What distinguishes a spatial database from a non-spatial database?

A spatial database is specifically designed to store, manipulate, and query data related to objects in a defined space. This includes geographic information systems (GIS) that handle data points representing real-world phenomena, such as locations, areas, and volumes. Since spatial databases incorporate data types like points, lines, and polygons, they enable complex spatial queries and analysis that go beyond traditional data storage.

In contrast, a non-spatial database traditionally handles structured data without geographic context, such as text and numeric information. While both types of databases can manage various forms of data, the key distinction lies in the ability of spatial databases to understand and represent spatial relationships and geographic dimensions. This allows for functionalities such as spatial indexing and queries that can assess proximity, intersections, and other spatial relationships.

The other options do not accurately represent the core attributes that differentiate spatial databases from non-spatial databases. Storing images does not define a spatial database; both types can store various data formats. The characterization of spatial databases as unstructured is misleading, as they can be highly structured with defined schemas for spatial data types. Lastly, spatial databases do not exclusively contain text, as they support a wide range of spatial data types beyond just numerical or textual information.