Case Studies

Fraud DetectionFraud Detection

Neo4j is allowing organizations to develop the next generation of fraud detection systems, that are based on connected intelligence. This provides an enhanced degree of insight, compared to fraud detection algorithms that use basic statistical analysis and pattern recognition. Get the White Paper »

Geo is a Natural in Graph DatabasesGeo is a Natural in Graph Databases

A geographic routing problem sparked the invention of graph theory in 1736 by Leonhard Euler. It is no surprise that Neo4j is well suited for business applications involving geography, routing, and optimization. Get the White Paper »

Neo4j Powers Master Data ManagementNeo4j Powers Master Data Management

Neo4j is an ideal antidote to some of the greatest technical problems faced in MDM implementations, allowing iterative data model development, and a simple way of working with inherently complex data that significantly reduces project complexity. Get the White Paper »

Graph Databases are the Natural Way to Map your Network.Graph Databases are the Natural Way to Map your Network

Graph databases are used for operating & analyzing networks and data centers. Network management applications built by Neo4j customers include network failure & degradation analysis, QoS mapping, OSS network inventory mapping and network asset management. Get the White Paper »

Case Study: Glassdoor Expands Its Integrated Social Platform With Neo4jCase Study: Glassdoor Expands Its Integrated Social Platform With Neo4j

Glassdoor is an online jobs & career community providing anonymous inside information to job seekers. As the first online job site to let you find jobs through their network of Facebook friends, Glassdoor uses Neo4j to provide real-time job recommendations to their users. Get the White Paper »

Neo4j Connects and Builds Relationships in Social AppsNeo4j Connects and Builds Relationships in Social Apps

Graphs are the ideal representation of a social network, which comprise people, and relationships between people. Common queries with social networks—for example friends of friends—are notorious for bogging down performance in relational databases. Get the White Paper »

Neo4j White Papers

Graph Databases: The Super Fast New Way to Access Social DataGraph Databases: The Super Fast New Way to Access Social Data

A new type of database significantly changes the standard direction taken by NOSQL. Graph databases, unlike their NOSQL and relational brethren, are designed for lightning-fast access to complex data found in social networks, recommendation engines and networked systems. Get the White Paper »

NoSQL, Big Data, and GraphsNoSQL, Big Data, and Graphs

It used to be that databases were just tasked with digitizing forms and automating business processes. The data was often tabular – take an accounting ledger, for example –and the processes being modeled were reasonably static. Today, the types of data that we are interested in are much more diverse and dynamic. Get the White Paper »

Scaling with Neo4j

Scalability means different things to different people. The Neo4j scalability package is known as high availability, or HA. This whitepaper helps you understand what it means to scale with Neo4j, and what HA provides. Get the White Paper »

White Paper: Fraud DetectionFraud Detection: Discovering Connections with Graph Databases

Banks and Insurance companies lose billions of dollars every year to fraud. Traditional methods of fraud detection play an important role in minimizing these losses. However increasingly sophisticated fraudsters have developed a variety of ways to elude discovery, both by working together, and by leveraging various other means of constructing false identities. Graph databases offer new methods of uncovering fraud rings and other sophisticated scams with a high-level of accuracy, and are capable of stopping advanced fraud scenarios in real-time. Get the White Paper »

Bloor Group Product Watch: The Rise of the Graph Database

Nowhere is the case for NoSQL more solid than with graph databases like from Neo Technology. With graph queries you tend to want to navigate your way through a network of connections. Many, if not all of which, might be exactly the same kind of entity, such as a person, as illustrated in the graph, which shows a simple data network of customer information. Get the White Paper »