Understanding VPS Virtualization: KVM vs OpenVZ

Not all “VPS” products are built the same way underneath. The virtualization technology determines how isolated your server really is from its neighbours, and what you’re allowed to do inside it.

KVM: full virtualization

KVM (Kernel-based Virtual Machine) gives each VPS its own complete virtual hardware and its own kernel, entirely separate from the host machine’s kernel and from every other VPS on it. This means you can run a different OS/kernel version than the host, install custom kernel modules, use Docker or other container tooling inside the VPS, and get resource allocation (RAM, CPU) that’s genuinely dedicated rather than a soft limit.

OpenVZ: container-based virtualization

OpenVZ (and similar container technologies like LXC) creates isolated environments that all share the SAME host kernel. This is lighter-weight (more VMs can fit on the same hardware, memory can sometimes be overcommitted/shared), but comes with real restrictions: no custom kernel modules, no running your own container tooling inside it, and resource “guarantees” that historically have been softer/more overselling-prone than KVM’s hardware-level allocation.

Practical differences that affect you

• Kernel-level software (custom kernel modules, certain VPN configurations, Docker) generally requires KVM — OpenVZ’s shared kernel can’t accommodate it.
• Resource isolation is stronger on KVM — your allocated RAM and CPU are genuinely yours, not a limit enforced on top of a shared pool.
• Noisy neighbours are less of a risk on KVM specifically because of that stronger isolation.
• Price — OpenVZ VPS plans are often cheaper precisely because of the higher density hosts can achieve per physical machine.

Which should you choose?

For anything beyond a very simple, low-resource workload — and especially anything needing Docker, custom kernel work, or performance guarantees you can rely on — KVM is the safer default, which is why it’s what DozeHost’s VPS plans run on. OpenVZ-style plans can still make sense for extremely cost-sensitive, lightweight workloads where the restrictions genuinely don’t matter.