Oracle has aimed a helping hand at Big Data architectures such as Hadoop and NoSQL with analytics tools designed for tackling social network data.
The Big Data Spatial and Graph is made up of two main components; a distributed property graph with more than 35 parallel, in-memory analytic functions, and a collection of spatial-analysis functions.
These functions are designed to evaluate data based on how near or far something is or to process and visualise geospatial data and imagery.
Additionally, users will be able to generate recommendations based on interests, profiles and past behaviours from social media data.
The company is now aiming at applying these tools to work with social network data and on Big Data architectures.
Steve Pierce, CEO, Think Huddle, said: "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."
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