Neo4j, the graph data platform market leader, powers more than 4,200 startups, 800+ enterprises, 75% of the Fortune 500, and 200K+ developers, all while delivering the definitive foundation for connected data at unlimited scale and developer velocity.
With Neo4j, developers and data scientists get a trusted platform and advanced tools to build today’s intelligent applications and machine learning workflows. Powered by native graph technology, Neo4j stores and manages data in a more natural, connected state, maintaining data relationships that deliver lightning-fast queries, deeper context for analytics, and a pain-free modifiable data model.
Illustrative, Codeless Search-to-Storyboard Design of Neo4j Bloom
Visualization is a critical tool for getting the most out of your Neo4j graphs, whether it’s empowering developers to quickly prototype, or enabling analysts and data scientists to follow their intuition in exploring interesting patterns and algorithm results. The illustrative, codeless search-to-storyboard design of Neo4j Bloom provides a breakthrough graph communication and data visualization for users to share the innovative work of their graph analytics and development teams, streamlining conversations and projects.
Bringing Findings to Life Through Visual Explanation
Neo4j Bloom requires a minimum of fuss to start using, while remaining highly flexible across many analytics domains (fraud detection, network analysis, and supply chain management are just a few examples). Even developers can take advantage of Bloom’s search phrase and deep linking capabilities to land users directly into any part of the graph that might be of interest, based on the relevant analytics. Bloom aims to empower users across domains and bring findings to life through visual explanation. These findings can then be used to build even more powerful analytics.
A few domains for which Bloom is a powerful ally were mentioned above. Taking any of these, or others, into account, one activity that a user might be interested in is hypothesis generation. Imagine having a problem to solve (for example, identifying malicious network traffic), and what you believe to be the relevant data to solve it (perhaps a large volume of summarized network traffic from your organization), but no idea where to begin. Bloom can help.
Now that you know more about Bloom and its benefits, time to talk about this release of Bloom. Some product releases break new ground, others are more about sowing and reaping, incrementally realizing the benefits of previous innovations while preparing for further gains.
Today we are thrilled to announce the release of Neo4j Bloom 1.8. With this release, we added a number of key enhancements and features to help our users and customers further extend the power of visualization and better understand relationships and their meanings, for a wide variety of situations including improving network security. To learn more about our previous releases on Neo4j Bloom, read our blog here.
Support for Date/Time Properties
Bloom now has improved support for Neo4j date, time, dateTime, localDateTime, and localTime types. Thinking about our malicious traffic scenario above, a cybersecurity analyst might start with a single example of known bad traffic with only information about the timing of activity, and ingress and egress points into a network. Using Bloom’s enhanced date/time capabilities, it will be easier to identify this example and see what the rest of the pattern looks like, perhaps identifying malicious external addresses and other characteristics important to finding similar activity in the graph.
From there, an analyst may want to create a .png image of their viewport by triggering the Export Screenshot action found at the new Export icon on the canvas or from the context menu. This image can be shared with team members and used to explain the types of patterns to look for and systems to patch or harden.
Multi-User Editing of Perspective
Team members can now also work simultaneously on the same Perspective (a view in Bloom of a specific set of node and relationship types in your graph, and the associated styling and search phrases). Once again, an analyst may identify a pattern that leads to finding other parts of an organization’s IT infrastructure potentially exposed to the same type of cyber threat, and decide to apply a styling rule in Bloom that highlights these nodes. A colleague working from the same Perspective would instantly see these changes in Bloom and be able to identify the same nodes using the same styling cues. Bloom will also alert users of shared perspectives to recent changes, along with the user who made the change.
In short, any edits to the Perspective will now be updated in real time for users that have access to the same Perspective. If any changes are found, they are merged, the current Perspective is refreshed, and a notification appears in the Perspective drawer.
The notifications tell you which user has made changes and when they were made.
Support for SSO: OIDC / OAuth
Finally, enterprises can now configure Single Sign-On login for Bloom under certain circumstances. See the documentation to learn how you can leverage this capability. Supported providers at this time include OpenID Connect (OIDC) OAuth 2.0 providers Okta, KeyCloak, and Azure AD. SSO has been tested on Neo4j 4.2.x and 4.3.x deployments. This is yet another enhancement aimed to make it easier to get down to business and start exploring your data.
How to Upgrade
- Users of Neo4j Desktop should automatically receive the update, or install the latest version of Bloom using the Graph Apps drawer.
- Users of the server plugin or a self-hosted web application can download the updates on our downloads page.
- AuraDB users should see the update appear automatically with a future AuraDB update.
Wish to Become a Bloom Co-Designer?
We’re interested in learning about how you use Bloom and sharing how we design an experience tailored for your needs. If you’re up for a conversation, sign up here.
As a bonus, enjoy a reward of $100, a charity donation, or a special community acknowledgment for your time.