonly used in distributed databases?

Relational Model

Hierarchical Model

Key-Value Model

Object-Oriented Model

4. What is the role of a distributed lock manager in a distributed database system?

A distributed lock manager is used for decorative purposes in distributed databases.

A distributed lock manager is irrelevant in distributed databases.

A distributed lock manager ensures that transactions have exclusive access to resources, preventing conflicts.

A distributed lock manager only applies to centralized databases.

5. Explain the role of a distributed lock in maintaining data integrity.

Distributed locks are not used for data integrity.

Distributed locks ensure immediate consistency across all nodes.

Distributed locks prevent simultaneous access to shared resources, maintaining data integrity.

Distributed locks only apply to centralized databases.

6. Discuss the concept of eventual consistency in distributed databases.

Eventual consistency ensures immediate synchronization of data across all nodes in a distributed database.

Eventual consistency prioritizes immediate consistency over time.

Eventual consistency allows temporary inconsistencies that will be resolved in the future.

Eventual consistency is irrelevant in distributed databases.

7. What role does the 'Paxos algorithm' play in distributed databases?

Query Optimization

Consensus Protocol

Data Encryption

Load Balancing

8. What is the role of the 'Paxos algorithm' in achieving consensus in distributed databases, and why is it challenging?

Load Balancing

Consensus Protocol

Data Encryption

Query Optimization

9. In distributed databases, what does ACID stand for?

Atomicity, Consistency, Isolation, Durability

Availability, Concurrency, Integrity, Durability

Atomic, Causal, Isolated, Durable

Agility, Compatibility, Isolation, Decoupling

10. What is sharding, and how does it contribute to distributed database scalability?

Sharding is a process of breaking a database into small, independent pieces to improve data security.

Sharding is a method to replicate data across multiple nodes for fault tolerance.

Sharding involves dividing a database into partitions to distribute the workload and enhance scalability.

Sharding is only applicable to centralized databases.

11. Explore the challenges and benefits of implementing blockchain technology in distributed databases, and discuss its potential impact on data integrity and decentralization.

Consistency Model

Query Optimization

Load Balancing

Handling Network Failures

12. How does the 'Raft consensus algorithm' differ from the 'Paxos algorithm' in terms of simplicity and usability in distributed systems?

Load Balancing

Consensus Protocol

Data Encryption

Query Optimization

13. Explain the concept of data partitioning in distributed databases.

Data partitioning is irrelevant in distributed databases.

Data partitioning involves dividing a database into partitions to distribute the workload and improve performance.

Data partitioning only applies to centralized databases.

Data partitioning is a process of combining multiple databases into a single entity.

14. How does the 'Vector Clock' algorithm help maintain causality in distributed databases?

Concurrency Control

Query Optimization

Data Encryption

Logical Clock Synchronization

15. What is the purpose of the 'MapReduce' paradigm in distributed databases?

Data Replication

Query Optimization

Data Encryption

Load Balancing

16. In distributed databases, elaborate on the challenges and strategies associated with achieving a globally consistent view of data across multiple nodes.

Network Latency

Data Encryption

Query Optimization

Load Balancing

17. What is ACID in the context of distributed databases?

A chemical compound.

An acronym for Atomicity, Consistency, Isolation, and Durability – ensuring reliability in database transactions.

A programming language.

A type of distributed database.

18. What is the primary advantage of using distributed databases over centralized databases?

Distributed databases have slower performance than centralized databases.

Distributed databases are harder to manage.

Distributed databases provide better fault tolerance and scalability.

Centralized databases are more secure than distributed databases.

19. Explain the principles and challenges of achieving quorum-based consistency in distributed databases, and analyze its impact on system reliability and performance.

Consistency Model

Query Optimization

Load Balancing

Handling Network Failures

20. What is the role of a distributed coordinator in a distributed database system?

To manage a single database.

To coordinate transactions and ensure consistency across multiple databases.

To create backups for data security.

To limit access to the database.

21. How does data replication contribute to fault tolerance in distributed databases?

Ensuring Data Redundancy

Optimizing Query Performance

Load Balancing

Handling Network Failures

22. What is a distributed transaction?

A transaction that occurs only on weekends.

