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VOOZH | about |
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VOOZH | about |
Big data is a blanket term for the non-traditional strategies and technologies needed to gather, organize, process, and gather insights from large datasets. While the problem of working with data that exceeds the computing power or storage of a single computer is not new, the pervasiveness, scale, and value of this type of computing has greatly expanded in recent years.
In a previous guide, we discussed some of the general concepts, processing stages, and terminology used in big data systems. In this article, we will take a look at one of the most essential components of a big data system: processing frameworks. Processing frameworks compute over the data in the system, either by reading from non-volatile storage or as it is ingested into the system. Computing over data is the process of extracting information and insight from large quantities of individual data points.
We will cover the following frameworks:
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Former Senior Technical Writer at DigitalOcean, specializing in DevOps topics across multiple Linux distributions, including Ubuntu 18.04, 20.04, 22.04, as well as Debian 10 and 11.
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Love the detailed pros and cons of current data processing frameworks. Thanks for sharing!
Great Article! Rich information
Also take a look at Wallaroo: Ultrafast and elastic data processing engine. http://www.wallaroolabs.com/community
Who are the authors of this article, because I found the same paper published in a scientific journal in December 2017.
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