- A
Amazon Timestream
Timestream is a fast, scalable, serverless time-series database.
- B
Amazon RDS with MySQL
Why wrong: RDS is a relational database not optimized for time-series workloads.
- C
Amazon Neptune
Why wrong: Neptune is a graph database, not suitable for time-series.
- D
Amazon DynamoDB
Why wrong: DynamoDB can be used but lacks native time-series functions and efficient range queries for recent data.
Question 266 of 1,730
Amazon Timestream for Time-Series Data in AWS Database Specialty
This DBS-C01 practice question tests your understanding of workload-specific database design. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A startup is building a social media analytics platform that requires storing time-series data with frequent writes and queries for the last hour. Which AWS database service is BEST suited for this workload?
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
✓
Amazon Timestream
Amazon Timestream is a purpose-built time-series database that efficiently handles high-frequency writes and recent-time queries (e.g., last hour) with automatic data tiering (in-memory store for recent data, magnetic store for historical). Its serverless architecture and built-in time-series functions (e.g., interpolation, smoothing) make it ideal for social media analytics workloads requiring low-latency queries on recent data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Amazon Timestream
Why this is correct
Timestream is a fast, scalable, serverless time-series database.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon RDS with MySQL
Why it's wrong here
RDS is a relational database not optimized for time-series workloads.
- ✗
Amazon Neptune
Why it's wrong here
Neptune is a graph database, not suitable for time-series.
- ✗
Amazon DynamoDB
Why it's wrong here
DynamoDB can be used but lacks native time-series functions and efficient range queries for recent data.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose DynamoDB (Option D) because of its high write throughput and TTL features, but they overlook the lack of native time-series query functions and automatic data tiering, which are essential for efficient recent-time queries in this workload.
Detailed technical explanation
How to think about this question
Amazon Timestream uses a two-tier storage model: an in-memory store for data within a configurable retention period (default 24 hours) enabling sub-second query latency, and a magnetic store for older data optimized for analytical queries. Under the hood, it automatically partitions data by time and dimensions, and its query engine supports SQL with time-series extensions like `BIN()` and `INTERPOLATE_LINEAR()`, which are critical for real-time analytics dashboards. In a real-world scenario, a social media platform tracking 10,000+ metrics per second would benefit from Timestream's automatic compression and partitioning, avoiding the manual tuning required in DynamoDB or RDS.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon Timestream — Amazon Timestream is a purpose-built time-series database that efficiently handles high-frequency writes and recent-time queries (e.g., last hour) with automatic data tiering (in-memory store for recent data, magnetic store for historical). Its serverless architecture and built-in time-series functions (e.g., interpolation, smoothing) make it ideal for social media analytics workloads requiring low-latency queries on recent data.
What should I do if I get this DBS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on DBS-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A startup is building a social media analytics platform. The workload is write-heavy, with millions of events per day containing user actions (likes, shares, comments). The data model is simple: each event is a JSON document with a timestamp, user ID, and action type. Queries are primarily aggregations over time (e.g., count of likes per hour) and require low-latency responses for dashboards. The team wants to minimize operational overhead and cost. Which database service is most appropriate?
easy- A.Amazon ElastiCache for Redis to store aggregated counts.
- B.Amazon RDS for PostgreSQL with TimescaleDB extension.
- ✓ C.Amazon Timestream, a purpose-built time-series database.
- D.Amazon DynamoDB with global secondary indexes on timestamp and action type.
Why C: Amazon Timestream is the most appropriate service because it is purpose-built for time-series data, supporting high write throughput and providing built-in aggregation functions for time-based queries. It is serverless, minimizing operational overhead and cost. Option A (ElastiCache) is a caching layer, not a durable database. Option B (RDS with TimescaleDB) requires manual scaling and management, increasing overhead. Option D (DynamoDB) is optimized for key-value access, not efficient for time-series aggregations without additional processing and secondary indexes.
Variation 2. A company wants to store and analyze time-series sensor data from millions of IoT devices. The data is append-only and rarely updated. Queries aggregate data over time ranges. Which AWS database service is most cost-effective and performant for this workload?
easy- A.Amazon DynamoDB with time-series design pattern
- ✓ B.Amazon Timestream
- C.Amazon Redshift
- D.Amazon RDS for MySQL with partitioning by date
Why B: Amazon Timestream is purpose-built for time-series data, offering automatic tiered storage (in-memory for recent data and magnetic for historical data) and optimized query performance for time-range aggregations. Its serverless architecture eliminates provisioning overhead, making it the most cost-effective and performant choice for append-only IoT sensor data with infrequent updates.
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Last reviewed: Jul 4, 2026
This DBS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DBS-C01 exam.
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