{"title":"PaaS-BDP - A Multi-Cloud Architectural Pattern for Big Data Processing on a Platform-as-a-Service Model","authors":"Thalita Vergilio, M. Ramachandran","doi":"10.5220/0006632400450052","DOIUrl":null,"url":null,"abstract":": This paper presents a contribution to the fields of Big Data Analytics and Software Architecture, namely an emerging and unifying architectural pattern for big data processing in the cloud from a cloud consumer’s perspective. PaaS-BDP (Platform-as-a-Service for Big Data) is an architectural pattern based on resource pooling and the use of a unified programming model for building big data processing pipelines capable of processing both batch and stream data. It uses container cluster technology on a PaaS service model to overcome common shortfalls of current big data solutions offered by major cloud providers such as low portability, lack of interoperability and the risk of vendor lock-in.","PeriodicalId":414016,"journal":{"name":"International Conference on Complex Information Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Complex Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0006632400450052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
: This paper presents a contribution to the fields of Big Data Analytics and Software Architecture, namely an emerging and unifying architectural pattern for big data processing in the cloud from a cloud consumer’s perspective. PaaS-BDP (Platform-as-a-Service for Big Data) is an architectural pattern based on resource pooling and the use of a unified programming model for building big data processing pipelines capable of processing both batch and stream data. It uses container cluster technology on a PaaS service model to overcome common shortfalls of current big data solutions offered by major cloud providers such as low portability, lack of interoperability and the risk of vendor lock-in.