What is one benefit of deploying the spatiotemporal big data store across multiple nodes?

Choosing to deploy the spatiotemporal big data store across multiple nodes indeed results in increased data storage capacity. This distributed architecture allows for the horizontal scaling of resources, meaning that as the volume of data grows, more nodes can be added to accommodate the additional storage requirements. Each node can handle a portion of the data load, which not only improves capacity but also enhances the system's ability to handle large datasets more efficiently.

Moreover, with a distributed approach, data can be spread across different physical or virtual servers, thus allowing for more extensive data processing and analysis capabilities. This is particularly important in big data environments where the integration of spatiotemporal data can be essential for real-time decision-making. By leveraging multiple nodes, organizations can effectively manage large volumes of complex geographical and temporal datasets.

The other options, while they may seem relevant, do not specifically capture the primary advantage of deploying the big data store in a multi-node configuration. For example, operational costs might not be significantly reduced with additional nodes due to the costs associated with maintaining them. Similarly, while maintenance might benefit from resource distribution, it can also become more complicated as the system grows. Application development speed may see some indirect benefits but is not a direct outcome of deploying a spati