Graph databases facilitate discovery and analysis closely connected facts. This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big Data Analytics.

Before looking into a graph database provider, make sure your intended use works well with the graph model. This means any application that can benefit from using graphs to manage data relationships.

Relational databases are well-suited to conventional data analysis such as reporting and classical statistical analysis (what you learned in the college Statistics 101 class, for example).

NoSQL databases are specialized to store different types of data like Key Value, Documents, Column Family, Time Series, Graph, and IoT data. Pascal Desmarets talks about how to perform data ...

Alternate data models in NoSQL offerings. Lucene, Solr and ElasticSearch offer text and document indexing functions, for example to implement real-time search as users enter terms. Graph databases ...

Graph databases—like other NoSQL databases—typically use their own custom query methodology instead of SQL. One commonly used graph query language is Cypher , originally developed for the ...

Graph databases, such as Neo4j, ... MongoDB is far and away the most popular of the NoSQL databases. Its document data model gives developers great flexibility, ...

Peter Neubauer introduces Graph databases and how they compare to RDBMS' and where they stand in the NOSQL-movement, followed by examples of using a graph database in Java with Neo4j.

NoSQL databases are often associated with "big data" tasks, handling large volumes of data in various forms: Columnar databases, for dealing with massive collections of simple structured data ...

“Most graph system growth has been around the property graph data model, not RDF,” Boncz said. As a result, the Social SNB aimed at property graph data has received considerably more attention ...