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Data Store ManagementmediumMultiple SelectObjective-mapped

DEA-C01 Data Store Management Practice Question

A data engineer is designing a data storage solution for IoT sensor data that is ingested at high velocity. The data is time-series and needs to be queried by time range. Which TWO AWS services are suitable for this use case? (Choose TWO)

⚠ Common exam trap

Many exam-takers choose Amazon RDS or Redshift because they are familiar with SQL-based querying, overlooking that Timestream and DynamoDB are purpose-built for high-velocity time-series ingestion and time-range queries, while RDS and Redshift incur performance and cost penalties for such workloads.

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 automatically scales to handle high-velocity IoT sensor data, with built-in time-based partitioning and query optimization for time-range queries. It supports SQL-like queries with time-series functions (e.g., `BETWEEN`, `DATE_BIN`) and separates storage into a memory store for recent data and a magnetic store for historical data, enabling efficient querying by time range.

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 RDS

    Why it's wrong here

    RDS is not optimized for time-series data and high-velocity ingestion.

  • Amazon Redshift

    Why it's wrong here

    Redshift is for analytical workloads, not real-time ingestion.

  • Amazon Timestream

    Why this is correct

    Timestream is a time-series database built for IoT and operational applications.

  • Amazon DynamoDB

    Why this is correct

    DynamoDB can handle high-velocity writes and supports time-series queries with proper key design.

  • Amazon S3

    Why it's wrong here

    S3 is not designed for high-velocity writes and low-latency queries on time-series data.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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Same concept, more angles

1 more way this is tested on DEA-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 data engineer needs to store streaming data from IoT devices for real-time analytics. The data has a fixed schema and requires low-latency queries. Which AWS service should be used?

easy
  • A.Amazon DynamoDB
  • B.Amazon Redshift
  • C.Amazon S3
  • D.Amazon Timestream

Why D: Amazon Timestream is a time-series database purpose-built for IoT and operational applications that generate large volumes of time-stamped data. It automatically manages data retention and storage tiers (memory and magnetic) to provide fast query performance for recent data and cost-effective storage for historical data, making it ideal for real-time analytics on streaming IoT data with a fixed schema.

Last reviewed: Jun 24, 2026

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This DEA-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 DEA-C01 exam.