AWS Certified Solutions Architect – ProfessionalContinuously Improve Existing SolutionsEasy
A financial institution uses an on-premises data warehouse that struggles to scale with increasing data volumes and query complexity, leading to batch processing delays. They want to migrate to AWS to improve performance and enable real-time analytics capabilities. The solution must support petabyte-scale data, complex SQL queries, and integrate with existing business intelligence (BI) tools. Which AWS service is the most appropriate for this requirement?
- AAmazon S3 with Amazon Athena.
- BAmazon DynamoDB with DynamoDB Accelerator (DAX).
- CAmazon Redshift.
- DAmazon RDS for PostgreSQL.
Show answer & explanationAnswer & explanation
Correct answer: C. Amazon Redshift.
Amazon Redshift is a fully managed, petabyte-scale data warehouse service that is optimized for complex analytical queries and integrates well with standard SQL-based BI tools. It directly addresses the scaling and performance issues of an on-premises data warehouse for analytical workloads.
Why the other options are wrong
- A. While S3 and Athena can handle large datasets and SQL queries, Athena is serverless and designed for ad-hoc queries, not a persistent, high-performance data warehouse for complex, frequent analytical workloads. It might be used as part of a larger data lake solution, but Redshift is more suitable for a dedicated data warehouse.
- B. Amazon DynamoDB is a NoSQL database, not designed for complex analytical SQL queries typical of a data warehouse. DAX is a cache for DynamoDB, further indicating its operational database focus.
- D. Amazon RDS for PostgreSQL is a relational database service, suitable for transactional workloads. While it can handle some analytical queries, it is not optimized for the petabyte-scale and complex analytical performance requirements of a dedicated data warehouse like Redshift.
Amazon Redshift
Amazon Redshift is a fully managed, petabyte-scale, columnar data warehouse service that enables fast, complex analytical queries on large datasets.
- Optimized for analytical processing (OLAP).
- Columnar storage for high query performance.
- Scales to petabytes of data.
- Integrates with BI tools using standard SQL.
Memory trick: Redshift is the red giant star of data warehouses, massive and powerful for analytics.