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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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ReductStore v1.18.0 Released with Resilient Deployments and the Multi-entry API

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

ReductStore v1.18.0 Released

We are pleased to announce the release of the latest minor version of ReductStore, 1.18.0. 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 1.18.0?

In this release, we have added support for resilient deployments to build a more robust, fault-tolerant, and highly available ReductStore cluster. Now, you can implement hot-standby configurations, automatic failover, and seamless recovery to ensure uninterrupted service even in the face of hardware failures or network issues. You can also elastically scale read-only nodes to handle increased read workloads without impacting the performance of the primary nodes.

Additionally, we have introduced a new Multi-entry API that allows you to efficiently manage and query multiple entries in a single request. This API is designed to optimize performance and reduce latency when working with large datasets, making it easier to retrieve and manipulate data in bulk.

ReductStore v1.17.0 Released with Query Links and S3 Storage Backend Support

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

ReductStore v1.17.0 Released

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.

Building a Resilient ReductStore Deployment with NGINX

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

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.

NGINX Resilient Deployment