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Workshops of the EDBT/ICDT 2025 Joint Conference, EDBT/ICDT-WS 2025

作者： Skvortsov, Evgeny Xia, Yilin Ludäscher, Bertram Bowers, Shawn Google LLC WA United States University of Illinois Urbana-Champaign School of Information Sciences IL United States Gonzaga University Department of Computer Science SpokaneWA United States

graph transformations are a powerful computational model for manipulating complex networks, but handling temporal aspects and scalability remain significant challenges. We present a novel approach to implementing these transformations using Logica, an open-source logic programming language and system that operates on parallel databases like DuckDB and BigQuery. Leveraging the parallelism of these engines, our method enhances performance and accessibility, while also offering a practical way to handle time-varying graphs. We illustrate Logica's graph querying and transformation capabilities with several examples, including the computation of the well-founded solution to the classic "Win-Move" game, a declarative program for pathfinding in a dynamic graph, and the application of Logica to the collection of all current facts of Wikidata for taxonomic relations analysis. We argue that clear declarative syntax, built-in visualization and powerful supported engines make Logica a convenient tool for graph transformations. Copyright © 2025 for this paper by its authors.

关键词： graph databases

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Schema-Based Query Optimisation for graph databases

Proceedings of the ACM on Management of Data

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Proceedings of the ACM on Management of Data 2025年第1期3卷 1-29页

作者： Chandan Sharma Pierre Genevès Nils Gesbert Nabil Layaïda Tyrex team Univ. Grenoble Alpes CNRS Inria Grenoble INP LIG Grenoble France

Recursive graph queries are increasingly popular for extracting information from interconnected data found in various domains such as social networks, life sciences, and business analytics. graph data often come with schema information that describe how nodes and edges are organized. We propose a type inference mechanism that enriches recursive graph queries with relevant structural information contained in a graph schema. We show that this schema information can be useful in order to improve the performance when evaluating recursive graph queries. Furthermore, we prove that the proposed method is sound and complete, ensuring that the semantics of the query is preserved during the schema-enrichment process.

关键词： graph databases graph schema query optimisation relational algebra

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Top Ten Challenges Towards Agentic Neural graph databases

arXiv

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arXiv 2025年

作者： Bai, Jiaxin Wang, Zihao Zhou, Yukun Yin, Hang Fei, Weizhi Hu, Qi Deng, Zheye Cheng, Jiayang Zheng, Tianshi Tsang, Hong Ting Gao, Yisen Xie, Zhongwei Li, Yufei Fan, Lixin Yuan, Binhang Wang, Wei Chen, Lei Zhou, Xiaofang Song, Yangqiu Department of Computer Science and Engineering HKUST Hong Kong Department of Mathematical Sciences Tsinghua University Beijing China AI Group WeBank Institute of Artificial Intelligence Beihang University China Wuhan University China Sichuan University China

graph databases (GDBs) like Neo4j and Tigergraph excel at handling interconnected data but lack advanced inference capabilities. Neural graph databases (NGDBs) address this by integrating graph Neural Networks (GNNs) for predictive analysis and reasoning over incomplete or noisy data. However, NGDBs rely on predefined queries and lack autonomy and adaptability. This paper introduces Agentic Neural graph databases (Agentic NGDBs), which extend NGDBs with three core functionalities: autonomous query construction, neural query execution, and continuous learning. We identify ten key challenges in realizing Agentic NGDBs: semantic unit representation, abductive reasoning, scalable query execution, and integration with foundation models like large language models (LLMs). By addressing these challenges, Agentic NGDBs can enable intelligent, self-improving systems for modern data-driven applications, paving the way for adaptable and autonomous data management solutions. © 2025, CC BY.

