Which service is commonly used for big data processing on AWS?

The service commonly used for big data processing on AWS is Amazon EMR, which stands for Elastic MapReduce. This service is designed to make it easy to process vast amounts of data efficiently using frameworks such as Apache Hadoop, Spark, and HBase. EMR allows users to quickly set up clusters and process data in a scalable manner, leveraging the power of the cloud to handle large datasets without the need for extensive on-premises infrastructure.

Amazon EMR is particularly well-suited for applications that require batch processing, data transformation, and large-scale data analyses, making it a preferred choice for organizations dealing with big data workloads. Furthermore, it integrates seamlessly with other AWS services such as S3 for storage, enabling a streamlined workflow for data scientists and developers.

Other options, while useful for their respective use cases, do not target big data processing in the same manner. For instance, Amazon RDS primarily serves as a managed relational database service, AWS Lambda is focused on serverless computing and event-driven processing, and Amazon Lightsail provides a simplified cloud infrastructure for web applications but lacks the specialized tools and scaling capabilities necessary for big data operations.