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2015•Computer engineering & SoftwareRequires access

The Application of MongoDB in Meteorological Sensor Data Processing

Bai Chang-qin

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Abstract

Massive scale data continues to emerge. The demand for storage and processing unstructured data is increasing. Traditional relational database is hard to hand efficiently. NoSQL technology is better able to solve such problems. This article will introduce NoSQL,MongoDB,and MongoDB is applied when dealing with a large number of sensor data of the meteorological parameters. Facts have proved that as the representative of No SQL,MongoDB has a good performance when storing and accessing massive amounts of unstructured data.

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What this paper is about

Massive scale data continues to emerge. The demand for storage and processing unstructured data is increasing. Traditional relational database is hard to hand efficiently. NoSQL technology is better able to solve such problems. This article will introduce NoSQL,MongoDB,and MongoDB is applied when dealing with a large number of sensor data of the meteorological parameters. Facts have proved that as the representative of No SQL,MongoDB has a good performance when storing and accessing massive amounts of unstructured data.

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Available abstract

Massive scale data continues to emerge. The demand for storage and processing unstructured data is increasing. Traditional relational database is hard to hand efficiently. NoSQL technology is better able to solve such problems. This article will introduce NoSQL,MongoDB,and MongoDB is applied when dealing with a large number of sensor data of the meteorological parameters. Facts have proved that as the representative of No SQL,MongoDB has a good performance when storing and accessing massive amounts of unstructured data.

Key concepts: NoSQL, Computer science, SQL, Database, Unstructured data, Relational database, Computer data storage, Relational database management system

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