Compare RedHat OpenShift vs. Kubermatic Kubernetes Platform

Red Hat OpenShift is a broad, integrated application platform that combines Kubernetes with developer tools and Red Hat’s own operating system. This comes with a subscription model priced by worker-node cores.

Kubermatic Kubernetes Platform (KKP) focuses on managing multiple standard Kubernetes clusters from one dashboard, across clouds and your own data centers. With KKP, you pay for Kubernetes management rather than a bundled application platform, keep your workloads portable, and avoid being tied to a single infrastructure vendor. As a German provider, Kubermatic also offers self-hosted and air-gapped deployment options for organizations that need greater control over their infrastructure and data.

In short: OpenShift offers a more integrated, all-in-one platform; KKP offers greater flexibility, centralized multicluster management, and freedom from vendor lock-in, with self-hosted deployment options that support European data sovereignty.

Kubermatic KKP can be a more cost-effective alternative if you mainly need to manage Kubernetes clusters rather than use OpenShift’s full set of platform features.

OpenShift bundles Kubernetes with developer tools and other capabilities in a subscription priced by worker-node cores. If you don’t need all these features, you may be paying for more than your team requires. Add-ons such as OpenShift AI can also incur additional costs.

KKP’s Community Edition is free and open source, while the paid Enterprise Edition adds features and commercial support. KKP is also infrastructure-independent, giving you more freedom to choose where and how to run your clusters.

Kubermatic reports that customers switching from OpenShift save at least 43% in the first year. Actual savings depend on your infrastructure, workloads, and support requirements.

Kubermatic KKP is a strong European alternative for organizations prioritizing data sovereignty. Headquartered in Germany, Kubermatic was the only Germany-headquartered vendor included in Gartner’s 2025 and 2026 Magic Quadrants for Container Management. KKP has an open-source core and can run fully self-hosted, including in air-gapped environments, giving organizations greater control over their infrastructure and data.

Swisscom, for example, runs its sovereign Kubernetes service on KKP, a project featured as a CNCF case study.

Red Hat is owned by US-based IBM, which may raise additional jurisdictional considerations under laws such as the US CLOUD Act. For organizations seeking greater operational control and reduced dependence on foreign providers, KKP offers a compelling alternative.

Kubermatic AI is a strong alternative for teams that want to get more out of their GPUs. Instead of every team deploying its own copy of a model, Kubermatic AI runs each model once and shares it across teams, each with its own access key and GPU quota.

It runs on your existing GPUs and Kubernetes clusters, whether on-premises, in the cloud or in sovereign environments, and is built on Kubermatic’s CNCF AI Conformant platform, with Kueue for job scheduling and KubeLB for routing AI traffic.

OpenShift AI, by contrast, is sold as an add-on to an OpenShift subscription, with GPUs licensed separately unless you buy Red Hat’s higher-tier AI Enterprise bundle.

Kubermatic is one of the strongest on-premises Kubernetes platforms, especially for organizations running many clusters across their own data centers. It manages every cluster from one platform and automates creation, upgrades, and scaling across on-premises environments such as VMware vSphere, OpenStack, Nutanix and KubeVirt. KKP is fully self-hosted, can run air-gapped, and is built on an open-source core, so you’re never tied to one infrastructure vendor.

BWI, the German armed forces’ IT partner, for example, uses Kubermatic to run a sovereign AI platform on its own infrastructure, from the data center to the field.

Other on-premises options include Red Hat OpenShift, SUSE Rancher Prime and VMware vSphere Kubernetes Service, and the right choice depends on your existing infrastructure and scale.

Kubermatic KKP is a strong choice for enterprises that run many Kubernetes clusters across multiple clouds and on-premises environments. It manages every cluster from one platform, from AWS, Azure and Google Cloud to vSphere, OpenStack and Nutanix, and is built on an open-source core, so you’re not tied to one vendor. KKP can be fully self-hosted, which makes it well suited to enterprises with European data sovereignty requirements.

Other options depend on your setup: Amazon EKS, Azure AKS and Google GKE are convenient if you mainly use one public cloud, Red Hat OpenShift suits organizations that want an all-in-one application platform, and SUSE Rancher Prime is another established multi-cluster management option.

Data sovereignty means your clusters and data stay under your own legal and operational control. KKP supports this in five ways:

• Location: It’s self-hosted, on-premises or in a European cloud.
• Access: Only your team administers it. Kubermatic has no built-in access.
• Jurisdiction: Kubermatic is a German vendor under EU law, not the US CLOUD Act.
• Transparency: The core is open source and auditable.
• Independence: It can run fully air-gapped.

Swisscom built its sovereign Kubernetes service on KKP. Read the full CNCF article.

BWI, the German armed forces’ IT partner, for example, uses Kubermatic to run a sovereign AI platform on its own infrastructure. Read the BWI story.