Neo4j Adds Visualization Tool to Its Graph Database

Among the Neo4j 3.4 database enhancements are horizontal scaling, 3D geospatial search, performance improvements of more than 50 percent and numerous operational improvements.

Neo4j, whose graph search platform was the central tool used by a 300-member team from the International Consortium of Investigative Journalists to research the Panama Papers project that won a 2017 Pulitzer Prize, has released both a new version of the database and a new app to facilitate use of it.

Among the Neo4j 3.4 database enhancements are horizontal scaling, 3D geospatial search, performance improvements of more than 50 percent and numerous operational improvements. The new app, Neo4j Bloom, is a search-based graph visualization product that transforms the abstract concepts of data relationships into tangible, easy-to-understand illustrated views of data.

Some background: Graph search, an open-source database project built on all the networking people around the world do online every day, is the most far-reaching search IT to go mainstream since Google started storing up and ranking websites in 1999. Basically, a graph search database anonymously uses all the contacts in all the networks in which you work to help you find information.

Anything you touch, any service you use and anything people in your networks touch eventually can help speed information back to you. It avoids anything non-relevant that would slow down the search.

New Visualizer: Neo4j Bloom

Neo4j’s goal is to make connected data–powered by a graph database–accessible to more types of users. To do this, the company also released Neo4j Bloom, which aims to simplify communication between developers and line-of-business stakeholders. Now non-technical users can deploy visualization techniques to read the data more efficiently.

CEO and co-founder Emil Eifrem said in a media advisory that he believes these capabilities are essential to mainstream graph-technology use cases, such as fraud detection, real-time recommendation engines and knowledge graphs that power artificial intelligence.

"With Neo4j 3.4 and Neo4j Bloom, we've extended the capabilities of the Neo4j Graph Platform both to make it more accessible and easy-to-use, and to stay ahead of the increasing performance demands of our existing customers," Eifrem said.

Data Visualization for Non-Technical Users

"Neo4j Bloom is specifically designed to illuminate connections between data points in an intuitive way, especially for executives and stakeholders who might not be very technical," Eifrem said.

Neo4j Bloom is fully integrated with the Neo4j Graph Platform. Unlike traditional data discovery tools, Bloom reveals how data elements are related to each other, visualizing the context that these connections expose.

Without needing to know a query language, users can explore the graph through search phrases and then zoom in and select nodes in the graph to review and edit their properties. They can also create storyboards for better collaboration between different stakeholders.

The product is expected to be released by the end of Q2 2018, Eifrem said.

New Features in Neo4j Database

Improvements in the 3.4 release, according to Neo4j, include:

  • Multi-Clustering: Users can create and manage multiple cluster-based tenants, where each operates within its own scalable Causal Cluster. As a step toward fully-sharded horizontal scaling, Multi-Clustering can be used to logically partition graphs; create highly-available, large-scale multi-tenant SaaS systems; or oversee multiple graph database implementations across the enterprise. An example would be building GDPR-compliant data lineage systems by country.
  • Date/Time and 3D geospatial data types: Neo4j 3.4 extends use cases by adding date/time and three-dimensional geospatial search functions to Cypher. Customers can now easily build radial search functions such as "find all available sales personnel within 100 miles whose technical skills align with this partner" or real-time bicycle delivery systems that consider the distance to address, the time of day and the elevation changes in their calculations.
  • Performance improvements: Neo4j maintains its performance leadership with 70 percent faster Cypher execution, 100 percent faster backups, and 30 to 50 percent faster data loading and overall writes due to native string indexes.
  • Administration and security: Administrators now have new diagnostic tooling, automatic cache warming upon restart, property-level security and rolling upgrades.

To learn more about Neo4j 3.4, go here.

Chris Preimesberger

Chris J. Preimesberger

Chris J. Preimesberger is Editor-in-Chief of eWEEK and responsible for all the publication's coverage. In his 15 years and more than 4,000 articles at eWEEK, he has distinguished himself in reporting...