Object storage, block storage, and VM disk solve different storage problems. VM disk is the system or data disk attached to one virtual machine. Block storage presents raw disk capacity that an operating system can format and mount. Object storage keeps files as API-addressable objects inside buckets rather than exposing a normal filesystem.
The important nuance is that VM disk and block storage are not always separate technologies. A VM disk is commonly presented to the operating system as a block device. In architecture decisions, however, “VM disk” describes data that is operationally coupled to one server, while an attached block volume and an object bucket create clearer storage boundaries.
For teams using Raff Technologies, this guide answers the practical question: what should live on the VM disk, what belongs on an attached volume, and what should move into object storage? For the wider production model that also covers backups and restore testing, read Storage and Recovery Architecture for Production Apps.
The quick storage decision
Use this framework before choosing a storage layer.
| Workload or data | Better default | Why |
|---|---|---|
| Operating system and packages | VM disk | They belong to the server runtime |
| Application code and deployment files | VM disk | They should be reproducible from source or build artifacts |
| Temporary processing files | VM disk or block volume | The choice depends on size, lifetime, and disk pressure |
| Self-hosted database data | Block volume or managed database | The workload expects disk and filesystem semantics |
| Persistent container data | Block volume | State must survive container recreation |
| User uploads and media | Object storage | Files should scale separately from the app server |
| Reports, exports, and build artifacts | Object storage | They are durable file objects, not server runtime |
| Backup exports and archives | Object storage | Retention should not depend on the source VM |
| Short-term recovery point | Snapshot or backup product | Primary storage and recovery points solve different problems |
A useful default is:
Use VM disk for runtime, block storage for disk-like persistent data, and object storage for durable files accessed through an API.
This is a starting point, not an absolute rule. The correct choice depends on how the application reads the data, how independently the data must grow, and what the recovery plan requires.
Object storage and block storage use different access models
The defining difference is not capacity. It is how applications access and modify data.
Amazon Web Services describes block storage as data divided into addressable blocks, while object storage keeps data as objects with identifiers and metadata. Google Cloud’s storage comparison makes the same distinction and separates both models from shared file storage.
Block storage behaves like a disk
A block volume appears to the operating system as a disk device. You create a filesystem, mount it, and let software read or write through normal disk operations.
That makes block storage a strong fit for:
- PostgreSQL, MySQL, MongoDB, and other self-hosted databases
- Docker or container data directories
- Stateful applications that require a mounted path
- Search indexes and application state
- Large processing workspaces
- Data that needs to grow separately from the VM system disk
The application usually does not need to understand a storage API. It writes to a filesystem path, and the operating system handles the underlying blocks.
Object storage behaves like an API service
Object storage keeps data in buckets. Applications upload and retrieve objects by key through HTTP and an object-storage API such as S3.
That makes object storage a strong fit for:
- User uploads
- Images, audio, video, and documents
- Static assets
- Generated reports and exports
- Backup archives
- Logs and artifacts kept for longer retention
- Files that several app servers or workers need to access
Object storage is not a drop-in replacement for a database data directory or an application that expects a normal mounted disk. The application must use an object-storage client, SDK, command-line tool, or compatible integration.
VM disk is a lifecycle decision
A VM disk is the disk attached to the virtual machine for its operating system and local data. From inside Linux or Windows, it behaves like a normal disk. Operationally, the important question is whether the data should remain coupled to that server.
VM disk is the simplest choice when the data belongs to the machine itself:
- Operating system
- Packages and dependencies
- Application runtime
- Service configuration
- Controlled local logs
- Caches
- Temporary files
- Rebuildable application assets
For a prototype or a small single-server application, the VM disk can also hold a modest database or small set of files. That can be a reasonable starting point when the team understands the trade-off.
The model becomes risky when the same disk turns into the permanent home for everything:
VM disk ├── operating system ├── application ├── database ├── user uploads ├── reports ├── logs └── backup archives
In that layout, one full disk can affect the whole application. Storage growth can force a compute resize. Rebuilding or replacing the VM also becomes a data-migration event. Backup and restore scope becomes harder to explain.
The decision is therefore not “Is VM disk bad?” It is “Which data should remain tied to this VM?”
Block storage is for persistent filesystem data
Choose an attached block volume when software needs a disk but the data deserves a clearer boundary than the system disk provides.
A common layout is:
VM system disk └── OS, packages, application runtime Attached block volume └── database files, container state, application data
This separation is valuable when:
- Storage needs to grow without adding CPU or RAM
- A database or service needs a dedicated mount path
- Persistent container data should be separated from the host runtime
- Disk usage, ownership, and recovery need clearer monitoring
- The team may replace or rebuild the app VM independently
Block storage does not remove operational responsibility. A self-hosted database still needs database-aware backups, restore tests, monitoring, capacity planning, and a safe upgrade process. A volume stores active data; it is not automatically a historical recovery copy.
For the narrower volume decision, read Block Storage Volumes for Databases, Containers, and App Data.
Object storage is for durable file objects
Choose object storage when files should exist independently from any single app server and the application can access them through an API.
A common SaaS pattern is:
Application VM ├── validates the request └── stores object metadata in the database Object storage └── stores the uploaded file
The database might keep the owner, object key, filename, size, content type, access status, and creation date. The bucket stores the actual file.
