The Forgotten Document-Oriented Database Management Systems: An Overview and Benchmark of Native XML DODBMSes in Comparison with JSON DODBMSes
The Forgotten Document-Oriented Database Management Systems: An Overview and Benchmark of Native XML DODBMSes in Comparison with JSON DODBMSes
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DOI：
10.1016/j.bdr.2021.100205
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发表时间：
2021-02-01
影响因子：
3.3
通讯作者：
Pedersen, Torben Bach
中科院分区：
文献类型：
--
作者：
Truica, Ciprian-Octavian;Apostol, Elena-Simona;Pedersen, Torben Bach
在当前的大数据背景下，已经提出并实现了许多新的NoSQL解决方案，用于存储，管理和从半结构化数据中提取信息和模式。开发这些解决方案是为了通过引入半结构化和灵活的模式设计来缓解关系数据库中存在的刚性数据结构问题。由于当前由不同来源和设备生成的数据，特别是来自物联网传感器和执行器的数据，根据应用程序的不同，使用XML或JSON格式，因此需要以XML格式存储和查询半结构化数据的数据库技术。因此，原生XML数据库最初被设计为使用标准化的查询语言来操作XML数据，即，XQuery和Node.js被重新命名为NoSQL面向文档的数据库系统。目前，这些解决方案中的大多数已经被更现代的基于JSON的数据库管理系统所取代。但是，我们相信基于XML的解决方案仍然可以在异构集合上执行复杂查询时提供性能。不幸的是，现在的研究缺乏对以XML存储和查询文档的数据库技术与更现代的JSON格式的可伸缩性和性能的明确比较。此外，据我们所知，这些数据库技术没有符合大数据的基准。在本文中，我们提出了一个比较选定的面向文档的数据库系统，要么使用XML格式编码的文件，即，BaseX、eXist-db和Sedna，或者JSON格式，即，MongoDB、CouchDB和Couchbase。为了强调性能差异，我们还提出了一个基准测试，使用一个大型DBLP语料库上的异构复杂模式。(C)2021作者爱思唯尔公司出版
In the current context of Big Data, a multitude of new NoSQL solutions for storing, managing, and extracting information and patterns from semi-structured data have been proposed and implemented. These solutions were developed to relieve the issue of rigid data structures present in relational databases, by introducing semi-structured and flexible schema design. As current data generated by different sources and devices, especially from IoT sensors and actuators, use either XML or JSON format, depending on the application, database technologies that store and query semi-structured data in XML format are needed. Thus, Native XML Databases, which were initially designed to manipulate XML data using standardized querying languages, i.e., XQuery and XPath, were rebranded as NoSQL Document Oriented Databases Systems. Currently, the majority of these solutions have been replaced with the more modern JSON based Database Management Systems. However, we believe that XML-based solutions can still deliver performance in executing complex queries on heterogeneous collections. Unfortunately nowadays, research lacks a clear comparison of the scalability and performance for database technologies that store and query documents in XML versus the more modern JSON format. Moreover, to the best of our knowledge, there are no Big Data-compliant benchmarks for such database technologies. In this paper, we present a comparison for selected Document-Oriented Database Systems that either use the XML format to encode documents, i.e., BaseX, eXist-db, and Sedna, or the JSON format, i.e., MongoDB, CouchDB, and Couchbase. To underline the performance differences we also propose a benchmark that uses a heterogeneous complex schema on a large DBLP corpus. (C) 2021 The Authors. Published by Elsevier Inc.