demonstration

Two for one: querying property graph databases using SPARQL via gremlinator

Authors:

Dharmen Punjani,

Sören AuerAuthors Info & Claims

GRADES-NDA '18: Proceedings of the 1st ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)

Article No.: 12, Pages 1 - 5

https://doi.org/10.1145/3210259.3210271

Published: 10 June 2018 Publication History

Abstract

In the past decade Knowledge graphs have become very popular and frequently rely on the Resource Description Framework (RDF) or Property Graphs (PG) as their data models. However, the query languages for these two data models - SPARQL for RDF and the PG traversal language Gremlin - are lacking basic interoperability. In this demonstration paper, we present Gremlinator, the first translator from SPARQL - the W3C standardized language for RDF - to Gremlin - a popular property graph traversal language. Gremlinator translates SPARQL queries to Gremlin path traversals for executing graph pattern matching queries over graph databases. This allows a user, who is well versed in SPARQL, to access and query a wide variety of Graph databases avoiding the steep learning curve for adapting to a new Graph Query Language (GQL). Gremlin is a graph computing system-agnostic traversal language (covering both OLTP graph databases and OLAP graph processors), making it a desirable choice for supporting interoperability for querying Graph databases. Gremlinator is planned to be released as an Apache TinkerPop plugin in the upcoming releases.

References

[1]

Renzo Angles, Marcelo Arenas, Pablo Barceló, et al. 2016. Foundations of Modern Graph Query Languages. CoRR abs/1610.06264 (2016).

[2]

Christian Bizer and Andreas Schultz. 2009. The berlin sparql benchmark. (2009).

[3]

Diego Calvanese, Benjamin Cogrel, et al. 2017. Ontop: Answering SPARQL queries over relational databases. Semantic Web 8, 3 (2017), 471--487.

Digital Library

[4]

Artem Chebotko, Shiyong Lu, and Farshad Fotouhi. 2009. Semantics preserving SPARQL-to-SQL translation. Data & Knowledge Engineering 68, 10 (2009), 973--1000.

Digital Library

[5]

Souripriya Das, Jagannathan Srinivasan, Matthew Perry, et al. 2014. A Tale of Two Graphs: Property Graphs as RDF in Oracle. In EDBT. 762--773.

[6]

Brendan Elliott, En Cheng, Chimezie Thomas-Ogbuji, et al. 2009. A complete translation from SPARQL into efficient SQL. In Proceedings of the 2009 International Database Engineering & Applications Symposium. ACM, 31--42.

Digital Library

[7]

Jorge Pérez, Marcelo Arenas, and Claudio Gutierrez. 2006. Semantics and Complexity of SPARQL. In International semantic web conference. Springer, 30--43.

Digital Library

[8]

Freddy Priyatna, Oscar Corcho, and Juan Sequeda. 2014. Formalisation and experiences of R2RML-based SPARQL to SQL query translation using Morph. In Proceedings of the 23rd international conference on World wide web. ACM, 479--490.

Digital Library

[9]

Jyothsna Rachapalli, Vaibhav Khadilkar, Murat Kantarcioglu, et al. 2011. RETRO: A Framework for Semantics Preserving SQL-to-SPARQL Translation. The University of Texas at Dallas 800 (2011), 75080--3021.

[10]

Marko A. Rodriguez. 2015. The Gremlin graph traversal machine and language (invited talk). In Proceedings of the 15th Symposium on Database Programming Languages, Pittsburgh, PA, USA, October 25-30, 2015. 1--10.

Digital Library

[11]

Mariano Rodriguez-Muro and Martin Rezk. 2015. Efficient SPARQL-to-SQL with R2RML mappings. Web Semantics: Science, Services and Agents on the World Wide Web 33 (2015), 141--169.

[12]

Michael Schmidt, Michael Meier, and Georg Lausen. 2010. Foundations of SPARQL query optimization. In Proceedings of the 13th International Conference on Database Theory. ACM, 4--33.

Digital Library

[13]

Harsh Thakkar. 2017. Towards an Open Extensible Framework for Empirical Benchmarking of Data Management Solutions: LITMUS. In The Semantic Web - 14th International Conference, ESWC 2017, Portorož, Slovenia, May 28 - June 1, 2017, Proceedings, Part II. 256--266.

[14]

Harsh Thakkar, Yashwant Keswani, Mohnish Dubey, Jens Lehmann, and Sören Auer. 2017. Trying Not to Die Benchmarking: Orchestrating RDF and Graph Data Management Solution Benchmarks Using LITMUS. In Proceedings of the 13th International Conference on Semantic Systems, SEMANTICS 2017, Amsterdam, The Netherlands, September 11-14, 2017. 120--127.

Digital Library

[15]

Harsh Thakkar, Dharmen Punjani, Yashwant Keswani, et al. 2018. A Stitch in Time Saves Nine - SPARQL querying of Property Graphs using Gremlin Traversals. CoRR abs/1801.02911 (2018).

[16]

Harsh Thakkar, Dharmen Punjani, Maria-Esther Vidal, et al. 2017. Towards an Integrated Graph Algebra for Graph Pattern Matching with Gremlin. In Proceedings of the 28th International Conference, DEXA 2017, Lyon, France, August 28-31, 2017, Proceedings, Part I. Springer, 81--91.

