Dominate the Cassandra Test 2025 – Unleash Your Big Data Brilliance!

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How does Cassandra ensure high availability?

By using single-node architecture

By implementing data compression techniques

Through distributed architecture and data replication

Cassandra ensures high availability through its distributed architecture and data replication. In this model, data is spread across multiple nodes in a cluster, which allows the system to handle failures gracefully. Each piece of data is replicated across several nodes, based on the configured replication factor. This means that if any individual node fails, the data is still accessible from other nodes that hold replicas.

Additionally, the distributed nature of Cassandra means there is no central point of failure, allowing the system to continue operating smoothly even when some nodes are down. This design provides resilience, load balancing, and increases fault tolerance, contributing significantly to overall availability. This mechanism is particularly important in environments where downtime is not acceptable and where data needs to be consistently available across various geographical regions.

The other choices do not support high availability in the same manner. A single-node architecture would actually create a single point of failure, compromising availability. Data compression techniques improve storage efficiency but do not inherently ensure availability. Having a single point of failure directly contradicts the goals of high availability. Thus, the correct answer highlights the foundational principles that make Cassandra a robust solution for maintaining continuous access to data.

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By having a single point of failure

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