Mapping RDF Databases to Property Graph Databases

Renzo Angles,Dominik Tomaszuk,Harsh Thakkar

doi:10.1109/access.2020.2993117

Abstract

RDF triplestores and property graph databases are two approaches for data management which are based on modeling, storing, and querying graph-like data. In spite of such common principles, they present special features that complicate the task of database interoperability. While there exist some methods to transform RDF graphs into property graphs, and vice versa, they lack compatibility and a solid formal foundation. This paper presents three direct mappings (schema-dependent and schema-independent) for transforming an RDF database into a property graph database, including data and schema. We show that two of the proposed mappings satisfy the properties of semantics preservation and information preservation. The existence of both mappings allows us to conclude that the property graph data model subsumes the information capacity of the RDF data model.

Highlights

The database systems based on graph-oriented models are gaining relevance in the industry due to their use in various application domains where complex data analytics is required [4]
Resource Description Framework (RDF) triplestores are based on the RDF data model [24], [41], their standard query language is SPARQL [19], and RDF Schema [11] allows to describe classes of resources and properties
Most graph database systems are based on the Property Graph (PG) data model [2], and a standard query language is in current development [23]

Summary

INTRODUCTION

The database systems based on graph-oriented models are gaining relevance in the industry due to their use in various application domains where complex data analytics is required [4]. RDF triple stores and graph database systems are two approaches for data management that are based on modeling, storing, and querying graph-like data. Most graph database systems are based on the Property Graph (PG) data model [2], and a standard query language is in current development [23]. We study three desirable properties of the above database mappings: computability, semantics preservation, and information preservation. Based on such analysis, we argued that any RDF database can be transformed into a PG database.

PRELIMINARIES

RDF DATABASES VERSUS PG DATABASES

INSTANCE MAPPING IM1 The instance mapping IM1 is defined as follows

GENERIC PROPERTY GRAPH SCHEMA

EXPERIMENTAL EVALUATION

VIII. CONCLUSIONS