SQUID: A scalable system for querying, updating and indexing dynamic graph databases

Akshay Kansal, Francesca Spezzano

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Graph databases such as chemical databases, protein databases, and RNA motif databases, are simply a collection of graphs. Querying a graph database involves the computation of a subgraph isomorphism problem (which is NP-complete) for each graph in the database. Therefore, an index is required to filter out false positives and reduce the number of subgraph isomorphisms to compute. In this demo, we introduce SQUID, a scalable system for querying, updating and indexing dynamic graph databases, i.e., databases changing over time, and showcase it on chemical databases. The tool uses a graph coarsening-based index that is able to answer both subgraph and supergraph queries. It also allows the database to be changed with an automatic index update. Also, it displays information found in the graph database in a concise manner that is easier to understand.

Original languageEnglish
Title of host publicationProceedings of the 31st International Conference on Scientific and Statistical Database Management, SSDBM 2019
EditorsTanu Malik, Carlos Maltzahn, Ivo Jimenez
Pages218-221
Number of pages4
ISBN (Electronic)9781450362160
DOIs
StatePublished - 23 Jul 2019
Event31st International Conference on Scientific and Statistical Database Management, SSDBM 2019 - Santa Cruz, United States
Duration: 23 Jul 201925 Jul 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference31st International Conference on Scientific and Statistical Database Management, SSDBM 2019
Country/TerritoryUnited States
CitySanta Cruz
Period23/07/1925/07/19

Keywords

  • Dynamic graph databases
  • Graph queries
  • Graph-coarsening
  • Indexing

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