For the interested -- you can find an empirical study of the sparql-gremlin mapping used by the plugin here: https://t.co/QGIzufzDKo— Harsh Thakkar (@Harsh9t) January 11, 2019

https://t.co/7T0EOs6yG7 - Made this tiny tool to discover related subreddits.The graph is created based on jaccard similarity between two subreddits. Jaccard similarity is constructed from set of shared users.Source code https://t.co/J9r1jl1JjR pic.twitter.com/4hcg7mI4sg— Andrei Kashcha (@anvaka) January 10, 2019

“3.4.0 Highlights - The Gremlin Recipes have been expanded with a new Anti-Patterns section that describes common pitfalls around Gremlin readability, maintainability and performance. https://t.co/NwUNY7zFqY #graphdb”

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

“Q: which product taxonomies are used in the Shopping / Ad industries? Google's Product Taxonomy is a de facto standard but it lacks freshness, coverage and/or finesse in some areas. I'm also looking at product taxonomies from Amazon, Ebay, Walmart, Target, Groupon. What else?”

So can any SemWeb gurus explain to me what the difference is between SHACL and ShEx? If SHACL is an official W3C recommendation, why use ShEx? Why is effort being split on this? Not a criticism at all, but a genuine question as I'm new to all this and only familiar with SHACL.— Bryan J. Brown (@bryjbrown) November 26, 2018

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.

Am I the only one who thinks there's nothing really wrong with the #RDF stack?To me it's such a powerful technology that 20 years in we're still exploring what it is capable of. To do that, we need to throw out the old software design paradigms and think graph- and Web-native.— Martynas Jusevicius (@namedgraph) November 27, 2018

Interactive visualization of the Gremlin graph database with D3.js - bricaud/graphexp

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

Graph analysis is not a new branch of data science, yet is not the usual “go-to” method data scientists apply today. However there are some…

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

Same neo4j linear regression procedures, now unlimited independent variables! More functionality without additional complexity for the…

At long last! With this, we aim to bridge the gap between semantic web and graph database communities. Happy graph-querying! https://t.co/8al1uLi1aC— Harsh Thakkar (@Harsh9t) August 17, 2018

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.

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

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

After the recent general availability for Storage Explorer, we also added new features in the latest 1.1 release to align with Azure Storage platform...

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....

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

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.