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Mongodb, couchbase: Performance comparison for image dataset

机译:Mongodb,Couchbase:图像数据集的性能比较

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In today's world data is growing very rapidly, which we call as big data. To deal with these large data sets, currently we are using NoSQL databases, as relational database is not capable for handling such data. These schema less NoSQL database allow us to handle unstructured data. Through this paper we are comparing two NoSQL databases MongoDB and CouchBase server, in terms of image storage and retrieval. Aim behind selecting these two databases as both comes under Document store category. Major applications like social media, traffic analysis, criminal database etc. require image database. The motivation behind this paper is to compare database performance in terms of time required to store and retrieve images from database. In this paper, firstly we are going describe advantages of NoSQL databases over SQL, then brief idea about MongoDB and CouchBase and finally comparison of time required to insert various size images in databases and to retrieve various size images using front end tool Java.
机译:在当今世界,数据正以非常快的速度增长,我们称之为大数据。为了处理这些大数据集,当前我们使用NoSQL数据库,因为关系数据库无法处理此类数据。这些无架构的NoSQL数据库使我们能够处理非结构化数据。通过本文,我们在图像存储和检索方面比较了两个NoSQL数据库MongoDB和CouchBase服务器。旨在选择这两个数据库,因为它们都属于“文档存储”类别。社交媒体,流量分析,犯罪数据库等主要应用程序需要图像数据库。本文背后的动机是根据存储和从数据库检索图像所需的时间比较数据库性能。在本文中,我们首先将介绍NoSQL数据库相对于SQL的优势,然后简要介绍MongoDB和CouchBase,最后比较在数据库中插入各种尺寸图像并使用前端工具Java检索各种尺寸图像所需的时间。

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