Spatio-Temporal Query Evaluation in Oracle Spatial and Graph Engine

Abstract

Spatio-temporal data analytics is increasingly central to enterprise systems that support mobility
intelligence, infrastructure monitoring, and geographic decision-making. Oracle Spatial and Graph
Engine provides a robust framework for storing, indexing, and querying geometric and temporal data,
yet performance outcomes depend on the interplay between indexing configuration, temporal filtering
strategies, and application-layer rendering behavior. This study evaluates containment, intersection,
shortest-path, and temporal window queries across both static geographic layers and dynamic
trajectory datasets. Results indicate that index granularity and temporal predicate formulation strongly
influence execution efficiency, while user-perceived responsiveness in Oracle APEX interfaces is
shaped by refresh and caching mechanisms. The findings demonstrate that effective spatio-temporal
query evaluation requires unified tuning across database, network, and interface layers to maintain
performance and interpretability in operational geospatial applications.