Local NVMe vs Network Storage: An Honest Comparison
When choosing a server, storage often decides perceived speed more than the CPU does. This guide compares local NVMe with network storage (SAN, Ceph, cloud volumes) — on latency, throughput, persistence and exposure to noisy neighbours — and shows why databases and build servers run noticeably faster on a cloud server with local NVMe .
Cloud servers with local NVMeLocal NVMe is an SSD attached directly over PCIe inside the same host your VM runs on. Network storage — whether SAN, distributed Ceph or a cloud volume — lives on separate systems reached over a network. This single difference in the data path explains almost every pro and con that follows.
Local NVMe vs network storage: the basics
With local NVMe the path to the data is short: CPU, RAM and flash sit in the same machine. With network storage, every request travels across the network to a storage node and back — plus the overhead of the storage cluster. That costs latency but brings one decisive advantage for persistence.
Latency and throughput
For lots of small, random accesses, latency matters most — and local NVMe has orders-of-magnitude lower latency because there are no network hops in between. On sequential throughput, well-connected network storage can come closer, but it is capped by the uplink. Anyone with many parallel random writes feels the difference most sharply.
| Criterion | Local NVMe | Network storage (SAN/Ceph) |
|---|---|---|
| Latency | Very low (direct over PCIe) | Higher (network hops) |
| Random IOPS | Very high | Depends on network and neighbours |
| Throughput | Full local bandwidth | Capped by the uplink |
| Persistence on host failure | Tied to the host | Independent of the compute host |
| Live migration | Limited | Easy |
| Noisy neighbours | Only local VMs | Shared storage cluster |
| Best for | Databases, builds, caches | High availability, large shared volumes |
The persistence trade-off
Here network storage wins, fair and square: because the data is decoupled from compute, it survives the failure of a single host and enables live migration and easy scaling. Local NVMe, by contrast, is tied to its host — if that goes down, the data is there. The answer to this is clean backups and, where needed, redundancy at the application level.
Noisy neighbours on the SAN
A shared storage cluster has the same underlying problem as an overbooked host: when one neighbour floods the storage with IO, everyone else feels it. This is the storage flavour of overprovisioning — just for IOPS instead of CPU cycles. Local NVMe you share, at most, with the few VMs on the same host, not with an entire cluster.
Why local NVMe wins for databases and builds
- Databases (PostgreSQL, MySQL): benefit hugely from low latency on many small random writes — commit latency drops.
- CI/CD and build servers: lots of small file operations (node_modules, compiler caches) run much faster on local NVMe.
- Caches and search indexes (Redis persistence, Elasticsearch): low latency keeps response times stable.
- Analytics workloads: high sequential throughput without a network bottleneck.