Question 823 of 999

Design data storage solutions →mediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is Azure Data Explorer (ADX) because it is purpose-built for high-ingestion, time-series telemetry data from millions of IoT devices, offering both real-time dashboarding and alerting on fresh data and cost-effective long-term storage for historical queries over a 10-year retention period. ADX uses columnar storage and advanced indexing to handle billions of records per minute, making it the ideal choice for IoT telemetry storage and query scenarios where data is hot for 30 days then cold for occasional analysis. On the AZ-305 exam, this question tests your ability to match workload patterns to specialized data services—a common trap is choosing Azure Cosmos DB for its low latency, but Cosmos DB lacks ADX’s native time-series analytics and cost-efficient long-term retention. Remember the memory tip: “ADX for time-series, Cosmos for real-time transactions”—if the data is telemetry with a hot/cold lifecycle, always pick ADX.

AZ-305 Design data storage solutions Practice Question

This AZ-305 practice question tests your understanding of design data storage solutions. 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 company manages a fleet of millions of IoT devices that send telemetry data every minute. The data must be stored for 10 years to meet compliance requirements. For the first 30 days, data is accessed frequently for real-time dashboards and alerting. After 30 days, data is only accessed occasionally for historical analysis and reporting. The solution must be cost-effective and support high ingestion rates. Which Azure service should the company use to store and query this data?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "first"
Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.

Question 1mediummultiple choice

Read the full network assurance explanation →

A
Azure Blob Storage with Azure Data Lake Storage Gen2
Why wrong: Blob Storage provides scalable object storage but does not offer built-in time-series query capabilities. External tools are required for analysis, increasing complexity.
B
Azure Data Explorer
Azure Data Explorer is optimized for time-series data, supports high ingestion rates, and provides both real-time and historical querying with automatic data tiering for cost effectiveness.
C
Azure SQL Database
Why wrong: Azure SQL Database is a relational database not designed for high-frequency time-series ingestion. It would be expensive and struggle with the required ingestion throughput.
D
Azure Cosmos DB with SQL API
Why wrong: Cosmos DB is a multi-model database but its cost and performance for massive time-series workloads are suboptimal compared to a purpose-built service like ADX.

Full breakdown with real-world context →

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

Azure Data Explorer (ADX) is designed for high-ingestion, time-series telemetry data and supports real-time dashboards and alerting on fresh data, while also providing cost-effective long-term storage for historical queries. Its columnar storage and indexing enable fast analytics on billions of records, making it ideal for IoT scenarios with millions of devices sending data every minute and a 10-year retention requirement.

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 Blob Storage with Azure Data Lake Storage Gen2
Why it's wrong here
Blob Storage provides scalable object storage but does not offer built-in time-series query capabilities. External tools are required for analysis, increasing complexity.
✓
Azure Data Explorer
Why this is correct
Azure Data Explorer is optimized for time-series data, supports high ingestion rates, and provides both real-time and historical querying with automatic data tiering for cost effectiveness.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is a relational database not designed for high-frequency time-series ingestion. It would be expensive and struggle with the required ingestion throughput.
✗
Azure Cosmos DB with SQL API
Why it's wrong here
Cosmos DB is a multi-model database but its cost and performance for massive time-series workloads are suboptimal compared to a purpose-built service like ADX.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often choose Azure Blob Storage or Cosmos DB because they associate them with 'storage' or 'IoT,' but they fail to recognize that Azure Data Explorer is the only service purpose-built for high-velocity time-series analytics with built-in hot/cold tiering and native support for real-time alerting and long-term retention at scale.

Detailed technical explanation

How to think about this question

Azure Data Explorer uses a columnar storage engine with built-in indexing (e.g., inverted indexes for strings, range indexes for numbers) that allows it to ingest up to 200 MB/s per node and query data in sub-second latency. Its data retention policy can tier hot (fast, in-memory) and cold (cheaper, on blob) storage, automatically moving data older than 30 days to cold storage while still allowing queries via the same Kusto Query Language (KQL). In real-world IoT deployments, ADX can handle millions of devices sending telemetry every minute by batching ingestion and using streaming ingestion for near-real-time dashboards.

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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.

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 AZ-305 question test?

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

What is the correct answer to this question?

The correct answer is: Azure Data Explorer — Azure Data Explorer (ADX) is designed for high-ingestion, time-series telemetry data and supports real-time dashboards and alerting on fresh data, while also providing cost-effective long-term storage for historical queries. Its columnar storage and indexing enable fast analytics on billions of records, making it ideal for IoT scenarios with millions of devices sending data every minute and a 10-year retention requirement.

What should I do if I get this AZ-305 question wrong?

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

Are there clue words in this question I should notice?

Yes — watch for: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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