This model is valuable when:
- User files are part of the product
- Upload growth is unpredictable
- Multiple app instances need the same files
- Workers or functions process the same inputs and outputs
- Files must remain available when the app VM is rebuilt
- Reports, exports, or archives need their own retention policy
- VM backups should not grow with every uploaded file
Object storage can also act as the retained destination for database dumps and backup artifacts. The database itself still needs an appropriate primary storage layer and a tested restore procedure.
For the upload-specific decision, read App Uploads: VM Disk vs Object Storage for SaaS Teams.
VM disk is not the same as shared file storage
Searches for object storage vs block storage often include file storage as the third model. File storage exposes a shared hierarchical filesystem through protocols such as NFS or SMB. Multiple clients can access folders and files through familiar paths and permissions.
A VM disk also contains a filesystem, but it is not automatically shared file storage. It is normally attached to one VM. You could run a file server on that VM, but then your team owns the file-serving layer, availability model, permissions, backups, and scaling.
Choose shared file storage when several systems need normal filesystem paths and existing applications cannot use object APIs. Choose object storage when applications can work with buckets and object keys. Choose block storage when one workload needs a disk device and filesystem it controls.
Raff’s current public storage choices in this decision are Raff Volumes for attached block storage and Raff Object Storage for S3-compatible object storage.
Performance depends on the workload’s access pattern
“Which storage is faster?” is too broad to guide architecture.
Block storage is designed for workloads that perform frequent reads and writes through a filesystem or database engine. Databases, container state, and transactional applications depend on that behavior.
Object storage is designed around complete objects and API operations. It fits files that are uploaded, downloaded, listed, retained, or shared as objects. It is not intended to provide low-level disk access to a database engine.
VM disk performance depends on the underlying disk implementation and the VM plan. Its architectural advantage is simplicity. Its limitation is that runtime, persistent state, and capacity can become coupled unless the team separates them deliberately.
Use these questions instead of asking which option is fastest:
- Does the software expect a mounted filesystem or raw disk?
- Does it frequently update small parts of existing data?
- Is the data naturally handled as complete files or objects?
- Must several servers access the same files?
- Should storage capacity grow separately from compute?
- What must be restored after the VM is rebuilt?
The answers usually make the correct storage model clear.
Recovery requirements should shape the choice
Primary storage and backups are different layers.
A VM disk, attached volume, or object bucket holds active data. Snapshots and backups create recovery points. Replication or infrastructure durability cannot recover the correct previous state after every accidental deletion, bad migration, or application-level corruption.
For each data set, define:
- Which system is the source of truth?
- Can the data be recreated?
- How much data loss is acceptable?
- How quickly must the workload return?
- Where are recovery copies stored?
- Has the restore path been tested?
Examples:
| Data | Primary layer | Recovery consideration |
|---|---|---|
| OS and app runtime | VM disk | Rebuild from documented deployment process |
| Self-hosted database | Block volume or VM disk | Use database-aware backups and restore tests |
| User uploads | Object storage | Define access, retention, deletion, and recovery rules |
| Temporary workspace | VM disk or volume | Recreate or clean up; backup may be unnecessary |
| Backup archive | Object storage | Verify retention and test the restore workflow |
Raff separates these responsibilities across Raff VM, Raff Volumes, Raff Object Storage, and Raff Data Protection. The architecture is strongest when each layer has one clear job.
Most production applications use more than one layer
The choice is rarely object storage or block storage or VM disk for the entire system. A production application commonly uses all three.
Raff VM disk └── OS, packages, app runtime, temporary files Raff Volume └── self-hosted database or persistent container data Raff Object Storage └── uploads, reports, media, exports, archives Raff Data Protection └── snapshots, backups, retention, recovery workflow
This separation reflects a decision Raff makes at the platform level: storage should follow data behavior instead of forcing every byte into the server’s lifecycle. Compute can then change for compute reasons, while file capacity and persistent disk capacity can change according to their own workloads.
Start simpler when the workload is small. Add separation when it reduces a real risk: disk pressure, recovery scope, multi-server access, data growth, or operational ownership.
Common storage mistakes
Treating every file as block-storage data
A mounted volume can store uploads, but that does not make it the best long-term home for them. Files shared across app servers or accessed as complete objects usually fit object storage better.
Treating object storage like a normal disk
Object storage requires API-aware application behavior. Do not place a database data directory or ordinary filesystem-dependent application directly in a bucket.
Assuming a separate volume is a backup
A volume creates a storage boundary. It does not provide historical recovery by itself. Protect active data with an appropriate backup and restore plan.
Resizing compute only because storage is full
When disk capacity grows faster than CPU and RAM needs, separate storage may be cleaner than moving the whole workload to a larger VM plan.
Keeping retained backups on the source VM
A backup copy that depends on the same server and disk as the source has a weak failure boundary. Retained copies should follow a recovery design that survives loss of the source workload.
Choose the storage layer by data behavior
Use VM disk for the operating system, application runtime, controlled logs, caches, and temporary or rebuildable data. Use block storage when a database, container, or stateful application needs persistent filesystem behavior. Use object storage for uploads, media, reports, exports, artifacts, and backup files that should scale separately from compute.
Then design snapshots, backups, retention, and restore tests around those primary layers. The goal is not to use every product. It is to give each important data set a clear owner, access model, growth path, and recovery path.
Continue with Storage and Recovery Architecture for Production Apps to place these storage choices inside a complete production recovery design.