How Foxglove compares to Webviz, Cruise’s original ROS data visualization tool.
Webviz is a web-based tool developed by Cruise (RIP 🪦) for visualizing robotics data directly in a browser. It supports ROS bag files and live robot data, enabling tasks like debugging and analysis. Webviz allows users to customize layouts using panels such as 3D visualizations, plots, and image displays.
If you’re familiar with Foxglove’s history, you may know that many members of the Foxglove team previously worked at self-driving car company Cruise, and that Foxglove began as a fork of Cruise’s Webviz project. Many people are curious about how these two apps compare. While Foxglove and Webviz can appear similar at first glance, their capabilities have diverged significantly. In fact, a significant number of Foxglove users transitioned from Webviz to Foxglove to enhance and scale their workflows. So, why consider Foxglove when Webviz may already feel familiar? The answer lies in understanding the similarities, the differences, and what Foxglove brings to the table.
Foxglove is more than a multimodal data visualization tool—it’s a comprehensive platform purpose-built for robotics and embodied AI development. Supporting diverse data formats like MCAP, ROS, Protobuf, and JSON, Foxglove seamlessly facilitates live and recorded data analysis through over 20 visualization panels. It fosters collaboration with shareable layouts and extensible customization, empowering teams to work efficiently. Additionally, Foxglove simplifies uploading, streaming, organizing, and managing petabytes of data. Whether debugging complex 3D interactions, analyzing time-series data, or managing multimodal datasets, Foxglove delivers a modern, flexible, and robust solution designed to meet the challenges of robotics development.
“Foxglove helped us to supercharge our processes. We went from days to minutes when finding the root cause of an issue.” J’aime Laurenson, Product Lead at Wayve
Both Webviz and Foxglove offer the convenience of web-based applications, allowing you to start visualizing data by simply opening a browser and navigating to a URL. Built on modern web technologies like WebGL and WebAssembly, these platforms deliver rich, interactive visualizations that run seamlessly in a browser, making it easy to access and analyze robotics data without the need for complex installations or setups.
Both Webviz and Foxglove streamline robotics development by consolidating the tools needed for visualizing and debugging data into a single cohesive environment. Instead of juggling multiple tools in separate windows, like RViz or rqt, these platforms allow you to manage various workflows within a unified workspace.
With a variety of modular panels available, you can plot values of interest, render interactive 3D scenes, and drill down into topic messages, all within a tiled layout you can customize. Rearrange and configure these panels to suit your workflow, then share the final layout with your team to maintain alignment. This integrated approach eliminates context switching, keeping you focused and accelerating your robot iteration process.
Foxglove extends far beyond Webviz by introducing a range of powerful panels, specifically designed to meet the diverse needs of robotics teams across industries. Key panels have been thoughtfully redesigned to maximize performance and usability, ensuring they align with the complex workflows of modern robotics development.
Example of new panels:
Example of redesigned panels:
These are just a few examples of Foxglove’s modular panels, with over 20 out of the box to choose from.
Foxglove’s Image and 3D panel supports additional encodings including over 15 raw image formats and the four leading image and video encodings:
While both Foxglove and Webviz support ROS 1 Rosbridge connections and bag file playback, Foxglove expands on these capabilities with a broader range of data connection options and formats:
Foxglove’s extensive data connectivity options and supported formats make it a versatile tool for robotics teams handling diverse data formats and workflows.
Getting started with Webviz and Foxglove is easy with the web app, but Foxglove offers options for both a web and desktop app. Drawing from experiences with ROS, Foxglove understands the frustrations of installing native tools that require highly specific environments. With Foxglove, you can bypass those complications and begin working seamlessly. Access it instantly in your browser at app.foxglove.dev or download the desktop app for Linux, macOS, and Windows—whichever suits your workflow.
Unlike Webviz, Foxglove eliminates dependency challenges, ensuring you can view and analyze your robotics data in seconds. Whether you choose the convenience of a browser or the robustness of the desktop app, Foxglove guarantees a smooth and efficient start to your robotics development.
