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Difficulty: MediumHigh-Performing Database Solutions

A logistics company is designing a real-time package tracking dashboard. The tracking system must ingest millions of package coordinates daily from IoT sensors. The database must support high-volume write throughput and deliver single-digit millisecond latency for read queries. A solutions architect needs to design a high-performing database architecture that avoids read and write bottlenecks during peak operation hours.

Which combination of configurations will achieve this objective? (Select TWO.)

  1. Use Amazon DynamoDB with a composite primary key consisting of a high-cardinality Package ID as the partition key and a timestamp as the sort key.Answer
  2. Enable Amazon DynamoDB Accelerator (DAX) to cache read queries for the package status updates.Answer
  3. C
    Use Amazon DynamoDB with a partition key set to the shipping date formatted as YYYY-MM-DD.
  4. D
    Deploy Amazon RDS for PostgreSQL and configure read replicas to automatically handle write failovers during traffic surges.
  5. E
    Configure Amazon DynamoDB in Provisioned Capacity Mode with static Write Capacity Units (WCUs) to absorb sudden, unpredictable load spikes.

Answer

Use Amazon DynamoDB with a composite primary key consisting of a high-cardinality Package ID as the partition key and a timestamp as the sort key, and enable Amazon DynamoDB Accelerator (DAX) to cache read queries for the package status updates.
The correct approach uses Amazon DynamoDB with a high-cardinality Package ID partition key and a timestamp sort key to distribute writes evenly across partitions and prevent write bottlenecks. It also leverages Amazon DynamoDB Accelerator (DAX) to cache read queries, reducing response times to microseconds for frequently requested package tracking updates.

Step-by-Step Solution

1
Analyze the workload requirements for high write throughput and low-latency read queries.
Identify that the system requires a horizontally scalable database capable of handling high write rates and providing single-digit millisecond or better reads.
This guides the selection of a NoSQL database like DynamoDB over traditional relational databases for this specific scale.
2
Design the DynamoDB schema to prevent write bottlenecks.
Choose a high-cardinality attribute like Package ID as the partition key to distribute write traffic evenly across physical partitions, and use a timestamp as the sort key for historical tracking.
Distributing the writes prevents hot partitions, which cause ProvisionedThroughputExceededException or throttling.
3
Select a caching solution to optimize read performance and achieve sub-millisecond latency for hot keys.
Choose DynamoDB Accelerator (DAX) to cache reads in-memory.
DAX reduces read latency to microseconds for frequently accessed items without requiring application-side cache management code.

Key Concept

Designing partition keys with high cardinality and using in-memory caching to optimize NoSQL database performance under heavy read/write workloads.
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High-Performing Database Solutions

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