Object Storage vs Block Storage: Understanding the Fundamentals
Choosing between object storage and block storage is one of the most consequential infrastructure decisions you will make when building or scaling a web application. Pick the wrong one and you are either overpaying by 10x or dealing with performance bottlenecks that no amount of caching can fix.
The global object storage market alone is projected to reach $2.9 billion in 2026, growing at a 7.2% CAGR through 2035, according to Business Research Insights. That growth reflects a broader shift in how companies think about data. But object storage is not a universal replacement for block storage. Each serves a distinct purpose.
This guide breaks down exactly how these two storage types work, what they cost across major providers, and when to use each one based on real workload requirements.
How Block Storage Works
Block storage divides data into fixed-size chunks called blocks, typically 512 bytes to 4 KB each. Each block gets a unique address, and the storage system tracks where every block lives on disk. The operating system sees block storage as a raw disk volume, which means you can format it with any filesystem (ext4, XFS, NTFS) and mount it directly to a server.
This architecture makes block storage fast. Because the system accesses data at the block level without needing to parse metadata or traverse a namespace, read and write operations happen with minimal latency. AWS EBS gp3 volumes, for example, deliver a baseline of 3,000 IOPS and 125 MB/s throughput per volume.
Block storage volumes are typically attached to a single compute instance at a time (though multi-attach options exist for specific use cases). They behave exactly like a physical hard drive plugged into a server.
Common Block Storage Services
Every major cloud provider offers block storage:
- AWS Elastic Block Store (EBS) – gp3 volumes at $0.08/GB/month
- Google Cloud Persistent Disks – pd-ssd at $0.17/GB/month
- Azure Managed Disks – Premium SSD starting at $0.132/GB/month
- DigitalOcean Volumes – $0.10/GB/month
- Vultr Block Storage – $0.10/GB/month (HDD) or $0.20/GB/month (NVMe)
- Linode (Akamai) Block Storage – $0.10/GB/month
How Object Storage Works
Object storage takes a fundamentally different approach. Instead of blocks and disk addresses, it stores data as discrete objects within a flat namespace. Each object contains three things: the data itself, metadata (which can be extensive and custom), and a unique identifier.
There is no filesystem hierarchy. No directories, no file paths in the traditional sense. Objects live in buckets (or containers, depending on the provider), and you access them via HTTP APIs. Most object storage services are S3-compatible, meaning they use the same API protocol that Amazon established with Simple Storage Service.
This design trades raw I/O speed for massive scalability. Object storage systems can hold petabytes of data without performance degradation because the flat namespace eliminates the overhead of maintaining complex directory trees.
Common Object Storage Services
- AWS S3 Standard – $0.023/GB/month (first 50 TB)
- Cloudflare R2 – $0.015/GB/month, zero egress fees
- Backblaze B2 – $0.006/GB/month (lowest per-GB rate available)
- Google Cloud Storage – $0.020/GB/month (Standard)
- Azure Blob Storage – $0.018/GB/month (Hot tier)
- DigitalOcean Spaces – $0.020/GB/month (with $5/month base plan including 250 GB)
- Wasabi – $0.0069/GB/month, no egress fees
Price Comparison: The Cost Gap Is Significant
The pricing difference between object and block storage is not marginal. It is often 4x to 13x cheaper to store data in object storage compared to block storage on the same provider.
| Provider | Block Storage (per GB/month) | Object Storage (per GB/month) | Cost Ratio |
|---|---|---|---|
| AWS | $0.08 (EBS gp3) | $0.023 (S3 Standard) | 3.5x |
| Google Cloud | $0.17 (pd-ssd) | $0.020 (GCS Standard) | 8.5x |
| DigitalOcean | $0.10 (Volumes) | $0.020 (Spaces) | 5x |
| Vultr | $0.10 (HDD Block) | $0.006 (Object Storage) | 16.7x |
For 1 TB of storage, you would pay $80/month on AWS EBS gp3 versus $23/month on S3 Standard. Over a year, that is $684 in savings on a single terabyte. At 10 TB, the difference becomes $6,840 annually.
But price alone should not drive this decision. Block storage costs more because it delivers something object storage cannot: low-latency, random-access I/O suitable for running databases and operating systems.
Performance: Where Block Storage Wins
Block storage excels at workloads that require consistent, low-latency access to data. A MySQL database performing thousands of random reads per second needs sub-millisecond response times. Object storage, accessed over HTTP, typically adds 20-100ms of latency per request. That is acceptable for serving a profile photo but catastrophic for a database query.
Here is how the performance characteristics compare:
| Metric | Block Storage | Object Storage |
|---|---|---|
| Latency | Sub-millisecond to low single-digit ms | 20-100ms per request |
| IOPS | 3,000-256,000 (depending on tier) | Not applicable (request-based) |
| Throughput | 125 MB/s to 4,000 MB/s | Varies by connection, typically 1-10 Gbps |
| Access Pattern | Random read/write | Sequential, whole-object read/write |
| Partial Updates | Yes (modify individual blocks) | No (must rewrite entire object) |
AWS EBS io2 Block Express volumes can deliver up to 256,000 IOPS with sub-millisecond latency. No object storage service comes close to that for transactional workloads.
