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G.V() 3.34.79 Release Notes: Oracle Graph Support, new no-code exploration, and more

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G.V() 3.34.79 Release Notes: Oracle Graph Support, new no-code exploration, and more

Introduction

Our latest release, 3.34.79, is now available. In this new version, we’re bringing support for Oracle Graph (Oracle 23ai) as well as a flurry of user experience improvements, particularly on our no-code data explorer. Let’s dive in!
 

Oracle Graph Support

Our headline item for this release is the addition of support for Oracle Graph, available on Oracle 23ai using the SQL:2023 querying language. The graph database industry is constantly evolving, and the emergence of graph on relational technology is an exciting new direction that will undoubtedly contribute to further introducing the power of graph technology to the masses.
 
We’ve worked in direct collaboration with the Oracle Graph team to put together this integration, and we’re delighted to introduce G.V() to the Oracle Graph community as the first available IDE for SQL:2023, with first class graph visualization functionality.
 
As always, connecting your Oracle Graph instance to G.V() is a breeze:
 
Connecting G.V() to Oracle Graph is quick and easy, supports selecting which graph to connect to and with which user
Connecting G.V() to Oracle Graph is quick and easy, supports selecting which graph to connect to and with which user
 
This first release focuses on the ability to query, expolore and visualize graph (and relational data) from Oracle 23ai. In future updates, we will introduce the ability to edit data interactively and create parameterised reports – stay tuned.
 

New and improved path pattern search capabilities

We’ve thoroughly reworked our graph data explorer to allow performing complex path pattern searches with no code. This new user experience is available for all the databases we support, and can be triggered from individual nodes in any graph visualization.

With it, you can define path patterns to query from your data, using a combination of node and edge filters. Elements in the declared path can be filtering according to their label, direction and property values. Here it is in action:

No-code path exploration directly against your graph database in just a few clicks.
No-code path exploration directly against your graph database in just a few clicks.

This is a big first step towards no-code capabilities in G.V(). Next, we’re planning to add advanced conditional expressions for filters (AND/OR logic) and pattern repetition configurations.

Kuzu 0.11.0 upgrade brings single file database storage

The Kuzu team has recently announced the release of Kuzu 0.11.0, bringing DuckDB style single file database storage, along with many other new features and improvements.

This new storage format brings significant user experience improvements to both Kuzu and allows connecting to your Kuzu database from G.V() even more seamlessly. 

As this new release introduces a brand new storage format, you will need to migrate your Kuzu database to 0.11.0 to continue using it, as documented in their migration guide. You can then simply edit your Kuzu connection on G.V() by pointing to the path of your Kuzu database file.

As shown below, connecting to Kuzu 0.11.0 on G.V() is easy as 1-2-3:

Connecting to Kuzu using the single file storage method on G.V() takes less than 15 seconds.
Visualizing your Kuzu graph database using the single-file format is nearly instant!

In the next release of G.V(), we’ll introduce the ability to also upload these database files as copies, both on our web and desktop version. This will allow you to explore Kuzu data without needing to manage concurrency with other processes that may also access the database.

Improved Gremlin & Cypher syntax handling

We pride ourselves on delivering best in class query editing tools for the graph database languages we support. Following the recent release of Cypher25, we’ve upgraded our Cypher engine to support this new syntax.

We’ve also significantly reworked our Gremlin autocompletion engine to deliver better performance and accuracy on suggestions. One area of focus in this rewrite has been handling of nested traversal hints, which have historically been challenging to implement.

Our latest release introduces a fully functional autocompletion engine for nested traversal in Gremlin queries, making G.V() the most advanced developer tooling available to Apache TinkerPop users.

Single Sign On & User Federation  on our web version

The web version of G.V() (available on AWS Marketplace) now supports advanced Identity & Access Management features such as Single Sign On and User Federation via Keycloak. It’s available as a one click deploy on AWS Marketplace and we’re working on self-service deployment version. If you’d like to find out more about it, please contact us at support@gdotv.com.
 
With this, you can now manage users on G.V(), integrate our platform with your preferred identity solution and leverage industry standards for authentication such as SAML or OIDC to securely authenticate to G.V().
 
We’re in the process of adding Role-Based Access Control functionality to provide fine grained authorisation capabilities, bringing us closer to an enterprise offering for our product – watch this space.
 

Everything else

This is not an exhaustive list (and look) at what’s featured in our latest release. In no particular order, here’s a few other features and improvements you’ll find in this update:

  • Added schemaless data support for Google Cloud Spanner Graph
  • Added CSV/JSON export functionality on vertex and edge tables
  • Added support for Azure OpenAI private endpoints
  • Improved query result processing performance

What’s next

We regularly post previews of upcoming G.V() features on LinkedIn | X | BlueSky, so make sure to follow us on social media to find out more.

Our next release, planned for late August, will feature RDF/SPARQL support, making G.V() the first IDE to work across both Labeled Property Graph and Resource Description Framework technologies.

We’re also planning to begin integration work with GQL-native graph databases with a view to release in September. There’s a lot of other cool stuff going on that we’re not quite ready to talk about yet – but as always we’ve got tons of cool new features cooking.

Arthur Bigeard

Hey! I'm Arthur Bigeard, the founder of gdotv Ltd. I've discovered and grown a passion for Graph Databases in my previous jobs, which I've channeled into the making of our flagship product, G.V(). My mission is to create a universal, plug-and-play graph database client to simplify & accelerate the day-to-day tasks of graph data professionals.

→ Arthur Bigeard

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