Thesis (Selection of subject)Thesis (Selection of subject)(version: 285)
Assignment details
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Multi-model Benchmark
Thesis title in Czech: Multi-model Benchmark
Thesis title in English: Multi-model Benchmark
Key words: multi-model databases, experimental comparison, benchmarking
English key words: multi-model databases, experimental comparison, benchmarking
Academic year of topic announcement: 2018/2019
Type of assignment: diploma thesis
Thesis language:
Department: Department of Software Engineering (32-KSI)
Supervisor: doc. RNDr. Irena Holubová, Ph.D.
Author:
Guidelines
Most of the popular database systems can now be denoted as multi-model, that is, supporting multiple models. Such a system offers the possibility to use a combination of several logical models, such as graph and document, for data storage, to define relationships between the data and to query across the models. As in the other areas also in the world of multi-model databases we need to be able to test features of a particular system, compare it with a previous version or with other similar systems. However, the amount of available real-world multi-model data, together with respective operations (queries) is limited. And so is limited also the amount of existing benchmarks.

The aim of the thesis is analyze the existing benchmarks for multi-model databases and identify their disadvantages and limitations. On the basis of the identified findings the author will propose own benchmark and demonstrate its features using experiments with existing multi-model databases.
References
UniBench: Towards Benchmarking Multi-Model DBMS http://udbms.cs.helsinki.fi/?projects/ubench

Poess, M., Rabl, T., Jacobsen, H., Caufield, B.: TPC-DI: the first industry benchmark for data integration. PVLDB 7(13), 1367-1378 (2014). http://www.vldb.org/pvldb/vol7/p1367-poess.pdf

Ghazal, A., Rabl, T., Hu, M., Raab, F., Poess, M., Crolotte, A., Jacobsen, H.: BigBench: Towards an Industry Standard Benchmark for Big Data Analytics. In: ACM SIGMOD (2013) http://msrg.utoronto.ca/publications/pdf_files/2013/Ghazal13-BigBench:_Towards_an_Industry_Standa.pdf

Oliveira, F.R., del Val Cura, L.M.: Performance Evaluation of NoSQL Multi-Model Data Stores in Polyglot Persistence Applications. In: IDEAS. pp. 230-235 (2016) https://www.researchgate.net/publication/308034803_Performance_Evaluation_of_NoSQL_Multi-Model_Data_Stores_in_Polyglot_Persistence_Applications

Pluciennik, E., Zgorzalek, K.: The Multi-model Databases - A Review. In: BDAS. pp. 141-152 (2017). https://link.springer.com/chapter/10.1007/978-3-319-58274-0_12

https://db-engines.com/en/ranking
 
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