Docker has changed software development and application deployment through containerization. Its intuitive command-line interface, tools such as Docker Desktop, and the vast Docker Hub ecosystem have all made creating, sharing images, and running containerized applications incredibly accessible.
But many people don’t realise that the Docker engine isn’t the only containerization technology available.
This post will discuss some of the best alternatives to Docker and compare powerful options that adhere to the Open Container Initiative (OCI) standards.
Whether you’re concerned about security, optimizing for Kubernetes clusters, managing container images across different container registries, or simply seeking improvements in your container management strategy, by the end of this article, you will be able to find the best containerization platform for your specific needs.
Let’s get started!
What is Containerization?
Contents
- 1 What is Containerization?
- 2 Best Docker Alternatives for Containerization
- 3 Wrapping Up
- 4 FAQs on Docker Alternatives for Containerization
- 4.1 Is Podman better than Docker?
- 4.2 Do I need Kubernetes if I use Docker?
- 4.3 Is LXC faster than Docker?
- 4.4 What is the best containerization platform?
- 4.5 What is the difference between Docker and Kubernetes?
- 4.6 Are Docker alternatives suitable for high-traffic applications?
- 4.7 What is the difference between containerization and virtualization?
Containerization is a new way to deploy applications on a remote server. Traditionally, we’ve been copying the application’s source code and executing it on the remote server.
However, containerization technology allows us to bundle an application’s code and all its necessary dependencies, libraries, configuration files, and binaries, into a single, isolated unit called a container. This container image is a self-sufficient package that can run consistently across different computing environments, from a developer’s laptop to production servers in the cloud or on-premises data centers.
In Linux, containerization uses operating system-level virtualization features, such as namespaces and control groups (cgroups). Unlike traditional virtual machines (VMs) that require a full guest operating system for each instance, containers share the host system’s OS kernel. This makes containers very lightweight, faster to start, and less resource-intensive than VMs. This allows developers to deploy multiple containers on a single VM for higher density and more efficient use of underlying hardware resources.
📖 Suggested read: 20 Essential Docker Commands You Should Know
Best Docker Alternatives for Containerization
Docker is by far the most popular container runtime available. So much so that many people use the terms ‘Docker’ and ‘containers’ interchangeably – but it isn’t the only containerization technology.
Let’s take a look at alternative container runtimes that you can use instead of Docker:
Podman
Podman is a helpful tool for anyone working with software containers. It lets you easily find, download, run, build, and share containers using straightforward commands like search, pull, run, build, and push. One special thing about Podman is its ability to group related containers into ‘pods’, which makes it easier to manage applications where different parts need to work closely, similar to how bigger systems like Kubernetes operate.
If you prefer using a visual interface instead of typing commands, you can use the Podman Desktop application on Windows, macOS, and Linux. This app gives you a single screen to manage your containers, even if they were created with other tools such as Docker.
Podman Desktop makes building new container images simple, as well as getting images from online repositories, grouping containers into pods, and checking logs. It even helps you prepare and move your container applications to run on Kubernetes.
📖 Suggested read: How to Create a Docker Image for Your Application
Linux Containers
Linux Containers, often abbreviated as LXC, are one of the longest-standing options built directly on the Linux kernel and include features such as namespaces and groups. LXC aims to create environments close to a standard Linux installation but without a separate kernel. This differs slightly from Docker, which typically focuses on packaging a single application and its dependencies.
LXC is geared more towards running a ‘system container’ – a lightweight virtual machine that can run multiple services or a full init system inside. This ‘system container’ approach might not be a drop-in replacement for your Docker workflow and may require you to configure how you deploy applications.
LXC uses powerful Linux features and offers management tools and libraries (like liblxc). It mimics a full OS environment, which might be more than most people need for simple application isolation. LXC could be great if you needed to replicate a traditional server setup within a container, but if you are just looking to run your apps, it might introduce unnecessary complexity.
📖 Suggested read: Docker Security: Best Practices to Secure a Docker Container
Red Hat OpenShift
Red Hat OpenShift is much more than just a container runtime. It is a full-fledged application platform built on Kubernetes designed to handle the entire lifecycle of applications, from development and building to deployment and management at scale, even across different cloud environments or on your own servers.
