NoSQL Elasticsearch和MongoDB数据库应用程序在CRUD操作测试中的响应时间比较

Theresia Liana Sinaga, Novrido Charibaldi, N. Cahyana
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引用次数: 0

摘要

当前,人类生活在数据海洋时代,数据产生量不断增加,随之而来的是数据处理、数据存储、数据分析等方面的严峻挑战,尤其是大数据。大数据生产数量的增加会影响数据处理中访问数据库的速度、有效性和响应时间的速度。40多年来,关系数据库一直是数据存储、分析、处理和检索的主要模型。然而,由于对大规模数据存储的需求不断增加,数据处理系统的可扩展性和性能以及数据量的不断增长,出现了数据库的另一种替代方案,即NoSQL技术。根据之前关于响应时间和数据库性能比较的研究,平均得出NoSQL性能比关系数据库更有效和高效的结论。通过实现和测试,可以得出结论,NoSQL数据库应用MongoDB在CRUD测试的每个命令中都优于Elasticsearch NoSQL数据库应用,其中在使用JSON文件测试create data命令时,MongoDB数据库应用比Elasticsearch数据库应用快42.5倍。在测试将数据创建到包含不同数据量的数据库的命令时,MongoDB数据库应用程序比Elasticsearch数据库应用程序的平均响应时间快333.9倍。在测试一个包含不同数据量的数据库中读取数据的命令时,MongoDB数据库应用程序比Elasticsearch数据库应用程序快35.5倍。在测试包含不同数据量的数据库中数据的更新操作时,MongoDB数据库应用程序比Elasticsearch数据库应用程序快9.8倍。在测试不同数据量的数据库中数据的删除操作时,MongoDB数据库应用程序比Elasticsearch数据库应用程序快58.9倍。
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Perbandingan Waktu Respon Aplikasi Database NoSQL Elasticsearch dan MongoDB pada Pengujian Operasi CRUD
Currently, humans live in an era of data oceans, where the amount of data production is increasing from time to time, which is followed by severe challenges in terms of processing, storing, and analyzing data, especially big data. The increase in the number of large data production can affect the speed of access to the database, effectiveness, and speed of response time in the data processing. Relational databases have been the leading model for data storage, analysis, processing, and retrieval for more than forty years. However, due to the increasing need for large-scale data storage, the scalability and performance of a data processing system, as well as the constant growth of the amount of data, another alternative to databases emerged, namely NoSQL technology. Based on previous studies regarding the comparison of response time and database performance, the average concludes that NoSQL performance is more effective and efficient than relational databases. Based on the implementation and testing, it can be concluded that the NoSQL database application MongoDB is proven to be superior in every command of CRUD tested compared to the Elasticsearch NoSQL database application, where in testing the create data command with a JSON file, the MongoDB database application is 42.5 times faster than the Elasticsearch database application. In testing the command to create data into a database containing different amounts of data, the MongoDB database application is 333.9 times faster than the average response time of the Elasticsearch database application. In testing the read command for data in a database containing different amounts of data, the MongoDB database application is 35.5 times faster than the Elasticsearch database application. In testing the update operation of data in a database containing different amounts of data, the MongoDB database application is 9.8 times faster than the Elasticsearch database application. in testing the delete operation of data in a database containing different amounts of data, the MongoDB database application is 58.9 times faster than the Elasticsearch database application.
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