GRFusion: Graphs as First-Class Citizens in Main-Memory Relational Database Systems

The maturity of RDBMSs has motivated academia and industry to invest efforts in leveraging RDBMSs for graph processing, where efficiency is proven for vital graph queries. However, none of these efforts process graphs natively inside the RDBMS, which is particularly challenging due to the impedance mismatch between the relational and the graph models. In this demonstration, we present GRFusion, an in-memory relational database system, where graphs are managed as first-class citizens. GRFusion is realized inside VoltDB. The SQL and query engines of VoltDB are empowered to declaratively define graphs and execute cross-data-model query plans that consist of relational operators and newly-introduced graph operators. Using a social network and a real continental-sized road network covering the entire U.S., we demonstrate the functionality and the performance of GRFusion in evaluating queries that reference both relational tables and graphs seamlessly in the same query execution pipeline. GRFusion shows up to four orders-of-magnitude speed-up in query-time w.r.t. state-of-the-art approaches.