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LINUX Docker vs Podman for Your Home Lab: A Practical Comp... 2026-02-09 · docker · podman · containers

Docker vs Podman for Your Home Lab: A Practical Comparison

Linux 2026-02-09 docker podman containers linux

Docker changed how we deploy software. Instead of installing services directly on your server and dealing with dependency conflicts, you pull a container image and run it. Isolated, reproducible, disposable. For home labs, containers are the backbone — Jellyfin, Home Assistant, Nginx Proxy Manager, Pi-hole, Grafana, Nextcloud — all of it runs in containers.

But Docker isn't the only game anymore. Podman, developed by Red Hat, does the same thing with a different architecture. No daemon, rootless by default, and systemd-native. Fedora and RHEL ship Podman instead of Docker. Ubuntu and Debian still default to Docker.

Both run the same container images. Both use the same CLI syntax. The differences are architectural, and they matter more than you'd expect in a home lab.

How They Work: The Core Difference

Docker: Client-Daemon Architecture

Docker runs a persistent daemon (dockerd) as root. When you type docker run, the Docker CLI sends a request to the daemon, and the daemon does the actual work — pulling images, creating containers, managing networks.

┌──────────────┐     ┌──────────────┐     ┌──────────────┐
│  docker CLI  │────▶│   dockerd    │────▶│  containerd   │
│  (user)      │     │  (root)      │     │  (root)       │
└──────────────┘     └──────────────┘     └──────────────┘
                           │
                     ┌─────┴─────┐
                     │ Container │
                     └───────────┘

Everything goes through the daemon. This means:

Podman: Daemonless, Fork-Exec Model

Podman has no daemon. When you type podman run, Podman directly forks a container process using conmon (a small container monitor). No intermediary daemon.

┌──────────────┐     ┌──────────────┐
│ podman CLI   │────▶│    conmon     │────▶ Container
│ (user)       │     │ (per-container)│
└──────────────┘     └──────────────┘

This means:

The practical result: Podman containers show up in ps like normal processes. Docker containers are children of the daemon. This has real implications for systemd integration, logging, and process management.

Rootless Containers

This is Podman's headline feature and the biggest practical difference for home labs.

Docker: Root by Default

Docker's daemon runs as root. Containers launched through it have root-level access to the host kernel. Docker does support rootless mode (since Docker 20.10), but it's not the default, and many Docker tutorials and Compose files assume root.

# Docker rootless mode (opt-in, not default)
dockerd-rootless-setuptools install
export DOCKER_HOST=unix:///run/user/1000/docker.sock

Podman: Rootless by Default

Podman runs containers as your regular user by default. No daemon running as root. The container processes run under your UID with user namespaces providing isolation.

# This just works as a regular user — no sudo, no daemon
podman run -d --name nginx -p 8080:80 nginx

# Check: the container runs as your user
ps aux | grep nginx
# youruser  12345  ... conmon --api-version ...

Why Rootless Matters

A rootless container that gets compromised has the privileges of your regular user — not root. It can't modify system files, install kernel modules, or access other users' data. This is a real security improvement.

The trade-off: rootless containers have some limitations:

# Allow rootless containers to bind to port 80
sudo sysctl net.ipv4.ip_unprivileged_port_start=80

# Or make it persistent
echo "net.ipv4.ip_unprivileged_port_start=80" | sudo tee /etc/sysctl.d/99-unprivileged-ports.conf

For most home lab services, rootless works perfectly. The port limitation is easily worked around, and the security benefit is worth it.

Docker Compose vs Podman Pods (and podman-compose)

Docker Compose

Docker Compose is the standard way to define multi-container applications. You write a docker-compose.yml file and run docker compose up. It's excellent — declarative, version-controlled, and widely supported.

