Abstract
Intelligent manufacturing is a new trend that is a deep integration of information and industrialization. As to the information, database is very important. For the past 20 years, relational databases have been widely used in a lot of fields because of their rich feature, such as query capabilities and transaction management and so on. However, they do not have the capacity of storing and processing a large number of data effectively, and at the same time, they are not very efficient to make transactions and join operations. In order to adapt to the new demand, some of new databases have been invented which are not in accordance with relational model. These databases are known as NoSQL. The underlying data and transaction model of the NoSQL are different from relational database. Some of organizations have shown much interest in NoSQL and adopted this new technology, which promote further research on the NoSQL. In this thesis, we research NoSQL database about their origin and characteristics. Then, we compare between one of the NoSQL database, MongoDB , to the standard relational database, SQL Server . We contrast their performance from different aspects. Results show that MongoDB performs better than the relational database.
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Acknowledgments
This work is supported by subject of Science and Technology Commission of Shanghai Municipality in key technology development and demonstration application of the unmanned factory for industrial robot production (No. 14DZ1100700). We thank Shanghai Key Laboratory of Intelligent Manufacturing and Robotics for assistance with advice.
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Zhou, Ch., Yao, K., Jiang, Zy., Bai, Wx. (2017). Research on the Application of NoSQL Database in Intelligent Manufacturing. In: Yang, C., Virk, G., Yang, H. (eds) Wearable Sensors and Robots. Lecture Notes in Electrical Engineering, vol 399. Springer, Singapore. https://doi.org/10.1007/978-981-10-2404-7_33
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DOI: https://doi.org/10.1007/978-981-10-2404-7_33
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