A company has a requirement to store 100TB of data to AWS. This data will be exported using AWS Snowball and needs to then reside in a database layer. The database should have the facility to be queried from a business intelligence application. Each item is roughly 500KB in size. Which of the following is an ideal storage mechanism for the underlying data layer?
A. AWS DynamoDB
B. AWS Aurora
D. AWS Redshift
D. AWS Redshift
For this sheer data size, the ideal storage unit would be AWS Redshift.
AWS Documentation mentions the following on AWS Redshift:
Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers.
The first step to create a data warehouse is to launch a set of nodes, called an Amazon Redshift cluster. After you provision your cluster, you can upload your data set and then perform data analysis queries. Regardless of the size of the data set, Amazon Redshift offers fast query performance using the same SQL-based tools and business intelligence applications that you use today.
For more information on AWS Redshift, please refer to the URL below.
Option A is incorrect because the maximum item size in DynamoDB is 400KB.
Option B is incorrect because Aurora supports 64TB of data.
Option C is incorrect because we can create MySQL, MariaDB, SQL Server, PostgreSQL, and Oracle RDS DB instances with up to 16 TiB of storage.