Quick Note — Recommend a Solution for Storing Unstructured Data
AZ-305 › Unit 2 › Design data storage for semi-structured and unstructured data › Recommend a solution for storing unstructured data
Quick Note — Recommend a Solution for Storing Unstructured Data
This lesson teaches you how to evaluate Azure's unstructured-storage portfolio — Blob, File, Queue, Table, and Data Lake Storage Gen2 — and recommend the right service, account kind, and access tier for a given workload. The decisions you make here cascade through the rest of an architecture: cost, durability, throughput, and even what compute and analytics services you can choose downstream all hinge on whether you picked the right storage shape upstream.
Retrieval target
- Recommend a Solution for Storing Unstructured Data
- Closed-book recall
- 5 minutes
- Open the full lesson after a miss
Decision anchors
| Prompt | Compact answer |
|---|---|
Block blob vs Append blob vs Page blob | Block blob — the default; large files / objects up to $190.7 TiB, composed of variable-size blocks. Use for media, backups, logs uploaded as files. Append blob — optimized for append-only writes (log streams, audit trails); no in-place updates. Page blob — random-access 512-byte pages up to 8 TiB; the storage type behind unmanaged Azure VM disks. Pick by access pattern, not by file content. |
Blob access tiers — Hot, Cool, Cold, Archive | Hot — frequent access, highest storage cost, lowest access cost; no early-delete penalty. Cool — infrequent (-day retention), lower storage, higher access; 30-day early-delete fee. Cold — even cheaper than Cool, -day retention; online, slightly higher access cost. Archive — cheapest storage but offline; data must be rehydrated to Hot/Cool before read; -day retention.… |
Azure Data Lake Storage Gen2 (ADLS Gen2) | Azure Blob Storage with the Hierarchical Namespace (HNS) feature enabled — adds POSIX-style directories, ACLs per file/dir, and analytics-engine optimizations (path-prefix scans). Inherits all Blob primitives: tiers (Hot/Cool/Cold/Archive), redundancy (LRS/ZRS/GRS), lifecycle management, encryption. The standard storage for big-data analytics on Synapse, Databricks, HDInsight, Fabric. |
Azure File Share (Azure Files) | Microsoft's managed SMB / NFS file share in the cloud. Mount from Windows / Linux / macOS; accessible on-prem via VPN, ExpressRoute, or Azure File Sync. Two performance tiers: Standard (HDD-backed) and Premium (SSD-backed, separate File Storage account kind). Use for lift-and-shift workloads that need a real file system (legacy apps, scratch space for compute). |
Read the answers once, then cover the right-hand column and reconstruct each one from the prompt. A useful answer names the requirement, the recommended control or service boundary, and the nearest alternative it rejects. If you can only recognize the answer after seeing it, retrieval is not yet secure.
Ninety-second explanation
Without notes, explain:
- What requirement signals this learning objective rather than a neighbouring one?
- Which two solution families are most likely to be compared?
- Which hard constraint eliminates the strongest distractor?
- What identity, network, data, or failure boundary must appear in the design?
- Which operational test would prove the recommendation works?
Then compare your explanation with the full lesson. Record the missing decision rule—not merely the missed product name—in your error log.
When to open the full lesson
Open the curriculum-linked lesson when you cannot explain a comparison, when a scenario depends on a numeric limit or SKU feature, or when the service is on a retirement path. Use current Microsoft Learn documentation for availability, limits, pricing, naming, and migration milestones; the quick note is intentionally compact.
Source and freshness
Derived from the linked AZ-305 lesson and retrieval deck, grounded in both attached course sources. Reviewed 2026-08-02. Current Microsoft documentation controls changing product contracts.