Abstract
Nowadays, we see an explosion in the number of Database Management Systems (DBMS) in the market. Each one has its own characteristics. This spectacular development of DBMS is mainly motivated by the need for storing and exploiting the deluge of heterogeneous data for analytical purposes. As a consequence, companies and users are faced with huge range of choices and sometimes it is hard for them to find the relevant DBMS. Some Web sites such as DB-Engines (http://db-engines.com/en/) provide monthly a classification of hundreds of DBMS (303 in April 2016) using metrics related to usage and user feedbacks. These criteria are not always sufficient to help companies and users to make a good choice. Therefore, they have to be enhanced by qualitative measurements obtained by testing the activities of DBMS for a set of non-functional requirements. In this perspective, some council such as Transaction Processing Council publish non-functional requirement results of DBMS using their own benchmarks. Another serious producer of test data is the researchers via their scientific papers. Each year they publish a large amount of results of new solutions. To facilitate the exploitation of these test results by small companies and researchers from developing countries, the construction of a test data repository connected to recommender system is an asset for companies/users. In this paper, we first propose a repository for structuring and storing test data. Secondly, a recommender system is built on the top of this repository to advise companies to choose appropriate DBMS based on their requirements. Finally, a proof of concept of our recommender system is given to illustrate our proposal.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Ahmad, M., Aboulnaga, A., Babu, S., Munagala, K.: Interaction-aware scheduling of report-generation workloads. VLDB J. 20(4), 589–615 (2011)
Baralis, E., Meo, R., Psaila, G.: Data mining in data warehouses. In: SEBD, pp. 51–65 (1999)
Bouchakri, R., Bellatreche, L., Hidouci, K.-W.: Static and incremental selection of multi-table indexes for very large join queries. In: Morzy, T., Härder, T., Wrembel, R. (eds.) ADBIS 2012. LNCS, vol. 7503, pp. 43–56. Springer, Heidelberg (2012)
Brahimi, L., Ouhammou, Y., Bellatreche, L., Ouared, A.: More transparency in testing results: towards an open collective knowledge base. In: 10th IEEE International Conference on Research Challenges in Information Science, pp. 315–320 (2016)
Chen, Q., Hsu, M., Dayal, U.: A data-warehouse/OLAP framework for scalable telecommunication tandem traffic analysis. In: ICDE, pp. 201–210 (2000)
Chung, L., do Prado Leite, J.C.S.: On non-functional requirements in software engineering. In: Borgida, A.T., Chaudhri, V.K., Giorgini, P., Yu, E.S. (eds.) Conceptual Modeling: Foundations and Applications. LNCS, vol. 5600, pp. 363–379. Springer, Heidelberg (2009)
Cross, T.L., Lane, R.J., et al.: Selecting a database management system for agricultural record keeping. Technical report (1988)
Cross, V.V., Sudkamp, T.A.:Similarity and compatibility in fuzzy set theory: assessment and applications, vol. 93 (2002)
Dague, P., Travé-Massuyès, L.: Raisonnement causal en physique qualitative. Intellectica 38, 247–290 (2004)
Dede, E., Govindaraju, M., Gunter, D., Canon, R.S., Ramakrishnan, L.: Performance evaluation of a mongodb and hadoop platform for scientific data analysis. In: Proceedings of the 4th ACM Workshop on Scientific Cloud Computing, pp. 13–20 (2013)
Furtado, P., Nadal, S., Peralta, V., Djedaini, M., Labroche, N., Marcel, P.: Materializing baseline views for deviation detection exploratory OLAP. In: DAWAK, pp. 243–254 (2015)
Golfarelli, M., Rizzi, S.: Data warehouse testing: a prototype-based methodology. Inf. Softw. Technol. 53(11), 1183–1198 (2011)
Gomez-Uribe, C.A., Hunt, N.: The netflix recommender system: algorithms, business value, and innovation. ACM Trans. Manage. Inf. Syst. 6(4), 13 (2016)
Gross, D., Yu, E.: From non-functional requirements to design through patterns. Require. Eng. 6(1), 18–36 (2001)
Haftmann, F., Kossmann, D., Lo, E.: A framework for efficient regression tests on database applications. VLDB J. 16(1), 145–164 (2007)
Lauesen, S.: Task descriptions as functional requirements. Softw. IEEE 20(2), 58–65 (2003)
Ordonez, C., Chen, Z., García-García, J.: Interactive exploration and visualization of OLAP cubes. In: ACM DOLAP, pp. 83–88 (2011)
Park, Y., Shankar, M., Park, B., Ghosh, J.: Graph databases for large-scale healthcare systems: a framework for efficient data management and data services. In: Workshops Proceedings of the ICDE, pp. 12–19 (2014)
Pezzè, M., Zhang, C.: Automated test oracles: a survey. Adv. Comput. 95, 1–48 (2015)
Rosenmüller, M., Siegmund, N., Schirmeier, H., Sincero, J., Apel, S., Leich, T., Spinczyk, O., Saake, G.: Fame-DBMS: tailor-made data management solutions for embedded systems. In: Proceedings of the 2008 EDBT Workshop on Software Engineering for Tailor-Made Data Management, pp. 1–6 (2008)
Roukh, A., Bellatreche, L., Boukorca, A., Bouarar, S.: Eco-DMW: eco-design methodology for data warehouses. In: ACM DOLAP, pp. 1–10 (2015)
Siksnys, L., Thomsen, C., Pedersen, T.B.: MIRABEL DW: managing complex energy data in a smart grid. In: Cuzzocrea, A., Dayal, U. (eds.) DaWaK 2012. LNCS, vol. 7448, pp. 443–457. Springer, Heidelberg (2012)
Tort, A., Olivé, A., Sancho, M.-R.: An approach to test-driven development of conceptual schemas. Data Knowl. Eng. 70(12), 1088–1111 (2011)
Wagstaff, K.: Clustering with missing values: no imputation required. In: Banks, D., McMorris, F.R., Arabie, P., Gaul, W. (eds.) Classification, Clustering, and Data Mining Applications. Studies in Classification, Data Analysis, and Knowledge Organization, pp. 649–658. Springer, Heidelberg (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Brahimi, L., Bellatreche, L., Ouhammou, Y. (2016). A Recommender System for DBMS Selection Based on a Test Data Repository. In: Pokorný, J., Ivanović, M., Thalheim, B., Šaloun, P. (eds) Advances in Databases and Information Systems. ADBIS 2016. Lecture Notes in Computer Science(), vol 9809. Springer, Cham. https://doi.org/10.1007/978-3-319-44039-2_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-44039-2_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44038-5
Online ISBN: 978-3-319-44039-2
eBook Packages: Computer ScienceComputer Science (R0)