Robots generate massive amounts of data, and managing it well is harder than it looks. Storage fills up fast, cloud transfer gets expensive, and real time ingestion is unforgiving when you're running cameras and sensors at high frequency.

This article covers practical strategies for handling robotic data, introduces ReductStore, and walks through a hands on example. Along the way, we cover native ROS integration, Grafana dashboards, MCAP export for Foxglove, a Zenoh API, and native S3 and Azure backends. We also compare ReductStore against Rosbag and MongoDB so you can pick the right tool for each part of your stack.

ReductStore 1.19.0 is now available. This release extends the storage model for robotics and telemetry workloads and introduces new integration points for ROS and Zenoh.

To download the latest release, visit the Download Page.

What's new in 1.19.0?​

The first major change in v1.19 is licensing. ReductStore Core is now open source under Apache 2.0, which makes the core database easier to evaluate, integrate, and extend in production systems.

The second major change is the data model. ReductStore now supports hierarchical entry names, similar to ROS topics, and adds entry attachments for schemas and metadata. This makes it possible to represent structured robotics data without flattening topic hierarchies or moving context into external systems.

The release also introduces a native Zenoh API for direct ingestion and querying over Zenoh, and ReductBridge for ROS1 and ROS2 integration.

Grafana is a powerful tool for visualizing time-series data, and it is widely used for monitoring and analysis. However, it does not natively understand robotics data formats, such as ROS 2 messages, since they are usually stored in binary formats (e.g., CDR). ReductStore's flexible query engine and extension system can bridge this gap. With the ReductROS extension, you can extract ROS 2 messages as JSON directly in Grafana queries. This enables you to build rich dashboards and alerts on your robotics data without preprocessing it into a different format.