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Docker vs. Podman: Which Containerization Tool is Right for You
Containers run the world’s applications and data workloads. First conceptualized in the 1970s, containers offer a way to package everything needed to run an application or workload in a single object. Containers help solve the “it runs on my machine” problem by offering an isolated and portable solution to developing, testing, and shipping code. Tools like Kubernetes rely heavily on containers as a core component of their architecture. For now, containers aren’t going anywhere.
To run these containers, you’ll need a container management solution. Enter Docker and Podman.
Docker and Podman are used to build, manage, and deploy containers. Together, we'll unpack the similarities and differences between Docker and Podman, along with the unique functionality of each. We’ll explore things like daemon-based and daemonless architecture, multi-container management, and cross-platform integration. By the end, you'll be armed with the info you need to choose the perfect container solution for your needs.
If you’re new to these tools, you can also check out our Introduction to Docker course and Introduction to Podman for Machine Learning tutorial.
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What Are Podman and Docker?
Let’s start with an overview of these tools to start our comparison:
Overview of Docker
Docker is the de facto standard for building, running, and shipping containers. Containers are objects that combine OS-level dependencies and some sort of application code to package and run things like full-stack applications or ETL pipelines in their own, isolated environment. Containers are like little computers that have only the essentials to run some sort of code.
Docker is quite young and was first released as an open-source project in 2013. Since then, the project has exploded.
When it comes to running containers in an enterprise setting, almost all software and data teams reach for Docker.
Developers can run Docker on the three major operating systems, and it integrates nicely with almost all modern technologies. This means that a Data Engineer could write and package a data pipeline using a Docker container on their local Mac, and ship that container to run on AWS ECS.
Tools like the Docker CLI, Docker Desktop, and Docker Hub make it easy for developers of all skill levels to get started with.
If you’re looking for a more hands-on way to learn Docker, we have several Docker projects and info on Docker certifications geared to help level up your Docker skills!
Overview of Podman
Like Docker, Podman is an open-source tool for developing and managing containers. Podman was originally developed by Red Hat as a Linux-native alternative to Docker and was released in 2019.
Most notably, the underlying architecture of the two container runtimes differ; where Docker leverages daemons, Podman runs in a daemonless fashion (more on this later).
Unlike Docker, Podman does not require root access to the machine where the pods it manages run; this makes Podman a more security-conscious option for teams using containers to run their applications and workloads.
Podman users are provided a similar user experience to that of Docker; developers can leverage a CLI or GUI (Podman Desktop) to interact with Podman in their local environment.
Linux, Mac, and Windows users alike can use Podman to build and test their containers locally before deploying to some sort of remote environment, like Kubernetes.
Key Differences Between Podman and Docker
Daemon vs. daemonless architecture
The biggest difference between Docker and Podman is the underlying architecture each is built on. Docker heavily relies on a daemon, while Podman is daemonless.
You can think of a daemon as a process that runs in the background on the host operating system. In Docker’s case, its daemon is responsible for managing Docker objects (images and containers) and communicating with other systems. To run its daemon, Docker uses a package called dockerd.
Why is this important? For starters, daemons typically require root-level access to the machine they run on. This lends itself to security vulnerabilities - if a bad actor can get access to a daemon, they now have access to the entire machine.
Podman’s daemonless architecture comes with a few benefits. Since running daemons almost always requires root privileges, a daemonless architecture can be thought of as “rootless.” This means that users who don’t have system-level access to the machine their containers are running on can still use Podman; this isn’t always the case with Docker.
Instead of a daemon, Podman uses a Linux package known as systemd. Since systemd is native to the Linux operating system, Podman is often considered more “light-weight” than Docker; Podman users will usually see faster container spin-up times than when using Docker.
Building images and containers
Despite their fundamentally different architectures, both Docker and Podman share the same core purpose - creating and running images and containers. However, their approaches to this process differ slightly.
With Docker, an image is built by first adding commands to a Dockerfile. Then, a command like docker build is executed. This calls each of the statements in the Dockerfile, eventually building an image. An image can then be “run” as a container. As you may have guessed, this is done using the docker run command, and specifying an image ID or tag. To build and run multiple containers, we’ll use a special tool called docker-compose, which we’ll explore a bit later.