A transaction involving multiple databases that must be treated as a single, indivisible unit.

A transaction that is limited to a single server.

A transaction that is never committed to the database.

23. What is the significance of the two-phase commit protocol in distributed databases?

The two-phase commit protocol has no impact on distributed databases.

The two-phase commit protocol is only relevant in centralized databases.

The two-phase commit protocol ensures atomicity in distributed database transactions.

The two-phase commit protocol is used for data replication.

24. In the context of distributed databases, explain the principles and challenges of achieving data partitioning for massive datasets, and discuss the impact on query performance.

Data Replication

Query Optimization

Load Balancing

Consistency Model

25. What is the significance of a distributed hash table (DHT) in distributed databases?

Load Balancing

Data Encryption

Query Optimization

Data Indexing

26. How does the 'Chord algorithm' contribute to the scalability and efficiency of distributed hash tables (DHTs) in large-scale distributed systems?

Data Encryption

Query Optimization

Load Balancing

Node Lookup and Routing

27. Discuss the concepts and challenges associated with maintaining data privacy and security in distributed databases, particularly in environments with diverse access control requirements.

Data Replication

Query Optimization

Data Encryption

Consistency Model

28. Elaborate on the principles and challenges of achieving geo-replication in distributed databases, and analyze its impact on system performance and data consistency.

Data Replication

Query Optimization

Load Balancing

Consistency Model

29. Examine the principles and challenges of achieving elasticity and scalability in distributed databases, and propose strategies for dynamically adapting to changing workloads and data volumes.

Data Replication

Query Optimization

Load Balancing

Consistency Model

30. Why is partitioning important in distributed databases?

Partitioning has no impact on distributed databases.

Partitioning ensures that a database is only accessible to a single user.

Partitioning helps distribute the workload and improve performance in distributed databases.

Partitioning is only applicable to centralized databases.

31. Explain the term 'replica consistency' in the context of distributed databases.

Replica consistency refers to having different data on each replica in a distributed database.

Replica consistency is irrelevant in distributed databases.

Replica consistency ensures that all replicas in a distributed database have the same data at all times.

Replica consistency only applies to horizontal partitioning.

32. Elaborate on the role of 'vector clocks' in tracking causality and achieving consistency in distributed databases, and discuss scenarios where they prove beneficial.

Concurrency Control

Query Optimization

Data Encryption

Logical Clock Synchronization

33. What is the primary goal of distributed database systems?

Improved Performance

Data Redundancy

Centralized Control

Decreased Scalability

34. Why are distributed databases used?

To make databases more difficult to manage.

To reduce data redundancy and improve fault tolerance.

To limit access to the database.

To make databases slower.

35. What challenges does the 'CAP theorem' pose for distributed databases?

Ensuring Availability

Ensuring Consistency

Ensuring Partition Tolerance

Ensuring Performance

36. What is the role of a 'distributed transaction' in database systems?

Data Encryption

Ensuring Data Isolation

Query Execution

Transaction Management

37. Explore the challenges and benefits of implementing hybrid database architectures that combine both centralized and distributed components, and discuss scenarios where this approach is advantageous.

Consistency Model

Query Optimization

Load Balancing

Handling Network Failures

38. Define the term 'isolation' in the context of distributed databases.

Isolation is the process of isolating a distributed database from external access.

Isolation is irrelevant in distributed databases.

Isolation refers to the independence of transactions, ensuring they do not interfere with each other.

Isolation only applies to vertical partitioning.

39. What is a distributed database?

A database that is only accessible to a single user.

A database that is stored on a single computer.

A database that is spread across multiple locations or servers.

A database that contains only text data.

40. Explain the CAP theorem in the context of distributed databases.

CAP theorem describes the three essential properties of a distributed database: Consistency, Availability, and Partition Tolerance.

CAP theorem is irrelevant to distributed databases.

CAP theorem only applies to centralized databases.

CAP theorem stands for Centralized, Available, and Partitioned databases.

Distributed Databases MCQ Test 2