By Aileen Agricola | August 19, 2016
Quick summary of article published by datanami
1. It’s All About the Relationships
Relationships are “first-class citizens” in graph databases, unlike in relational databases, which must use special properties like foreign keys to link similar pieces of data.
2. Speedy Performance
For certain types of big data problems–particularly those that involve analyzing the relationships among millions or billions of entities–a graph database will outperform nearly every other type of out-of-the-box database in existence.
2. Semantics Matter
RDF stores are especially good at maintaining the connectedness of multiple entities, in much the same way that humans think about the world. In his new book “The Nature of Graph Data,” IT analyst Robin Bloor notes that the very nature of graphical structures enables them to naturally record both verbs and nouns.
4. Graphs Make a Difference
The Panama Papers, as the event has been dubbed, certainly would not have occurred if an inside source had not leaked to journalists a massive collection of 11.5 million documents from the law firm dating back to 1977. And the ICIJ may not have been able to dissect the complicated transactions involving numerous shell companies and beneficiaries without the benefit of graph technology, specifically the Neo4j database and a front-end graph interface form Linkurius.
5. Ask Tough Questions
Graph databases are already helping organizations in retail, financial services, healthcare, and security fields, and with the growth of new data from the IoT, the use cases for graph are expected to soar.