Big Data Integration in Cloud Environments : Requirements, Solutions and Challenges

Big Data Integration in Cloud Environments : Requirements, Solutions and Challenges

Sellami , R. and Defude , B. (2018). Big Data Integration in Cloud Environments : Requirements, Solutions and Challenges. In NoSQL Data Models, O. Pivert (Ed.). doi:10.1002/9781119528227.ch4

Date: 27 août 2018

Publication: Publications scientifiques 


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The production of huge amount of data and the emergence of Cloud computing have introduced new requirements for data management. Many applications need to interact with several heterogeneous data stores depending on the type of data they have to manage : traditional data types, documents, graph data from social networks, simple key-value data, etc. Interacting with heterogeneous data models via different APIs, and multiple data stores based applications imposes challenging tasks. Indeed, programmers have to be familiar with different APIs. In addition, the execution of complex queries over heterogeneous data models cannot, currently, be achieved in a declarative way as it is used to be with mono-data store application, and therefore requires extra implementation efforts. Moreover, the complex processes of Cloud discovery, and application deployment and execution are in general done manually by programmers. In this article, we present and discuss the requirements of big data integration in the cloud environments. Based on that, we analyze and discuss the current state of the art regarding the defined requirements using a set of well-defined criteria. We conclude this paper by a global synthesis and we highlight the most important challenges.


Cloud Computing, Big Data, NoSQL data stores, Relational data stores, Data integration, REST architecture, Query optimization.

NoSQL Data Models

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