Google Cloud BigQuery Graph IDE
& Graph Visualization Tool

Explore, query and visualize your graph data in Google Cloud BigQuery Graph with gdotv.

A Purpose-Built IDE for Google Cloud BigQuery Graph Developers

BigQuery Graph brings native property graph capabilities to Google’s BigQuery data warehouse, letting you model and query connected data at massive scale without leaving your existing data environment. Powered by GQL and fully interoperable with SQL, BigQuery Graph offers intuitive pattern matching, relationship traversals, and filtering capabilities to graph-based applications like fraud detection, customer 360 profiles and supply chain analysis.

gdotv is a graph database client specially built with a comprehensive suite of tools to query and investigate connected data in BigQuery Graph. It’s quick to setup and easy to use, turning queries into interactive graph visualizations instantly. Whether you’re a developer, a data scientist or a business analyst, you’ll derive insights from your data effortlessly with gdotv.

You can write and execute GQL and SQL queries against your BigQuery property graphs, then visualize their results across a variety of formats, suited both to graph and relational data outputs. gdotv streamlines day-to-day graph data tasks, with a wealth of Integrated Development Environment (IDE) features. Using the gdotv graph database client will ensure you get the most out of your BigQuery Graph data and your time.

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Google Cloud BigQuery Graph

Google LLC, Alphabet Inc.

Query languages supported by gdotv: GoogleSQL

Learn more about Google Cloud BigQuery Graph

Feature image for Google Cloud BigQuery Graph.

An Overview of Google Cloud BigQuery Graph

Google BigQuery Graph brings native property graph capabilities directly into BigQuery’s data warehouse environment, eliminating the need to maintain a separate graph database. Rather than copying or moving data, it creates a logical graph view over existing BigQuery tables, designating them as node or edge tables in place. This means teams can model entities and relationships on top of data they already have, with no ETL overhead.

https://gdotv.com/wp-content/uploads/2026/02/google-bigquery-graph-knowledge-graph-data-architecture.jpg

How Google BigQuery Graph processes your data

Queries are written in GQL (Graph Query Language), which conforms to both the ISO GQL and ISO SQL/PGQ standards, and can be freely interleaved with standard SQL – so traversal logic and relational aggregations can coexist in a single query against the same underlying tables.

The property graph model in BigQuery follows the labeled property graph convention, where both nodes and edges can carry arbitrary key-value properties drawn directly from their backing table columns. Edge tables declare explicit source and destination key references pointing to node tables, and labels are assigned at schema definition time, though a single table can contribute multiple labels if needed. This makes it straightforward to map an existing relational schema – where foreign keys already encode relationships – directly into a graph without restructuring anything.

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What’s Possible with Google Cloud BigQuery Graph + gdotv

Easy Installation & Setup

Effortlessly integrate gdotv with your Google Cloud BigQuery Graph graph database with a simplified plug-and-play database connector. The gdotv database client provides straightforward database connection and configuration instructions to get you started in less than a minute.

This BigQuery Graph IDE is available to download for Windows, macOS, and Linux with a one-click installer to get you started instantly.

Connecting to BigQuery Graph with the gdotv database visualization tool is as easy as 1-2-3!

Manage all your database connections and queries from one central console.

Centralized Connection Management

gdotv can be used to query and compare data from a huge range of graph database vendors – simultaneously! We don’t just work with BigQuery Graph: gdotv data visualization tools fully integrate with various other graph technologies, including all Apache TinkerPop™ compatible graph databases and most LPG and RDF providers.

gdotv is fully compatible with query languages like Gremlin, Cypher, Google SQL, SQL:2023, SPARQL and more. Using an intuitive UI, you can switch between your connections and queries seamlessly.

Customizable Data Visualization

You can create custom visualization rules for your BigQuery graph database with gdotv to determine the look and feel of your data.

The gdotv database client boasts easy-to-configure style options that you can use to customize vertices and edges based on their labels and property values.

You can choose any color, size, or background image and adjust other elements to match your preference.

A sample graph display in gdotv using loading custom image file URL from node properties

The Graph Data Explorer enables no-code path exploration directly against your Google Cloud BigQuery Graph graph database in just a few clicks

No-Code Data Exploration with the gdotv Graph Data Explorer

Use the built-in gdotv Graph Data Explorer to navigate your Google Cloud BigQuery Graph data without using queries.

The Graph Data Explorer allows you to define path patterns to query from your data, using filters on both your vertices and edges. Elements in the declared path can be filtering according to their label, direction, and property values, allowing you to perform complex path-pattern searches with no code.

Instantly Load & View Your Data Model

It’s always important to understand and verify your data schema.

This is why gdotv provides an overview of your data structure with the data model view. For Google Cloud BigQuery Graph, there are two methods to construct the data model. The first is that gdotv is able to directly retrieve the model, if available, using the Google Cloud BigQuery Graph Schema API. Otherwise, gdotv can construct the data model directly from your data itself.

This data model is always just a click away, meaning that you always have a bird’s-eye view of your vertices, edges, and properties right at your fingertips.