The process of building images and running them as containers is almost identical in Podman. Rather than a Dockerfile (although this file name would still work), Podman users will create a Containerfile. The syntax for composing the image is the same. Once the appropriate commands are added to the Containerfile, the image can built and run using the Podman CLI.
For the most part, Podman is compatible with most things Docker. You’ll find differences here and there, but for the most part, the Docker CLI can be swapped with the Podman CLI without a hitch.
Podman vs Docker Desktop
Docker Desktop for simplified multi-platform access
There are a few ways to work with Docker. Experienced software and data practitioners will typically lean on the Docker CLI (AKA the Docker client) to interact with their Docker images and containers.
However, there’s an even easier way to get started, and that’s with Docker Desktop.
Docker Desktop is a free, GUI-based tool that provides an interface for users to build and manage the images and containers that run their applications or workloads. A data engineer may use Docker Desktop to view the images available on their machine and spin that image into a container. Similarly, a Software Developer may pull down an image from Docker Hub to use as they get started with their next project.
The UI is simple and intuitive to use while maintaining complete visibility and control into your Docker environment.
However, Docker Desktop offers more than just viewing and managing Docker objects.
Users can do things like manage (down to the byte) the resources available to their Docker objects, attach to a running container, or launch a Kubernetes cluster on their local machine. Docker Desktop users can choose from hundreds of extensions, or jumpstart their Docker journey with helpful tutorials and sample environments. Lucky for you, Docker Desktop is widely accessible and runs on Mac, Windows, or Linux.
Podman Desktop features and limitations
Podman Desktop looks and feels quite similar to its Docker counterpart. From the Podman Desktop UI, users can view and manage containers, images, pods, and volumes. Like with Docker, Podman supports plugins and integrations to do things like run a Red Hat OpenShift cluster locally or work with LLMs using the Podman AI Lab.
If you have a custom plugin that you’d like to use, that's great—you can install it from Podman Desktop.
If you’re both a Docker and a Podman user, you may be startled to see both Docker and Podman objects from the Podman Desktop UI. This is no coincidence! We’ll take a closer look at what this implies shortly. In the meantime, this means that users can interact with both their Podman AND Docker objects, all via a single pane of glass.
The most common use case for containers is running them via Kubernetes. Despite Docker’s industry-standard title for containerization, Podman provides a more robust Kubernetes experience on Podman Desktop.
The ability to view and manage Kubernetes resources like nodes, pods, deployments (and much more) makes Kubernetes administration and development a first-class citizen on Podman Desktop. These tools, plus plugins like the aforementioned Red Hat OpenShift integration, differentiate Podman as a tool geared towards Kubernetes shops.
Podman Compose vs Docker Compose
Defining and managing multi-container apps with Docker
Some applications and workloads can be packaged in a single container. Some cannot. To make multi-container management easy, Docker offers a tool called Docker Compose. Docker Compose uses a single YAML file to define the components of your application.
Then, using the docker-compose CLI, these containers and services can be started, stopped, or rebuilt. A Docker Compose YAML file might look a little something like this:
yaml
version: '3'
services:
app:
image: python:3.10
container_name: app
command: run app --host=0.0.0.0
database:
image: postgres:13
container_name: database
ports: 5432
volumes:
- postgres_data:/var/lib/postgresql/data
volumes:
postgres_data
There’s a lot going on, but what Docker Compose allows us to do is define a YAML file with two services and a volume. Then, the command docker-compose up will spin up these containers, and we’ll have a running app.
For software and data teams running large applications and workloads, Docker Compose makes it easy to both develop locally, as well as ship and run code in a production environment.
Podman’s approach to multi-container applications
Running multi-container applications with Podman looks and feels exactly like working with Docker. Podman does this using Podman Compose. Like with Docker Compose, Podman Compose uses YAML files to define the components of an application in a declarative manner.
The podman-compose CLI can then be used to spin up, spin down, or restart the services defined in the YAML file.
For the most part, podman-compose can be used in place of docker-compose (there are a few incompatibilities here and there). Like with Docker, using Podman Compose allows for multi-container applications to be managed independently and flexibly.
Below, you’ll see a table that compares Docker vs Podman.
