Quick Answer
The correct answer is Azure Data Lake Storage Gen2 with Archive tier for cold data. This solution uniquely combines a hierarchical namespace for granular folder-level permissions with multi-protocol access including ABFS, REST, and NFS 3.0, which is essential for a petabyte-scale analytics platform ingesting IoT, logs, and transactional data. The Archive tier provides the most cost-effective storage for cold data accessed less than once a year, while the native support for Parquet format optimizes analytical workloads. On the AZ-305 exam, this question tests your ability to differentiate Azure storage services for big data scenarios, often using multi-protocol and hierarchical namespace requirements as traps—remember that Azure Blob Storage lacks native NFS 3.0, Azure Files lacks ABFS and hierarchical namespace, and Azure NetApp Files is prohibitively expensive at petabyte scale. A useful memory tip: think of ADLS Gen2 as the "Swiss Army knife" of data lakes—it alone combines hierarchical folders, multiple protocols, and tiered pricing for hot-to-cold analytics.
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 large enterprise is designing a data lake solution for its analytics platform. The data lake will store petabytes of structured and unstructured data from various sources, including IoT devices, logs, and transactional databases. The solution must support: - Multi-protocol access (ABFS, REST, and NFS 3.0) - Hierarchical namespace for folder-level permissions - Optimized for analytical workloads (Parquet format) - Cost-effective storage for cold data that is accessed less than once a year. Which Azure storage solution should the enterprise recommend for the data lake?
Azure NetApp Files Ultra tier
Why wrong: Expensive and does not support ABFS.
Azure Files Premium tier
Why wrong: Does not support ABFS or hierarchical namespace.
Azure Data Lake Storage Gen2 with Archive tier for cold data
Supports all required protocols and hierarchical namespace.
Azure Blob Storage with hierarchical namespace enabled
Why wrong: Does not support NFS 3.0.
Answer choices
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 with Archive tier for cold data
Option C is correct because Azure Data Lake Storage Gen2 supports hierarchical namespace, multi-protocol access (ABFS, REST, NFS 3.0), and can use Archive tier for cold data. Option A is wrong because Azure Blob Storage does not support NFS 3.0 natively. Option B is wrong because Azure Files does not support ABFS or hierarchical namespace. Option D is wrong because Azure NetApp Files does not support ABFS and is expensive for petabyte-scale.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Azure NetApp Files Ultra tier
Why it's wrong here
Expensive and does not support ABFS.
Azure Files Premium tier
Why it's wrong here
Does not support ABFS or hierarchical namespace.
Azure Data Lake Storage Gen2 with Archive tier for cold data
Why this is correct
Supports all required protocols and hierarchical namespace.
Related concept
Static NAT maps one inside address to one outside address.
Azure Blob Storage with hierarchical namespace enabled
Why it's wrong here
Does not support NFS 3.0.
Common exam traps
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
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
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AZ-305 NAT questions on configuration and troubleshooting.
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FAQ
Design data storage solutions — This question tests Design data storage solutions — Static NAT maps one inside address to one outside address..
The correct answer is: Azure Data Lake Storage Gen2 with Archive tier for cold data — Option C is correct because Azure Data Lake Storage Gen2 supports hierarchical namespace, multi-protocol access (ABFS, REST, NFS 3.0), and can use Archive tier for cold data. Option A is wrong because Azure Blob Storage does not support NFS 3.0 natively. Option B is wrong because Azure Files does not support ABFS or hierarchical namespace. Option D is wrong because Azure NetApp Files does not support ABFS and is expensive for petabyte-scale.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AZ-305 NAT questions on configuration and troubleshooting.
Static NAT maps one inside address to one outside address.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
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 company is building a petabyte-scale data lake for analytics. They need a storage solution that supports a hierarchical namespace, POSIX-like permissions (ACLs), and is optimized for big data analytics workloads using Apache Spark and Hive. The data must be accessible over the Azure Blob Storage API. Which Azure data service should they use?
hardWhy B: Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines a hierarchical namespace with POSIX-like ACLs and is natively optimized for big data analytics workloads like Apache Spark and Hive. It exposes data through the Azure Blob Storage API, meeting all stated requirements for petabyte-scale analytics.
Variation 2. A company is building a petabyte-scale data lake for analytics. The workload includes Apache Spark and Hive jobs that read and write large files. The storage solution must support a hierarchical namespace for efficient directory operations, POSIX-like access control lists (ACLs) for fine-grained permissions, and must be accessible via the Azure Blob Storage API for compatibility with existing tools. Furthermore, the solution should be optimized for analytics workloads with high throughput. Which Azure data service should they choose?
hardWhy A: Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines a hierarchical namespace with POSIX-like ACLs and is accessible via the Azure Blob Storage API. This service is specifically optimized for analytics workloads like Apache Spark and Hive, providing high throughput for petabyte-scale data lakes. The hierarchical namespace enables efficient directory operations, while the Blob Storage API ensures compatibility with existing tools.
Variation 3. A company is building a big data analytics platform that will process structured, semi-structured, and unstructured data using Azure Synapse Analytics and other tools. They need a storage layer that supports hierarchical namespaces and fine-grained access control at the directory level. Which Azure storage solution should they use?
mediumWhy B: Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines Azure Blob Storage with a hierarchical namespace, enabling directory-level access control lists (ACLs) and POSIX-compliant permissions. This is essential for the big data analytics platform described, as it must support structured, semi-structured, and unstructured data with fine-grained access control at the directory level, which Azure Synapse Analytics can directly query via ABFS (Azure Blob File System) driver.
Variation 4. An enterprise data platform must store petabytes of raw files for analytics and support fine-grained access control through Microsoft Entra ID. Which storage solution should be selected?
mediumWhy D: Azure Data Lake Storage Gen2 (ADLS Gen2) combines a hierarchical namespace with Azure Blob Storage, enabling petabyte-scale storage for raw files and fine-grained access control via POSIX-like ACLs integrated with Microsoft Entra ID (formerly Azure AD). This makes it the ideal solution for enterprise analytics requiring both massive capacity and granular security.
Last reviewed: Jun 20, 2026
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