Scalability: Where Object Storage Wins
Object storage was built for scale. AWS S3 stores over 350 trillion objects as of 2024 and handles millions of requests per second globally. There is no practical upper limit on how much data you can store in a single bucket.
Block storage volumes, by contrast, have hard size limits. An AWS EBS volume maxes out at 64 TB. A DigitalOcean Volume caps at 16 TB. Scaling block storage means adding more volumes and managing them across multiple mount points, which adds operational complexity.
Object storage also scales horizontally with zero effort from you. Need to store 500 TB of video files? Just upload them. The provider handles replication, distribution, and availability across data centers. With block storage at that scale, you would be managing dozens of volumes, potentially across multiple instances.
When to Use Block Storage
Choose block storage when your workload requires:
Databases
PostgreSQL, MySQL, MongoDB, Redis (persistent mode), and any other database engine needs block storage. These applications perform thousands of random I/O operations per second and require POSIX filesystem semantics. There is no workaround here.
Boot Volumes and Operating Systems
Your server OS needs a mounted filesystem. Block storage is the only option for root volumes on cloud instances.
High-Performance Computing
Scientific simulations, video rendering, and real-time analytics that process data in place need the low latency and high IOPS that only block storage provides.
Containers and Kubernetes Persistent Volumes
Stateful containers running databases or message queues (Kafka, RabbitMQ) need block storage via CSI drivers. Kubernetes PersistentVolumes backed by EBS, Persistent Disks, or equivalent services are standard practice.
Virtual Machine Disks
If you run VMs (VMware, KVM, Hyper-V), their virtual disks sit on block storage. The hypervisor needs raw block-level access to manage disk images efficiently.
When to Use Object Storage
Choose object storage when your workload involves:
Static Assets and Media Files
Images, videos, PDFs, CSS, JavaScript bundles, and any file served directly to users over HTTP belongs in object storage. Pair it with a CDN (Cloudflare, CloudFront, Fastly) and you get global distribution at minimal cost.
Backups and Archives
Database dumps, log archives, and disaster recovery snapshots are write-once, read-rarely data. Object storage tiers like S3 Glacier Deep Archive ($0.00099/GB/month) or Backblaze B2 ($0.006/GB/month) make long-term retention affordable. Storing 10 TB of archives on Glacier Deep Archive costs roughly $10/month.
Data Lakes and Analytics
Modern analytics stacks (Apache Spark, Presto, Athena, BigQuery) read directly from object storage. Parquet and ORC files stored in S3 or GCS serve as the foundation for data warehousing without the cost of provisioned block storage.
Application Logs
Shipping logs to object storage (via Fluentd, Vector, or CloudWatch Logs export) gives you cheap, durable retention. You can query them later with tools like Athena or store them indefinitely at archive-tier pricing.
User-Generated Content
Profile photos, document uploads, attachments in a SaaS product. These files are uploaded once, read many times, and never modified in place. Object storage handles this pattern perfectly, and pre-signed URLs let you offload uploads directly from the client browser to the storage bucket.
The Hybrid Approach: Using Both Together
Most production architectures use both storage types simultaneously. A typical web application might look like this:
- Block storage: 100 GB EBS gp3 volume for the PostgreSQL database ($8/month)
- Object storage: 2 TB S3 bucket for user uploads, static assets, and backups ($46/month)
Without object storage, that same 2 TB on block storage would cost $160/month. The hybrid approach saves $114/month while giving each workload the storage type it actually needs.
Here is a practical decision framework:
| Question | If Yes → Use |
|---|---|
| Does the application need a mounted filesystem? | Block Storage |
| Is the data accessed via HTTP/API? | Object Storage |
| Do you need sub-millisecond latency? | Block Storage |
| Is the data write-once, read-many? | Object Storage |
| Will the dataset grow beyond 10 TB? | Object Storage |
| Does the workload require random I/O? | Block Storage |
| Are you storing files for CDN delivery? | Object Storage |
Common Mistakes to Avoid
Storing static assets on block storage. This is the most expensive mistake teams make. If your 500 GB of product images sits on an EBS volume instead of S3, you are paying $40/month instead of $11.50/month and missing out on CDN integration.
Trying to run a database on object storage. Some teams attempt to use S3-backed filesystems (s3fs, goofys) for database workloads. The latency makes this impractical for anything beyond read-heavy analytics. A PostgreSQL database on s3fs would be unusable.
Ignoring egress costs. Object storage is cheap to store data in, but retrieving it can be expensive. AWS S3 charges $0.09/GB for data transferred to the internet. If you serve 10 TB/month directly from S3 without a CDN, that is $900 in egress fees alone. Cloudflare R2 and Backblaze B2 (via Bandwidth Alliance) eliminate egress charges entirely.
Over-provisioning block storage. Block storage charges for provisioned capacity, not used capacity. A 500 GB EBS volume costs $40/month whether you use 50 GB or 500 GB. Right-size your volumes and use monitoring to track actual usage.
Bottom Line
Object storage and block storage solve different problems. Block storage gives you the raw disk performance needed for databases, operating systems, and transactional workloads. Object storage gives you affordable, infinitely scalable capacity for files, backups, and static content.
For most hosting setups, the answer is both. Keep your database on block storage, put everything else in object storage, and you will have an architecture that scales without burning through your budget. The cost difference between getting this right and getting it wrong can easily reach thousands of dollars per year, even at modest scale.