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Design and implement data storagemediumMultiple ChoiceObjective-mapped

DP-203 Design and implement data storage Practice Question

This DP-203 practice question tests your understanding of design and implement data storage. 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.

You are designing a data storage solution for real-time analytics on IoT telemetry. The system must ingest 10,000 events per second and support sub-second query latency. Which Azure data store should you use?

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

Azure Data Explorer (ADX).

Azure Data Explorer (ADX) is purpose-built for high-velocity telemetry and log analytics, ingesting 10,000+ events per second with sub-second query latency via its columnar storage and distributed query engine. It supports real-time analytics on streaming IoT data without requiring pre-defined schemas or indexing, making it the optimal choice for this scenario.

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.

  • Azure Table Storage.

    Why it's wrong here

    Table Storage is a key-value store without real-time analytical capabilities.

  • Azure SQL Database with in-memory OLTP.

    Why it's wrong here

    In-memory OLTP is for transactional workloads, not high-throughput streaming analytics.

  • Azure Cosmos DB with analytical store.

    Why it's wrong here

    Cosmos DB analytical store is for near-real-time analytics but not optimized for 10K events/sec with sub-second query latency.

  • Azure Data Explorer (ADX).

    Why this is correct

    ADX is designed for real-time analytics on large volumes of streaming data with sub-second query latency.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Azure Cosmos DB's analytical store with a real-time analytics solution, but it is designed for hybrid transactional/analytical processing (HTAP) on operational data, not for high-velocity streaming telemetry analytics where ADX excels.

Detailed technical explanation

How to think about this question

ADX uses a Kusto Query Language (KQL) engine that leverages a columnar storage format and a distributed cluster architecture, enabling automatic indexing and data partitioning for high-speed ingestion and querying. Under the hood, it employs a 'shard' (extent) structure that allows data to be ingested in batches and immediately available for queries, with a built-in streaming ingestion policy that can handle up to 1 GB/s per node. In real-world IoT scenarios, ADX can ingest millions of events per second from devices like smart meters or industrial sensors, and queries like aggregations over time windows return in milliseconds due to its materialized views and pre-aggregation capabilities.

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.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this DP-203 question test?

Design and implement data storage — This question tests Design and implement data storage — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Azure Data Explorer (ADX). — Azure Data Explorer (ADX) is purpose-built for high-velocity telemetry and log analytics, ingesting 10,000+ events per second with sub-second query latency via its columnar storage and distributed query engine. It supports real-time analytics on streaming IoT data without requiring pre-defined schemas or indexing, making it the optimal choice for this scenario.

What should I do if I get this DP-203 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.

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Last reviewed: Jun 24, 2026

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