Block vs Object Storage: When to Use Which

Block and object storage solve different problems, and choosing the wrong one leads to either painful performance or painful bills. Block storage behaves like a raw disk attached to a server; object storage behaves like an effectively infinite key-value store reached over HTTP. This article compares them on architecture, performance, durability, and pricing, then maps common workloads to the right choice.

Two fundamentally different architectures

The split starts at the access model. Block storage exposes fixed-size blocks that an operating system mounts and formats with a filesystem, exactly like a physical SSD or HDD. The OS sees a device; your application sees files and directories on top of it. Object storage exposes whole objects - a blob plus metadata - addressed by a key and accessed through an API (typically S3-compatible). There is no filesystem, no partial in-place edit at the block level, and no OS-level mount; you PUT and GET whole objects.

Block storage: a disk for one machine

A block volume is typically attached to a single virtual machine at a time. It offers low-latency, high-IOPS reads and writes, supports in-place modification of any byte, and is the only sensible choice for workloads that need a real filesystem: boot disks, databases, and anything that mmaps files. The tradeoff is that capacity is provisioned and bounded - you size the volume up front and pay for the provisioned size whether or not it is full.

Object storage: a key-value store over HTTP

An object store scales to effectively unlimited capacity, is reached concurrently from anywhere over the network, and bills only for what you store. You cannot edit part of an object in place - you overwrite the whole object - and access latency is higher (tens of milliseconds rather than sub-millisecond). In exchange you get massive scale, high durability, and simple HTTP access.

Performance: IOPS vs throughput at scale

Block storage is measured in IOPS (operations per second) and latency. Provisioned-IOPS volumes deliver tens of thousands of consistent operations per second at sub-millisecond latency, which is what transactional databases need. Object storage is measured in aggregate throughput and request rate; a single GET is slower than a block read, but you can run enormous parallelism across many objects. The rule: block wins on latency for one machine; object wins on horizontal throughput and concurrency.

Snapshots, durability, and resilience

• Snapshots. Block volumes support point-in-time snapshots, often stored incrementally in object storage behind the scenes - the basis for backups and cloning.
• Durability. Object storage typically advertises eleven nines of durability via multi-device, often multi-facility, replication or erasure coding. Block durability is high but generally tied to a zone; resilience beyond that comes from snapshots and replication you configure.
• Availability. A block volume's availability is bounded by the single VM it attaches to; object storage is independently reachable and not coupled to any one instance.

Pricing models differ in kind, not just amount

The key billing difference: block storage charges for provisioned capacity, so a 1 TB volume that is 10 percent full still costs the full terabyte. Object storage charges for actual bytes, so it is far more efficient for sparse or unpredictable growth. On the other hand, block storage usually has no per-GB egress of its own - data leaves through the attached VM - while object storage meters egress directly.

When to use which

Choose block storage when

• You run a database (Postgres, MySQL, MongoDB) that needs low-latency random I/O.
• You need a boot disk or a real, mountable filesystem.
• Your application modifies files in place or memory-maps them.
• You need consistent, high IOPS for a single instance.

Choose object storage when

• You store large, write-once-read-many blobs: media, backups, logs, datasets, ML training data.
• You need to scale capacity without provisioning, and pay only for what you use.
• Many clients or services need concurrent access over the network.
• You serve static assets, ideally fronted by a CDN to cut egress.

Many real systems use both: a database on a block volume, with its backups, exports, and user-uploaded files in an object store. They are complements, not competitors.

How to decide for a given workload

1. Does it need a filesystem or in-place writes? If yes, block.
2. Does it need sub-millisecond latency and high IOPS from one machine? If yes, block.
3. Is it large, append-or-replace, accessed concurrently, or growing unpredictably? If yes, object.
4. Will it be served outward to users? Object plus a CDN, and model the egress.
5. Estimate cost both ways: provisioned GB times the block rate versus actual GB plus requests plus egress for object.

Compare current rates on the block storage and object storage pages, and if egress is in play, run the numbers through the egress cost calculator. For workloads that also need compute - say a database server - see the VPS and bare metal comparisons for the instance the volume attaches to.

Takeaway

Block storage is a fast, low-latency disk for a single machine, billed on provisioned capacity and ideal for databases and boot volumes. Object storage is a durable, infinitely scalable key-value store over HTTP, billed on actual bytes plus requests and egress, ideal for blobs and outward-served content. Pick by access pattern first and price second, expect to use both in most architectures, and validate the cost of each against the live comparison tables.