We are pleased to announce the release of the latest minor version of ReductStore, 1.9.0. 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 1.9.0?​

This release, version 1.9.0, introduces several key improvements and features to enhance the overall performance and user experience. These updates include optimizations for disk space management, the inclusion of replication support in the Web Console, and the provision of license information in the HTTP API.

In this article, we will compare two data storage solutions: ReductStore and Minio. Both offer on-premise blob storage, but they approach it differently. Minio provides traditional S3-like blob storage, while ReductStore is an alternative to store a history of blob data. We will focus on their application in scenarios that require storage and access to a history of unstructured data. This includes images from a computer vision camera, vibration sensor data, or binary packages common in industrial data.

Handling Historical Data​

S3-like blob storage is commonly used to store data of different formats and sizes in the cloud or internal storage. It can also accommodate historical data as a series of blobs. A simple approach is to create a folder for each data source and save objects with timestamps in their names:

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In this guide, we will explore the process of storing Kafka messages that contain unstructured data into a time series database.

Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time.

ReductStore allows to easily setup a data sink to store blob data for applications that need precise time-based querying or a robust system optimized for edge computing that can handle quotas and retention policies.

This guide builds upon an existing tutorial which provides detailed steps for integrating a simple architecture with these systems. To get started, revisit "Easy Guide to Integrating Kafka: Practical Solutions for Managing Blob Data" if you need help setting up the initial infrastructure.

You can also find the code for this tutorial in the kafka_to_reduct demo on GitHub.