Which service is described as a serverless ETL and data integration platform?

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Multiple Choice

Which service is described as a serverless ETL and data integration platform?

Explanation:
The concept being tested is identifying a serverless ETL and data integration platform. AWS Glue fits this role best because it is a fully managed, serverless service that handles extract, transform, and load tasks as well as data cataloging and discovery. With Glue, you can build ETL jobs that transform data stored in environments like S3, Redshift, or RDS, and you don’t need to provision or manage any servers—the service scales automatically and you pay for the resources used by the ETL jobs and the data catalog. It also provides features such as crawlers to infer schemas and a centralized Glue Data Catalog to organize metadata, plus support for workflows to orchestrate complex data pipelines. The other services are oriented differently: a streaming data ingestion service focused on delivering data to destinations with optional light transformations, rather than performing full ETL and data integration; a serverless query service that runs SQL against data in S3 but doesn’t orchestrate ETL pipelines; and a managed Kafka service for building real-time streaming applications, not a data integration platform.

The concept being tested is identifying a serverless ETL and data integration platform. AWS Glue fits this role best because it is a fully managed, serverless service that handles extract, transform, and load tasks as well as data cataloging and discovery. With Glue, you can build ETL jobs that transform data stored in environments like S3, Redshift, or RDS, and you don’t need to provision or manage any servers—the service scales automatically and you pay for the resources used by the ETL jobs and the data catalog. It also provides features such as crawlers to infer schemas and a centralized Glue Data Catalog to organize metadata, plus support for workflows to orchestrate complex data pipelines.

The other services are oriented differently: a streaming data ingestion service focused on delivering data to destinations with optional light transformations, rather than performing full ETL and data integration; a serverless query service that runs SQL against data in S3 but doesn’t orchestrate ETL pipelines; and a managed Kafka service for building real-time streaming applications, not a data integration platform.

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