Scalable, Secure Associative Database

Period of Performance: 10/28/2013 - 08/28/2014

$80K

Phase 1 SBIR

Recipient Firm

Applied Technical Systems, Inc.
3505 NW Anderson Hill Rd Array
Silverdale, WA 98383
Principal Investigator

Abstract

The Associative Model of Data offers a fundamentally different meta-model for data organization than the well-established relational data model. The associative model focuses on Items and Links among items rather than sets of records. We propose to compare and contrast the associative model with two closely related models, the Resource Description Framework (RDF) triple model and the Property Graph model popularized by modern open-source graph databases. By reviewing existing documentation, technical papers and implementations, we seek to identify a feature set appropriate for scaling out to petabyte scales subject to Multi-Level Security constraints. To effectively compare alternative implementations, we propose to establish a benchmark, consisting of both generative data and a collection of representative queries. The primary outcome of our Phase I effort will be an architectural design for a scalable, secure database embracing the associative/graph model of data. This database will be a critical enabling component of a larger data exploitation and analysis framework which will ultimately include natural language processing, information extraction, and large-scale data analysis capabilities.