Which federated ArcGIS Server is the spatiotemporal big data store registered with?

Which federated ArcGIS Server is the spatiotemporal big data store registered with?

• A. Standalone server
• B. Enterprise hosting server
• C. Cloud server
• D. Local development server

Answer: (B)

The correct answer highlights that the spatiotemporal big data store is registered with an Enterprise hosting server. This is because the spatiotemporal big data store is a component designed specifically to work within the architecture of ArcGIS Enterprise, which includes a robust server environment for handling large datasets effectively. An Enterprise hosting server provides the necessary capabilities, such as high availability, scalability, and integration with other components of the ArcGIS platform. This setup is crucial for managing and analyzing spatiotemporal data, especially when dealing with extensive datasets that require significant processing power and storage capacity. The other options reflect different server types that do not have the same level of compatibility or functionality needed to manage the complexity of a spatiotemporal big data store. A standalone server typically lacks the integration and management features essential for these operations. A cloud server may offer scale but, depending on how it is configured, might not be directly federated with the big data store effectively. Similarly, a local development server is primarily intended for development and testing purposes and is not suitable for handling extensive production-level data like a spatiotemporal big data store.

The correct answer highlights that the spatiotemporal big data store is registered with an Enterprise hosting server. This is because the spatiotemporal big data store is a component designed specifically to work within the architecture of ArcGIS Enterprise, which includes a robust server environment for handling large datasets effectively.

An Enterprise hosting server provides the necessary capabilities, such as high availability, scalability, and integration with other components of the ArcGIS platform. This setup is crucial for managing and analyzing spatiotemporal data, especially when dealing with extensive datasets that require significant processing power and storage capacity.

The other options reflect different server types that do not have the same level of compatibility or functionality needed to manage the complexity of a spatiotemporal big data store. A standalone server typically lacks the integration and management features essential for these operations. A cloud server may offer scale but, depending on how it is configured, might not be directly federated with the big data store effectively. Similarly, a local development server is primarily intended for development and testing purposes and is not suitable for handling extensive production-level data like a spatiotemporal big data store.