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Chapitre D'ouvrage Année : 2018

Big data integration in cloud environments: requirements, solutions and challenges

Résumé

This chapter focuses on the existing solutions of the state of the art supporting Big Data integration in cloud environments. Optimization is the ‘holy grail' of database management and, in the context of Big Data integration, it is clearly a major challenge. Choosing one or multiple data stores based on data requirements is a very important step before integrating heterogeneous data stores and deploying and running applications in a Cloud environment. Ruiz‐Alvarez proposes an automatic approach to selecting a cloud storage service according to the application requirements and the storage services capabilities. Object NoSQL Datastore Mapper (ONDM) is a framework aiming to facilitate persistent object storage and retrieval in NoSQL data stores. The chapter presents some substantial work proposing different unified data models to manage heterogeneous data integration. It analyzes how global queries are processed
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Dates et versions

hal-02006414 , version 1 (03-05-2023)

Identifiants

Citer

Rami Sellami, Bruno Defude. Big data integration in cloud environments: requirements, solutions and challenges. NoSQL data models: trends and challenges, 1, ISTE, pp.93 - 134, 2018, Computer engineering series: databases and big data set, 978-1-78630-364-6. ⟨10.1002/9781119528227.ch4⟩. ⟨hal-02006414⟩
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