Object storage and block storage solve different problems. Use block storage when software needs a disk or mounted filesystem with low-level read/write behavior, such as a self-hosted database, container data directory, or stateful application. Use object storage when the application handles durable files through an API, such as uploads, media, reports, archives, and backup artifacts. Keep VM disk for operating-system and application runtime data that can remain coupled to one server.
That distinction matters more than raw capacity. A 100 GB block volume and a 100 GB object bucket may hold the same number of bytes, but applications use them in fundamentally different ways.
For teams using Raff Technologies, the practical mapping is straightforward: Raff Volumes provide attached block storage, Raff Object Storage provides S3-compatible object storage, and the VM system disk remains the local runtime layer. Most production applications use more than one of these rather than choosing a single storage type for everything.
Object storage vs block storage: quick answer
| Decision | Block storage | Object storage | VM disk |
|---|---|---|---|
| Access model | Disk / filesystem | API / object key | Local disk on one VM |
| Best for | Databases, container state, mounted app data | Uploads, media, reports, archives, backup objects | OS, packages, runtime, caches, temporary files |
| Application sees | Device + filesystem path | Bucket + object key | Local filesystem path |
| Partial/in-place updates | Natural through filesystem/database I/O | Usually replace/update object through API | Natural through filesystem |
| Shared across app servers | Not by default | Yes, through API | No, tied to one VM |
| Scale storage separately from compute | Yes | Yes | Usually less clean operationally |
| Survive app-VM replacement cleanly | Yes, with correct attachment/recovery process | Yes, independent of VM lifecycle | Data is operationally coupled to the VM |
| Backup role | Primary persistent storage, not automatically backup | Can store durable files and backup artifacts | Primary server disk, not automatically backup |
| Typical Raff layer | Volumes | Object Storage | Raff VM |
A useful rule is:
If the workload expects a disk, choose block storage. If the application expects files as objects, choose object storage. If the data belongs to one server’s runtime, keep it on the VM disk.
The main difference is the access model
The most important difference between block storage and object storage is not performance, price, or maximum size. It is how software addresses and changes data.
Block storage exposes disk capacity
Block storage presents storage to the operating system as a block device. Linux or Windows can format it with a filesystem and mount it like a disk.
Software can then use ordinary filesystem paths:
/dev/volume ↓ filesystem ↓ /mnt/data ↓ application / database / container
The application usually does not know or care that the filesystem sits on attached cloud block storage.
This is why block storage is a natural fit for:
- PostgreSQL, MySQL, MongoDB, Redis, and other self-hosted data services;
- Docker volumes and persistent container data;
- search indexes;
- stateful application directories;
- package repositories or build caches that require a filesystem;
- workloads that need frequent small reads and writes to existing data;
- data that should grow independently from the VM system disk.
Object storage exposes objects through an API
Object storage organizes data as objects inside buckets. Applications refer to each object by a key and interact through HTTP APIs or SDKs rather than treating the bucket like a normal local disk.
A simple model is:
bucket ├── users/123/avatar.jpg ├── reports/2026-09/invoice.pdf └── exports/customer-42.csv
This model works well when the application naturally handles complete files or blobs.
Typical object-storage workloads include:
- user uploads;
- images and media;
- documents;
- exports and generated reports;
- software artifacts;
- log archives;
- static assets;
- backup exports;
- files consumed by several services or workers.
Raff Object Storage is S3-compatible, so applications can use common S3 SDKs and tooling against the Raff endpoint rather than building a proprietary storage integration.
VM disk is an operational boundary, not a third storage protocol
A VM disk is usually exposed to the guest operating system as block storage too. That can make comparisons such as “block storage vs VM disk” confusing.
The useful difference is operational.
VM disk means the data remains part of one server’s lifecycle. Attached block storage creates a clearer data boundary that can be managed separately from the root/system disk.
Keep VM disk for data that belongs to the server itself:
- operating system;
- packages and dependencies;
- application runtime;
- deployment files that can be recreated;
- bounded local logs;
- caches;
- temporary processing files;
- generated files that can be rebuilt safely.
A small prototype may also keep a database or uploads on the VM disk. That is not automatically wrong. It becomes risky when the VM disk silently turns into the permanent home for every type of production state.
