AZ-204 Develop for Azure storage Practice Question
You are developing a .NET application that needs to store and retrieve large binary objects (up to 4.7 TB) in Azure Blob Storage. The application requires the lowest possible latency for reads and must support object-level tiering. Which blob type should you use?
⚠ Common exam trap
A common mix-up: candidates confuse storage account tiers (Hot, Cool, Archive) with blob types, or assume Page blobs are suitable for large binary objects because of their high maximum size, overlooking that Page blobs lack object-level tiering and are designed for VHDs, not general binary storage.
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
✓
Block blob
Block blobs are designed for storing large binary objects up to approximately 4.74 TB and support object-level tiering (Hot, Cool, Cold, Archive). They offer the lowest read latency among Azure blob types because they can be accessed directly via HTTP/HTTPS and are optimized for streaming and random read access. Object-level tiering allows you to change the access tier of individual blobs without moving the storage account, which meets the requirement for granular cost optimization.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Block blob
Why this is correct
Block blobs are the standard choice for storing large amounts of unstructured object data, such as documents, images, and videos. They are optimized for streaming and parallel uploads, composed of individual blocks, and crucially support object-level tiering (Hot, Cool, Archive). This tiering capability allows for cost optimization based on access frequency, making them highly versatile for various data storage needs up to approximately 4.75 TB.
- ✗
Archive storage account
Why it's wrong here
Archive is a storage tier, not a distinct storage account type or blob type. It is designed for very infrequently accessed data with flexible latency requirements, typically hours for data retrieval, making it unsuitable for scenarios demanding immediate or low-latency access. While highly cost-effective for long-term retention, its retrieval characteristics preclude it from being a general solution for storing objects that might require regular access.
- ✗
Page blob
Why it's wrong here
Page blobs are specifically optimized for random read/write operations on fixed-size 512-byte pages, making them the underlying storage for Azure Virtual Machine VHDs. Unlike block blobs, they do not support object-level tiering (Hot, Cool, Archive), which is a critical feature for managing costs based on data access patterns for general-purpose objects. Their design is tailored for disk-like operations rather than general object storage.
- ✗
Append blob
Why it's wrong here
Append blobs are uniquely optimized for append operations, where new blocks are always added to the end of the blob, making them ideal for logging, auditing, or other scenarios requiring continuous data streams. They do not support arbitrary overwrites or random access within the blob, nor do they offer object-level tiering. This specialized append-only nature makes them unsuitable for general-purpose large binary objects that may require updates or varied access patterns.
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 |
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