Upgrading relational legacy data to the semantic web
Proceedings of the 15th international conference on World Wide Web
Survey of graph database models
ACM Computing Surveys (CSUR)
Model-independent schema translation
The VLDB Journal — The International Journal on Very Large Data Bases
Discovering simple mappings between relational database schemas and ontologies
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Learning highly structured semantic repositories from relational databases: the RDBToOnto tool
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
A framework for evaluating database keyword search strategies
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Keyword search over relational databases: a metadata approach
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
A comparison of RDB-to-RDF mapping languages
Proceedings of the 7th International Conference on Semantic Systems
On directly mapping relational databases to RDF and OWL
Proceedings of the 21st international conference on World Wide Web
Query languages for graph databases
ACM SIGMOD Record
Performance of graph query languages: comparison of cypher, gremlin and native access in Neo4j
Proceedings of the Joint EDBT/ICDT 2013 Workshops
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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.