Paper Info
Title
SQUID: A Scalable System for Querying, Updating and Indexing Dynamic Graph Databases
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.
Year
DOI
Venue
2019
10.1145/3335783.3335799
Proceedings of the 31st International Conference on Scientific and Statistical Database Management
Keywords
Field
DocType
Dynamic graph databases, graph queries, graph-coarsening, indexing
Data mining,Graph database,Computer science,Search engine indexing,Theoretical computer science,Isomorphism,Epigraph,Chemical database,Subgraph isomorphism problem,False positive paradox,Computation
Conference
ISSN
ISBN
Citations 
978-1-4503-6216-0
978-1-4503-6216-0
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Akshay Kansal100.68
Francesca Spezzano28019.08