The comparative analysis of modern ETL tools
Each data warehouse requires loading properly processed transactional data. The process that performs this task is known as extract-transform-load (ETL). The efficiency of its implementation affects how quickly the user will have the access to the current analytical data. The paper presents the resu...
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| Format: | Article |
| Language: | English |
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Lublin University of Technology
2021-06-01
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| Series: | Journal of Computer Sciences Institute |
| Subjects: | |
| Online Access: | https://ph.pollub.pl/index.php/jcsi/article/view/2631 |
| _version_ | 1831704058516209664 |
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| author | Vitalii Mayuk Ivan Falchuk Piotr Muryjas |
| author_facet | Vitalii Mayuk Ivan Falchuk Piotr Muryjas |
| author_sort | Vitalii Mayuk |
| collection | DOAJ |
| description | Each data warehouse requires loading properly processed transactional data. The process that performs this task is known as extract-transform-load (ETL). The efficiency of its implementation affects how quickly the user will have the access to the current analytical data. The paper presents the results of research efficiency of ETL performance of its stage with the use of Azure Synapse (AS) and Azure Data Factory (ADF). The research included selection, sorting and aggregating data, joining tables, and loading data into target tables. To evaluate the efficiency of these operations, the criterion of their execution time has been used. The obtained results indicate that the ADF tool provides a much higher time efficiency of loading transactional data into the data warehouse comparing to AS. |
| first_indexed | 2024-12-20T15:51:43Z |
| format | Article |
| id | doaj.art-370ab4ab25f94852a683185912f1f3f0 |
| institution | Directory Open Access Journal |
| issn | 2544-0764 |
| language | English |
| last_indexed | 2024-12-20T15:51:43Z |
| publishDate | 2021-06-01 |
| publisher | Lublin University of Technology |
| record_format | Article |
| series | Journal of Computer Sciences Institute |
| spelling | doaj.art-370ab4ab25f94852a683185912f1f3f02022-12-21T19:34:39ZengLublin University of TechnologyJournal of Computer Sciences Institute2544-07642021-06-011910.35784/jcsi.2631The comparative analysis of modern ETL toolsVitalii Mayuk0Ivan Falchuk1Piotr Muryjas2Department of Computer Science, Lublin University of TechnologyDepartment of Computer Science, Lublin University of TechnologyLublin University of TechnologyEach data warehouse requires loading properly processed transactional data. The process that performs this task is known as extract-transform-load (ETL). The efficiency of its implementation affects how quickly the user will have the access to the current analytical data. The paper presents the results of research efficiency of ETL performance of its stage with the use of Azure Synapse (AS) and Azure Data Factory (ADF). The research included selection, sorting and aggregating data, joining tables, and loading data into target tables. To evaluate the efficiency of these operations, the criterion of their execution time has been used. The obtained results indicate that the ADF tool provides a much higher time efficiency of loading transactional data into the data warehouse comparing to AS.https://ph.pollub.pl/index.php/jcsi/article/view/2631Azure Synapse, Azure Data Factory; ETL tools |
| spellingShingle | Vitalii Mayuk Ivan Falchuk Piotr Muryjas The comparative analysis of modern ETL tools Journal of Computer Sciences Institute Azure Synapse, Azure Data Factory; ETL tools |
| title | The comparative analysis of modern ETL tools |
| title_full | The comparative analysis of modern ETL tools |
| title_fullStr | The comparative analysis of modern ETL tools |
| title_full_unstemmed | The comparative analysis of modern ETL tools |
| title_short | The comparative analysis of modern ETL tools |
| title_sort | comparative analysis of modern etl tools |
| topic | Azure Synapse, Azure Data Factory; ETL tools |
| url | https://ph.pollub.pl/index.php/jcsi/article/view/2631 |
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