ROS2 is widely used for building robotic systems with sensors like cameras, LiDAR, and IMUs. While it's great for communication (e.g., publishing and subscribing to topics), it lacks a built-in solution for storing large amounts of unstructured data, such as images.

Bag files are commonly used to store data in ROS2, but they aren't a good fit for long-term storage or real-time streaming. They're mainly meant for recording and replaying mission data or episodes, not for managing large volumes of unstructured data.

Addressing this challenge, this blog post will guide you through setting up ROS2 with ReductStore a high-performance storage and streaming solution optimized for unstructured, time-series data.

We will focus specifically on image data, but if you are interested in a more general overview you can read How to Store and Manage Robotic Data which covers the challenges and strategies for storing and managing robotic data in general.

For the full code example, we will be using the reduct-ros-example repository, which provides a complete implementation of the concepts discussed in this article.

Your robot has a camera. You are storing what it sees as one image per frame, and that works until someone asks to watch it. Then you write a script that extracts ten thousand JPEGs from storage, sorts them by timestamp, and calls ffmpeg. You write that script again the next time anyone wants thirty seconds of footage.

Storing the encoded stream removes that step. ReductStore stores H.264 chunks as time-indexed records, and the ReductVideo extension returns an MP4 you can open in a player.

A rosbag recording is ultimately written to files, and a single file cannot grow forever. Something has to close it at some point, so rosbag2 makes you pick: ros2 bag record -a -b 100000 closes one every 100 kilobytes, or -d 9000 closes one every 9000 seconds. Either way, a recording that runs for hours comes out as a directory of many small files instead of one huge file that becomes awkward to work with.

Splitting a recording into five minute bags seems like a simple solution. The problem starts when you need to turn them back into one file.

A rosbag2 user reported that merging 300 GB of split recordings required roughly 600 GB of disk capacity. The original 300 GB stays on disk while another 300 GB is written out as the merged bag.

Splitting solves one problem. Merging creates another, and it is easy to underestimate.