Abstract

ETL (Extract, Transform, Load) tools play a crucial role in contemporary data management by enabling the extraction, transformation, and loading of data from various sources into designated systems for analysis and reporting purposes. Major cloud service providers including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) give robust ETL solutions tailored to diverse business needs. This document presents a comparative assessment of the primary ETL tools offered by AWS, Azure, and GCP—namely, AWS Glue, Amazon Data Pipeline, Azure Data Factory, Azure Synapse Studio, Google Cloud Dataflow, and Google Cloud Dataprep. The evaluation focuses on their respective features, integration capabilities, ease of use, and specific application scenarios, to aid organizations in selecting the most appropriate ETL tool based on their unique requirements and existing infrastructure.