- A
Azure Blob Storage
Why wrong: Blob Storage is object storage but does not provide native HDFS compatibility. While it can be used with Hadoop via the WASB driver, it lacks the hierarchical namespace and performance optimizations of ADLS Gen2.
- B
Azure Data Lake Storage Gen2
ADLS Gen2 combines Blob Storage with a hierarchical namespace and HDFS-compatible APIs, offering unlimited storage, high throughput, and lifecycle tiering for cost optimization.
- C
Azure Files
Why wrong: Azure Files is a fully managed file share for SMB and NFS protocols, not designed for big data analytics or HDFS workloads.
- D
Azure Disk Storage
Why wrong: Azure Disk Storage provides block-level storage for VMs, but it has capacity limits and is not suitable for large-scale distributed data processing.
Quick Answer
The answer is Azure Data Lake Storage Gen2. This service is the correct choice because it merges a hierarchical namespace with Azure Blob Storage, delivering full HDFS compatibility for Hadoop and Spark workloads. By using the `abfss://` driver, it provides unlimited storage and high throughput for parallel processing, while its tiered storage options—hot, cool, and archive—allow cost-effective management of older data. On the AZ-305 exam, this scenario tests your ability to distinguish between Azure storage solutions for big data analytics; a common trap is selecting standard Blob Storage, which lacks the hierarchical namespace required for true HDFS compatibility. Remember the key differentiator: ADLS Gen2 is essentially Blob Storage plus a filesystem layer, making it the only service that supports both the `wasbs://` and `abfss://` protocols. For a quick memory tip, think “Gen2 gives you the tree” — the hierarchical namespace is the tree structure that HDFS needs.
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 runs large-scale analytics workloads using Apache Hadoop and Spark. They need a cloud storage solution that is fully compatible with the Hadoop Distributed File System (HDFS) and provides unlimited storage with high throughput for parallel processing. They also want to take advantage of tiered storage to reduce costs for older data. Which Azure data service should they 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 Lake Storage Gen2
Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines a hierarchical namespace with Azure Blob Storage, providing full HDFS compatibility. This allows Apache Hadoop and Spark workloads to use the `wasbs://` or `abfss://` driver for unlimited storage and high throughput parallel processing, while also supporting tiered storage (hot, cool, archive) to reduce costs for older 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.
- ✗
Azure Blob Storage
Why it's wrong here
Blob Storage is object storage but does not provide native HDFS compatibility. While it can be used with Hadoop via the WASB driver, it lacks the hierarchical namespace and performance optimizations of ADLS Gen2.
- ✓
Azure Data Lake Storage Gen2
Why this is correct
ADLS Gen2 combines Blob Storage with a hierarchical namespace and HDFS-compatible APIs, offering unlimited storage, high throughput, and lifecycle tiering for cost optimization.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Files
Why it's wrong here
Azure Files is a fully managed file share for SMB and NFS protocols, not designed for big data analytics or HDFS workloads.
- ✗
Azure Disk Storage
Why it's wrong here
Azure Disk Storage provides block-level storage for VMs, but it has capacity limits and is not suitable for large-scale distributed data processing.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Blob Storage (which is object storage without a hierarchical namespace) with ADLS Gen2, assuming both are equally HDFS-compatible, but only ADLS Gen2 provides the required HDFS semantics and the `abfss://` driver for native Hadoop/Spark integration.
Detailed technical explanation
How to think about this question
Under the hood, ADLS Gen2 implements a hierarchical namespace on top of Blob Storage, enabling POSIX-like access control and atomic directory rename/delete operations critical for Hadoop/Spark. The `abfss://` driver (Azure Blob File System) uses OAuth 2.0 for secure access and leverages Azure's distributed architecture to achieve throughput up to 60 GB/s per account. In real-world scenarios, this allows data lakes to scale from terabytes to exabytes while using lifecycle management policies to automatically move cold data to cool or archive tiers, reducing storage costs by up to 80%.
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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Design data storage solutions — study guide chapter
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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 Lake Storage Gen2 — Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines a hierarchical namespace with Azure Blob Storage, providing full HDFS compatibility. This allows Apache Hadoop and Spark workloads to use the `wasbs://` or `abfss://` driver for unlimited storage and high throughput parallel processing, while also supporting tiered storage (hot, cool, archive) to reduce costs for older data.
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.
About these practice questions
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Last reviewed: Jun 11, 2026
This AZ-305 practice question is part of Courseiva's free Microsoft 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 AZ-305 exam.
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