Rerun
Claim this toolData layer for physical AI: visualize, query, transform, and train on multimodal robotics data.
Free plan available Visit Website Freemium Visit Website
Tracked since 2026
The Bottom Line
- Price
- Free plan available. Compare plans
Key facts
- Open-source SDK for logging, storing, querying, visualizing, and training on multi-rate, multimodal physical data.
- Commercial Hub provides managed catalog, byte-range indexing, and streaming to GPUs for scalable production use.
- Supports Python, Rust, C++ APIs with SQL/dataframe queries and a declarative visualization framework.
Pros
- Free and open-source SDK with full toolchain for local use
- Supports multiple programming languages (Python, Rust, C++)
- Unified data layer covering visualization, query, transform, and training
Cons
- Commercial Hub requires contacting sales for pricing and setup
- Primarily designed for physical AI and robotics, may be overkill for simpler data use cases
What is Rerun?
Rerun is an open-source SDK and commercial platform designed as a unified data layer for physical AI, particularly robotics and multimodal sensor data. The open-source SDK provides tools for logging, storing, querying, visualizing, and training on multi-rate, multimodal data, with native APIs in Python, Rust, and C++. It includes an interactive viewer, a declarative visualization framework, SQL and dataframe query capabilities, and a PyTorch dataloader for direct streaming of recordings to GPUs. The columnar .rrd file format enables efficient storage and retrieval of temporal data.
The commercial Rerun Hub extends the SDK with a managed catalog, byte-range indexing across object stores, and streaming dataset mixes for training. It provides single-tenant isolation, authentication/SSO, and deployment in the customer's preferred cloud region, all while keeping data in the customer's own S3-compatible buckets. Rerun is built with a focus on open source stewardship, contributing to projects like egui and wgpu.
Data compiled by Toolradar Pricing checked · How we evaluate
Source rerun.io Key Features
- Log, store, and convert multi-rate multimodal data in columnar .rrd files
- SQL and dataframe queries across recordings and catalog
- Declarative visualization framework with interactive viewer (desktop + web)
- PyTorch dataloader for streaming recordings directly to GPUs
- Byte-range indexing for fast lookups across object stores
- Catalog and metadata management with single-tenant isolation
- Auth and SSO for team collaboration
- Deployment in customer's own cloud region with S3-compatible storage
Pricing Plans
Pricing checked Oct 2, 2026. Source: rerun.io/pricing, read Oct 2, 2026
| Plan | Price | Details |
|---|---|---|
| Open source SDK | Free forever |
+7 more Show less
|
| Commercial Hub | Contact us |
+6 more Show less
|
Is Rerun worth the price?
Good value
The free open-source SDK is genuinely generous, offering a full-featured local solution with no cost, ideal for individual developers and small teams.
The Commercial Hub's 'contact us' pricing suggests it is likely expensive, targeting enterprises with managed infrastructure, SSO, and dedicated support. Best for teams that need scalable, secure data management for physical AI workloads.
Hidden Costs & Gotchas
Potential minimum commitment for dedicated support
Rerun by the numbers
| Metric | Rerun | Peer median | Position (1 is best) |
|---|---|---|---|
| Free plan | Yes | 9 of 18 have one | n/a |
| Listed as an alternative to | 3 tools | 2 | #7 of 18 (joint) |
Listed as an alternative to: #6 on 2026-10-16 to #7 on 2026-11-02 (rank among 18 tools, 1 is best).
Each position is counted among the tools that have data for that row, as noted under it. All AI Data Labeling data · How we compute this. Advertising and placement fees are not inputs to any position.
Cite this: Toolradar, “Rerun by the numbers”, Nov 2026.
Reviews
$99 Free with your review
Write a review Review Rerun, get a free AI guide
Share your experience and we will send you Improve Your Thinking Patterns Using ChatGPT, free.
Best Rerun Alternatives
Top alternatives based on features, pricing, and user needs.
Still deciding?
Most buyers shortlist 2 or 3 tools before committing. Pull a side-by-side comparison or browse the full alternatives shortlist below.
Explore More
Rerun FAQ
What types of data does Rerun handle?
Rerun handles multi-rate, multimodal data common in physical AI, such as sensor streams, camera images, lidar scans, robot state logs, and any time-series data with spatial or temporal structure.
Can I use Rerun with my existing object storage (e.g., S3)?
Yes, Rerun Hub is designed to work with your own S3-compatible object stores, keeping your data in your buckets while providing byte-range indexing and catalog management.
How does Rerun support training on recorded data?
Rerun includes a PyTorch dataloader that can stream dataset mixes directly from object storage to GPUs, enabling training without an explicit export step. The dataloader is column-aware and video-codec-aware.
What programming languages are supported by the Rerun SDK?
The Rerun SDK offers native APIs in Python, Rust, and C++, with all three sharing the same underlying data model and capabilities.
Is the Rerun viewer available as a web application?
Yes, the interactive viewer is available both as a desktop application and as a web application, built with WebGPU and WebGL support via the egui and wgpu projects.
How does Rerun handle multi-rate data (different frequencies for different sensors)?
Rerun stores data in columnar chunks indexed by time, so multi-rate data is naturally handled by logging each sensor at its own frequency, and queries can align timestamps across streams.
Can I deploy Rerun Hub in my own cloud region?
Yes, Rerun Hub is single-tenant and can be deployed in the cloud region you choose, ensuring data residency and compliance requirements.
What is the difference between the open-source SDK and Rerun Hub?
The open-source SDK is a free, local toolchain for logging, querying, visualizing, and training. Rerun Hub is a commercial managed backend that provides a persistent catalog, byte-range indexing across object stores, and multi-user collaboration features.
Source: rerun.io