Property graphs provide a lot of flexibility in data modeling; but how do you know when to use which feature?

When building graph data models we frequently have to deal with a degree of polymorphism for our entities just like the real world. For instance – I’m a person, but I’m also a parent, a spouse, a sibling, a child, a… Implicit categorisation Sometimes the entity categories are entirely defined by relationships to other entities. […]

The graph database market is very exciting, as the long list of vendors continues to grow. You may not know that there are huge differences in the origin story of the dozens of graph databases on the market today. It’s this origin story that greatly impacts the superpowers and weaknesses of the various offerings.

Graph databases and document databases make up a subcategory of non-relational databases or NoSQL. NoSQL databases were created to get a handle on large amounts of messy Big Data, moving very quickly. Managers use the non-relational toolkit to gain business insights and detect patterns in information on the fly, as Big Data streams into the system. Many companies, especially those with a large web presence like Google, Facebook, and Twitter, consider NoSQL databases a must-have.

Graph databases are shaped the way we think, so why can't people get their heads around them?

How can companies step themselves into the world of graph databases? Neo4j thinks it has an answer. It has been offering a Startup Program for startups with 19 employees or fewer; more than 650 startups with fewer than 20 employees took advantage of having free access to Neo4j Enterprise clusters.

Neo4j’s Alicia Frame explains how life science researchers can exploit graph databases to get truly granular insight into big data to make major leaps forward in medical research.Complex data sets hold the key to advancing medical breakthroughs. These data sets tend to be voluminous and heterogeneous by nature, presenting an insurmountable challenge for traditional data analysis methods as they struggle to link patterns and outcomes. The unfortunate consequence is a slowdown in the progress of research.Anyone who works in life sciences is aware that they are working with highly connected information; the challenge is making sense of these connections. Unfortunately, many scientists are still using relational databases and spreadsheets which makes mapping important patterns and connections unintuitive and difficult, if not impossible.Graph technologyGraph technology is emerging as an enabler for researchers to trawl gargantuan amounts of unstructured data, turning it into valuab

How to model #Facebook posts and user reactions, using #Neo4j #graphdatabase #socialmedia #data #analytics #softwareengineering #knowledgegraph

Ontotext releases GraphDB 9.2 featuring the anticipated support for RDF*/SPARQL* and improvements in the plug-ins for semantic similarity and versioning.

Graphs #Analytics for Fraud Detection, using Graph #NeuralNetworks for Anomaly detection. GraphSAGE is Stanford #opensource project: deep neural network-based NRL toolkit, implemented in Tensorflow, making it ideal to develop an anomaly detection system

haystack discoveries that evade traditional analytic workflow.

Managing multiple truths in #datamodeling, #ontologies & #knowledgegraphs by @palexop #semantics #vagueness #datascience #dataengineering #EmergingTech #dmzone #presentation

This article shows how an RDF Graph CRUD application can be rapidly developed, yet without losing the flexibility that HTML5/JavaScript offers, from which it can be concluded that there is no reason preventing the use of RDF Graphs as the backend for production-capable applications.

Learn how to use Neo4j to integrate a BigQuery public dataset with Stackdriver logs into a graph database, to surface new conclusions from complex data.

Gain a basic understanding of graph-based meta data management in enterprise data governance with Apache Atlas as a prime example.

Learn use cases for training machine learning with graph features and improving machine learning accuracy With graph-based features.

This article will explain how to create property graphs in AnzoGraph, including loading and inserting properties, and how to query your property graphs.

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

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

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