Converting relational to graph databases

TLDR

Graph database management systems efficiently store increasingly connected data and scale to large datasets, yet converting a relational persistent layer to a graph store remains a difficult task for administrators. This paper proposes a methodology that exploits the source schema and constraints to convert a relational database into a graph database. The method translates conjunctive SQL queries into graph traversal operations, enabling query execution on the target graph store. Experimental results demonstrate the feasibility of the conversion and the efficient query answering on the graph database.

Abstract

Graph Database Management Systems provide an effective and efficient solution to data storage in current scenarios where data are more and more connected, graph models are widely used, and systems need to scale to large data sets. In this framework, the conversion of the persistent layer of an application from a relational to a graph data store can be convenient but it is usually an hard task for database administrators. In this paper we propose a methodology to convert a relational to a graph database by exploiting the schema and the constraints of the source. The approach supports the translation of conjunctive SQL queries over the source into graph traversal operations over the target. We provide experimental results that show the feasibility of our solution and the efficiency of query answering over the target database.