By Mike.Hallett-Oracle on Jun 16, 2015
We have just added Oracle Big Data Spatial and Graph support for Hadoop and NoSQL database technologies. For over a decade, Oracle has offered leading spatial and graph analytic technology for the Oracle Database: we have now applied this expertise to work with social network data and to exploit Big Data architectures.
Oracle Big Data Spatial and Graph includes two main components:
A distributed property graph database with 35 built-in graph analytics to discover graph patterns in big data, such as communities and influencers within a social graph
A wide range of spatial analysis functions and services to evaluate data based on how near or far something is to one another, or whether something falls within a boundary or region
Property Graph Data Management and Analysis
Property graphs are commonly used to model and analyze relationships, such as communities, influencers and recommendations, and other patterns found in social networks, cyber security, utilities and telecommunications, life sciences and clinical data, and knowledge networks.
Property graphs model the real-world as networks of linked data comprising vertices (entities), edges (relationships), and properties (attributes) for both. Property graphs are flexible and easy to evolve; metadata is stored as part of the graph and new relationships are added by simply adding an edge.
Oracle Big Data Graph provides an industry leading property graph capability on Apache HBase and Oracle NoSQL Database with a Groovy-based console; parallel bulk load from common graph file formats; text indexing and search; querying graphs in database and in memory; ease of development with open source Java APIs and popular scripting languages; and an in-memory, parallel, multi-user, graph analytics engine with 35 standard graph analytics.
Spatial Analysis and Services – Enrich and Categorize Your Big Data with Location
With the spatial capabilities, users can take data with any location information, enrich it, and use it to harmonize their data. For example, Oracle Big Data Spatial can look at datasets like Twitter feeds that include a zip code or street address, and add or update city, state, and country information. These results can be visualized on a map with the included HTML5-based web mapping tool. Location can be used as a universal key across disparate data commonly found in Hadoop-based analytic solutions.
“Big Data systems are increasingly being used to process large volumes of data from a wide variety of sources. With the introduction of Oracle Big Data Spatial and Graph, Hadoop users will be able to enrich data based on location and use this to harmonize data for further correlation, categorization and analysis. For traditional geospatial workloads, it will provide value-added spatial processing and allow us to support customers with large vector and raster data sets on Hadoop systems.” - Steve Pierce, CEO, Think Huddle
Your Spatial & Graph specialist contact in EMEA is Hans Viehmann (firstname.lastname@example.org).
You can attend a live web-conference on Spatial & Graph on Tuesday, July 21st at 6:00 PM UK / 7:00 PM CET
- Learn more about Oracle Big Data Spatial and Graph at the OTN product website
- Oracle.com Spatial & Graph page
- Read the Data Sheet
- Read the Spatial Feature Overview
- Blog: https://blogs.oracle.com/bigdataspatialgraph/