Feature/Aspect |
Docker |
Podman |
Architecture |
Docker leverages a daemon as a core architectural component. |
Daemonless architecture. |
Security |
Requires root privileges to build, run, and manage containers. |
The daemonless nature of Podman’s architecture makes it a more security-conscious container management tool. |
User Tooling |
Docker Desktop, docker CLI |
Podman Desktop, podman CLI |
Compatibility |
Windows, Mac, Linux |
Native to Linux, available for Windows and Mac. |
Adoption |
Industry-standard for container orchestration with a massive community and nearly universal compatibility. |
Alternative to Docker with a smaller, yet growing, community. |
Use Cases and Best Scenarios for Podman vs Docker
Let’s now explore the key question you may be asking - when should you use Docker, and when should you use Podman? Let’s take a closer look.
When to use Docker
Docker is the de facto standard for building, running, and shipping containers. If you’re just getting started with containerization (especially on your personal machine), try using Docker.
It’s simple to get your first (or fiftieth) container up and running using tools like Docker Desktop or the Docker CLI. Docker has a massive community, and chances are, what you’re trying to do has already been done. This helps to make things like troubleshooting easier.
Docker offers more cross-platform consistency than Podman. Most importantly, Docker integrates with nearly every container-based service, including AWS ECS, Azure AKS, and Google Cloud Run.
This means that when it comes time to run your containers in production, you’re able to easily integrate with the service of your choice. The ability to move from local development to production is one of the most powerful parts of containerizing your code with Docker.
It’s not just Software and Data Engineering teams that use Docker. AI and ML Engineers, Data Scientists, and even Data Analysts use Docker to power the work they do!
When to use Podman
For developers working in a security-sensitive or heavily regulated environment, Podman may be your container manager de jour. Remember, Podman is rootless, meaning that a user running Podman locally does not require root access to their machine to build and manage containers locally. Below are a few more reasons why it may make sense to lean toward Podman over Docker.
- You’re developing locally on a Linux machine.
- Underlying resource usage and container spin-up time is important to you.
- You plan on shipping your containers to a Kubernetes cluster or want to mimic a Kubernetes environment on your local machine.
Here’s the other thing to keep in mind: for the most part, Podman and Docker are interchangeable. That means that if you start using Docker and realize that Podman is the tool for you, it’s easy to switch between the two offerings.
Conclusion
Running containers requires a tool to manage these objects. Together, we explored two of the most popular containerization tools: Docker and Podman.
The industry standard for containerization, Docker is used by millions to run the world’s applications and data workloads. Docker’s architecture is built on top of the Docker daemon, which requires root access to the system the container runs on.
To interact with Docker, developers can leverage the Docker CLI or Docker Desktop, both of which offer the ability to manage things like images, containers, and volumes. Docker’s widespread adoption means a large and vibrant community, as well as support across all three major operating systems and almost every container-based service.
Podman offers an alternative container management solution. Podman is daemonless and rootless, meaning a user does not need root access to the machine they are using to run Podman. This is attractive for teams that demand a more security-conscious container management tool. Like Docker, Podman offers both a CLI and a UI to build and manage containers. Although native to Linux, Podman can be run on both Windows and Mac and integrates quite well with tools like AWS ECS and Azure AKS.
Regardless of the tool you choose, learning to “containerize” the code you write is one of the quickest ways to grow your development skills. If you’re looking to learn more about Docker and Podman, don’t be afraid to get your hands dirty with courses like Introduction to Docker or Containerization and Virtualization Concepts. Best of luck, and happy coding!
Podman vs Docker FAQs
What is a container?
A container is an object that contains everything needed to run an application or data workload. You can think of containers like little computers that have only the essentials to run some sort of code. Luckily, we can run these containers on our local machines as well as on servers that make a solution accessible to the world.
Why would I use a container in my project?
Using a container in your projects allows you to package your code in a single object. Why is this important? It means that can easily share your code with other developers or even ship your code to production without having to recreate your entire local environment.
Why do I need to use a container manager like Docker or Podman?
To build, run, and manage a container you need to use a container manager. Docker and Podman provide tools to create and test your container before deploying your solution into the world. Without a tool like Docker or Podman, these tasks would be quite tricky.
What does daemonless mean?
A daemon is a process that always runs in the background. Daemonless means that the tool exists without always having a process running in the background.
Are there any other container managers besides Docker or Podman?
Containerd and LXC are both popular container management systems to help build, run, and manage containers at scale.
Jake is a data engineer specializing in building resilient and scalable data infrastructure using Airflow, Databricks, and AWS. Jake is also the instructor for DataCamp's Introduction to Data Pipelines and Introduction to NoSQL course.
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