[17]

F Zemke. 2006. Converting sparql to sql. Technical Report. Technical Report, October 2006.

Cited By

Bruyat JChampin PMédini LLaforest F(2024)PRSC: From PG to RDF and back, using schemasSemantic Web10.3233/SW-243675(1-41)Online publication date: 15-Oct-2024
https://doi.org/10.3233/SW-243675
Wang JWang S(2023)Research on Improved General Property Graphs Query Method Based on TinkerPop2023 12th International Conference of Information and Communication Technology (ICTech)10.1109/ICTech58362.2023.00019(40-45)Online publication date: Apr-2023
https://doi.org/10.1109/ICTech58362.2023.00019
Jamshidi KMariappan MVora KKalavri VSalihoğlu S(2022)Anti-vertex for neighborhood constraints in subgraph queriesProceedings of the 5th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)10.1145/3534540.3534690(1-9)Online publication date: 12-Jun-2022
https://dl.acm.org/doi/10.1145/3534540.3534690
Show More Cited By

Two for one: querying property graph databases using SPARQL via gremlinator
1. Information systems
  1. Data management systems

Recommendations

S2CTrans: Building a Bridge from SPARQL to Cypher
Database and Expert Systems Applications
Abstract
In graph data applications, data is primarily maintained using two models: RDF (Resource Description Framework) and property graph. The property graph model is widely adopted by industry, leading to property graph databases generally outperforming ...
Querying Heterogeneous Property Graph Data Sources based on a Unified Conceptual View
ICSIE '20: Proceedings of the 9th International Conference on Software and Information Engineering

With the great success of NoSQL (Not only SQL) databases, data becomes more heterogeneous than ever. Hence, it is essential to provide solutions to integrate such heterogeneous databases and facilitate accessing them. This paper proposes an Ontology ...
Empirical study on the usage of graph query languages in open source Java projects
SLE 2019: Proceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering

Graph data models are interesting in various domains, in part because of the intuitiveness and flexibility they offer compared to relational models. Specialized query languages, such as Cypher for property graphs or SPARQL for RDF, facilitate their use. ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

GRADES-NDA '18: Proceedings of the 1st ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)

June 2018

94 pages

ISBN:9781450356954

DOI:10.1145/3210259

Editors:
Akhil Arora
American Express Big Data Labs
,
Arnab Bhattacharya
Indian Institute of Technology, Kanpur, India
,
George Fletcher
Eindhoven University of Technology
,
Josep Lluis Larriba Pey
UPC
,
Shourya Roy
American Express Big Data Labs
,
Robert West
EPFL

Copyright © 2018 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

SIGMOD: ACM Special Interest Group on Management of Data

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 June 2018

Check for updates

Author Tags

Qualifiers

Demonstration

Funding Sources

WDAqua ITN

Conference

SIGMOD/PODS '18

Sponsor:

SIGMOD

SIGMOD/PODS '18: International Conference on Management of Data

June 10, 2018

Texas, Houston

Acceptance Rates

GRADES-NDA '18 Paper Acceptance Rate 10 of 26 submissions, 38%;

Overall Acceptance Rate 29 of 61 submissions, 48%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
327
Total Downloads

Downloads (Last 12 months)11
Downloads (Last 6 weeks)1

Reflects downloads up to 11 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Bruyat JChampin PMédini LLaforest F(2024)PRSC: From PG to RDF and back, using schemasSemantic Web10.3233/SW-243675(1-41)Online publication date: 15-Oct-2024
https://doi.org/10.3233/SW-243675
Wang JWang S(2023)Research on Improved General Property Graphs Query Method Based on TinkerPop2023 12th International Conference of Information and Communication Technology (ICTech)10.1109/ICTech58362.2023.00019(40-45)Online publication date: Apr-2023
https://doi.org/10.1109/ICTech58362.2023.00019
Jamshidi KMariappan MVora KKalavri VSalihoğlu S(2022)Anti-vertex for neighborhood constraints in subgraph queriesProceedings of the 5th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)10.1145/3534540.3534690(1-9)Online publication date: 12-Jun-2022
https://dl.acm.org/doi/10.1145/3534540.3534690
Alotaibi RLei CQuamar AEfthymiou VOzcan F(2021)Property Graph Schema Optimization for Domain-Specific Knowledge Graphs2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00085(924-935)Online publication date: Apr-2021
https://doi.org/10.1109/ICDE51399.2021.00085
Thakkar HAngles RRodriguez MMallette SLehmann J(2020)Let's build Bridges, not Walls: SPARQL Querying of TinkerPop Graph Databases with Sparql-Gremlin2020 IEEE 14th International Conference on Semantic Computing (ICSC)10.1109/ICSC.2020.00080(408-415)Online publication date: Feb-2020
https://doi.org/10.1109/ICSC.2020.00080
Tomaszuk DAngles RThakkar H(2020)PGO: Describing Property Graphs in RDFIEEE Access10.1109/ACCESS.2020.30020188(118355-118369)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3002018
Angles RThakkar HTomaszuk D(2020)Mapping RDF Databases to Property Graph DatabasesIEEE Access10.1109/ACCESS.2020.29931178(86091-86110)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2993117

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents