• Corpus ID: 64622863

Graph Databases

  title={Graph Databases},
  author={Ian S. Robinson and Jim Webber and Emil Eifr{\'e}m},
Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. Learn how different organizations are using graph… 
Graph Databases: Their Power and Limitations
Recent advances and limitations in graph modelling as well as future directions are discussed, including pattern matching in graphs providing, in principle, an arbitrarily complex identity function.
Exploiting NoSQL Graph Databases and in Memory Architectures for Extracting Graph Structural Data Summaries
This paper provides the definitions of the summaries with the methods to automatically extract them from NoSQL graph databases only and with the help of in-memory architectures and demonstrates the benefit of the proposition by experimental results.
GraphTQL: A visual query system for graph databases
GraphTQL is developed, a visual query system that provides greater expressiveness and ease in the query formulation and a comparison with a graphical query interface for SPARQL showed better results for GraphTQL regarding the number of queries correctly formulated by users, thenumber of errors and the time spent for query formulation.
Combining Two Types of Database System for Managing Property Graph Data
  • Kazuma Kusu, K. Hatano
  • Computer Science
    2018 IEEE International Conference on Big Data (Big Data)
  • 2018
This study analyzes how node and edge properties can be queried more efficiently while maintaining the structure of the graph and proposes an approach, which separately stores nodes/edges information and property information into separate data structures.
A model and query language for temporal graph databases
A temporal graph data model, where nodes and relationships contain attributes (properties) timestamped with a validity interval, is introduced, where graphs in this model can be heterogeneous, that is, relationships may be of different kinds.
GraphChi-DB: Simple Design for a Scalable Graph Database System - on Just a PC
A new data structure, Parallel Adjacency Lists (PAL), for efficiently managing graphs with billions of edges on disk, which can store graphs more compactly while allowing fast access to both the incoming and the outgoing edges of a vertex, without duplicating data.
Foundations of Modern Query Languages for Graph Databases
The importance of formalisation for graph query languages is discussed, with a summary of what is known about SPARQL, Cypher, and Gremlin in terms of expressivity and complexity; and an outline of possible future directions for the area.
System G Distributed Graph Database
A novel distributed graph database called System G designed for efficient graph data storage and processing on modern computing architectures is discussed and the efficiency of System G for storing data and processing graph queries on state-of-the-art platforms is experimentally shown.
Graph Database for Recipe Recommendations
This work presents a recipe recommender as a graph database, Neo4j application, that recommends a variety of recipes with the help of a data set containing thousands of ingredients based on availability of ingredients with a user.
Visualisation of Relational Database Structure by Graph Database
This paper presents the RELATIONS-Graph application, which automatically generates a directed graph which presents links between tables and attributes which constitute a relational database and has been applied to SQL Server 2014 SP1 DBMS using the Microsoft .NET technology and the Neo4j graph database, also by .NET API.


A performance evaluation of open source graph databases
A qualitative study and a performance comparison of 12 open source graph databases using four fundamental graph algorithms on networks containing up to 256 million edges are conducted.
NoSQL Databases for RDF: An Empirical Evaluation
This work is the first systematic attempt at characterizing and comparing NoSQL stores for RDF processing and compares their key characteristics when running standard RDF benchmarks on a popular cloud infrastructure using both single-machine and distributed deployments.
XML Step by Step, Second Edition
This hands-on learning title demonstrates step by step how to create effective XML documents and display them on the Web, and reviews the latest W3C standards, shows how to process XML in Internet Explorer 6.0 and MSXML 4.0, and expands coverage of namespaces, cascading style sheets (CSS), and other technologies.
Graph-Based Data Mining
Using databases represented as graphs, the Subdue system performs two key data mining techniques: unsupervised pattern discovery and supervised concept learning from examples. Applications to large
Learning in Graphical Models
This paper presents an introduction to inference for Bayesian networks and a view of the EM algorithm that justifies incremental, sparse and other variants, as well as an information-theoretic analysis of hard and soft assignment methods for clustering.
Database System Concepts
This acclaimed revision of a classic database systems text provides the latest information combined with real-world examples to help readers master concepts in a technically complete yet easy-to-understand style.
Knowledge representation: logical, philosophical, and computational foundations
  • J. Sowa
  • Computer Science
    Computational Linguistics
  • 2001
This chapter discusses knowledge representation, meaning, purpose, context, and agents in the context of ontology, as well as some examples of knowledge acquisition and sharing.