Release Notes

G.V() 2.10.17 Release Notes

G.V() 2.10.17 Release Notes

Today’s update announcement is actually a batch of the last two feature releases (2.5.9 and 2.10.17) which happened just a couple weeks apart of each other. The focus of both of these updates is mostly on the Large Graph View and its performance.

New Graph Filtering and Navigation options

As part of release 2.5.9, two new major features have been added to the Large Graph View to allow more advanced filtering and navigation options: the graph filtering view and the vertex neighbors highlighting tool.  
 
Graph Filtering View

The purpose of this view is simple: to provide new filtering capabilities built upon the data available in your graph. To do so, we now leverage element property values to display filtering and element selection options. It also allows quickly determining the spread of values for a given property on a vertex or edge. 

As always a picture is worth a thousand words and we’ve made a quick animation highlighting these new capabilities which you can check out below:

demo of graph filters on G.V() based on property values of vertices and edges

The filtering view includes a few nifty features to assist with navigation, such as the ability to sort filters by name or size and a search bar so you can quickly get to the property value you’re looking for. It’s a really powerful tool that also allows for some quick insights on your graph, so make sure to try it out!

Vertex Neighbors Highlighting

We’ve reworked and improved the neighbor navigation and highlighting tools available on G.V() to provide a more advanced and insightful experience. Previously, G.V() allowed incrementally selecting neighbors for a vertex but the UI was somewhat hidden and unclear. To remediate this, we’ve added a new tab under the Vertex Details tab as shown below:

This new capability calculates the maximum number of consecutive hops via a neighbor’s edges and their consecutive vertices and edges to reach the farthest (and closest) points of the graph from the currently selected vertex. 

Each calculated hop then contains a report of which vertices can be found at that hop as well as how much of the graph they cover. 

We’ve got another animation to illustrate this functionality further, shown below:

The example above is pretty insightful as it pertains to airports, countries and routes between them. It allows viewing how many hops (in this case airplane route) are required to travel from one country or airport to any airport, country or continent shown on the graph. Note that in this example for brevity only a subset of all airports and routes are showing but this should give you a good idea of where this tool can be effective in delivering visual insights from your graph.

Advanced Corporate Proxy Configuration Options

Some of our users, maybe yourself, need to deploy and use G.V() within a fairly airtight environment. Sometimes this would require the use of a corporate proxy of which your graph databases may be hidden behind. This new release of G.V() finally brings full proxy support to allow connecting to any graph database behind a proxy, through a set of new options that can easily be configured and detailed in our documentation. 

Large Graph View Performance and UX improvements

The Large Graph View is a core component of G.V() that we’ve been continuously investing in since we first introduced it in 2022. It is powered by the SigmaJS graph visualization library (and it’s sister graph library, Graphology). Earlier this year, the SigmaJS team has announced the release of its long awaited v3, which we have proudly supported and sponsored. If you’re interested in building graph visualization then you simply must check SigmaJS/Graphology – it’s free and open-source!

This new v3 SigmaJS version is of course relevant to this post as we’ve now officially upgraded G.V() to use it, and it brings significant performance improvements as well as new rendering capabilities to provide a more versatile visual experience to the framework. The goal of these improvements is to allow SigmaJS (and therefore G.V()) to render more elements, faster, and increase the speed of processing graph updates for re-renders (e.g. when switching stylesheets in G.V()).

We’ve taken the opportunity with upgrading to SigmaJS v3 to also review the rendering of element labels to give them a crisper look and feel. Most important however is that with this new release, SigmaJS finally supports the drawing of curved edges. This may seem like a small change but it is extremely useful for graphs that contain many bidirectional relationships, as these were previously difficult to tell apart visually in G.V(), as shown in the comparison below:

A graph display with curved edges
The same display without curved edges

 

 

With this new capability it’s now much easier to understand relationships in complex, highly interconnected graphs.

This is our first big project with the SigmaJS team and we’re hoping to bring more in the future, so stay tuned! 

What’s next for G.V()?

We’re working on a few big projects behind the scenes but it’s too early yet for us to share more details. In the meantime you can expect to continue seeing regular updates to our product with a focus on user experience and performance. If you have any thoughts of your own on what you’d like to see next in G.V(), make sure to let us know by emailing us at support@gdotv.com. Our goal is to provide the best graph database tooling possible and there’s no better way to achieve this than by listening to what our users want and need from our product – your feedback is what drives our roadmap.

G.V() 1.57.81 Release Showcase

Hey! We’re starting a new tradition of releasing blog posts to quickly show case new features of G.V() whenever a feature update is released. To kick this off, let’s have a look at what’s in store for this update!

 Improved Query Editor User Experience

G.V()’s query editor is an essential part of the software and one that hasn’t seen too much change since it was first released. So we thought now’s a good time for a fresh coat of paint and a little rework of the user experience. 

First of all, we’ve redesigned all the popups to match the overall style of the application better. 

We’ve also reworked the sidebar popup to be permanent but easily toggled – it now contains some useful shortcuts such as a view of your data model as you type your query and it will continue to display context- aware information as you type your query (e.g. Gremlin documentation, data model documentation, etc). Moreover, when highlighting a specific step in your query, this assistant feature will also display the corresponding documentation. 

We’ve also added a never seen before (in the Apache TinkerPop world!) syntax highlighting feature that will really improve readability, especially on complex queries. Check it out: 

 

G.V() Gremlin Syntax Highlighting demo

This is a first phase of improvements that will soon be followed by more – our focus will be on additional highlighting and query writing assistance scenarios (e.g. project/select key highlights, labels and property keys documentation display on highlight, etc).

 Apache TinkerPop 3.7.0 Official Support and G.V() Playground upgrade

 G.V() now officially supports Apache TinkerPop 3.7.0! Thanks to the addition of Properties on Elements in this new version, all users using Gremlin Server 3.7.0 will benefit from considerable performance improvements when fetching large amounts of vertices and/or edges through G.V().

We’ve also upgraded our own in-memory graph, G.V() Playground, to 3.7.0 meaning that it will also benefit from the same performance improvements. 

We’ve added GoLang as a translation target to G.V(), as has been introduced in this new release of Apache TinkerPop. 

There are further performance improvements that were made to the result serialization aspects of G.V() which all Apache TinkerPop graph systems and versions will benefit from in this new release. 

New Amazon Neptune Audit Logs View

There’s a new Amazon Neptune log view in G.V() to complement the previously released Slow Query Logs view. Much like the former, it is designed to allow users to quickly profile and debug Gremlin queries running on their Amazon Neptune database. We’ve also added some additional controls on both tables to select the columns to display.

Note that much like the Slow Query logs view, this requires the use of the AWS CLI in order to fetch the logs from Amazon CloudWatch. Check out our documentation and the Amazon Neptune Audit Logs user guide for more details.

The addition of this Audit Log View makes it easier than ever to identify queries running against your database and re-run them if necessary. Once again, GIF demo time!

Amazon Neptune Audit Log view

 

Everything else…

There’s a few bug fixes and other minor improvements in this release, for reference, see the full release notes below:

G.V() is a continuously evolving software – we have monthly feature releases and monthly maintenance releases running in tandem to ensure both that  new features regularly hit the shelves and any defects/bugs are promptly squashed. We’ll post about every feature release to give you a better idea of what’s changing (and why you should update!). 

If you have already, make sure to also subscribe to our newsletter to keep up with all things G.V(). See you next month!