Webviz is good for visualizing ROS data as an individual developer or hobbyist, but it lacks built-in features for collaborative workflows or sharing debugging setups with a team.
While Foxglove is committed to providing general-purpose tools for robotics across diverse applications, we understand that every robotics team has unique, project-specific requirements that may not always be addressed out of the box. To bridge this gap, custom extensions were introduced, empowering you to develop bespoke panels tailored to your specific needs. Instead of waiting for new features, you can directly add custom functionality to your local Foxglove instance and share it in the Foxglove extensions registry.
What sets Foxglove apart are its additional team-oriented features. Organization Layouts enable you to create, edit, and share your custom visualization layouts across your entire team. Additionally, Foxglove provides a central repository where team members can upload, access, and explore shared data. Teams can quickly locate events of interest and stream relevant data directly into visualizations for deeper analysis. This collaborative approach streamlines debugging and fosters more effective teamwork, making Foxglove a valuable tool for scaling your development.
Webviz relies on the ROS ecosystem to record and access data, it does not have additional data collection and ingestion capabilities. Foxglove streamlines data collection and management with the Foxglove Agent, enabling real-time or on-demand ingestion of recordings. Whether you’re importing data, uploading local files, or connecting to a live robot, the Foxglove Agent ensures seamless data serialization, transportation, and processing.
Foxglove handles asynchronous data streams from diverse sources or massive datasets with ease, indexing data by device, time, and topic for organized management. With customizable retention policies and smooth integration into existing data pipelines, you can optimize storage and maintain efficiency. Flexible access through the UI, API, or CLI lets you retrieve exactly the data you need for streamlined exploration, analysis, and decision-making.
Webviz does not have any data management capabilities. Foxglove, on the other hand, provides a central data repository that allows you to upload, explore, set retention policies, and stream your robotics data.
The Timeline view in Foxglove displays each device’s data availability across time. It highlights whether data is ready to stream, actively being processed, or available for import from your robot’s disk using the Foxglove Agent. Use the Timeline to zoom in on specific devices and time ranges to see the status of your data. From there, you can fetch data that’s available for import, visualize it for in-depth analysis, or export it for use with other tools.
Devices in Foxglove serve as representations of all the real and simulated robots your organization tracks. They act as a central reference point for managing and organizing data collected during operations.
When importing data, you can associate each recording with the device that generated it. This linkage ensures that all data is properly categorized and traceable, making it easier to analyze recordings, understand context, and troubleshoot specific robot behaviors. By organizing recordings under their respective devices, Foxglove streamlines data management and enhances collaboration across your team.
Events are key markers within your organization’s recordings, allowing you to quickly identify and categorize specific moments or periods of interest. These events streamline data exploration and help you focus on relevant subsets, improving efficiency during analysis.
Each event is tied to a specific device and requires essential information: a timestamp and a duration. For instantaneous events, the duration is set to zero. Events can also include optional metadata, providing additional context or details to enhance searchability and categorization. By leveraging events, you can simplify the process of locating and analyzing critical moments in your recordings, making your workflows more precise and efficient.
Foxglove’s modern, intuitive interface and support for diverse data formats, including ROS (1 and 2), MCAP, Flatbuffers, Protobuf, and JSON, and video codecs like H.264, H.265, VP9, and AV1, and time-series, text, geospatial and sensor data, ensure a seamless experience for both real-time and historical analysis. Foxglove’s management and performance handling large datasets allows teams to gain actionable insights efficiently, whether debugging complex systems or monitoring live operations.
“The integration was surprisingly straightforward, enabling us to quickly transition from using multiple disjointed tools to a unified workflow. This significantly reduced the barriers for team members to engage with system data.” Scott Butters, Staff Machine Learning Engineer, Aescape
Check out the Why Foxglove guide to learn more, sign up and get started for free, and join our discord community to share your projects and experiences and work with the best of them!
