If you care about sustainability, I have a data challenge to pull your hair out. What is the path in this supply chain that leads to the least CO2 emissions?…

A curated list of resources for graph-related topics, including graph databases, analytics and science - graphgeeks-lab/awesome-graph-universe

Graph-Powered Analytics And Machine Learning With TigerGraph - Driving Business Outcomes with Connected Data

Explore how using Neo4j Graph Database and Databricks together can deliver groundbreaking analytics and GenAI outcomes.

The Rise of Graph Jobs, The Disappearance of Graph Technology? Join me for this fun presentation at KGC on May 8, 2024, in NYC, where I delve into a "State of…

Many global corporations are managing multiple supply chains, and they depend on those operations to not only deliver goods on time but to respond to divergent customer and supplier needs. According to a McKinsey study, it’s estimated that significant disruptions to production now occur every 3.7 years on average, adding new urgency to supply chain […]

Change & Risk Require New Enterprise Tools As AI systems, bots (both digital and physical), AI leveraged smart digital identities, and IoT devices invade your enterprise, it increases the pace of change and risk. This brief article focuses on why you should be deploying TODA, EMS and graphs in your

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 offering.

New players, new features, platforms, and ticking boxes. Let's talk graph with Neo4j.

What are the options for querying graphs, and how do we go from that to the equivalent of a virtual machine for databases?

If the history of relational databases is any indication, what is going on in graph databases right now may be history in the making.

Graph databases are crossing the chasm to mainstream use cases, adding features such as machine learning to their arsenal and becoming more cloud and developer friendly. Last year was a breakout year, and graph database growth and evolution is well under way in 2019.

Here's why and how a startup founded by a duo of researchers some months back is attracting big enterprise clients and serious funding

A $325 million Series F funding round, bringing Neo4j's valuation to over $2 billion. A social network of 3 billion people, distributed across 1000 servers. The latter is a demo; the former is not. But both are real signs that the graph market and Neo4j are getting huge.

GDS 2.0 and AuraDS from Neo4j bring graph data science one step closer to mainstream adoption.

In the new knowledge-based digital world, encoding and making use of business and operational knowledge is the key to making progress and staying competitive. Here's a shortlist of technologies and processes that can support this transition, and what they are about.

Graphs are everywhere. That has been the motto of graph aficionados for years, and now the world seems to be waking up to this.

Amazon Neptune just added another query language, openCypher, to its arsenal. That may not sound like a big deal in and of itself, but coupled with updates in machine learning and data science features, it points towards the future of graph databases.

vendors company,url,SPARQL,RDF-Star,Gremlin,Cypher,misc query,distrib,open source,parent,speaker,notes AgensGraph,a href="https://bitnine.net/agensgraph/"https://bitnine.net/agensgraph//a,Y,SQL,Bitnine AllegroGraph,a href="https://allegrograph.com/products/allegrograph/"https://allegrograp...

Graphs. Such a simple idea. Map a problem onto a graph then solve it by searching over the graph or by exploring the structure of the graph. What could be easier? Turns out, however, that working with graphs is a vast and complex field. Keeping up is challenging. To help keep up, you just need an editor who knows most people working with graphs, and have that editor gather nearly 70 researchers to summarize their work with graphs. The result is the book Massive Graph Analytics. — Timothy G. Mattson, Senior Principal Engineer, Intel Corp Expertise in massive-scale graph analytics is key for solving real-world grand challenges from healthcare to sustainability to detecting insider threats, cyber defense, and more. This book provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. Massive Graph Analytics will be beneficial to students, researchers, and practitioners in academia, national

TigerGraph unveiled a new tool that provides users with a dedicated, open source environment for building machine learning models with graph databases.

Can Machine Learning Do Symbolic Manipulation?  I spent some time over the holidays engaged in a fascinating online conversation. The gist of it was a variation of an argument that has been going on in the realm of artificial intelligence from the time of Minsky and Seymour Papert: Whether it is possible for neural networks to… Read More »DSC Weekly Digest 04 Jan 2022: Can Machine Learning Do Symbolic Manipulation?

Last week Google added Graph Neural Network support to TensorFlow. This comes in the wake of PyTorch Geometric getting a lot of support from Meta (formerly...

Papers With Code highlights trending Machine Learning research and the code to implement it.

Open Source Tool - Cybersecurity Graph Database in Neo4j - GitHub - amberzovitis/GraphKer: Open Source Tool - Cybersecurity Graph Database in Neo4j

With organizations struggling to manage growing amounts of data, Gartner predicts adoption of graph technology will increase exponentially by 2025.

Memgraph, the streaming graph application platform, today announced Memgraph 2.0, the public launch of its source-available platform, which makes it easy

The Data Exchange Podcast: Paco Nathan on recent trends in large-scale graph technologies and novel applications of graph databases.

Very honored to have been invited by Jesús Barrasa Amy Hodler and Jim Webber to write the foreword for their book "Knowledge Graphs Data in Context for...