Personally, I am always most excited by technology when it can have a positive impact on society and the lives of ordinary people. Curing…

Image taken from wikipedia, Couple of days ago I was presenting “How to use similarity algorithms” in a Neo4j online meetup with Mark Needham. Among other use-cases we discussed how the…

Discover what's new in the 3.5 release of the Neo4j graph database, including a Go language driver, full-text search and indexing, TLS encryption and more.

Today we want to make this available in a first release under an Apache License for you to try out and test. It works with Neo4j from 3.4.x

Whether you’re creating a new graph data model and queries, or exploring an existing graph dataset, it can be useful to have an interactive query environment that allows you to visualize the results. In this blog post we show you how to achieve this by connecting an Amazon SageMaker notebook to an Amazon Neptune database. […]

Gremlin is one of the most popular query languages for exploring and analyzing data modeled as property graphs. There are many…

by Dr. Xu Yu, CEO and Dr. Victor Lee, Director of Product Management [Excerpted from the eBook Native Parallel Graphs: The Next Generation of Graph Database for Real-Time Deep Link Analytics] Until recently, graph database designs fulfilled some but not all of the graph analytics...

Watch the GraphConnect presentation by Dom Davis, cofounder of Tech Marionette, to discover the benefits of building a meta graph model for your domain.

Discover how the super nerdy math of graph theory and predictive modeling is also driving bottom-line business growth – including definitions and examples.

Stardog 5.1 adds support for GraphQL, an expressive path query SPARQL extension, and stored functions.

Graph analytics is a hot topic, but what does it mean? At the DC GraphTour, I learned the difference between graph queries, graph algorithms, and graph analytics. Next up: San Francisco GraphTour.

Discover Neo4j Bloom, the latest product from the Neo4j team. This graph data visualization tool helps traditional Neo4j users communicate with their non-technical peers in a simple manner that reveals and explains the concepts of data connectedness for all people, regardless of technical background.

Bye Bye Silos! Those who stay on their islands will fall back. This statement is valid on nearly any level of our increasingly complex society, ranging from whole cultural areas down to single individuals.

I usually mention both as unique/key features of RDF: global identifiers and zero-cost merge— Martynas Jusevicius (@namedgraph) June 8, 2018

For the milestone of the 3.4 release, we’ve implemented a set of information retrieval features exposed via new database object View.

“Which #RDF graph partitioning technique gives better performance in cluster triplestore? checkout our empirical evaluation of RDF graph partitioning techniques in different architectures. https://t.co/wRlrR8lOSa #EKAW2018 #BigData”

SAN FRANCISCO, May 2, 2018 -- Neo4j, the leading platform for connected data, today announced Neo4j 3.4, which includes horizontal scaling, performance

Neo4j tunes its graph engine for AI applications - SiliconANGLE

Recently RedisGraph published a blog [1], comparing their performance to that of TigerGraph’s, following the tests [2] in TigerGraph’s benchmark report [3], which requires solid performance on 3-hop, 6-hop, and even 10-hop queries. Multi-hop queries on large data sets are the future of graph analytics....

This release candidate is the first one with a cluster-ready ArangoSearch integration, the long awaited GeoJSON support and Google’s S2 Geo Index.

Learn how to find similar items in the Knowledge Graph with machine learning.

Alethio’s data scientists dig into the Ethereum blockchain to identify the major players across the transaction network. Leveraging the…

Enables Users to Experience the World’s Fastest Graph Analytics Platform Designed to Unleash the Power of Interconnected Data for Deeper Insights and Better Outcomes

This article takes a look at insight into evaluating a graph database gained from benchmarking different graph databases. Also explore loading capabilities.

A knowledge graph is the only realistic way to manage enterprise data in full generality, at scale, in a world where connectedness is everything.