Risky single-disk model VM disk ├── OS ├── application ├── database ├── user uploads ├── reports ├── backups └── unbounded logs
In that design, a full disk can affect the entire application, storage growth can force unnecessary compute resizing, and rebuilding the server becomes a data-recovery project.
The better question is not “Can this data live on the VM disk?” It is “Should this data stay coupled to this VM?”
Block storage vs object storage vs file storage
Searches for object storage vs block storage often include file storage as a third model. File storage is different from both.
| Storage type | Access model | Common examples |
|---|---|---|
| Block storage | Raw block device formatted with a filesystem | Database disks, VM volumes, container state |
| Object storage | Bucket/object API | S3-style uploads, media, archives, artifacts |
| File storage | Shared hierarchical filesystem | NFS/SMB shared folders, legacy shared-file workloads |
File storage exposes normal directories and files to multiple clients through protocols such as NFS or SMB.
This is useful when several systems need shared filesystem semantics and the application cannot use an object API.
A VM disk contains a filesystem, but it is not automatically shared file storage. You can turn a VM into an NFS or SMB server, but then your team owns the file-service availability, permissions, patching, backups, and scaling.
Choose file storage when the workload genuinely requires a shared mounted filesystem. Choose object storage when the application can use buckets and object keys. Choose block storage when one workload needs a disk it controls.
Use block storage for self-hosted databases
A database data directory is a classic block-storage workload.
Database engines expect filesystem and storage behaviors that object storage does not provide as a direct replacement for the active data directory.
A self-hosted pattern can look like:
Application VM ↓ private network Database VM ↓ Attached block volume ↓ Database files
The attached volume creates a cleaner boundary between the database’s persistent state and the VM system disk.
That does not make the database managed or automatically protected. Your team still owns:
- database installation and patching;
- authentication and network access;
- monitoring;
- storage growth;
- database-aware backups;
- restore testing;
- replication or high availability when required;
- upgrades and incident recovery.
If you do not want to own those responsibilities, a Managed Database may be a cleaner architecture than running the engine yourself on a volume.
For the operating-model decision, use Managed Database vs Self-Hosted.
Use block storage for persistent container data
Containers are designed to be recreated. Important data should not disappear when a container is replaced.
A block volume is appropriate when the containerized service expects persistent filesystem state:
Docker host ↓ container ↓ mounted path attached block volume
Examples include:
- a self-hosted database container;
- stateful application data;
- plugin or extension data;
- search indexes;
- queue or service state that genuinely belongs on a filesystem.
Do not use a block volume merely because the application writes files. If those files are user uploads or generated artifacts that need to be shared across several app instances, object storage may be the better layer.
For a broader Docker infrastructure decision, see Docker VPS Hosting: What Developers Should Know.
Use object storage for uploads and media
User uploads are one of the clearest object-storage use cases.
A SaaS application can keep metadata in the database and place the actual file in object storage:
User upload ↓ Application validates request ↓ Object Storage stores file ↓ Database stores owner, object key, status and metadata
This creates several useful boundaries:
- file capacity can grow independently from the app VM;
- files survive application-server replacement;
- several app servers or workers can access the same objects;
- VM backups do not need to expand with every upload;
- file retention and application deployment can be managed separately.
This pattern fits images, PDFs, customer documents, exports, audio/video, and other durable application files.
Use App Uploads: VM Disk vs Object Storage for the deeper migration and architecture decision.
Use object storage for backup artifacts—but do not confuse that with backup strategy
Object storage is a practical destination for exported backup files because the backup artifact can live independently from the source VM.
Examples include:
- database dumps;
- application exports;
- configuration archives;
- long-retention backup objects;
- artifacts copied from a backup workflow.
But putting a file in object storage does not automatically create a complete backup strategy.
You still need to define:
- what is backed up;
- how often;
- retention;
- encryption and access;
- RPO and RTO;
- restore procedure;
- restore owner;
- restore-test cadence.
Likewise, an attached volume is not a backup simply because it is separate from the system disk.
For the wider recovery design, use Cloud Storage Architecture for Production Apps: Backup & Recovery and Snapshots vs Backups.
Performance: do not ask which storage type is “faster” in isolation
Block storage and object storage are optimized for different access patterns, so a generic performance ranking is not very useful.
