Features
Log multimodal, multi-rate data with Python, C++, or Rust SDK
Interactive viewer with 2D, 3D, map, graph, and tensor views
SQL and dataframe queries over recordings and catalog
Transform data with derived columns and schema evolution
Train directly via PyTorch dataloader from .rrd files or Hub streams
Store data as column-chunks in .rrd files for efficiency
Declarative visualization framework with blueprint defaults and overrides
Byte-range indexing and retrieval from object storage (Hub)
Team collaboration with shared recordings and link sharing (Hub)
Open source SDK under Apache-2.0/MIT license
Web viewer for browser-based visualization
Layers and local catalog for organizing recordings
Support for time-series, 3D, and tensor data modalities
Distributed tracing for LLM agents
Capture prompts, retrievals, tool calls, outputs
Human annotations on traces
Create datasets from traces
Run experiments to compare changes
OpenTelemetry-native instrumentation
Self-host locally, Docker, or Kubernetes
Cloud instances with free tier
Vendor agnostic: any model or framework
3M+ monthly downloads, 9k+ GitHub stars
