Modern robots collect a lot of data from sensors, cameras, logs, and system outputs. Managing this data well is important for debugging, performance tracking, and training machine learning models.

Over the past few years, we've been building a storage system from scratch. As part of that work, we spoke with many robotics teams across different industries to understand their challenges with data management.

Here's what we heard often:

• Only a subset of what robots generate is actually useful
• Network connections are not always stable or fast
• On-device storage is limited (hard drive swaps is not practical)
• Teams rely on manual workflows with scripts and raw files
• It's hard to find and extract the right data later
• ROS bag files get large quickly and are difficult to manage

In this article, we compare four tools built to handle robotics data: ReductStore, Foxglove, Rerun, and Heex. We look at how they work, what they're good at, and which use cases they support.

If you're working with robots and need to organize, stream, or store data more effectively, this overview should help.

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.