This work offers a comparison between cloud services that help in the ETL process, focusing on the cloud database management environment, BigQuery. With the exponential increase in the amount of data generated and the growing adoption of cloud technologies, the use of efficient systems for data processing and integration becomes essential. The research includes a literature review that addresses the main concepts of ETL and an analysis of the main cloud services currently on the market. Among these services, BigQuery stands out, a powerful solution developed by Google Cloud Platform that provides a flexible and scalable environment for processing and analyzing large volumes of data. BigQuery is a cloud-based data storage and processing system that uses a columnar architecture to provide fast and efficient queries against large-scale datasets. In addition, BigQuery is integrated with other Google Cloud ecosystem services, such as Google Data Studio, Google Cloud Storage, etc., providing BI, storage, and other solutions. During the research, different features and functionalities of cloud services will be compared. Criteria such as performance, scalability, cost, among others, will be considered. The goal is to identify the benefits and limitations of each service and provide a thorough analysis to help choose the best cloud service option to support the ETL process based on needs. At the conclusion of the study, it is intended to provide a comprehensive overview of cloud services currently on the market, with a detailed focus on BigQuery. This allows you to choose which service is most suitable for each specific need for data processing and integration in the cloud environment.