Title: GeaBase: a high-performance distributed graph database for industry-scale applications

Authors: Zhisong Fu; Zhengwei Wu; Houyi Li; Yize Li; Min Wu; Xiaojie Chen; Xiaomeng Ye; Benquan Yu; Xi Hu

Addresses: Ant Financial, Inc., Huang Long Wan Ke Center Building I, Hangzhou, Zhejiang, China ' Ant Financial, Inc., Huang Long Wan Ke Center Building I, Hangzhou, Zhejiang, China ' Ant Financial, Inc., Huang Long Wan Ke Center Building I, Hangzhou, Zhejiang, China ' Ant Financial, Inc., Huang Long Wan Ke Center Building I, Hangzhou, Zhejiang, China ' Ant Financial, Inc., Huang Long Wan Ke Center Building I, Hangzhou, Zhejiang, China ' Ant Financial, Inc., Huang Long Wan Ke Center Building I, Hangzhou, Zhejiang, China ' Ant Financial, Inc., Huang Long Wan Ke Center Building I, Hangzhou, Zhejiang, China ' Ant Financial, Inc., Huang Long Wan Ke Center Building I, Hangzhou, Zhejiang, China ' Ant Financial, Inc., Huang Long Wan Ke Center Building I, Hangzhou, Zhejiang, China

Abstract: Graph analytics have been gaining traction rapidly in the past few years. It has a wide array of application areas in the industry, ranging from e-commerce, social networks and recommendation systems to fraud detection and virtually any problem that requires insights into data connections, not just data itself. In this paper, we present GeaBase, a new distributed graph database that provides the capability to store and analyse graph-structured data in real-time at massive scale. We describe the details of the system and the implementation, including novel update architecture, called update centre (UC), and a new language that is suitable for both graph traversal and analytics. We also compare the performance of GeaBase to a widely used open-source graph database Titan. Experiments show that GeaBase is up to 182x faster than Titan in our testing scenarios. We also achieve 22x higher throughput on social network workloads in the comparison.

Keywords: distributed; graph database; high-performance; graph query language.

DOI: 10.1504/IJHPCN.2019.103537

International Journal of High Performance Computing and Networking, 2019 Vol.15 No.1/2, pp.12 - 21

Received: 16 Feb 2018
Accepted: 25 Jun 2018

Published online: 08 Nov 2019 *

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