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9 posts tagged with "comparison"

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ReductStore vs. MongoDB: Which One is Right for Your Data?

· 7 min read
Anthony Cavin
Data Scientist - ML/AI, Python, TypeScript

ReductStore and MongoDB Comparison

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.

ReductStore and IoTDB: Time Series Data Specialists

· 6 min read
Anthony Cavin
Data Scientist - ML/AI, Python, TypeScript

IoTDB and ReductStore Comparison

With the vastly growing amount of data produced world-wide, it is no surprise that there are an ever increasing number or methods and approaches to dealing with this influx. It is also no surprise that specialized solutions are developed for subsets of this data. Reductstore, as we've covered in numerous previous articles, is highly specialized in handling one such subset, time-series data. But it is not the only one. IoTDB is another such solution, and also very good at what it does. In this article, we will help you to understand the differences between the two, and where one can excel over the other.

The MinIO alternative for Time-Series Based Data

· 10 min read
Anthony Cavin
Data Scientist - ML/AI, Python, TypeScript

MinIO vs ReductStore

The amount of data generated world-wide is expanding exponentially, and will only increase further in coming years. In fact, over 90% of the data worldwide has been generated in the last two years, and 40% of data in 2020 was generated by machines. Not to mention that 80 to 90 percent of data is unstructured. Not only is timely processing of said data ever more important, the data itself is often time-stamped and must be handled in a time-based structure. Due to the rise of AI/ML, Robotics, IoT, and edge-computing, solutions that can efficiently leverage much cheaper and plentiful unstructured object/blob storage while maintaining the ability to organize, read, and transmit time-series based data from multiple sources and in multiple formats are in great demand. ReductStore and MinIO are two solutions designed to meet this demand.