ETL Technologies for Big Data: A Comparative Study

There is a significant increase in the generation of massive data worldwide. Various sources such as social media applications, blockchain technology, and numerous other systems are responsible for generating data. This information can be structured or unstructured, originating from different sources. In this context, the ETL (Extract, Transform, and Load) process plays a crucial role where demands for efficient business decisions in contemporary systems are grown.During the processing phase, the entire method is organized in a pipeline structure to ensure that the resulting data contains valuable and pertinent insights. Indeed, selecting an appropriate ETL technology can be challenging due to the abundance of options available. This article delves into several technologies used for performing ETL processes with the aim of examining their strengths when weaknesses. This can provide assistance to researchers and industry professionals in making informed decisions and choosing the most suitable technologies to meet their specific requirements.