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DP-203 Design and implement data storage Practice Question

A company is designing a data storage solution for IoT device telemetry data. The data is append-only, needs to be stored cost-effectively for long-term analytics, and must support querying by device ID and timestamp. Which Azure storage solution should they use?

⚠ Common exam trap

Candidates often confuse Azure Blob Storage with ADLS Gen2, assuming that Blob Storage alone supports hierarchical namespace and efficient querying, when in fact ADLS Gen2 is required for the hierarchical namespace and POSIX-like directory structure that enables partition pruning and cost-effective analytics on append-only data.

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 the cost-effective, append-only blob storage of Azure Blob Storage with a hierarchical namespace that enables directory-level operations and POSIX-like access control. This makes it ideal for storing large volumes of IoT telemetry data at low cost while supporting efficient querying by device ID and timestamp through partition pruning in tools like Azure Synapse Analytics or Apache Spark.

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 Data Lake Storage Gen2

    Why this is correct

    Azure Data Lake Storage Gen2 suits append-only telemetry because its hierarchical namespace organises data into directories partitioned by device ID and timestamp, enabling efficient partition pruning during analytics queries. It also layers the cost-effective Hot, Cool and Archive tiers over Blob storage, satisfying the long-term retention requirement without sacrificing query performance.

  • ✗

    Azure Cosmos DB

    Why it's wrong here

    Cosmos DB bills provisioned or serverless request units plus storage, making long-term retention of high-volume telemetry expensive. It is tempting because it indexes device ID and timestamp efficiently for queries, but the cost-effective long-term storage requirement points to Blob Storage instead.

  • ✗

    Azure SQL Database

    Why it's wrong here

    Azure SQL Database is a relational engine with provisioned compute and per-GB pricing, so it cannot store append-only telemetry cost-effectively at scale. It is tempting because SQL queries by device ID and timestamp are natural, but the cost and volume requirements rule out a transactional database.

  • ✗

    Azure Blob Storage with hot access tier

    Why it's wrong here

    The hot tier stores frequently accessed data at the highest per-GB cost, contradicting the long-term cost-effective requirement; Blob Storage's archive or cool tiers fit instead. Hot is tempting because Blob Storage itself suits append-only telemetry, but the tier choice breaks the cost constraint.

Quick reference

Azure Blob Storage Tier Comparison

TierStorage CostRetrieval CostLatencyUse Case
HotHighestLowestImmediateActive data, frequent reads
CoolLowerHigherImmediateData accessed < once / month
ColdLower stillHigherImmediateData accessed < once / quarter
ArchiveLowestHighest + rehydration delayHoursLong-term compliance retention

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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