abstract

Incremental View Maintenance for Property Graph Queries

Author:

Gábor SzárnyasAuthors Info & Claims

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

Pages 1843 - 1845

https://doi.org/10.1145/3183713.3183724

Published: 27 May 2018 Publication History

Abstract

Graph processing challenges are common in modern database systems, with the property graph data model gaining widespread adoption. Due to the novelty of the field, graph databases and frameworks typically provide their own query language, such as Cypher for Neo4j, Gremlin for TinkerPop and GraphScript for SAP HANA. These languages often lack a formal background for their data model and semantics. To address this, the openCypher initiative aims to standardise a subset of the Cypher language, for which it currently provides grammar specification and a set of acceptance tests to allow vendors to implement their openCypher compatible engine.

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Cited By

Bergami GFox OMorgan G(2024)Matching and Rewriting Rules in Object-Oriented DatabasesMathematics10.3390/math1217267712:17(2677)Online publication date: 28-Aug-2024
https://doi.org/10.3390/math12172677
Srivastava SSingh A(2022)Fraud detection in the distributed graph databaseCluster Computing10.1007/s10586-022-03540-326:1(515-537)Online publication date: 24-Jan-2022
https://doi.org/10.1007/s10586-022-03540-3
Bergami G(2021)On Efficiently Equi-Joining GraphsProceedings of the 25th International Database Engineering & Applications Symposium10.1145/3472163.3472269(222-231)Online publication date: 14-Jul-2021
https://dl.acm.org/doi/10.1145/3472163.3472269

Index Terms

Incremental View Maintenance for Property Graph Queries
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
        Query operators
    2. Query languages
      1. Query languages for non-relational engines
2. Mathematics of computing
  1. Discrete mathematics
    1. Graph theory
      1. Graph algorithms
      2. Graph enumeration

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Published In

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 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.

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SIGMOD: ACM Special Interest Group on Management of Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 May 2018

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Hungarian Academy of Sciences

Conference

SIGMOD/PODS '18

Sponsor:

SIGMOD

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

June 10 - 15, 2018

TX, Houston, USA

Acceptance Rates

SIGMOD '18 Paper Acceptance Rate 90 of 461 submissions, 20%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

Bergami GFox OMorgan G(2024)Matching and Rewriting Rules in Object-Oriented DatabasesMathematics10.3390/math1217267712:17(2677)Online publication date: 28-Aug-2024
https://doi.org/10.3390/math12172677
Srivastava SSingh A(2022)Fraud detection in the distributed graph databaseCluster Computing10.1007/s10586-022-03540-326:1(515-537)Online publication date: 24-Jan-2022
https://doi.org/10.1007/s10586-022-03540-3
Bergami G(2021)On Efficiently Equi-Joining GraphsProceedings of the 25th International Database Engineering & Applications Symposium10.1145/3472163.3472269(222-231)Online publication date: 14-Jul-2021
https://dl.acm.org/doi/10.1145/3472163.3472269
Anzum NSalihoglu SKalavri VYakovets N(2021)R2GSync and edge viewsProceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)10.1145/3461837.3464515(1-9)Online publication date: 20-Jun-2021
https://dl.acm.org/doi/10.1145/3461837.3464515

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