A car sales company receives daily uploads from vendors as compressed files (up to 5 KB each) to Amazon S3 containing new listings. The company wants near-real-time visibility of new listings, an automated processing workflow to feed a dashboard, and the ability to run one-off queries and analytics at scale, all in the most cost-effective way. Which solution is the best fit?

The correct solution leverages serverless services, which are cost-effective for small, frequent files and intermittent queries. AWS Glue is ideal for processing diverse data formats, and S3 Event Notifications triggering AWS Lambda provide a highly scalable, event-driven orchestration for near-real-time processing. Amazon Athena allows cost-effective, ad-hoc querying directly on S3 data without managing infrastructure. Amazon QuickSight is a fully managed BI service for dashboards. The incorrect options involve provisioned clusters (EMR, OpenSearch Service, Redshift Spectrum), which incur higher costs for always-on resources, especially for small, frequent uploads and intermittent queries. While EMR and Redshift Spectrum can handle analytics, they are overkill and more expensive for this use case compared to serverless alternatives.