Which database service supports petabytes of data and provides columnar storage on high-performance disks?

Amazon Redshift is designed specifically for large-scale data storage and analytics, supporting petabytes of data effectively. It utilizes a columnar storage architecture, which is optimal for analytical queries because it allows for efficient reading of only the required data columns rather than entire rows. This capability leads to faster query performance and reduces the amount of I/O required.

Additionally, Amazon Redshift operates on high-performance disks known as SSDs, which further enhances the speed of data retrieval and processing. This combination of columnar storage and high-performance disk usage makes Redshift particularly well-suited for data warehousing and complex analytical workloads, enabling organizations to run large-scale analytics and retrieve insights from massive datasets efficiently.

In contrast, services like Amazon RDS and Amazon Aurora are primarily intended for transactional databases and do not utilize the same columnar storage approach best suited for analytic tasks. Amazon DynamoDB, while allowing for scalability, is a NoSQL database primarily designed for key-value and document data models, rather than the structured data queries typically associated with petabyte-scale analytics. Therefore, Redshift stands out as the appropriate choice for handling petabytes of structured data with high efficiency.