Oracle Spatial and Graph, formerly Oracle Spatial, is a free option component of the Oracle Database. The spatial features in Oracle Spatial and Graph aid users in managing geographic and location-data in a native type within an Oracle database, potentially supporting a wide range of applications — from automated mapping, facilities management, and geographic information systems (AM/FM/GIS), to wireless location services and location-enabled e-business. The graph features in Oracle Spatial and Graph include Oracle Network Data Model (NDM) graphs used in traditional network applications in major transportation, telcos, utilities and energy organizations and RDF semantic graphs used in social networks and social interactions and in linking disparate data sets to address requirements from the research, health sciences, finance, media and intelligence communities.
Components The geospatial feature of Oracle Spatial and Graph provides a SQL schema and functions that facilitate the storage, retrieval, update, and query of collections of spatial features in an Oracle database. (The spatial component of a spatial feature consists of the geometric representation of its shape in some coordinate space — referred to as its "geometry".)
Geospatial data features The Oracle Spatial geospatial data features consist of:
a schema - MDSYS (as in "multi-dimensional system") - that prescribes the storage, syntax, and semantics of supported geometric data types a spatial indexing system operators, functions, and procedures for performing area-of-interest queries, spatial join queries, and other spatial analysis operations functions and procedures for utility and tuning operations vector performance acceleration for substantially faster querying and more efficient use of CPU, memory, and partitioning support for parametric curves (NURBS) for mathematically precise representation of free-form curves that can be reproduced exactly for 2D and 3D data a topology data model for working with data about nodes, edges, and faces in a topology a GeoRaster feature to store, index, query, analyze, and deliver GeoRaster data (raster image and gridded data and its associated metadata) with virtual mosaics, raster-algebra operations, image processing, Java API, and GDAL-Based ETL Wizard 3-dimensional data-types and operators including Triangulated Irregular Networks (TINs), Point Clouds and LiDAR data sets with Spatial R-tree indexing, SQL operators and analysis functions, and metadata for visualization geocoding that converts location and address data into formal geographic coordinates from point addresses and address ranges, and supports reverse geocoding a routing engine that creates fastest or shortest routes with driving distances, times, directions and turn-specific geometries based on commercial and publicly available street network data, and restrictions and conditions for advanced routing, such as truck-specific routing Open Geospatial Consortium-compliant Web Services for geocoding, routing, mapping, business-directory, catalog, and geospatial feature transactions Spatial Visualization components to render data on maps.
Network Data Model The Network Data Model feature is a property graph model used to model and analyze physical and logical networks used in industries such as transportation, logistics, and utilities. Its features include:
Persistent management of the network connectivity in the database A data model for representing capabilities or objects (modeled as nodes and links) in a network with a PL/SQL API for managing network data. User-determined link and node properties, such as costs and restrictions, including temporal properties. Association of real world objects with network elements to simplify application development and maintenance. A Java API for in-memory network path analytics, including shortest path, nearest neighbors, within cost, and reachability, with partitioned loading of large networks into memory.
RDF semantic The RDF Semantic Graph feature supports the World Wide Web Consortium (W3C) RDF standards. It provides RDF data management, querying and inferencing that are commonly used in a variety of applications ranging from semantic data integration to social network analysis and linked open data applications. Its features include:
… excerpt ends here. Continue reading the full article.
