Corpus ID: 64622863

Graph Databases

@inproceedings{Robinson2013GraphD,
  title={Graph Databases},
  author={I. Robinson and J. Webber and Emil Eifr{\'e}m},
  year={2013}
}
  • I. Robinson, J. Webber, Emil Eifrém
  • Published 2013
  • Computer Science
  • 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… CONTINUE READING
    283 Citations

    Topics from this paper

    Graph Databases: Their Power and Limitations
    • 32
    • PDF
    Exploiting NoSQL Graph Databases and in Memory Architectures for Extracting Graph Structural Data Summaries
    • 4
    • PDF
    Combining Two Types of Database System for Managing Property Graph Data
    GraphChi-DB: Simple Design for a Scalable Graph Database System - on Just a PC
    • 15
    • PDF
    Foundations of Modern Query Languages for Graph Databases
    • 147
    • PDF
    System G Distributed Graph Database
    • 2
    • Highly Influenced
    • PDF
    Graph Database for Recipe Recommendations
    • 2
    Visualisation of Relational Database Structure by Graph Database
    • 2
    • PDF
    Optimizing Tree Patterns for Querying Graph- and Tree-Structured Data
    • 6
    • Highly Influenced
    • PDF

    References

    SHOWING 1-8 OF 8 REFERENCES
    NoSQL Databases for RDF: An Empirical Evaluation
    • 101
    • PDF
    XML Step by Step, Second Edition
    • 6
    Graph-Based Data Mining
    • 477
    • PDF
    Learning in Graphical Models
    • 1,543
    • PDF
    Database System Concepts
    • 1,682
    • PDF
    Knowledge representation: logical, philosophical, and computational foundations
    • J. Sowa
    • Computer Science
    • Computational Linguistics
    • 2001
    • 2,933
    • PDF
    Bayesian Networks and Decision Diagrams
    • 27