A global retail corporation is migrating its inventory management and analytics platform to AWS. The inventory system requires a database that supports rigid schema enforcement and complex SQL join queries across multiple tables for real-time stock reconciliation. Concurrently, the data science team needs to run complex, long-running analytical queries across terabytes of historical sales data to predict future inventory demands. To minimize operational overhead, the company wants fully managed services where AWS handles database patching, backups, and setup. Which combination of AWS services should the company select?
- Amazon Aurora for the inventory system, and Amazon Redshift for historical sales analyticsCevap
- BAmazon DynamoDB for the inventory system, and Amazon Aurora for historical sales analytics
- CAmazon EC2 instances running self-managed relational database software for the inventory system, and Amazon Redshift for historical sales analytics
- DAmazon Aurora for the inventory system, and Amazon EBS volumes for historical sales analytics
Cevap
Amazon Aurora for the inventory system, and Amazon Redshift for historical sales analytics
The correct answer combines Amazon Aurora and Amazon Redshift. Amazon Aurora is a fully managed relational database that provides the high performance, ACID compliance, and complex join capabilities required for the inventory system. Amazon Redshift is a fully managed data warehouse designed specifically for high-performance analysis of large-scale historical datasets, offloading analytical processing from the transactional database to prevent performance degradation.
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Anahtar Kavram
Selecting the appropriate AWS database or analytics service based on application requirements (relational vs. non-relational, transaction processing vs. analytical warehousing, and managed vs. self-managed services).