What is the fully managed data warehouse service that allows cost-effective analysis of large datasets?

Amazon Redshift is recognized as a fully managed data warehouse service that facilitates cost-effective analysis of large datasets. It is designed specifically for analytical workloads and can handle complex queries across massive volumes of data with high performance. Redshift employs a columnar storage architecture, which significantly improves query performance and reduces the amount of disk I/O during data retrieval.

One of the key features of Amazon Redshift is its scalability, allowing users to scale their data warehouse cluster up or down based on their needs without significant disruption. This makes it a favorable choice for analyzing large datasets, as organizations can adjust their resources according to the data size and query complexity.

Additionally, Redshift integrates well with various AWS services, enabling users to easily import data from S3, RDS, and other sources, further enhancing its utility for large-scale data analysis. The service also incorporates advanced features like automated backups, data encryption, and a management console that simplifies monitoring and maintenance tasks.

In contrast, other services such as Amazon DynamoDB and Amazon RDS are tailored more for transactional or operational workloads rather than analytic ones. AWS Snowflake, while it is a powerful cloud data platform, is not a native AWS service and represents a different technology.