If you’re collecting high-rate sensor or video data at the edge and need zero-downtime ingestion and fault-tolerant querying, an active–active ReductStore setup fronted by NGINX is a clean, practical pattern.

This tutorial walks you through the reference implementation, explains the architecture, and shows production-grade NGINX snippets you can adapt.

What We’ll Build​

We’ll set up a ReductStore cluster with NGINX as a reverse proxy, separating the ingress and egress layers. This architecture allows for independent scaling of write and read workloads, ensuring high availability and performance.

We are pleased to announce the release of the latest minor version of ReductStore, 1.16.0. 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 1.16.0?​

The v1.16.0 release introduces two new extensions designed to enhance data workflows for robotics and columnar data, along with support for replicating context records during queries.

In robotics development, effective visualization and analysis tools are essential for monitoring, debugging, and interpreting complex sensor data. Platforms like RViz, Foxglove, and Rerun play a key role at the visualization layer of the observability stack. They help developers interact with both live and recorded data. These tools rely on timely, well-structured access to the underlying data streams. That's where ReductStore comes in. It handles the data logging, storage, and processing, with a focus on capturing high-volume time-series data efficiently. ReductStore aims to integrate with tools like RViz, Foxglove, and Rerun, supporting a complete observability pipeline: from raw data ingestion to actionable insights.