High-Performance with an In-GPU Graph Database Cache

Shin Morishima, Hiroki Matsutani

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Although graph databases have great potential to directly represent huge and complex network structures, such as social and logistics networks, they currently do not perform well enough. To achieve a two-orders-of-magnitude performance improvement on graph database queries, the authors propose caching the graph database in distributed GPUs connected with a 10-Gbit Ethernet (10GbE) network. Property read, traverse, and graph search queries are accelerated by 25.9, 252.4, and 383.2 times, respectively, compared to those using Neo4j for a huge graph consisting of 3.2 million nodes whose degree is 100.

Original languageEnglish
Article number8123479
Pages (from-to)58-64
Number of pages7
JournalIT Professional
Issue number6
Publication statusPublished - 2017 Nov 1


  • GPU
  • NoSQL
  • graph database

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Science Applications


Dive into the research topics of 'High-Performance with an In-GPU Graph Database Cache'. Together they form a unique fingerprint.

Cite this