Like other NoSQL databases, a graph database is schema-less. Thus, in terms of performance and flexibility, graph databases hew closer to document databases or key-value stores than they do ...

Some graph databases require you to define a schema for your graph—i.e. defining labels or names for your vertices, edges, and properties prior to populating any data—while other databases ...

With the popularity of graph databases driven by such benefits, we’ve seen an emergence of new players to the market, creating a bonafide landscape of tools and technologies. Let’s consider a deep ...

Many are schema-less allowing you to manage your data more efficiently. Many support a powerful query language, SPARQL. Some allow for simultaneous graph search and full-text search of content stores.

Going schema-less can get you started quickly; it's simpler and more flexible, at least up to a certain point. The simplicity of not using a schema can be deceiving though. Because, in the end ...

RDF is a graph data model that has been around since 1997. It's a W3C standard, and it's used to power schema.org and Open Graph, among other things. Plus, there's a bunch of RDF-based graph ...

Graph databases have been around in one form or another since the early oughts, but they were generally slower, more complex to work with, ... (a data schema language).

News. Neo4j 2.0: The Graph Database Has Arrived. By John K. Waters; January 14, 2014; Neo Technology, the commercial sponsor of the Neo4j open-source NoSQL graph database implemented in Java, on ...

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.

Emerging graph database benchmarks are already helping to overcome performance, scalability and reliability issues. ... The Semantic Publishing Benchmark uses an older web data schema called RDF.