AWS Certified Solutions Architect Associate SAA-C03 Practice Question
A company stores several petabytes of sales data in AWS. Business analysts must run frequent, complex SQL queries (for example, joins, aggregations, and time-window analytics) and receive results in seconds while minimizing cost. Which AWS managed service provides the best price-performance fit for this large-scale, columnar analytics workload?
Amazon Redshift is purpose-built for data warehousing and analytics. Its columnar storage format and massively parallel processing (MPP) architecture make complex queries on large data sets faster and cheaper than row-store OLTP engines such as Amazon Aurora or Amazon RDS for MySQL. DynamoDB is a NoSQL key-value store and is not optimized for ad-hoc SQL analytics. Therefore, Amazon Redshift is the most cost-effective choice for this scenario.
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Why is Amazon Redshift optimized for analytics workloads?
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Why are DynamoDB and relational databases not suitable for large-scale SQL analytics?