Abstract

Presently, we are observing an explosion of data that need to be stored and processed over the Internet, and characterized by large volume, velocity and variety. For this reason, software developers have begun to look at NoSQL solutions for data storage. However, operations that are trivial in traditional Relational DataBase Management Systems (DBMSs) can become very complex in NoSQL DBMSs. This is the case of the join operation to establish a connection between two or more DB structures, whose construct is not explicitly available in many NoSQL databases. As a consequence, the data model has to be changed or a set of operations have to be performed to address particular queries on data. Thus, open questions are: how do NoSQL solutions work when they have to perform join operations on data that are not natively supported? What is the quality of NoSQL solutions in such cases? In this paper, we deal with such issues specifically considering one of the major NoSQL document oriented DB available on the market: MongoDB. In particular, we discuss an approach to perform join operations at application layer in MongoDB that allows us to preserve data models. We analyse performance of the proposes approach discussing the introduced overhead in comparison with SQL-like DBs.

Highlights

  • We are observing to an explosion of heterogeneous data coming from social media, entertainment transmissions, Cloud computing services and Internet of Things (IoT)

  • This is the case of the join operation to establish a connection between two or more DB structures, whose construct is not explicitly available in many NoSQL databases

  • Open questions are: how do NoSQL solutions work when they have to perform join operations on data that are not natively supported? What is the quality of NoSQL solutions in such cases? In this paper, we deal with such issues considering one of the major NoSQL document oriented DB available on the market: MongoDB

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Summary

Introduction

We are observing to an explosion of heterogeneous data coming from social media, entertainment transmissions, Cloud computing services and Internet of Things (IoT) Such data need to be stored and processed for Future Internet applications ad services. With the advent of Future Internet applications, there is an increasing need to pass from SQL-Like to NoSQL DBMS(s) able to efficiently manage a huge volume of heterogeneous data in different domains including smart cities [3], industry 4.0 [4], marketing [5], robotics [6], transportation [7], healthcare [8,9], genomics [10,11], and so on. They have been tested all basic operations (CRUD) but none of these

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