If you just want to build and run containers, this might not be the right tool for you. Red Hat OpenShift is designed to provide a consistent environment with integrated tools for building, automating deployments (like CI/CD pipelines), and managing applications, not just basic container orchestration.
The platform offers different ways to use it, either as a managed service on clouds like AWS or Azure, where Red Hat handles the underlying infrastructure, or as a self-managed service for more control. It also has built-in security, developer tools, and the ability to manage virtual machines alongside containers.
While Red Hat OpenShift is a powerful tool, especially for larger teams or complex applications that need this robust management and security, it is also more complex than just using Docker. Therefore, you must weigh whether the comprehensive features justify the potential learning curve and operational overhead for your needs.
📖 Suggested read: How to Install WordPress on Docker in 2025 [Step-By-Step Guide]
Apptainer
Apptainer, which used to be called Singularity, is another tool for packaging and running software inside containers, similar to how Docker works. It’s open-source software, now part of the Linux Foundation, and designed to be straightforward, quick, and safe. Apptainer is particularly popular in environments where many people share the same computer systems, like university computing clusters or research labs, and for running software that needs a lot of computing power.
It primarily focuses on performance-intensive applications commonly found in High-Performance Computing (HPC), scientific research, and AI/ML workloads. It is designed for environments where maximizing computational performance, managing complex software stacks, ensuring reproducibility, and handling specialized hardware like GPUs is very important.
Apptainer is different in handling containers and interacting with the computer it’s running on. It packs everything into a single file, making the container easy to copy, move between computers, or share with others. Apptainer also lets the software inside the container easily use special hardware on the host machine, like powerful graphics cards (GPUs) or fast network connections, which is important for scientific computing.
Its security approach is also quite simple: by default, you have the same permissions inside the container as you do outside, which helps prevent users from accidentally gaining extra privileges on the system.
📖 Suggested read: What Are Docker Logs And How To Use Them
Containerd
Containerd is a core container runtime focused on managing the complete container lifecycle. This includes tasks like image transfer and storage, container execution and supervision, low-level storage, and network attachments.
It might surprise you that Docker uses containerd under the hood (or components derived from it), meaning containerd isn’t necessarily a replacement for the entire Docker developer experience, but rather the engine component that does the heavy lifting.
However, it is much lower-level than the Docker run command, as it exposes the distinct stages of container creation and execution. Rather than providing developers with a simple, all-in-one command-line interface, it’s designed more for integration into larger systems or for users who need fine-grained control.
It has well-established documentation, API, and client libraries, particularly for the Go client for programmatic control. You can easily use this client to connect to the daemon, pull images, create OCI specs, manage snapshots (container filesystems), and much more.
While containerd is a crucial piece of the container ecosystem and the standard runtime interface (CRI) implementation for Kubernetes, it doesn’t directly replace the user-facing Docker command-line tool and its associated build/compose functionalities out of the box. Instead, it replaces the runtime part that Docker traditionally managed.
If you are looking for just the runtime component, containerd is the go-to option. However, replicating the full Docker developer workflow requires other tools (such as nerdctl for a Docker-compatible CLI or build tools like BuildKit).
📖 Suggested read: Bringing Containerization to RunCloud’s Cloud Architecture
Cri-o
If you are working with Kubernetes, you might already be familiar with CRI-O. It is a lightweight Kubernetes Container Runtime Interface (CRI) implementation. This means its primary purpose isn’t to be a general-purpose container engine like Docker, but rather to provide exactly what Kubernetes needs to manage container lifecycles (pods) efficiently and reliably, using standard OCI-compliant runtimes like runc underneath.
CRI-O acts as the bridge between the Kubernetes kubelet and the low-level container operations. It handles pulling images from any OCI-compliant registry, managing container storage, generating the OCI runtime spec, launching the actual runtime (like runc), setting up networking via CNI, and using conmon for monitoring. Concentrating only on these Kubernetes-essential tasks, it aims to be more stable and resource-efficient within a cluster than a more feature-rich daemon like Docker’s.
If you are thinking of replacing Docker, you can use CRI-O to replace the runtime component on the Kubernetes nodes. However, you should note that it doesn’t offer a direct replacement for the Docker command-line interface or tools such as Docker Compose for local development workflows.
