Describe considerations for working with non-relational data on Azure →easyMultiple ChoiceObjective-mapped
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
A company is migrating on-premises Hadoop HDFS data to Azure. They want to keep the same file system semantics for compatibility with existing analytics jobs. Which Azure storage solution 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) provides Hadoop-compatible file system semantics (hierarchical namespace) and is built on Blob Storage. Azure Blob Storage does not have a hierarchical namespace by default. Azure Cosmos DB and Azure SQL are not file systems.
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
Azure Blob Storage is a general-purpose object storage service that organizes data in a flat, container-based namespace. Without enabling the hierarchical namespace feature, it lacks HDFS-compatible POSIX semantics such as atomic directory renames and true directory listings, meaning Hadoop jobs (e.g., Spark, MapReduce) cannot directly rely on it as a native HDFS file system. Even though Blob Storage can hold the same data, the missing file-system abstraction forces workarounds (like WASB with slower rename operations) that break analytic workloads, so it is not the best landing zone for a straightforward HDFS migration.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is a fully managed relational database engine optimized for transactional queries and structured schemas. It does not support Hadoop's file-based access patterns, cannot be mounted as a distributed file system, and does not provide APIs or drivers for HDFS utilities. Migrating HDFS data into SQL Database would require converting files into tables, which is impractical for large-scale, schema-on-read analytics data that is typical of Hadoop workloads. Therefore, it is an incorrect target for an HDFS-to-Azure data lake migration.
- ✓
Azure Data Lake Storage Gen2
Why this is correct
Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct migration target because it is built on Azure Blob Storage but adds a hierarchical namespace that mirrors HDFS. It exposes a native HDFS-compatible ABFS driver plus a REST API, enabling Hadoop, Spark, and Databricks to read and write data with full file-system semantics like atomic rename and POSIX file permissions. ADLS Gen2 is specifically designed for big data analytics and is the Azure service that most closely and natively replaces an on-premises Hadoop HDFS cluster.
- ✗
Azure Cosmos DB
Why it's wrong here
Azure Cosmos DB is a globally distributed, multi-model NoSQL database service designed for low-latency, schema-flexible data access. It does not provide a file-based storage interface, hierarchical namespace, or HDFS compatibility, so Hadoop file operations such as block reads, directory listings, and rename are entirely unsupported. Using Cosmos DB for HDFS migration would require rearchitecting the entire data layer into document or graph data, which loses the file-oriented nature of the original workload and is therefore incorrect.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Data Lake Storage Gen2
Data Lake Storage Gen2 is a cloud-based storage service that combines a scalable data lake with enterprise-grade file system capabilities for big data analytics.
Key term
Azure Cosmos DB
Azure Cosmos DB is a fully managed, globally distributed NoSQL database service that offers fast reads and writes anywhere in the world with automatic scaling and multiple consistency models.
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