31 posts tagged with "news"

ReductStore 1.19.0 is now available. This release extends the storage model for robotics and telemetry workloads and introduces new integration points for ROS and Zenoh.

To download the latest release, visit the Download Page.

What's new in 1.19.0?​

The first major change in v1.19 is licensing. ReductStore Core is now open source under Apache 2.0, which makes the core database easier to evaluate, integrate, and extend in production systems.

The second major change is the data model. ReductStore now supports hierarchical entry names, similar to ROS topics, and adds entry attachments for schemas and metadata. This makes it possible to represent structured robotics data without flattening topic hierarchies or moving context into external systems.

The release also introduces a native Zenoh API for direct ingestion and querying over Zenoh, and ReductBridge for ROS1 and ROS2 integration.

Hello, everyone!

Starting with ReductStore v1.19, we are changing how we license and package the project. From this version onward, ReductStore is split into two editions: ReductStore Core and ReductStore Pro.

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.