Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...

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.

Imagine a graph database that's not aimed at the growing graph database market, selling to Fortune 500 without sales, and claiming to be the fastest without benchmarks. Dgraph is unique in some ...

Amazon’s graph database service offers ACID properties, immediate consistency, and auto-scaling storage for billions of relationships ...

For a few decades, structured data are typically arranged as relational tables and stored in relational databases. Recent years have witnessed the blossom of graph databases, for which graph becomes ...

Understanding pointers and references in Go can be challenging for many developers, especially those new to low-level programming languages. In this article, I’ll walk you through a program that ...

Graph databases, based on mathematics known for three centuries, are starting to yield value for businesses beyond Facebook and Twitter.

The Bulgarian graph database startup Graphwise today announced a major upgrade to its flagship GraphDB tool, adding new features aimed at boosting enterprise knowledge management and creating a more ...

A graph database uses graph structures for semantic queries with nodes, edges and properties to represent and store data.

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...