How does Cassandra handle write and read requests?

Cassandra handles write and read requests effectively by leveraging partitioning and replication in a distributed system. This architecture allows Cassandra to achieve high availability and fault tolerance.

In Cassandra, data is divided into partitions, which means that it can distribute data across multiple nodes in a cluster. This partitioning enables the system to manage large volumes of data efficiently, ensuring that no single node becomes a bottleneck. When a write request is made, it is sent to multiple nodes according to the defined replication factor, which increases durability; if one node fails, others can still provide access to the data.

Furthermore, data is replicated across different nodes to enhance reliability and availability. The use of a tunable consistency model allows applications to choose the level of consistency required for their operations, providing flexibility based on use cases, such as needing fast writes with eventual consistency versus requiring strong consistency for critical data.

Through this design, Cassandra offers a highly scalable solution that meets the demands of modern applications, where both read and write requests can be handled concurrently and efficiently without the risks associated with centralized architectures.