With the rapid growth of time-series data in AI, IoT, and industrial automation, choosing the right database solution can significantly impact performance, scalability, and efficiency. As we covered briefly in our whitepaper, ReductStore and TimescaleDB are two powerful but distinct solutions, each designed to handle time-series data in different ways. ReductStore specializes in unstructured time-series data, making it ideal for edge computing and large binary objects. TimescaleDB, on the other hand, is an extension of PostgreSQL, optimized for structured time-series data with robust querying capabilities. In this article, we'll explore these differences between ReductStore and TimescaleDB, as well as their other strengths, and when to use each.

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.

With the rapid expansion of data-driven applications, choosing the right database for your workload has never been more crucial. As data complexity increases, so do the number of specialized solutions. ReductStore, as we've covered before, is a powerful alternative for handling time series unstructured data, but it's not the only player in the space. MongoDB, one of the most widely used NoSQL databases, also offers an effective solution for managing large-scale data. However, each has their own key areas of strength. In this article, we'll break down the differences between ReductStore and MongoDB, and help you determine which is best suited for your needs.