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Oracle Analytics, Enterprise Performance Management (EPM) and Big Data Updates for Oracle Partners in Europe,...

Big Data Spatial and Graph Analytics for Hadoop

Mike Hallett
Partner Development for Business Analytics

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:

  1. 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
  2. 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 (
hans.viehmann@oracle.com).

You can attend a live web-conference on Spatial &
Graph on Tuesday,
July 21st at 6:00 PM UK / 7:00 PM CET

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