research-article

Cypher: An Evolving Query Language for Property Graphs

Authors:

Nadime Francis,

Alastair Green,

Paolo Guagliardo,

Tobias Lindaaker,

Victor Marsault,

Stefan Plantikow,

Andrés TaylorAuthors Info & Claims

SIGMOD '18: Proceedings of the 2018 International Conference on Management of Data

Pages 1433 - 1445

https://doi.org/10.1145/3183713.3190657

Published: 27 May 2018 Publication History

Abstract

The Cypher property graph query language is an evolving language, originally designed and implemented as part of the Neo4j graph database, and it is currently used by several commercial database products and researchers. We describe Cypher 9, which is the first version of the language governed by the openCypher Implementers Group. We first introduce the language by example, and describe its uses in industry. We then provide a formal semantic definition of the core read-query features of Cypher, including its variant of the property graph data model, and its ASCII Art graph pattern matching mechanism for expressing subgraphs of interest to an application. We compare the features of Cypher to other property graph query languages, and describe extensions, at an advanced stage of development, which will form part of Cypher 10, turning the language into a compositional language which supports graph projections and multiple named graphs.

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Index Terms

Cypher: An Evolving Query Language for Property Graphs
1. Information systems
  1. Data management systems
    1. Database design and models
      1. Graph-based database models
    2. Query languages
      1. Query languages for non-relational engines
2. Software and its engineering
  1. Software notations and tools
    1. Formal language definitions

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cover image ACM Conferences

SIGMOD '18: Proceedings of the 2018 International Conference on Management of Data

May 2018

1874 pages

ISBN:9781450347037

DOI:10.1145/3183713

General Chairs:
Gautam Das
University of Texas at Arlington, USA
,
Christopher Jermaine
Rice University, USA
,
Philip Bernstein
Microsoft Research, USA

Copyright © 2018 ACM.

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Published: 27 May 2018

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June 10 - 15, 2018

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https://doi.org/10.3390/ijgi13020036
Austern GBloch TAbulafia Y(2024)Incorporating Context into BIM-Derived Data—Leveraging Graph Neural Networks for Building Element ClassificationBuildings10.3390/buildings1402052714:2(527)Online publication date: 16-Feb-2024
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Wang RYang DHsieh MChen YLin W(2024)GenAI-Assisted Database Deployment for Heterogeneous Indigenous–Native Ethnographic Research DataApplied Sciences10.3390/app1416741414:16(7414)Online publication date: 22-Aug-2024
https://doi.org/10.3390/app14167414
Gu ZCorcoglioniti FLanti DMosca AXiao GXiong JCalvanese D(2024)A systematic overview of data federation systemsSemantic Web10.3233/SW-22320115:1(107-165)Online publication date: 12-Jan-2024
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