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Cloud-Based NoSQL Data Migration

机译:基于云的NoSQL数据迁移

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Cloud computing has enabled the Database-as-a-Service (DBaaS) model to manage large volumes of user-generated data using NoSQL data repositories. There are several NoSQL implementations such as document, columnar, and key-value which ensure high availability, fault tolerance and scalability to serve distinct client requirements. Nonetheless, different NoSQL data models may also introduce unnecessary heterogeneity in DBaaS, which further restricts the user to migrate the application services according to business or technology changes. In this paper, we propose a NoSQL data migration framework to foster data portability across cloud-based heterogeneous NoSQL data repositories. The proposed approach involves data standardisation and classification stages to render an efficient mapping, and translation between cloud-based different NoSQL data stores. The current implementation of the framework supports three different data models: document, columnar and graph. Moreover, the framework is meta-model driven, and therefore allows developers to extend the support for new database models. Our approach includes an online compression algorithm for data migration (document to graph) whereby a graph database requires up to 46% less space. There is also a significant reduction (37% to 55%) in the number of nodes in the compressed graph database.
机译:云计算使数据库即服务(DBaaS)模型能够使用NoSQL数据存储库管理大量用户生成的数据。有几种NoSQL实现,例如文档,列和键值,可确保高可用性,容错性和可伸缩性来满足不同的客户端需求。尽管如此,不同的NoSQL数据模型也可能会在DBaaS中引入不必要的异构性,这进一步限制了用户根据业务或技术变化而迁移应用程序服务。在本文中,我们提出了一种NoSQL数据迁移框架,以促进跨基于云的异构NoSQL数据存储库之间的数据可移植性。所提出的方法涉及数据标准化和分类阶段,以提供有效的映射,以及在基于云的不同NoSQL数据存储之间的转换。该框架的当前实现支持三种不同的数据模型:文档,列式和图形。此外,该框架是元模型驱动的,因此允许开发人员扩展对新数据库模型的支持。我们的方法包括用于数据迁移(从文档到图形)的在线压缩算法,其中图形数据库所需的空间最多减少46%。压缩图数据库中的节点数量也显着减少(37%至55%)。

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