Graph visualization tools

Neo4j Bloom is a data exploration tool that visualizes data in the graph and allows users to navigate and query the data without any query language or programming.

Users can write patterns similar to natural language questions to retrieve data and traverse layers of the graph. Bloom also allows appropriate users to edit, update, or correct the graph when missing information or bad data is found.

Neo4j Bloom is available in the following formats:

NeoDash is an open-source, low-code Dashboard Builder for Neo4j. As a part of Neo4j Labs, NeoDash is developed and supported via the online Community.

NeoDash lets you build an interactive dashboard with tables, graphs, bar charts, line charts, maps and more. Dashboards can be saved and shared directly from your Neo4j database.

GraphXR is a start-to-finish web-based visualization platform for interactive analytics. For technical users, it’s a highly flexible and extensible environment for conducting ad hoc analysis. For business users, it’s an intuitive tool for code-free investigation and insight.

GraphXR supports a wide range of applications including law enforcement, medical research, and knowledge management.

Kineviz also has a graph app version of this tool that can be installed in Neo4j Desktop. The blog post about the graph app is included in the resources below.

yWorks provides sophisticated solutions for the visualization of graphs, diagrams, and networks with yFiles, a family of high-quality, commercial software programming libraries. The yFiles libraries enable you to easily create sophisticated graph-based applications powered by Neo4j. They support the widest range of desktop and web technologies and layout algorithms with the highest quality and performance. With the wide-ranging extensibility and large feature set, all your visualization needs can be satisfied.

yWorks also provides a free graph explorer app that is based on the yFiles technology. It can be installed in Neo4j Desktop.

Linkurious Enterprise is an on-premises and browser-based platform that works on top of graph databases. It brings graph visualization and analysis capabilities to analysts tasked to detect and analyze threats in large volumes of connected data. Organizations such as the French Ministry of Economy and Finance, Zurich Insurance or Bank of Montreal use Linkurious Enterprise to fight financial crime, terror networks or cyber threats.

Graphistry brings a human interface to the age of big and complex data. It automatically transforms your data into interactive, visual investigation maps built for the needs of analysts. Quickly surface relationships between events and entities without writing queries or wrangling data. Harness all of your data without worrying about scale, and pivot on the fly to follow anywhere your investigation leads you.

Ideal for everything from security, fraud, and IT investigations to 3600 views of customers and supply chains, Graphistry turns the potential of your data into human insight and value.

Graphlytic is a highly customizable web application for graph visualization and analysis. Users can interactively explore the graph, look for patterns with the Cypher language, or use filters to find answers to any graph question. Graph rendering is done with the Cytoscape.js library which allows Graphlytic to render tens of thousands of nodes and hundreds of thousands of relationships.

The application is provided in three ways: Desktop, Cloud, and Server. Graphlytic Desktop is a free Neo4j Desktop application installed in just a few clicks. Cloud instances are ideal for small teams that need them get up and running in very little time. Graphlytic Server is used by corporations and agencies with highly sensitive data typically in closed networks.

Tom Sawyer Perspectives is a robust platform for building enterprise-class graph and data visualization and analysis applications. It is a complete graph visualization software development kit (SDK) with a graphics-based design and preview environment. The platform integrates enterprise data sources with the powerful graph visualization, layout, and analysis technology to solve big data problems. Enterprises, system integrators, technology companies, and government agencies use Tom Sawyer Perspectives to build a wide range of applications.

KeyLines makes it easy to build and deploy high-performance network visualization tools quickly. Every aspect of your application can be tailored to suit you, your data and the questions you need to answer. KeyLines applications work on any device and in all common browsers, to reach everyone who needs to use them. It is also compatible with any IT environment, letting you deploy your network visualization application to an unlimited number of diverse users. You can build a custom application that is scalable and easy to use.

SemSpect is a highly scalable knowledge graph exploration tool that uses visual aggregation to solve the hairball problem faced by standard graph visualization approaches. The data guided construction of the exploration tree empowers the users to build complex requests intuitively without query syntax. Its meta level approach is very effective for grasping the overall structure of the graph data, while flexible access to node and relationship details ensures easy inspection and filtering. SemSpect furthermore allows to define query-based node labels during exploration to refine the graph data schema.

SemSpect is available as follows:

This library was designed to combine JavaScript visualization and Neo4j in a seamless integration. Connection to Neo4j is simple and straightforward, and because it is built with Neo4j’s property graph model in mind, the data format Neovis expects aligns with the database. Customizing and coloring styles based on labels, properties, nodes, and relationships is defined in a single configuration object. Neovis.js can be used without writing Cypher and with minimal JavaScript for integrating into your project.

To maximize functionality and data analysis capabilities through visualization, you can also combine this library with the graph algorithms library in Neo4j to style the visualization to align with results of algorithms such as page rank, centrality, communities, and more. Below, we see a graph visualization of Game Of Thrones character interactions rendered by neovis.js, and enhanced using Neo4j graph algorithms by applying pagerank and community detection algorithms to the styling of the visualization.

An advantage of enhancing graph visualization with these algorithms is that we can visually interpret the results of these algorithms.

Popoto.js is a JavaScript library that is built upon D3.js. Popoto.js will help users build queries in a visual way to execute against Neo4j. Users can also customize the results and the visual display. Along with the visualization, you can include auto-complete searches for potential queries, see the Cypher translations that are generated from the visualization, review text results from queries, and more.

To use Popoto.js in your application, you simply need to include each component independently bound to a container id in an HTML page. The rest of the content will be generated from that.

As the first line on D3’s website states "D3.js is a JavaScript library for manipulating documents based on data." You can bind different kinds of data to a DOM and then execute different kinds of functions on it. One of those functions includes generating an SVG, canvas, or HTML visualization from the data in the DOM.

Neo4j’s movie example applications use d3.js, and you can find a variety of other projects using Neo4j and d3. The complicated part of D3 (or any embeddable library that doesn’t have direct Neo4j connection) is converting your graph data into the expected map format for export. D3 expects two different collections of graph data - one for nodes[] and one for links[] (relationships). Each of these maps includes arrays of properties for each node and relationship that d3 then converts into circles and lines. Version 4 and 5 of d3.js also support force-directed graphs, where the visualization adjusts to the user’s view pane.

This library offers a variety of visualizations designed to handle large, dynamic data sets. There are a variety of formats to style your data, including timeline, dataset, graph2d, graph3d, and network. The most common format seen with Neo4j is the network visualization.

Even with the network format, there are numerous customizations available for styling nodes, labels, animations, coloring, grouping, and others. For additional information and to see everything that is available, check out their docs and examples linked in the resources below.

While some libraries are meant to include all the capabilities in one bundle, Sigma.js touts a highly-extensible environment where users can add extension libraries or plugins to provide additional capability. This library takes exported data in either JSON or GEXF formats.

Users can start from a very basic visualization right out of the box, and then begin adding custom functions and rendering for styling preferences. Once the requirements surpass what is possible there, users can write and use their own custom plugins for specific functionality. Be sure to check out the repository, though, for any existing extensions!

Vivagraph.js was built to handle different types of layout algorithms for arranging nodes and edges. It manages data set sizes from very small to very large and also renders in WebGL, SVG, and CSS-based formats. Customizations and styling are available through CSS modifications and extension libraries. It also can track changes in the graph that update the visualization accordingly.

This library is also meant to visualize and render network node graphs and offers customization and extensibility for additional features. Cytoscape.js responds to user interaction and works on touch screen interfaces, allowing users to zoom, tap, and explore in the method that is relevant to them. You can customize styling and web page view with a variety of style components.