# docker-compose.yml
services:
  app:
    image: nextcloud
    ports:
      - "8080:80"
    volumes:
      - nextcloud_data:/var/www/html
    depends_on:
      - db

  db:
    image: mariadb
    environment:
      MYSQL_ROOT_PASSWORD: secret
      MYSQL_DATABASE: nextcloud
    volumes:
      - db_data:/var/lib/mysql

volumes:
  nextcloud_data:
  db_data:

docker compose up -d
docker compose logs -f
docker compose down

Podman Compose

Podman has a compatibility tool called podman-compose that reads Docker Compose files and translates them to Podman commands. It works for most common Compose files.

# Install podman-compose
pip install podman-compose
# Or on Fedora:
sudo dnf install podman-compose

# Use it like Docker Compose
podman-compose up -d
podman-compose down

podman-compose handles the basics well — services, volumes, networks, environment variables. Complex Compose features (build contexts, profiles, extensions) might have edge cases. For standard home lab stacks, it works.

Podman Pods (Kubernetes-Style)

Podman also has a native concept called "pods" — groups of containers that share a network namespace (like Kubernetes pods). Containers in a pod communicate over localhost.

# Create a pod
podman pod create --name nextcloud-pod -p 8080:80

# Add containers to the pod
podman run -d --pod nextcloud-pod --name nextcloud-app nextcloud
podman run -d --pod nextcloud-pod --name nextcloud-db \
  -e MYSQL_ROOT_PASSWORD=secret \
  -e MYSQL_DATABASE=nextcloud \
  mariadb

# Manage the pod
podman pod ps
podman pod stop nextcloud-pod
podman pod rm nextcloud-pod

Pods are useful if you're learning Kubernetes concepts. For pure home lab use, podman-compose with Docker Compose files is more practical — you can reuse the vast ecosystem of existing Compose files without modification.

Generate Kubernetes YAML from Podman

One of Podman's neat tricks: it can export running containers or pods as Kubernetes YAML.

# Generate Kubernetes YAML from a running pod
podman generate kube nextcloud-pod > nextcloud.yaml

# Later, deploy from that YAML
podman play kube nextcloud.yaml

This is a genuine advantage if you're planning to eventually move workloads to Kubernetes.

Systemd Integration

This is where Podman really shines in a home lab context.

Docker: Systemd via Wrapper

Docker containers are managed by the Docker daemon. To integrate with systemd (auto-start on boot, restart on failure), you either rely on Docker's --restart=always flag or write a systemd unit that wraps Docker commands:

# /etc/systemd/system/my-container.service (Docker)
[Unit]
Description=My Container
After=docker.service
Requires=docker.service

[Service]
Restart=always
ExecStart=/usr/bin/docker start -a my-container
ExecStop=/usr/bin/docker stop my-container

[Install]
WantedBy=multi-user.target

This works, but the container lifecycle is really managed by Docker, not systemd. You have two init systems in play.

Podman: Native Systemd Integration

Podman can generate systemd units directly. Since Podman containers are regular processes (not children of a daemon), systemd can manage them natively.

# Generate a systemd unit from a running container
podman generate systemd --new --name my-container > ~/.config/systemd/user/my-container.service

# Enable and start it
systemctl --user daemon-reload
systemctl --user enable --now my-container

The --new flag is important: it tells the generated unit to create a fresh container on start and remove it on stop, rather than just starting/stopping an existing container. This is the correct pattern for reliable operation.

With Podman 4.x+, there's an even better approach: Quadlet files.

Quadlet: The Modern Way

Quadlet lets you define containers as systemd-native units using a simple .container file format:

# ~/.config/containers/systemd/jellyfin.container
[Unit]
Description=Jellyfin Media Server

[Container]
Image=docker.io/jellyfin/jellyfin:latest
PublishPort=8096:8096
Volume=jellyfin-config:/config:Z
Volume=jellyfin-cache:/cache:Z
Volume=/mnt/media:/media:ro
AutoUpdate=registry

[Service]
Restart=always

[Install]
WantedBy=default.target

# Reload systemd to pick up the new unit
systemctl --user daemon-reload

# Start it
systemctl --user start jellyfin

# Enable auto-start on boot
systemctl --user enable jellyfin

# Check logs (standard journalctl!)
journalctl --user -u jellyfin -f

Quadlet files are clean, declarative, and fully integrated with systemd. Logs go to the journal. systemctl manages lifecycle. Auto-updates work through podman auto-update. This is arguably the best container management experience on a Linux home lab server.

