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 ingests millions of IoT sensor data points per second. They need a fully managed analytics service optimized for time-series data that can ingest high-velocity data, perform real-time analytics, and store data for historical analysis. The solution must integrate with Azure Stream Analytics for stream processing. Which Azure data service should they choose?
Why wrong: Cosmos DB does support time-series but is not optimized for high-velocity ingestion and real-time analytics like ADX.
B
Azure SQL Database
Why wrong: Azure SQL Database is a relational database best for OLTP workloads, not designed for high-throughput time-series ingestion.
C
Azure Data Explorer (ADX)
ADX is purpose-built for large-scale time-series data, providing rapid data ingestion, real-time analytics, and seamless integration with Azure Stream Analytics.
D
Azure Blob Storage
Why wrong: Azure Blob Storage is object storage without native analytics query capabilities, requiring additional services like Azure Data Lake Analytics for processing.
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 the correct choice because it is a fully managed, high-performance analytics service optimized for time-series and log data. It can ingest millions of IoT sensor data points per second, perform real-time analytics with sub-second query latency, and store data for historical analysis. ADX natively integrates with Azure Stream Analytics for stream processing, making it ideal 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 Cosmos DB
Why it's wrong here
Cosmos DB does support time-series but is not optimized for high-velocity ingestion and real-time analytics like ADX.
✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is a relational database best for OLTP workloads, not designed for high-throughput time-series ingestion.
✓
Azure Data Explorer (ADX)
Why this is correct
ADX is purpose-built for large-scale time-series data, providing rapid data ingestion, real-time analytics, and seamless integration with Azure Stream Analytics.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Blob Storage
Why it's wrong here
Azure Blob Storage is object storage without native analytics query capabilities, requiring additional services like Azure Data Lake Analytics for processing.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Data Explorer with Azure Cosmos DB or Azure SQL Database because they all support time-series data, but only ADX is purpose-built for high-velocity ingestion and real-time analytics with native Stream Analytics integration.
Detailed technical explanation
How to think about this question
Azure Data Explorer uses a columnar storage engine with a Kusto Query Language (KQL) that supports time-series functions like series_decompose and series_fir for anomaly detection. Its ingestion pipeline can handle up to 200 MB/s per node using the LightIngest tool or Event Hubs, and it automatically partitions data by ingestion time for efficient historical queries. In a real-world IoT scenario, ADX can ingest telemetry from millions of devices, run real-time aggregations with materialized views, and retain raw data for months using a hot/cold storage tier.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AZ-305 question in full detail.
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 (ADX) — Azure Data Explorer (ADX) is the correct choice because it is a fully managed, high-performance analytics service optimized for time-series and log data. It can ingest millions of IoT sensor data points per second, perform real-time analytics with sub-second query latency, and store data for historical analysis. ADX natively integrates with Azure Stream Analytics for stream processing, making it ideal for this scenario.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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