Block storage fits workloads that need:
- low-level filesystem operations;
- frequent reads and writes;
- small changes to existing data;
- database I/O;
- mounted paths;
- operating-system-level access.
Object storage fits workloads that need:
- complete-object upload/download;
- durable file retention;
- API-based access;
- large numbers of independent objects;
- access from multiple application instances;
- separation from one server’s filesystem.
An object store may be highly scalable and durable while still being the wrong primary storage layer for a transactional database. A block volume may provide excellent database I/O while still being the wrong way to distribute millions of uploaded files across an application fleet.
Match the storage interface to the workload first. Optimize performance inside the correct storage model second.
Scaling: separate storage growth from compute growth
One common reason to move state away from the VM root disk is that storage and compute often grow at different rates.
Imagine an application with stable CPU/RAM demand but rapidly growing file uploads.
If files live on the VM disk:
more files → larger VM disk requirement → possibly larger VM plan or more complicated migration
If files live in object storage:
app compute stays stable → object capacity grows independently
The same principle applies to self-hosted database storage. If the database needs more disk but not more CPU or RAM, an attached volume gives storage its own capacity path.
This does not mean “always separate everything.” An early-stage workload may be simplest on one VM. Separate layers when the independence creates real value in scaling, recovery, operations, or multi-server access.
Recovery: primary storage and recovery copies are different layers
The primary storage decision answers where active data lives.
The recovery decision answers how you get the correct data back after failure, deletion, corruption, or a bad change.
| Data | Primary storage | Recovery approach |
|---|---|---|
| OS / runtime | VM disk | Rebuild or VM-level recovery |
| Self-hosted database | Block storage | Database-aware backup/PITR + tested restore |
| User uploads | Object storage | Retention/version/recovery policy appropriate to workload |
| Temporary workspace | VM disk or volume | Often rebuild instead of backup |
| Backup archive | Object storage / backup destination | Retention + restore procedure |
A volume can fail logically because data is deleted or corrupted. Object storage can contain the wrong version of a file. Replicas can copy a destructive change. VM snapshots can be insufficient for application-aware recovery.
For production systems, define the recovery model separately from the active-storage model.
Security and access differ by storage model
Block storage is generally accessed through the VM that has the device mounted. Security therefore includes the VM’s operating system, administrator access, filesystem permissions, encryption choices, and network exposure of the application using the disk.
Object storage is accessed through service credentials and APIs. Security therefore includes:
- bucket access policy;
- API credentials;
- application permissions;
- public/private object exposure;
- signed or temporary access patterns where appropriate;
- credential rotation;
- retention and deletion permissions.
Do not make a bucket public merely because files need to be downloadable. Likewise, do not expose a self-hosted database publicly merely because its data sits on durable block storage.
The storage layer changes the access boundary, not the need for least privilege.
Cost comparisons need the whole workload
A useful storage-cost comparison includes more than price per GB.
For block storage, consider:
- provisioned capacity;
- VM resources required to operate the workload;
- snapshots/backups;
- database or service operations;
- monitoring and recovery work.
For object storage, consider:
- stored capacity;
- request/access pattern;
- data movement where applicable;
- retention;
- application integration work;
- lifecycle policies.
For VM disk, consider the cost of keeping storage coupled to the server, including whether storage growth forces VM resizing or enlarges every VM backup.
The cheapest GB is not automatically the cheapest architecture.
How Raff maps to the storage decision
Raff currently provides distinct layers for these needs:
Raff VM
Use Raff VM for the operating system, application runtime, caches, temporary files, and local data that should remain tied to one server.
Raff Volumes
Use Volumes when a workload needs attached persistent block storage with normal disk/filesystem behavior and a storage lifecycle separate from the VM root disk.
Strong fits include self-hosted databases, container state, and stateful application data.
Raff Object Storage
Use Object Storage for S3-compatible buckets that hold uploads, media, reports, exports, archives, and backup artifacts independently from app-server compute.
Raff Data Protection
Use Data Protection for VM snapshots and scheduled backup workflows. Treat that as a recovery layer rather than another type of active application storage.
The goal is not to place Raff products into every architecture. Choose the storage layer from the workload’s access pattern and recovery requirement, then map the appropriate infrastructure to it.