CompTIA DataSys+ (DS0-001)Database FundamentalsHard

A data engineering team is building a data pipeline that processes real-time events. They need a database that can handle extremely high write throughput and low-latency reads for individual records, but where strong consistency across all nodes is not a strict requirement. Which characteristic of NoSQL databases makes them particularly suitable for this scenario?

  1. AStrict schema enforcement
  2. BReferential integrity
  3. CEventual consistency
  4. DACID compliance
Show answer & explanation

Correct answer: C. Eventual consistency

NoSQL databases often prioritize availability and partition tolerance over strong consistency, leading to eventual consistency. This means that data might not be immediately consistent across all nodes after a write, but will eventually become consistent, which is acceptable for scenarios prioritizing high write throughput and low latency over immediate global consistency.

Why the other options are wrong

  • A. Strict schema enforcement is characteristic of relational databases, not NoSQL, which typically offers flexible schemas.
  • B. Referential integrity is enforced by foreign keys in relational databases, ensuring relationships are valid, which is not the primary focus of this high-throughput, low-latency, eventually consistent scenario.
  • D. ACID compliance (Atomicity, Consistency, Isolation, Durability) is a hallmark of relational databases, ensuring strong consistency, which contradicts the 'not a strict requirement' part.

Eventual Consistency

A consistency model in distributed computing that guarantees that if no new updates are made to a given data item, eventually all accesses to that item will return the last updated value.

  • Common in NoSQL databases for high availability and scalability.
  • Data may not be immediately consistent across all nodes.
  • Sacrifices immediate consistency for performance and availability (part of CAP theorem).

Memory trick: Eventually, all data will agree, but not always at once.

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