SBIR Phase I: GraphSQL: Powering Relational DBMS with Fast and Easy-to-Use Graph Analytics

This Small Business Innovation Research (SBIR) Phase I project will develop novel technologies and a software system which adds fast, and easy-to-use graph analytics to the relational database system (RDBMS). Querying and analyzing massive graph data (graph analytics) not only can enrich and enhance business, social and government intelligence, but also can help significantly advance scientific and technology discovery. However, most of the existing graph data (business, financial, governmental, and social networking data) are stored in the traditional RDBMS that provides little fundamental support for graph analytics. This is because graph analytics requires extensive recursive and traversal operations, which are hard to represent and prohibitively expensive to execute in RDBMS. To address this fundamental challenge, this project will develop a powerful graph engine and transparently connect RDBMS with the graph engine. The anticipated results of the project include novel techniques for building a graph processing engine and connectors between RDBMS and the graph engine, and a beta-version software system, which will be tested and employed by two or three early adopters/customers. The broader impact/commercial potential of this project will be to help deliver better insights into the complex nature of relationships between people, their decisions and their interactions with others in all areas of businesses and intelligence, such as online social networking, marketing and advertisement, banking and finance, logistics and transportation, telecommunications, healthcare and hospitals, homeland security, bio-engineering and drug discovery, etc. The technologies and software developed in this project can also directly contribute to the five major analytics segments (end-user query and reporting analysis, data warehouse management, financial performance and strategy management applications, custom relationship analytics applications, and data warehouse generation), each with the global revenue of more than one billion dollars.