Amazon Athena : Serverless Architecture and Troubleshooting |
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| © 2023 by IJCTT Journal | ||
| Volume-71 Issue-5 |
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| Year of Publication : 2023 | ||
| Authors : Amol Kulkarni | ||
| DOI : 10.14445/22312803/IJCTT-V71I5P110 | ||
How to Cite?
Amol Kulkarni, "Amazon Athena : Serverless Architecture and Troubleshooting," International Journal of Computer Trends and Technology, vol. 71, no. 5, pp. 57-61, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I5P110
Abstract
Data Analysis is of topmost import important for the survival of any organization in today's digital and competitive world. In order to store enormous amounts of data, different OLTP ERP Systems like SAP S/4HANA, Amazon S3, Oracle Net Suite etc. are available, but accessing that data in a simple and easiest way is tricky due to the heavy cost involved in Extraction, transformation and loading ETL operations, maintenance, monitoring and data visualization in data warehousing. Serverless Systems come into the picture for data analysis due to their features like simplicity, ease of operation, automatic scalability and less cost for accessing huge data. There are various serverless systems available in the market, like Amazon Athena, Amazon Glue, Microsoft Azure, and Google Big Query. In all these serverless systems, Amazon Athena is best used for cost savings, easy access to huge amounts of data, tight integration with Amazon S3, scalability, security and simplicity. This paper aims to explain the serverless architecture of Amazon Athena and how to troubleshoot different issues in Amazon Athena while accessing huge data.
Keywords
Amazon S3, AWS Glue, Business Intelligence(BI), ETL, Machine Learning(ML), SQL.
Reference
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