Publications Library
Explore our collection of books, papers, and other resources to deepen your understanding of graphs.
Books
Getting Started with the Graph Query Language (GQL)
Ricky Sun, Jason Zhang, Yuri Simione
Packt · August 22, 2025
Learn how to build and query graph databases with this first comprehensive guide to ISO-standard GQL, featuring 50+ hands-on examples and a real-world case study that will change the way you work with connected data.
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The Essential Criteria of Graph Databases
Ricky Sun
Elsevier · January 18, 2024
This book expands the horizons of graph applications by highlighting innovative use cases in real-time decision-making and risk management. It shows how high-performance graph databases enable more effective artificial intelligence by addressing black-box behavior, inefficiency, and data silos.
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Breaking the Latency Barrier: Real-Time Incremental Community Detection with Live Graph Data on a Unified Graph Database Framework
Victor Wang, Ricky Sun, Jason Zhang
Springer · December 23, 2025
This paper introduces a novel real-time and incremental Louvain algorithm, integrated into a unified graph database framework that leverages Storage-Compute Clustering and High-Density Computing technologies.
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A Graph Analytics Supercharge Case Study of GPU Versus CPU on Performance, Greenness, and Cost
Ricky Sun, Victor Wang, Jason Zhang
Springer · June 21, 2025
This paper presents a unique case study that examines the efficacy of GPUs versus CPUs in the context of graph analytics. We evaluate performance metrics, energy consumption, and cost implications of GPU and CPU deployments, using data from a real-world application.
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A Unified Graph Framework for Storage-Compute Coupled Cluster and High-Density Computing Cluster
Lynsey Lin, Jamie Chen, Ricky Sun, Jason Zhang, Victor Wang
ACM · June 2024
This paper presents a novel unified framework that integrates distributed computing and high-density graph computing. Our approach leverages a hybrid architecture that combines the strengths of both paradigms, enabling efficient graph traversal and computation while ensuring scalability and flexibility.
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Graph XAI: Graph-augmented AI with ADEV
Ricky Sun, Yuri Simione, Jason Zhang, Victor Wang
CEUR Workshop Proceedings · 2023
Today's big data and AI frameworks face problems like questionable accuracy, shallow data processing depth, black-box in-explainability, and oftentimes low processing speed. This paper summarizes the work of Ultipa, introducing Graph XAI (Graph-augmented AI) and highlighting ADEV (Accuracy, Depth, Explainability, and Velocity).
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Design of Highly Scalable Graph Database Systems without Exponential Performance Degradation
Ricky Sun, Jamie Chen
ACM BiDEDE · June 2023
This paper presents three architectural approaches (HTAP, GRID, SHARD) for building scalable graph databases without performance degradation.
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The Linked Data Benchmark Council (LDBC): Driving Competition and Collaboration in the Graph Data Management Space
Jason Zhang, Bin Yang, Xinsheng Li, et al.
TPCTC · 2023
Standard benchmarks for graph data management, driving competition and collaboration in the industry.
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