DEA-C01 Data Store Management Practice Question
A data engineering team is building a real-time analytics pipeline using Amazon Kinesis Data Streams, AWS Lambda, and Amazon DynamoDB. The Lambda function consumes records from the stream and writes aggregated data to a DynamoDB table. The application requires that each record be processed exactly once to avoid duplicates. The Lambda function is idempotent, but occasionally duplicate records are written due to retries from Kinesis. The team needs to ensure exactly-once semantics for DynamoDB writes. Which solution should they implement?
⚠ Common exam trap
A common mix-up: candidates assume idempotent Lambda functions alone guarantee exactly-once processing, but they overlook that Kinesis retries can still cause duplicate writes unless a conditional write with a unique identifier is used at the database level.
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 TransactWriteItems with a condition check on a unique transaction ID.
DynamoDB TransactWriteItems with a condition check on a unique transaction ID ensures that the write only succeeds if the transaction ID does not already exist in the table. This provides exactly-once semantics by preventing duplicate writes even when Kinesis retries deliver the same record multiple times. The condition check acts as a distributed lock at the item level, guaranteeing idempotency without relying on downstream deduplication.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable DynamoDB Streams and use a second Lambda to deduplicate.
Why it's wrong here
Introduces complexity and eventual consistency.
- ✓
Use DynamoDB TransactWriteItems with a condition check on a unique transaction ID.
Why this is correct
Condition check ensures only one write succeeds per unique ID.
- ✗
Use the Kinesis Client Library (KCL) to checkpoint after processing and ignore duplicates.
Why it's wrong here
Checkpointing does not prevent duplicates from being written.
- ✗
Ensure the Lambda function is idempotent by using upsert operations.
Why it's wrong here
Idempotency alone may not prevent duplicates if multiple writes are attempted.
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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