Cassandra Practice Test

Which of the following best describes the consistency model Cassandra provides?

1. Strong consistency

2. Eventual consistency

3. Immediate consistency

4. Partial consistency

The correct answer is: Eventual consistency

Cassandra is designed to provide eventual consistency, which is a fundamental aspect of its architecture tailored for distributed systems. This means that after a write is made to the database, not all nodes will immediately reflect that change; however, the system guarantees that given enough time, all updates will propagate and all nodes will eventually converge to the same value. This model is suitable for scenarios where high availability and partition tolerance are critical, allowing users to read from any node, even if it might not be the most up-to-date version of the data. Eventual consistency enables Cassandra to maintain performance and scalability, especially in environments where network partitions can occur and where operations might be distributed across multiple data centers. In such cases, the flexibility of eventual consistency allows the system to remain responsive rather than become unresponsive waiting for all nodes to synchronize immediately. Other models such as strong consistency or immediate consistency imply that all nodes are required to see the same data at the same time, which can lead to performance trade-offs and reduced availability in distributed systems. Such approaches are not in line with the design goals of Cassandra, which prioritizes availability and partition tolerance over immediate consistency. Partial consistency lacks the specific aspects of eventual convergence that Cassandra employs to ensure that all changes will eventually be consistent across