What are the benefits of using a distributed processing model in Relativity?

Using a distributed processing model in Relativity offers significant advantages, especially in terms of improving processing speed and reducing downtime. This model allows tasks to be handled across multiple servers rather than relying on a single server. By distributing the workload, the system can process data more quickly, as more resources are available to handle simultaneous tasks. This increased efficiency results in faster case processing times, allowing for quicker access to data and more timely decision-making.

Additionally, when processing is distributed, if one server encounters issues or goes down, the impact on the overall system is minimized. Other servers can continue to process tasks, thereby reducing downtime and enhancing system reliability. This redundancy ensures that the processing environment remains robust, allowing users to continue their work with minimal interruptions, which is particularly critical in legal contexts where timely access to information is essential.

The benefits highlighted by the correct choice contribute to a more efficient, responsive, and effective processing environment in Relativity, aligning well with the needs of users who may be managing large volumes of data.