{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T04:21:36Z","timestamp":1747196496385,"version":"3.40.5"},"reference-count":39,"publisher":"Walter de Gruyter GmbH","issue":"2","license":[{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Databases provide an efficient way to store, retrieve and analyze data. Oracle relational database is one of the most popular database management systems that is widely used in a different variety of industries and businesses. Therefore, it is important to guarantee that the database access and data manipulation is optimized for reducing database system response time. This paper intends to analyze the performance and the main optimization techniques (Forall, Returning, and Bulk Collect) that can be adopted for Oracle Relational Databases. The results have shown that the adoption of Forall and Bulk Collect approaches bring significant benefits in terms of execution time. Furthermore, the growth rate of the average execution time is lower for Bulk Collect than Forall. However, adoption of Returning approach doesn\u2019t bring significant statistical benefits.<\/jats:p>","DOI":"10.2478\/cait-2019-0019","type":"journal-article","created":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T09:31:22Z","timestamp":1560936682000},"page":"117-132","source":"Crossref","is-referenced-by-count":3,"title":["Performance Analysis and Optimization Techniques for Oracle Relational Databases"],"prefix":"10.2478","volume":"19","author":[{"given":"Fernando","family":"Almeida","sequence":"first","affiliation":[{"name":"Faculty of Engineering , Oporto University & INESC TEC , Porto , Portugal"}]},{"given":"Pedro","family":"Silva","sequence":"additional","affiliation":[{"name":"Higher Polytechnic Institute of Gaya , ISPGaya , V. N. Gaia , Portugal"}]},{"given":"Fernando","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"Higher Polytechnic Institute of Gaya , ISPGaya , V. N. Gaia , Portugal"}]}],"member":"374","published-online":{"date-parts":[[2019,6,18]]},"reference":[{"key":"2025051317330417628_j_cait-2019-0019_ref_001_w2aab3b7b7b1b6b1ab1ab1Aa","doi-asserted-by":"crossref","unstructured":"1. Blaheta, R., K. Georgiev, O. Jaki, R. Kohut, S. Margenov, J. Stary. High Performance Computing in Micromechanics with an Application. \u2013 Cybernetics and Information Technologies, Vol. 17, 2017, No 5, pp. 5-16. https:\/\/doi.org\/10.1515\/cait-2017-005010.1515\/cait-2017-0050","DOI":"10.1515\/cait-2017-0050"},{"key":"2025051317330417628_j_cait-2019-0019_ref_002_w2aab3b7b7b1b6b1ab1ab2Aa","doi-asserted-by":"crossref","unstructured":"2. Dimitrov, D., E. Atanassov. Accounting Services for Heterogeneous Computing Resources. \u2013 Cybernetics and Information Technologies, Vol. 17, 2017, No 5, pp. 81-88. https:\/\/doi.org\/10.1515\/cait-2017-005710.1515\/cait-2017-0057","DOI":"10.1515\/cait-2017-0057"},{"key":"2025051317330417628_j_cait-2019-0019_ref_003_w2aab3b7b7b1b6b1ab1ab3Aa","doi-asserted-by":"crossref","unstructured":"3. Hellerstein, J., M. Stonebraker, J. Hamilton. Architecture of a Database System. \u2013 Foundations and Trends in Databases, Vol. 1, 2007, No 2, pp. 141-259. https:\/\/doi.org\/10.1561\/190000000210.1561\/1900000002","DOI":"10.1561\/1900000002"},{"key":"2025051317330417628_j_cait-2019-0019_ref_004_w2aab3b7b7b1b6b1ab1ab4Aa","unstructured":"4. Feuerlicht, G. Database Trends and Directions: Current Challenges and Opportunities. \u2013 In: J. Pokorn\u00fd, V. Sn\u00e1sel, K. Richta, Eds. Dataeso. 2010, pp. 163-174. CEUR-WS.org."},{"key":"2025051317330417628_j_cait-2019-0019_ref_005_w2aab3b7b7b1b6b1ab1ab5Aa","unstructured":"5. 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