A Recommender for Choosing Data Systems based on Application Profiling and Benchmarking

  • Elton Figueiredo de Souza Soares IBM Research
  • Renan Souza IBM Research
  • Raphael Melo Thiago IBM Research
  • Marcelo de Oliveira Costa Machado IBM Research http://orcid.org/0000-0002-0894-9750
  • Leonardo Guerreiro Azevedo IBM Research


In our data-driven society, there are hundreds of possible data systems in the market with a wide range of configuration parameters, making it very hard for enterprises and users to choose the most suitable data systems. There is a lack of representative empirical evidence to help users make an informed decision. Using benchmark results is a widely adopted practice, but like there are several data systems, there are various benchmarks. This ongoing work presents an architecture and methods of a system that supports the recommendation of the most suitable data system for an application. We also illustrates how the recommendation would work in a fictitious scenario.
Palavras-chave: data system advisor, database recommendation, database benchmarking


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SOARES, Elton Figueiredo de Souza; SOUZA, Renan; THIAGO, Raphael Melo; MACHADO, Marcelo de Oliveira Costa; AZEVEDO, Leonardo Guerreiro. A Recommender for Choosing Data Systems based on Application Profiling and Benchmarking. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 36. , 2021, Rio de Janeiro. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 265-270. ISSN 2763-8979. DOI: https://doi.org/10.5753/sbbd.2021.17883.