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Alexey Timin
Software Engineer - Database, Rust, C++

A software engineer with a passion for databases, Rust, and C++, always looking for new challenges and opportunities to build efficient, scalable systems for managing large amounts of data.

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Data Acquisition System for Manufacturing: Shop Floor to Cloud

· 7 min read
Alexey Timin
Software Engineer - Database, Rust, C++

ReductStore on DAQ edge device

As modern manufacturing becomes increasingly data-driven, the need for efficient data acquisition systems is more critical than ever. In my previous article, Building a Data Acquisition System for Manufacturing, we discussed the challenges of data acquisition in manufacturing and how ReductStore can help solve them. Here we will learn how to use ReductStore at the edge of the shop floor and stream data to the cloud.

Building a Data Acquisition System for Manufacturing

· 13 min read
Alexey Timin
Software Engineer - Database, Rust, C++

Large manufacturing plants generate vast amounts of data from machines and sensors. This data is valuable for monitoring machine health, predicting failures, and optimizing production. It also serves as a foundation for building industrial AI models for predictive maintenance, quality control, and process optimization.

A Data Acquisition (DAQ) system collects this data, processes it, and stores it for further analysis. It typically consists of edge devices that gather real-time data, central servers or cloud storage for retention, and software that enables analytics and AI-driven insights.

DAQ System based on ReductStore

An example of a 3 tier DAQ system based on ReductStore.

Traditional automation solutions like SCADA and historians are complex, expensive, and not optimized for modern cloud-based AI applications. They often limit access to data, making it difficult for engineers and data scientists to develop machine learning models and gain actionable insights.

In this article, we’ll explore the challenges of building a modern DAQ system for manufacturing and how ReductStore can simplify the process and support ELT (Extract, Load, Transform) workflows for advanced analytics and AI applications.

ReductStore v1.14.0 Released With Many Improvements

· 6 min read
Alexey Timin
Software Engineer - Database, Rust, C++

ReductStore v1.14.0 Released

We are pleased to announce the release of the latest minor version of ReductStore, 1.14.0. ReductStore is a time series database designed for storing and managing large amounts of blob data.

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

What's new in 1.14.0?

This release introduces several new features and enhancements, including new conditional query operators, I/O and replication settings, and data browsing in the Web console.