Neo4j Blog

Welcome to This Week in Neo4j where I share the most interesting things I found in our community over the last seven days. This week we had an exciting presentation by Andrew Jefferson about Deep Learning on Graphs as part of the online meetup. There’s also good news for Azure users - David Allen has done a major overhaul of our offerings in the marketplace. We’re also... Read more →

Graph technology refers to the storage, management and querying of data graphical representation. Here, your indices become vertices and your relationships are converted into edges. Through analysis of the fine-grained relationships, by using graph analysis, you can find out oddities with the help of algorithms and queries. A primary advantage of graph databases is that they are indexed... Read more →

TL;DR: Starting with Neo4j 3.5, Enterprise Edition source code will no longer be published to the open source commons, including future versions. This does not impact Neo4j Community Edition. We will continue to deliver the world’s best and most comprehensive graph database as open source. This does not affect customers, partners, OEMs or Neo4j Desktop users. Code contributions from... Read more →

Editor’s Note: This presentation was given by Syed Haniff at GraphConnect Europe in May 2017. Presentation Summary UBS bank was relying on a data distribution model that was no longer serving its internal consumers, largely because it required its users to manually join returned data to glean any data insights. The data services team knew it had to create a platform that was simple,... Read more →

When it comes to NoSQL databases, data consistency models can sometimes be strikingly different than those used by relational databases (as well as quite different from other NoSQL stores). The two most common consistency models are known by the acronyms ACID and BASE. While they’re often pitted against each other in a battle for ultimate victory (please someone make a video of that), both... Read more →

Graph technologies are the scaffolding for building intelligent applications, enabling more accurate predictions and faster decisions. In fact, graphs are underpinning a wide variety of artificial intelligence (AI) use cases. This blog series is designed to help you better leverage graph analytics to effectively innovate and develop intelligent applications faster. Last week we looked... Read more →