Data variety, come as you are in multi-model data warehouses

作者：

Highlights：

• We investigate the performances of a multi-model DBMS to store multidimensional data for OLAP analyses.

• We define a multidimensional schema for the UniBench benchmark dataset and an ad-hoc OLAP workload for it.

• We propose and quantitatively compare three logical solutions implemented on the PostgreSQL multi-model DBMS.

• The querying performances of a multi-model solution are slightly worse than those of a full-relational solution.

• A multi-model solutions brings advantages in terms of extendibility, flexibility, evolvability, ETL.

摘要

•We investigate the performances of a multi-model DBMS to store multidimensional data for OLAP analyses.•We define a multidimensional schema for the UniBench benchmark dataset and an ad-hoc OLAP workload for it.•We propose and quantitatively compare three logical solutions implemented on the PostgreSQL multi-model DBMS.•The querying performances of a multi-model solution are slightly worse than those of a full-relational solution.•A multi-model solutions brings advantages in terms of extendibility, flexibility, evolvability, ETL.

论文关键词：OLAP,Multi-model databases,Data variety,Data warehouse

论文评审过程：Received 16 July 2020, Revised 18 December 2020, Accepted 29 January 2021, Available online 4 February 2021, Version of Record 23 November 2021.

论文官网地址：https://doi.org/10.1016/j.is.2021.101734