Mobile robots produce a lot of data (camera images, IMU readings, logs, etc). Storing this data reliably on each robot and syncing it to the cloud can be hard. ReductStore makes this easier: it's a lightweight, time-series object store built for robotics and industrial IoT. It stores binary blobs (images, logs, CSV sensor data, MCAP, JSON) with timestamps and labels so you can quickly find and query them later.

This introduction guide explains a simple setup where each robot stores data locally and automatically syncs it to a cloud ReductStore instance backed by Amazon S3.

Robotics teams today wrestle with data that grows faster than their infrastructure. Every robot generates streams of images, sensor readings, logs, and events in different formats. These data piles are fragmented, expensive to move, and slow to analyze. Teams often rely on generic cloud tools that are not built for robotics. They charge way too much per gigabyte (when it should cost little per terabyte), hide the raw data behind proprietary APIs, and make it hard for robots (and developers) to access or use their own data.

ReductStore introduces a new category: a database purpose built for robotics data pipelines. It is open, efficient, and developer friendly. It lets teams store, query, and manage any time series of unstructured data directly from robots to the cloud.

We are pleased to announce the release of the latest minor version of ReductStore, 1.17.0. ReductStore is a high-performance storage and streaming solution designed for storing and managing large volumes of historical data.

To download the latest released version, please visit our Download Page.

What's new in 1.17.0?​

This release includes several new features and enhancements. First, there are query links for simplified data access. Second, there is support for S3-compatible storage backends.

These new features enhance the usability and flexibility of ReductStore for various use cases in the cloud and on-premises environments and make it easier to share and access data stored in the database.