SQUID: A Scalable System for Querying, Updating and Indexing Dynamic Graph Databases
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.
Kansal, Akshay and Spezzano, Francesca. (2019). "SQUID: A Scalable System for Querying, Updating and Indexing Dynamic Graph Databases". SSDBM '19: Proceedings of the 31st International Conference on Scientific and Statistical Database Management, 218-221. https://dx.doi.org/10.1145/3335783.3335799