关键词： graph databases

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Logica-TGD: Transforming graph databases Logically

arXiv

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arXiv 2025年

graph transformations are a powerful computational model for manipulating complex networks, but handling temporal aspects and scalability remain significant challenges. We present a novel approach to implementing these transformations using Logica, an open-source logic programming language and system that operates on parallel databases like DuckDB and BigQuery. Leveraging the parallelism of these engines, our method enhances performance and accessibility, while also offering a practical way to handle time-varying graphs. We illustrate Logica’s graph querying and transformation capabilities with several examples, including the computation of the well-founded solution to the classic "Win-Move" game, a declarative program for pathfinding in a dynamic graph, and the application of Logica to the collection of all current facts of Wikidata for taxonomic relations analysis. We argue that clear declarative syntax, built-in visualization and powerful supported engines make Logica a convenient tool for graph transformations. © 2025, CC BY.

关键词： graph databases

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graph databases: The key to foolproof fraud detection?

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Computer Fraud and Security 2016年第3期2016卷 5-8页

作者： Eifrem, Emil Neo Technology United States

Technology has made life more convenient - but it has also made life more insecure. This is especially true in the context of our growing use of cyberspace as the place we choose to shop, entertain ourselves, manage o... 详细信息

关键词： graph databases

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graph databases: Neo4j Analysis 19

Graph Databases: Neo4j Analysis

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19th International Conference on Enterprise Information Systems (ICEIS)

作者： Guia, Jose Soares, Valeria Goncalves Bernardino, Jorge Polytech Coimbra ISEC Rua Pedro Nunes Coimbra Portugal Univ Fed Paraiba Informat Ctr Joao Pessoa Paraiba Brazil Univ Coimbra CISUC Ctr Informat & Syst Coimbra Portugal

ISBN: (纸本)9789897582479

The volume of data is growing at an increasing rate. This growth is both in size and in connectivity, where connectivity refers to the increasing presence of relationships between data. Social networks such as Facebook and Twitter store and process petabytes of data each day. graph databases have gained renewed interest in the last years, due to their applications in areas such as the Semantic Web and Social Network Analysis. graph databases provide an effective and efficient solution to data storage and querying data in these scenarios, where data is rich in relationships. In this paper, it is analyzed the fundamental points of graph databases, showing their main characteristics and advantages. We study Neo4j, the top graph database software in the market and evaluate its performance using the Social Network Benchmark (SNB).

关键词： graph databases NoSQL databases Neo4j

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The Ring: Worst-case Optimal Joins in graph databases using (Almost) No Extra Space

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ACM TRANSACTIONS ON DATABASE SYSTEMS 2024年第2期49卷 1-45页

作者： Arroyuelo, Diego Gomez-Brandon, Adrian Hogan, Aidan Navarro, Gonzalo Reutter, Juan Rojas-Ledesma, Javiel Soto, Adrian Pontificia Univ Catolica DCC Escuela Ingn Vicuna Mackenna 4860 Santiago 7821093 Chile Pontificia Univ Catolica IMFD Vicuna Mackenna 4860 Santiago 7821093 Chile Univ A Coruna Campus Elvina La Coruna 15071 Spain CITIC Campus Elvina La Coruna 15071 Spain IMFD Campus Elvina La Coruna 15071 Spain Univ Chile Beauchef 851Edificio NorteTercer Piso Santiago 8370456 Chile IMFD Beauchef 851Edificio NorteTercer Piso Santiago 8370456 Chile Pontificia Univ Catolica Inst Ingn Matemat & Computac Vicuna Mackenna 4860 Santiago 7821093 Chile Univ Adolfo Ibanez Diagonal Torres 2640 Santiago 7941169 Chile IMFD Diagonal Torres 2640 Santiago 7941169 Chile

