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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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Visualize Robotics Data in Grafana with ReductStore

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

Grafana query editor with ReductROS extension

Grafana is a powerful tool for visualizing time-series data, and it is widely used for monitoring and analysis. However, it does not natively understand robotics data formats, such as ROS 2 messages, since they are usually stored in binary formats (e.g., CDR). ReductStore's flexible query engine and extension system can bridge this gap. With the ReductROS extension, you can extract ROS 2 messages as JSON directly in Grafana queries. This enables you to build rich dashboards and alerts on your robotics data without preprocessing it into a different format.

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.