A company receives marketing campaign data from a vendor. The company ingests the data into an Amazon S3 bucket every 40 to 60 minutes. The data is…

The most efficient solution with the least operational overhead is to use an event-driven, serverless architecture. An Amazon S3 PutObject event can trigger an AWS Lambda function. This function then connects to the Amazon Redshift cluster and executes a COPY command to load the data from the newly arrived CSV file in S3 directly into the target Redshift table. This approach is fully automated, requires no server management, scales automatically, and uses the most performant method (COPY command) for ingesting data from S3 into Redshift.

1. AWS Redshift Database Developer Guide

Loading data from Amazon S3: The COPY command is the recommended method for loading data into Amazon Redshift from files on Amazon S3. It is significantly more efficient than INSERT statements for bulk data loads. (See section: "Loading data from Amazon S3").

2. AWS Lambda Developer Guide

Using AWS Lambda with Amazon S3: This guide details how to configure an S3 bucket to publish object-created events and invoke a Lambda function in response

forming the basis of an event-driven pipeline. (See section: "Tutorial: Using an Amazon S3 trigger to invoke a Lambda function").

3. AWS Redshift Database Developer Guide

Working with Redshift Spectrum: "With Redshift Spectrum

you can query your data in Amazon S3 without having to load or transform it." This confirms that Spectrum does not load data into Redshift's local storage. (See section: "Amazon Redshift Spectrum overview").

4. AWS Database Migration Service User Guide

What is AWS Database Migration Service?: "AWS Database Migration Service (AWS DMS) is a cloud service that makes it easy to migrate relational databases

data warehouses

NoSQL databases

and other types of data stores." This highlights that DMS's primary use case is migration

not file-based ETL.