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<p>“Not Only SQL” (NoSQL) solutions are becoming increasingly widespread in modern data warehouses. However, integrating these solutions, known for their schema-less structures, introduces a significant challenge when engaging in online analytical processing. A notable challenge is the lack of standardized representation for various online analytical processing operations (OLAP). Furthermore, managing and handling data with varying or absent schemes can introduce complexities and interfere with the smooth execution of OLAP operations. This paper aims to deal with the prior challenge. We propose an innovative algebra designed for OLAP operations in document-oriented NoSQL data warehouses. This OLAP algebra encloses essential operators like <i>Project, Select, Union and Aggregate</i> as well as more complex operators such as <i>Slice, Dice, Roll-up, Drill-down, and Pivot</i>. Introducing an algebra for OLAP operators in NoSQL databases improves performance, standardizes operations, simplify data analysis, and maximizes flexibility and scalability. To assess the effectiveness of the proposed algebra, we conducted a comprehensive evaluation using a COVID-19 case study implemented under MongoDB.</p>

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A formal algebra for document-oriented NoSQL data warehouses: formalisation and evaluation

  • 期刊论文

  • 发表日期：

    2025年1月21日

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  • Senda Bouaziz,
  • Soumaya Boukettaya,
  • Ahlem Nabli,
  • Faiez Gargouri

摘要

“Not Only SQL” (NoSQL) solutions are becoming increasingly widespread in modern data warehouses. However, integrating these solutions, known for their schema-less structures, introduces a significant challenge when engaging in online analytical processing. A notable challenge is the lack of standardized representation for various online analytical processing operations (OLAP). Furthermore, managing and handling data with varying or absent schemes can introduce complexities and interfere with the smooth execution of OLAP operations. This paper aims to deal with the prior challenge. We propose an innovative algebra designed for OLAP operations in document-oriented NoSQL data warehouses. This OLAP algebra encloses essential operators like Project, Select, Union and Aggregate as well as more complex operators such as Slice, Dice, Roll-up, Drill-down, and Pivot. Introducing an algebra for OLAP operators in NoSQL databases improves performance, standardizes operations, simplify data analysis, and maximizes flexibility and scalability. To assess the effectiveness of the proposed algebra, we conducted a comprehensive evaluation using a COVID-19 case study implemented under MongoDB.