Access your data model

Intuitive interface with syntax highlighting and validation

Take Advantage of Syntax Validation

Using gdotv language highlighting and syntax checking for GoogleSQL makes your code easier to understand and visually parse, warning you of any error that would prevent it from executing against your Google Cloud BigQuery Graph instance.

State-of-the-Art GoogleSQL Editor

The gdotv GoogleSQL code editor is the most powerful available – it offers data schema-accurate auto completion and embedded official documentation for GoogleSQL to give you all the information and suggestions you need to write your Google Cloud BigQuery Graph queries faster and more effectively.

gdotv’s built-in documentation for GoogleSQL, right at your fingertips

Google Cloud BigQuery Graph + gdotv Blog Posts

April 8, 2026

Introducing Support for Apache HugeGraph, GoogleSQL, SHACL Constraints, & More [gdotv v3.59.116 Release Notes]

Joe Stainke

January 27, 2025

G.V() Brings Interactive Graph Visualization To Google Cloud’s Spanner Graph

Arthur

Frequently Asked Questions (FAQs)

How can I get started with Google Cloud BigQuery Graph and gdotv?

Getting started with Google Cloud BigQuery Graph and gdotv is easy. It’s just one simple installation, available on Windows, macOS and Linux. No prerequisites, additional configuration or installation required. You can get started in seconds.

gdotv automatically detects your connection setting requirements based on your database hostname and prompts you for the required information for an easy onboarding experience.

Want a step-by-step walkthrough? Make sure to check out our demo, Get Started with Google Cloud BigQuery Graph + gdotv on YouTube.
Why use GQL (Graph Query Language)?

GQL is an ISO standard language designed for property graphs. It makes the use of graphs straightforward by providing a common structure of language and features that all graph database providers can leverage directly in their technologies.

Since Google Cloud Spanner is a multi-model database with support for relational and graph database, it has combined both querying formats under GoogleSQL, offering an unprecedented degree of flexibility and interoperability between SQL and ISO GQL.
What's the advantage of using LPGs over RDF?

Graph databases typically fall into two models: Labeled Property Graph (LPG) and Resource Description Framework (RDF).

The LPG model covers a broad class of databases, including Google Cloud BigQuery Graph, that use nodes, edges, properties and labels to represent graphs. They are optimised for real-time use and excel in applications like fraud detection, social network analysis and recommendation algorithms. There are also a wide range of methods to enforce schema compliance, with flexible conventions and definitions.

The RDF model refers to a highly standardized form of data management using global identifiers. Information is stored as a series of directed “triple” statements connecting a subject, predicate and object together. In addition, various languages built on RDF (such as RDFS and OWL) allow the construction of sophisticated ontologies and semantic reasoning. The high level of standardization also simplifies data integration from disparate sources. This makes RDF ideal for applications in large knowledge graph construction and research.

LPGs excel when performance and ease-of-use are a priority. Users typically find LPGs more intuitive, and they can be tailored to specific use-cases quickly and easily without the semantic complexity or steep learning curve of RDF.
What graph data visualization scenarios do gdotv customers most often implement?
Organizing data derived via powerful data visualization tools have several real-life applications. Graph visualization and analysis resources allow users to make informed decisions based on actual data.

Here are a few examples of the type of companies or clients that can leverage Google Cloud BigQuery Graph along with the robust data visualization aspect offered by gdotv:

Data scientists and managers: Visual data analysis allows users to uncover and understand emerging patterns and relationships between data points, discover valuable insights to make informed decisions on ways to transform business processes.

Cybersecurity groups: Build security graphs to represent protected assets, infrastructure, code dependencies or networks and visualize the connected relationships throughout the organization.

Business intelligence analysts: Create customized reports and visualizations that can be easily executed for analysts to investigate and communicate on interaction between business data points.

Fraud detection: Detect fraud patterns by modeling relationships between transactions and financial actors, then interactively visualize graph data to uncover and present potentially suspicious behavior.
How does gdotv secure my data?

gdotv Desktop runs locally on your device – no deployment needed and no handing over your data to a third-party system. Everything happens within your organisation’s network, and we have no access to your data.

gdotv Web versions run within your own environment, providing the same security benefits.

It’s easy to install and configure too: our setup wizard gets you connected to your graph database in seconds.
Can I connect more than one database at a time?

Yes! Whether you’d like to access multiple BigQuery Graph instances, or interact with other graph technologies at the same time, gdotv doesn’t limit you to a single database. You can establish as many connections as you like from within the intuitive UI and seamlessly switch between them.

Connecting is easy, and there’s no need to manage multiple vendor-specific user interfaces. With gdotv, query and compare results from all your RDF and labeled property graph databases under one umbrella.

gdotv: The Google Cloud BigQuery Graph IDE

Turn your graph data into connected insights when you use gdotv to query, explore, and visualize your Google Cloud BigQuery Graph graph database.

Sign up for a free trial today and discover how gdotv amps up your productivity as the perfect Google Cloud BigQuery Graph IDE and graph visualization tool.

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Google Cloud BigQuery Graph IDE& Graph Visualization Tool