Value Added Course_NoSQL Databases

What is data partitioning in NoSQL databases?

• Data partitioning is the process of merging datasets for better performance.

• Data partitioning refers to the encryption of data in NoSQL databases.

• Data partitioning is the method of backing up data in NoSQL databases.

• Data partitioning is the process of dividing a dataset into smaller partitions for improved performance and scalability in NoSQL databases.

How does sharding improve database performance?

• Sharding eliminates the need for indexing in databases.

• Sharding consolidates data into a single server for faster access.

• Sharding improves database performance by distributing data across multiple servers for parallel processing.

• Sharding reduces the number of servers required for data storage.

What are the key differences between replication and data distribution?

• Replication is only used for backup purposes.

• Data distribution is solely about data security.

• Replication and data distribution are the same concept.

• Replication focuses on data redundancy and availability, while data distribution emphasizes performance and access optimization.

Explain the CAP theorem in the context of NoSQL databases.

• The CAP theorem guarantees all three properties: Consistency, Availability, and Partition Tolerance.

• The CAP theorem is only applicable to SQL databases and not to NoSQL systems.

• The CAP theorem states that in a distributed system, you can only guarantee two of the following three properties: Consistency, Availability, and Partition Tolerance.

• In NoSQL databases, CAP theorem states that data must be stored in a single location for efficiency.

What are the advantages of using sharding in a NoSQL database?

• Advantages of sharding include improved performance, enhanced scalability, better fault tolerance, and efficient resource utilization.

• Limited data availability

• Slower query response times

• Increased data redundancy

How does replication ensure data availability in NoSQL systems?

• Replication improves performance by compressing data before storage.

• Replication reduces data redundancy by storing data in a single location.

• Replication ensures data availability by creating multiple copies of data across different nodes, allowing access even if some nodes fail.

• Replication eliminates the need for backups in NoSQL systems.

What is the role of consistency in data distribution?

• Consistency is irrelevant to data distribution accuracy.

• Consistency ensures uniformity in data distribution, leading to accurate analysis and reliable conclusions.

• Consistency only affects data storage, not distribution.

• Consistency leads to data redundancy and inefficiency.

Describe the process of data partitioning in Cassandra.

• Data partitioning in Cassandra is achieved by using a partition key to hash data into tokens, distributing it evenly across nodes.

• Data partitioning in Cassandra relies on a centralized server to manage data distribution.

• Data partitioning in Cassandra is done by manually assigning data to specific nodes.

• Cassandra uses a single partition key for all data, leading to uneven distribution.

What are the different consistency models available in NoSQL databases?

• Partial Consistency

• Immediate Consistency

• Strong Consistency, Eventual Consistency, Causal Consistency, Read Your Writes, Session Consistency

• Strong Isolation

How does MongoDB handle data replication?

• MongoDB uses a single node for data storage.

• Data is replicated using a master-slave configuration.

• Replication is handled through manual backups only.

• MongoDB handles data replication using replica sets, where a primary node replicates data to secondary nodes.