Quick Answer
The answer is Azure Data Lake Storage Gen2 because it provides petabyte-scale storage for cold historical data at minimal cost while meeting a five-minute query SLA. This solution combines a hierarchical namespace with Azure Blob Storage’s tiered access tiers—Cool or Archive—allowing you to store rarely accessed regulatory data cheaply, yet query it quickly via tools like Azure Synapse or PolyBase. On the AZ-305 exam, this scenario tests your ability to balance cost against performance for cold data workloads, often appearing as a trap where candidates mistakenly choose Azure Archive Storage alone, which lacks the fast query capability. Remember that ADLS Gen2 is essentially Blob Storage with a file-system structure, so it supports both low-cost tiers and on-demand queries. A useful memory tip: “Cold data needs a warm path—ADLS Gen2 keeps the archive cool but the query fast.”
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 multinational corporation needs to store and analyze petabytes of historical data for regulatory reporting. The data is rarely accessed but must be available for queries within 5 minutes. Which Azure storage solution should they choose to minimize cost?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Azure SQL Database
Why wrong: Azure SQL Database is expensive for petabyte-scale data.
Azure Data Lake Storage Gen2
ADLS Gen2 is cost-effective for large volumes of data and supports fast queries with query acceleration.
Azure Files
Why wrong: Azure Files is not suitable for analytics workloads.
Azure Cosmos DB
Why wrong: Azure Cosmos DB is not designed for petabyte-scale analytics.
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
Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines a hierarchical namespace with Azure Blob Storage's massive scalability, enabling petabyte-scale storage at low cost. It supports fast queries via tools like Azure Synapse or PolyBase, meeting the 5-minute query SLA for cold data, while its tiered storage (e.g., Cool or Archive access tiers) minimizes cost for rarely accessed historical data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Azure SQL Database
Why it's wrong here
Azure SQL Database is expensive for petabyte-scale data.
Azure Data Lake Storage Gen2
Why this is correct
ADLS Gen2 is cost-effective for large volumes of data and supports fast queries with query acceleration.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Azure Files
Why it's wrong here
Azure Files is not suitable for analytics workloads.
Azure Cosmos DB
Why it's wrong here
Azure Cosmos DB is not designed for petabyte-scale analytics.
Common exam traps
The trap here is that candidates often choose Azure SQL Database or Cosmos DB for 'query performance' without considering the massive cost and architectural mismatch for petabyte-scale cold data, or they pick Azure Files thinking 'file storage' implies analytical capability, ignoring its lack of native query engines and higher cost per GB.
Detailed technical explanation
ADLS Gen2 leverages Azure Blob Storage's object store with a hierarchical namespace, allowing POSIX-like access control and directory operations without the overhead of a traditional file system. Its integration with Apache Hadoop and Spark via the ABFS driver enables distributed analytics directly on stored data, while lifecycle management policies can automatically move cold data to the Archive tier, reducing storage costs to ~$0.002/GB/month. In practice, a financial institution storing 10 PB of trade records could query a year's subset in under 5 minutes using Synapse serverless SQL, paying only for compute on demand.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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
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FAQ
Design data storage solutions — This question tests Design data storage solutions — Read the scenario before looking for a memorised answer..
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's massive scalability, enabling petabyte-scale storage at low cost. It supports fast queries via tools like Azure Synapse or PolyBase, meeting the 5-minute query SLA for cold data, while its tiered storage (e.g., Cool or Archive access tiers) minimizes cost for rarely accessed historical data.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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