New generation databases also called NoSQL (Not only SQL) databases are highly scalable, flexible, and low-latent. These types of databases emerge as a result of the rigidity shown by traditional databases to handle today’s data which is voluminous, highly diversified and generated at a very high rate. With NoSQL, problems such as database expansion difficulties, low query performance and low storage capacity are addressed. However, the inherent complexity of contemporary datasets coupled with programmers’ low NoSQL modeling competence are increasingly making database modeling and design vastly challenging, especially when parameters like consistency, availability and scalability are to be balanced in accordance with system requirements. As such, a schema suggestion model for NoSQL databases is posed to address this balancing issue. The proposed model aims to abstractly suggest schemas at the initial stage of system development based on user defined system requirements and CRUD (Create, Read, Update and Delete) operations among others. This is achieved through the adaptation of exploratory and experimental approaches of research. Also, few mathematical formulas are introduced to calculate clusters availability during entity mappings. A comparison was conducted between the schema produced using the proposed model and the one without. Results obtained shows substantial improvement in the areas of security and read–write query performance.

中文翻译：

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NoSQL文档存储数据库的自动模式建议模型

新一代数据库也称为NoSQL（不仅SQL）数据库，具有高度可伸缩性，灵活性和低延迟性。这些类型的数据库的出现是由于传统数据库在处理当今的数据（这些数据非常庞大，高度多样化且生成速度非常快）方面表现出的刚性。使用NoSQL，可以解决数据库扩展困难，查询性能低和存储容量低等问题。但是，当代数据集固有的复杂性以及程序员低的NoSQL建模能力正日益使数据库建模和设计面临巨大挑战，尤其是当要根据系统需求平衡诸如一致性，可用性和可伸缩性之类的参数时。因此，提出了用于NoSQL数据库的架构建议模型来解决此平衡问题。提出的模型旨在根据用户定义的系统要求以及CRUD（创建，读取，更新和删除）操作等在系统开发的初始阶段抽象地建议架构。这是通过采用探索性和实验性研究方法来实现的。另外，很少引入数学公式来计算实体映射期间的群集可用性。在使用建议的模型生成的模式与未使用模型生成的模式之间进行了比较。获得的结果显示出在安全性和读写查询性能方面的实质性改进。这是通过采用探索性和实验性研究方法来实现的。另外，很少引入数学公式来计算实体映射期间的群集可用性。在使用建议的模型生成的模式与未使用模型生成的模式之间进行了比较。获得的结果显示出在安全性和读写查询性能方面的实质性改进。这是通过采用探索性和实验性研究方法来实现的。另外，很少引入数学公式来计算实体映射期间的群集可用性。在使用建议的模型生成的模式与未使用模型生成的模式之间进行了比较。获得的结果显示出在安全性和读写查询性能方面的实质性改进。