We present an indexing scheme for triple-based graphs that supports join queries in worst-case optimal (wco) time within compact space. This scheme, called a ring, regards each triple as a cyclic string of length 3. Each rotation of the triples is lexicographically sorted and the values of the last attribute are stored as a column, so we obtain the order of the next column by stably re-sorting the triples by its attribute. We show that, by representing the columns with a compact data structure called a wavelet tree, this ordering enables forward and backward navigation between columns without needing pointers. These wavelet trees further support wco join algorithms and cardinality estimations for query planning. While traditional data structures such as B-Trees, tries, and so on, require 6 index orders to support all possible wco joins over triples, we can use one ring to index them all. This ring replaces the graph and uses only sublinear extra space, thus supporting wco joins in almost no space beyond storing the graph itself. Experiments querying a large graph (Wikidata) in memory show that the ring offers nearly the best overall query times while using only a small fraction of the space required by several state-of-the-art approaches. We then turn our attention to some theoretical results for indexing tables of arity d higher than 3 in such a way that supports wco joins. While a single ring of length d no longer suffices to cover all d! orders, we need much fewer rings to index them all: O(2(d)) rings with a small constant. For example, we need 5 rings instead of 120 orders for d = 5. We show that our rings become a particular case of what we dub order graphs, whose nodes are attribute orders and where stably sorting by some attribute leads us from an order to another, thereby inducing an edge labeled by the attribute. The index is then the set of columns associated with the edges, and a set of rings is just one possible graph shape. We show that other shapes, l

关键词： Worst-case optimal joins graph patterns graph databases graph indexing column stores wavelet trees

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Expression and efficient evaluation of fuzzy quantified structural queries to fuzzy graph databases

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FUZZY SETS AND SYSTEMS 2019年 366卷 3-17页

作者： Pivert, Olivier Slama, Olfa Thion, Virginie Univ Rennes 1 IRISA Lannion France

This paper deals with fuzzy quantified queries in a graph database context. We study a particular type of structural quantified query and show how it can be expressed in an extension of the Neo4j Cypher query language. A processing strategy based on a compilation mechanism that derives regular (nonfuzzy) queries for accessing the relevant data is also described. Then, some experiments are performed that show the tractability of this approach. (C) 2018 Elsevier B.V. All rights reserved.

关键词： graph databases Fuzzy quantified queries

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graph databases Assessment: Janusgraph, Neo4j, and Tigergraph

Graph Databases Assessment: JanusGraph, Neo4j, and TigerGrap...

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International Conference on Information Technology and Education (ICITED)

作者： Monteiro, Jessica Sa, Filipe Bernardino, Jorge Polytech Coimbra ISEC Rua Pedro Nunes P-3030199 Coimbra Portugal

ISBN: (纸本)9789811965876;9789811965852;9789811965845

Over time, data growth across technology platforms has become a challenge for relational databases. Therefore, it becomes difficult to store and process massive volumes of data and data where the schema is represented by graphs, such as social networking sites. graph databases emerged as the solution, wherein entities from the domain of interest are represented by nodes and relationships between them by edges. The main objective of this paper is to find out which of the top three open source graph databases are the most complete and efficient. According to DB-Engines Ranking, the top three graph databases are: Janusgraph, Neo4j, and Tigergraph. We apply the OSSpal methodology, which consists of an evaluation based on qualitative and quantitative measures to these databases. The evaluation categories of the OSSpal methodology are focused on software functionalities, attributes and features, available documentation, support and service, user community, and graph database development.

关键词： graph databases NoSQL databases OSSpal methodology Open source tools Janusgraph Neo4j Tigergraph

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In-Memory graph databases for Web-Scale Data

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COMPUTER 2015年第3期48卷 24-35页

作者： Castellana, Vito Giovanni Morari, Alessandro Weaver, Jesse Tumeo, Antonino Haglin, David Villa, Oreste Feo, John Pacific NW Natl Lab High Performance Comp Grp Richland WA 99352 USA Pacific NW Natl Lab Data Sci Grp Richland WA 99352 USA Pacific NW Natl Lab Data Intens Sci Comp Grp Richland WA 99352 USA

A software stack relies primarily on graph-based methods to implement scalable resource description framework databases on top of commodity clusters, providing an inexpensive way to extract meaning from volumes of het... 详细信息

关键词： Internet database management systems graph theory pattern clustering Web-scale data commodity clusters graph-based methods heterogeneous data inmemory graph databases scalable resource description framework databases software stack Algorithm design and analysis Clustering algorithms Data structures Pattern matching Resource description framework Resource management Software development RDF databases SPARQL big data graph databases high-performance computing multithreading

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