Mirantis Container Runtime
Mirantis Container Runtime (MCR) is similar to ‘Docker Engine – Enterprise’. It is designed to be compatible with the core Docker API and commands you might already know. The main goal of MCR is to provide this familiar Docker Engine functionality, but specifically tailored for enterprise needs, along with commercial support (like 24×7 options) and enhanced security features, which might be necessary if your organization has stricter requirements than those that standard open-source Docker offers.
MCR heavily emphasizes security aspects often required by large organizations or regulated industries. For example, it uses FIPS 140-2 validated cryptography, has secure default configurations, and offers capabilities like enforcing the use of digitally signed images to secure the software supply chain.
It has broad capability as it supports both Linux and Windows containers. It can run in standalone mode, as part of a Kubernetes deployment, or in Docker Swarm clusters. This means you can use it in various infrastructure setups without demanding a complete overhaul of orchestration strategies.
Wrapping Up
Choosing the right container runtime is a critical decision that depends heavily on your team’s needs, your infrastructure, and the type of applications you’re building. While Docker has been the default choice for years, it’s clear that the container landscape in 2025 offers powerful alternatives such as Podman, LXC, containerd, CRI-O, and OpenShift, each with unique strengths.
If you manage large Kubernetes clusters, CRI-O or containerd might make sense. If you need a daemon-less solution with strong security principles, Podman is a compelling option. And if you operate in highly regulated enterprise environments, Mirantis Container Runtime brings Docker compatibility with hardened security features.
However, while choosing the right containerization platform is critical, managing your servers and deployments effectively is equally important – and that’s where RunCloud comes in.
RunCloud simplifies server management for developers and teams working with containerized or traditional PHP-based applications. Whether you’re using Docker, containerd, or another runtime under the hood, RunCloud helps you:
- Deploy web applications faster
- Set up automated backups
- Manage server security with best practices baked in
- Monitor performance from a unified dashboard
- Scale projects effortlessly as your infrastructure grows
Instead of worrying about the underlying complexities of servers and deployments, you can focus entirely on building and shipping better software.
If you’re ready to streamline your application deployments and server management, no matter what container runtime you use, sign up for RunCloud today.
Thousands of developers and businesses already trust RunCloud to manage their mission-critical projects. Discover a simpler, faster, more scalable way to run your applications.
FAQs on Docker Alternatives for Containerization
Is Podman better than Docker?
Podman isn’t inherently ‘better’, but it offers advantages such as a daemonless architecture for enhanced security and rootless container execution. Docker has a more mature ecosystem and wider initial adoption, which makes it a strong choice for many workflows.
Do I need Kubernetes if I use Docker?
No, you don’t automatically need Kubernetes just for using Docker, as Docker excels at managing containers on a single host. Kubernetes becomes necessary to orchestrate, scale, and manage containerized applications across multiple hosts or clusters.
Is LXC faster than Docker?
LXC can exhibit slightly better performance in certain benchmarks due to operating at a lower level, closer to the kernel, often termed ‘system containers’. However, for typical application container workloads managed by Docker, the performance difference is usually negligible and less critical than Docker’s developer-focused tooling. The choice often depends on whether you must run full OS-like environments (LXC) or isolated applications (Docker).
What is the best containerization platform?
There is no single ‘best’ containerization platform; the ideal choice depends on your specific use case, team expertise, and requirements. Docker remains extremely popular for its ease of use and rich ecosystem, while Podman is favored for security-focused or daemonless environments.
What is the difference between Docker and Kubernetes?
Docker primarily focuses on building, shipping, and running individual containerized applications, often on a single machine. On the other hand, Kubernetes is a container orchestration platform designed to automate the deployment, scaling, and management of containerized applications across clusters of machines. Simply put, Docker creates the containers, and Kubernetes manages them at scale in production environments.
Are Docker alternatives suitable for high-traffic applications?
Docker alternatives like Podman, containerd, and CRI-O are suitable and commonly used for high-traffic, production-grade applications. The ability to handle high traffic effectively relies heavily on the orchestration layer (like Kubernetes) and the application architecture.
What is the difference between containerization and virtualization?
Virtualization creates virtual machines (VMs), each running a complete operating system instance with its own kernel on top of a hypervisor. Containerization packages an application and its dependencies, isolating them at the process level while sharing the host OS kernel. Therefore, containers are much lighter, faster to start, and consume fewer resources than VMs.