OCI Compatibility

Both Docker and Podman use OCI (Open Container Initiative) standard images and runtimes. This means:

# These produce identical results
docker build -t myapp .
podman build -t myapp .

# Same image format
docker pull ghcr.io/linuxserver/jellyfin
podman pull ghcr.io/linuxserver/jellyfin

The alias docker=podman approach works for a surprising number of workflows. Many people migrate by simply adding the alias and finding that everything works.

Migrating from Docker to Podman

If you're already running Docker and want to try Podman:

Step 1: Install Podman

# Fedora (already installed)
# Debian/Ubuntu
sudo apt install podman podman-compose

# Verify
podman --version

Step 2: Alias (Quick Test)

# Add to your .bashrc / .zshrc
alias docker=podman

# Test your existing commands
docker ps
docker images

Step 3: Migrate Containers

For each service, recreate it with Podman. If you used Docker Compose, podman-compose may work directly:

# Try your existing compose file
podman-compose -f docker-compose.yml up -d

Step 4: Migrate Volumes

Docker and Podman store volumes in different locations. You'll need to copy data:

# Docker volumes are in /var/lib/docker/volumes/
# Podman rootless volumes are in ~/.local/share/containers/storage/volumes/

# Export from Docker
docker run --rm -v myvolume:/data -v $(pwd):/backup alpine tar czf /backup/myvolume.tar.gz -C /data .

# Import to Podman
podman volume create myvolume
podman run --rm -v myvolume:/data -v $(pwd):/backup alpine tar xzf /backup/myvolume.tar.gz -C /data

Step 5: Convert to Systemd (Optional)

Replace Docker's restart policies with proper systemd units:

# For each container, generate a Quadlet file or systemd unit
podman generate systemd --new --name my-service > ~/.config/systemd/user/my-service.service
systemctl --user daemon-reload
systemctl --user enable --now my-service

Common Migration Issues

Performance Comparison

For most home lab workloads, Docker and Podman perform identically. The containers run the same OCI runtime (runc or crun). The differences are marginal:

Aspect Docker Podman
Container startup Slightly faster (daemon pre-loaded) Slightly slower (fork-exec)
Steady-state performance Same Same
Network (rootful) Same Same
Network (rootless) Same (if rootless) Slightly slower (slirp4netns/pasta)
Memory overhead Daemon uses ~50-100 MB No daemon overhead
Image pulls Same Same

The daemon overhead is the main measurable difference. Docker's daemon consumes 50-100 MB of RAM sitting idle. With Podman, if you're not running containers, nothing is running. On a RAM-constrained system, this matters. On a 64 GB server, it doesn't.

Rootless networking (Podman's default) adds some latency compared to rootful networking. Using pasta instead of slirp4netns largely closes this gap. For home lab services that aren't latency-sensitive, you won't notice.

When to Use Docker

When to Use Podman

The Honest Verdict

For a home lab in 2026:

Docker is the safe choice. Enormous community, universal documentation, everything just works. If you're starting out with containers and self-hosting, Docker plus Docker Compose is the path of least resistance.

Podman is the modern choice. Better security model, better systemd integration, no daemon to babysit. If you're on Fedora or RHEL, Podman is the natural fit. If you care about doing things "the right way" from a systems perspective, Podman is more elegant.

The good news: you don't have to choose permanently. They use the same image format, the same CLI syntax, and the same container runtime. You can start with Docker, learn the concepts, and migrate to Podman later when you want rootless containers and systemd integration. Or you can start with Podman and use alias docker=podman when following Docker tutorials.

The containers don't care. They run the same either way.