Enhancement of NoSQL Database Performance Using Parallel Processing
Journal of Information Systems Engineering and Management, ISSN: 2468-4376, Vol: 9, Issue: 2
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Most Recent News
University of Baghdad Researcher Highlights Recent Research in Information Systems Engineering (Enhancement of NoSQL Database Performance Using Parallel Processing)
2024 JUN 26 (NewsRx) -- By a News Reporter-Staff News Editor at Information Technology Daily -- Research findings on information systems engineering are discussed in
Article Description
In the burgeoning realm of big data, document-oriented NoSQL databases stand out for their flexibility and scalability. This paper delves into the optimization of these databases, specifically through the lens of parallel processing techniques. A comparative study was conducted against the traditional non-parallel approaches, where marked performance enhancements were observed. For instance, the execution time for retrieving movies of a specific year decreased by over 80% when parallel processing was applied, plummeting from 1.578765 seconds to a brisk 0.300000 seconds. Memory usage and CPU utilization were meticulously recorded, revealing up to a 70% reduction in peak memory consumption in certain queries, and a moderate fluctuation in CPU usage between 49.25% to 75.2%. This indicates not only improved efficiency but also a prudent utilization of system capacity, without overtaxing resources. However, the study identified scenarios, such as highly complex queries, where the gains from parallel processing were less pronounced, suggesting a marginal improvement in CPU utilization. While the findings advocate for the adoption of parallel processing in handling intensive data retrieval tasks, it is recommended that future research should further scrutinize the scalability thresholds and explore alternative parallelization strategies to fortify the efficacy of document-oriented NoSQL databases.
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