#Oracle offers #GraphDatabase, Graph #Analytics free of charge with purchase of main Oracle product license. 2 different products: Database built over Oracle's relational store using RDF/SPARQL. Analytics in-memory engine, custom query language

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

In this short technical blog, I will show you how to use GSQL to search a graph for all the occurrences of a small graph pattern. We call this pattern matching. Consider the problem of matching a pattern of vertices and directed edges in a...

When developing web applications with frameworks like Vue.js the best approach is to subdivide it into well-defined and reusable components for the user...

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

Given a set of business entities such as two merchants for financial services or two doctors for healthcare, how are they related? Do they have customers or patients in common and how is their relationship evolving over a period of time?

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.

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. […]

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

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…

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

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.

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.

Discover a new way to visualize and explore your connected data with SemSpect: a unique approach to graph visualization that doesn't depend on using random or best-guess Cypher queries in order to explore your data's meta-graph and that is compatible with Neo4j (including RDF datasets).