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.

The evolving landscape of NoSQL databases and NoSQL database management systems (NoSQL DBMS) has everything to do with Big Data analytics.

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 ...

A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data. Unlike traditional databases organized in rows and columns, graph databases ...

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, ...

Graph Databases Show the Connections Between Data; A graph database uses nodes, relationships between nodes and key-value properties instead of tables to represent information. This model is typically ...

Data modeling flexibility: Because they are schema-less, they are ideal for various types of data formats, such as document stores, key-value stores, and graph databases.

By multi-model, Franz said its semantic graph database supports ingestion of different JSON documents as well as Resource Description Framework (RDF), or triplestore, data—another World Wide Web ...

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, ...