A solutions architect is choosing purpose-built databases for two new workloads in the same platform. The first stores hierarchical, schema-flexible product documents queried by attribute with single-digit millisecond latency at very large scale. The second must answer queries that walk many connected relationships, such as which accounts ultimately funded a given transaction through chains of intermediaries. The team wants a fully managed AWS service that fits each access pattern natively rather than forcing both onto one relational engine. Which two services correctly match these workloads? Select TWO.
- AAmazon Redshift for the schema-flexible product documents, using its columnar storage to serve low-latency lookups
- BAmazon DynamoDB for the schema-flexible product documents queried at scale with single-digit millisecond latency Correct
- CAmazon RDS for PostgreSQL for the relationship traversal, relying on recursive multi-table joins across intermediaries
- DAmazon Neptune for the queries that traverse many connected relationships between funding accounts and intermediaries Correct
- EAmazon ElastiCache for the schema-flexible product documents to provide the primary durable document store
Why A is wrong: Redshift is a columnar data warehouse tuned for analytical scans, not single-item low-latency document lookups, so it is the wrong fit here.
Why B is correct: DynamoDB is a managed key-value and document store giving single-digit millisecond latency at very large scale, matching the flexible-document access pattern.
Why C is wrong: Recursive joins on a relational engine grow expensive as relationship depth increases, which is exactly the pattern a graph database is meant to replace.
Why D is correct: Neptune is a managed graph database built to traverse highly connected relationships efficiently, which suits the multi-hop funding-chain queries.
Why E is wrong: ElastiCache is an in-memory cache, not a durable primary document store, so using it as the system of record would risk data loss.