The correct combination is AWS Glue Jobs and AWS Glue Workflows. Glue Jobs execute the ETL logic to read JSON from Amazon S3, convert to Parquet, and write to Amazon Redshift using JDBC or COPY. Glue Workflows provide orchestration and time-based scheduling so the pipeline runs automatically at the specified interval. The option AWS Glue Data Catalog is only for metadata and schemas. It does not transform, load, or schedule pipelines. AWS Glue DataBrew is a visual, interactive data prep tool and is not the right choice for production ETL into Redshift on a schedule. AWS Glue Data Quality focuses on rules and validations, not core ETL execution or orchestration. Look for cues like convert format, load into Redshift, and automated scheduling to map to Glue Jobs for ETL and Workflows for orchestration. If a question emphasizes scheduling a single job only, Glue Triggers may be sufficient. When you see visual preparation or interactive profiling, think DataBrew rather than production ETL. Distinguish the Data Catalog (metadata) from services that actually run the ETL.