Object Storage vs Block Storage:
Which Does Your App Actually Need?
Block storage and object storage solve fundamentally different problems. Using the wrong one for a workload does not usually cause immediate failures — it causes cost overruns, performance problems, and architectural constraints that compound over time. Understanding the actual difference is the prerequisite for making the right choice.
Block Storage: What It Is and When to Use It
Block storage presents a raw storage volume to a virtual machine, identical in behaviour to a physical disk. The VM's operating system formats it with a filesystem and reads and writes directly to disk blocks at low latency — typically sub-millisecond for NVMe-backed block storage. Block storage supports random read and write access, which is the pattern that database engines require: PostgreSQL, MySQL, and most other relational databases access their data files with random I/O at high frequency.
The key constraints of block storage: it is mounted to a single VM at a time (most configurations do not support simultaneous multi-VM access), it requires the volume to be formatted and mounted before use, and it cannot be accessed directly from the internet — it is a disk, not an API. Block storage pricing is approximately $0.10–0.15/GB/month.
Object Storage: What It Is and When to Use It
Object storage exposes data through an HTTP API. You PUT an object (a file) with a key (a path-like identifier), and you GET it back later using that key. There is no filesystem, no mount operation, and no single VM it is attached to. Anyone with the correct credentials and network access can read or write objects using any HTTP client — which means your application, your CDN, your CI/CD pipeline, and your analytics stack can all access the same objects directly without going through a server.
Object storage latency is higher than block — typically 5–50ms per operation — but it scales to essentially unlimited capacity, and it supports features that block storage does not: presigned URLs (temporary authenticated access for specific objects), multipart upload (parallel upload of large files), lifecycle policies (automatically delete objects after N days or move them to cheaper storage tiers), and S3-compatible APIs (the AWS S3 API has become the de-facto standard, meaning the AWS SDK, MinIO, and any S3-compatible tool will work without code changes). Object storage pricing is approximately $0.02–0.05/GB/month — 3–5x cheaper than block storage per GB.
Choosing the Right Storage Type
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Database files (PostgreSQL, MySQL data directory) — Block storage. Databases require random read/write with sub-millisecond latency. Object storage is incompatible with this access pattern.
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OS disk and application binaries — Block storage. The VM's operating system must be on a block volume.
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User-uploaded images, videos, documents — Object storage. High throughput, HTTP access, CDN integration, and cost-effective at scale.
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Database backups — Object storage. Backups are large sequential writes that do not require low-latency random access. Store pg_dump or WAL archives in object storage and save 70% on storage cost.
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Application logs and audit trails — Object storage. Append-heavy, large volume, infrequent random access. Object lifecycle policies can auto-delete old logs.
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Machine learning datasets — Object storage. Large, sequential read workloads that ML training frameworks can stream directly from S3-compatible APIs.
The Cost Impact at Scale
For 10TB of media files — a modest size for an e-commerce platform or content site — block storage costs $1,000–1,500/month. The same 10TB on object storage costs $200–500/month. Over a year, that difference is $6,000–15,000. Over three years, it funds meaningful product development. The correct hybrid pattern is clear: database and OS on NVMe block storage for performance; user content, backups, and logs on object storage for cost and scale.
Hyper App's object storage is S3-compatible, meaning you can use the AWS SDK without modification, configure presigned URLs for direct browser uploads, and set lifecycle rules to automatically expire old objects. There are no egress fees within the platform — data moving from object storage to compute instances in the same region is free.