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Difficulty: HardHigh-Performing Database Solutions

A digital marketing platform is launching a real-time bidding and analytics engine. The system must process ad request queries with sub-millisecond read latency for user profiles. Additionally, the system needs to persist bid transaction logs, which experience highly unpredictable, spiky write traffic. A solutions architect is designing a high-performing, scalable database architecture to support these requirements.

Which combination of database configurations will meet these requirements? (Select TWO.)

  1. Use Amazon DynamoDB with Amazon DynamoDB Accelerator (DAX) to store and serve user profile data.Answer
  2. Configure Amazon DynamoDB with On-Demand capacity mode to store bid transaction logs.Answer
  3. C
    Use Amazon DynamoDB with a partition key based on monotonically increasing transaction timestamps to store bid transaction logs.
  4. D
    Deploy an Amazon RDS PostgreSQL database with a read replica in a different Availability Zone to handle transaction logging and act as the primary write destination during failover.
  5. E
    Configure Amazon DynamoDB with Provisioned Capacity Mode and set static Read and Write Capacity Units to handle the bid transaction logs.

Answer

Use Amazon DynamoDB with Amazon DynamoDB Accelerator (DAX) to store and serve user profile data, and configure Amazon DynamoDB with On-Demand capacity mode to store bid transaction logs.
The correct architecture uses DynamoDB Accelerator (DAX) to deliver the required sub-millisecond (microsecond-level) read latency for user profiles by serving reads from an in-memory cache. Simultaneously, configuring DynamoDB with On-Demand capacity mode ensures that the system handles highly unpredictable, spiky write traffic for bid transaction logs without manual capacity management or performance throttling.

Step-by-Step Solution

1
Analyze the read latency requirement for user profiles.
The requirement specifies sub-millisecond read latency under high throughput.
DynamoDB Accelerator (DAX) is an in-memory cache that reduces DynamoDB response times to microseconds, satisfying this requirement.
2
Analyze the write traffic requirement for transaction logs.
The requirement specifies highly unpredictable and spiky write traffic that must be persisted.
DynamoDB On-Demand capacity mode is ideal for spiky workloads as it dynamically scales to accommodate write peaks without throttling or manual scaling configuration.
3
Evaluate the partition key design for the transaction logs.
Using monotonically increasing values like timestamps creates hot partitions.
High-performing DynamoDB designs require high-cardinality partition keys to distribute data and throughput evenly across partitions.

Key Concept

High-performing database architectures leverage caching (like DAX) for microsecond read latency and dynamic scaling modes (like DynamoDB On-Demand) to handle spiky, unpredictable write traffic without performance bottlenecks.
Estimated Time:2m 0s
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High-Performing Database Solutions

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