Graph databases are often referred to as NoSQL databases. Graph databases are identical to conventional network model databases and also represent general graphs, however, network-model databases ...

This model works best when you’re dealing mainly with data from any one table. ... Graph databases—like other NoSQL databases—typically use their own custom query methodology instead of SQL.

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.

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.

Which NoSQL data model do you need? The four main types of NoSQL data ... A graph database is well-suited for applications where data elements are interconnected and the number of ...

This is where graph databases and NoSQL come into play. Unlike relational databases, which work particularly well with structured data, graph databases are designed to model and store data as ...

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 ...

While relational databases remained strong, the 2000s saw the emergence of XML databases, and NoSQL, the idea that databases didn't need to be structured in a purely tabular form, began to get hot.

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.

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 ...