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What is a Graph Database?

By   /  October 7, 2017  /  No Comments

Graph DatabaseGraph Databases refers to a category of  NoSQL databases that represent data whose relations are well represented as a set of nodes. These nodes have an undetermined number of connections and are evaluated through computer algorithms.

Good Graph Database use cases include:

  • Social relationships (nodes are people)
  • Public transport links (nodes can be bus or train stations)
  • Roadmaps (nodes are street intersections or highway intersections)
  • Anything requiring traversing a graph to find the shortest routes, nearest neighbors, etc.)

Other Definitions of Graph Databases Include:

  • “A set of nodes, edges, and properties to represent and store data. The relationships between data points often matter more than the individual points themselves.” (Donna Burbank, DATAVERSITY®)
  • “A Property Graph consisting of nodes and relationships between the nodes, with attributes called properties.” (Akshay Pore, DATAVERSITY®)
  • “A database designed to treat the relationships between data as a first-class citizen in the Data Model.” (Neo4j)
  • “A graph data model consists of vertices that represent the entities in a domain, and edges that represent the relationships between these entities.” (InfoWorld)


Image credit: Neo4j

Businesses Use Graph Databases to:

  • Handle applications requiring traversal between data points.
  • Store properties of each data point as well as relationships between them.
  • Ask complex queries to determine relationships between data points.
  • Detect patterns between data points.

 

Photo Credit: jijomathaidesigners

About the author

Michelle Knight enjoys putting her information specialist background to use by writing technical articles on enhancing Data Quality, lending to useful information. Michelle has written articles on W3C validator for SiteProNews, SEO competitive analysis for the SLA (Special Libraries Association), Search Engine alternatives to Google, for the Business Information Alert, and Introductions on the Semantic Web, HTML 5, and Agile, Seabourne INC LLC, through AboutUs.com. She has worked as a software tester, a researcher, and a librarian. She has over five years of experience, contracting as a quality assurance engineer at a variety of organizations including Intel, Cigna, and Umpqua Bank. During that time Michelle used HTML, XML, and SQL to verify software behavior through databases Michelle graduated, from Simmons College, with a Masters in Library and Information with an Outstanding Information Science Student Award from the ASIST (The American Society for Information Science and Technology) and has a Bachelor of Arts in Psychology from Smith College. Michelle has a talent for digging into data, a natural eye for detail, and an abounding curiosity about finding and using data effectively.

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