DBS-C01 Workload-Specific Database Design Practice Question
A company is building a real-time leaderboard for an online game using Amazon DynamoDB. The leaderboard must update scores within seconds and support queries for top 100 players. Which TWO design patterns should be used? (Choose TWO.)
⚠ Common exam trap
Watch out — candidates often assume a GSI on score alone can efficiently return a global top-N list, but DynamoDB requires a hash key for GSIs and cannot perform a global ordered scan without a partition key, making it unsuitable for leaderboard queries.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use DynamoDB Streams to trigger a Lambda function that updates a separate leaderboard table.
DynamoDB Streams can capture score updates in near real-time and trigger a Lambda function to maintain a separate leaderboard table optimized for top-100 queries. This decouples the write-heavy game table from the read-heavy leaderboard, ensuring low-latency updates without contention.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a global secondary index on the score attribute for efficient range queries.
Why it's wrong here
GSI can help but real-time updates require more than just indexing.
- ✓
Use DynamoDB Streams to trigger a Lambda function that updates a separate leaderboard table.
Why this is correct
Streams and Lambda provide real-time processing.
- ✗
Store the leaderboard in Amazon ElastiCache for Redis for low-latency reads.
Why it's wrong here
ElastiCache is not a DynamoDB design pattern.
- ✓
Enable DynamoDB Accelerator (DAX) for faster reads of the leaderboard.
Why this is correct
DAX caches reads, reducing latency.
- ✗
Set the sort key to the score attribute for natural ordering.
Why it's wrong here
While useful, it's not a complete solution for real-time top-N updates.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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