Academmia

Compare Azure Storage Services

az-900•mixed•

Azure architecture and services

Compare Azure Storage Services

Short Summary

Azure has multiple storage services because “storage” isn’t one thing: it depends on how you read and write data. In this lesson, I compare Blob Storage, Azure Files, Queue Storage, Table Storage, and Azure managed disks. The goal is to pick the service that matches your data shape (objects, files, messages, entities, or blocks) and your access pattern.

Learning Objectives

By the end of this lesson, you will be able to:

  • Differentiate object, file-share, message, NoSQL entity, and VM-attached block storage in Azure.
  • Select the correct Azure storage service for a scenario (Blob, Files, Queues, Tables, or managed disks).
  • Explain how a storage account relates to Blob/Files/Queue/Table services.
  • Contrast Azure managed disks with shared storage options used by multiple machines.
  • Identify common mistakes when choosing between these storage services.

Core Concepts

One idea to keep straight: “storage account” vs “managed disk”

A storage account is the container and address space (endpoints) for several Azure Storage data services:

  • Azure Blob Storage
  • Azure Files
  • Azure Queue Storage
  • Azure Table Storage

An Azure managed disk is different: it’s block-level storage created for and attached to a Virtual Machine (VM). You don’t browse a managed disk directly over the internet the way you do with blobs; you use it through the VM’s Operating System (OS) file system.

Azure Blob Storage: object storage for unstructured data

What it is: An object store for “blobs” (binary large objects), optimized for large amounts of unstructured data (images, documents, logs, backups, video/audio).

How you access it: Typically via Hypertext Transfer Protocol (HTTP) / HTTP Secure (HTTPS) using Representational State Transfer (REST) APIs, SDKs, CLI tools, or portal tools.

When it fits: When you store files as objects and fetch them by URL/key, stream content, archive data, or write logs.

When it’s not the best fit: When you need classic shared-folder semantics (mount a drive, file locking, SMB-style permissions).

Azure Files: managed file shares (shared folders in the cloud)

What it is: Fully managed cloud file shares that behave like a traditional file server share.

How you access it: Mounted using Server Message Block (SMB) and, where supported, Network File System (NFS); also accessible via REST/SDKs.

When it fits: When multiple machines (cloud or on-premises) need to read/write the same set of files via file share semantics (lift-and-shift apps, shared tools/configs, common exports, shared user profiles).

When it’s not the best fit: When you want internet-addressable object storage with URL-based access and massive object-scale patterns (Blob is usually the first stop there).

Azure Queue Storage: simple messaging for asynchronous work

What it is: A queue service for storing lots of messages so components can communicate reliably without being online at the same time.

How you access it: Through authenticated HTTP/HTTPS calls using APIs/SDKs.

When it fits: When you want a backlog of work (for example, “process these uploaded files later”) or you need to decouple parts of an app.

When it’s not the best fit: When you treat the queue as your primary data store, or when you need advanced messaging features (ordering guarantees, sessions, complex routing).

Azure Table Storage: schemaless NoSQL entities (simple structured data)

What it is: A Not Only SQL (NoSQL) key/attribute-style store for large amounts of structured data that doesn’t need joins, foreign keys, or complex relational queries.

How you access it: Via APIs/SDKs. Data is organized as entities with properties (schemaless at the table level).

When it fits: When you need fast lookups by key and flexible schema (e.g., device inventory, user preferences, lightweight metadata, many small records).

When it’s not the best fit: When you need relational modeling, joins, complex reporting queries, or strict relational constraints.

Azure managed disks: block storage attached to VMs

What it is: Block-level storage volumes used as OS disks or data disks for Azure VMs.

How you access it: Through the VM (the OS sees it as a disk device). It’s designed for VM workloads and performance tiers.

When it fits: When a VM needs durable disk storage for its OS, databases, or application data that lives “on the machine.”

When it’s not the best fit: When you want multiple machines mounting the same storage as a shared folder (Azure Files is the typical starting point there).

Practical Understanding

Practical Situation 1: Hosting images/documents for web access

You need to store product images and let web clients fetch them quickly by URL.

Good fit: Azure Blob Storage, because it’s optimized for object storage and URL/HTTP access patterns.

Common misunderstanding: “Azure Files is also for files, so it’s the same thing.” Blob is object storage accessed like objects/URLs; Files is a mounted share (SMB/NFS) with file share semantics.

Practical Situation 2: Several VMs need the same shared folder

You have multiple Virtual Machines (VMs) that all need to read and write the same set of files (shared configs, shared exports, shared tooling).

Good fit: Azure Files, because it provides a managed file share that multiple machines can mount.

Common misunderstanding: “I’ll attach the same managed disk to all VMs and use it like a shared drive.” Managed disks are VM-attached block storage; they are not the typical “shared folder for many machines” solution.

Practical Situation 3: Decoupling an upload step from a processing step

Users upload files, and you want a background worker to process them later (resize, virus scan, transform) without slowing the upload experience.

Good fit: Azure Queue Storage, because it’s designed to hold messages that represent “work to do” asynchronously.

Common misunderstanding: “I’ll store the file itself inside the queue message.” Queues are for lightweight messages (instructions/IDs), not for storing the actual data payload.

Practical Situation 4: Storing simple structured records without relational queries

You want to store lots of small structured items (e.g., settings per customer, a device list with properties, lightweight metadata) and you mostly query by key.

Good fit: Azure Table Storage, because it’s a schemaless NoSQL store that’s great for key-based access at scale.

Common misunderstanding: “It’s basically SQL in a table.” Despite the name, Table Storage isn’t a relational database. If you need joins and relational constraints, look at a relational database service instead.

Common Pitfalls

  • Mistake: Choosing Azure Files for public, URL-based object delivery. Correction: Use Azure Blob Storage when your access pattern is object/URL/HTTP-based.

  • Mistake: Using Azure Blob Storage when you need a shared folder mounted by multiple machines. Correction: Use Azure Files when you need file share semantics (SMB/NFS mounts).

  • Mistake: Treating Azure Queue Storage as a database or long-term data store. Correction: Use queues for “work items” and store real data in a storage service designed for it (Blob, Table, a database, etc.).

  • Mistake: Assuming Azure Table Storage provides relational database features (joins, relationships, SQL queries). Correction: Use Table Storage for key/attribute access and flexible schema; use a relational database when you need relational querying and constraints.

  • Mistake: Assuming a managed disk is the same as “shared storage.” Correction: Use Azure managed disks for VM-attached block storage; use Azure Files for shared access by multiple machines.

  • Mistake: Picking a service only by the word “file” instead of by access pattern. Correction: Start by asking: “Do I access this as objects, as a mounted share, as messages, as entities, or as a VM disk?”

Check Your Understanding

  • You need to store and serve large video files globally to clients over HTTPS. Which storage service fits best, and why?
  • You have two VMs that must read and write the same set of files at the same time. Why is a file share different from a managed disk here?
  • In an app, you want to buffer background tasks so your front-end stays fast. What should go into the queue message, and what should not?
  • You need to store millions of simple records where you mostly fetch by key and don’t need joins. What makes Table Storage a better fit than a relational database for that scenario?
  • In one sentence, describe the biggest “chooser rule” that separates Blob Storage from Azure Files.

Further Reading