Coolify vs Dokploy: Self-Hosted PaaS Compared for 2026

If you are paying Vercel, Render, or Railway for a side project that gets a few hundred visits a day, the math stops making sense around the time your first managed Postgres add-on shows up on the invoice. A $5–$10 VPS plus a self-hosted control plane gives you push-to-deploy, automatic TLS, and a database on hardware you fully control. Two open-source projects dominate that space in 2026: Coolify and Dokploy. They solve the same problem and look similar in a screenshot, but they make different bets under the hood, and those bets decide which one fits how you actually work.

We ran both on fresh single-node VPS instances to compare the parts that matter to a solo developer: how they deploy, what they cost in RAM, and how much they fight you when something breaks.

The architectural split that decides everything

The biggest difference is not the UI — it is the orchestration layer underneath.

Coolify runs your apps as plain Docker containers managed directly by the Docker daemon. On a single server, that is exactly what it sounds like: containers, a reverse proxy (Traefik or Caddy, your choice), and a Postgres instance backing Coolify itself. Multi-server support exists — you connect additional hosts over SSH and schedule deployments to them — but each host is still running standalone Docker, not a cluster.

Dokploy is built on Docker Swarm with Traefik as the router. Even on a single machine, Dokploy initializes Swarm mode. For one server that mostly means Swarm’s rolling-update and health-check machinery is doing the work of restarting your containers. The payoff arrives when you add nodes: Dokploy can schedule services across a Swarm cluster without you wiring up networking by hand.

That distinction maps cleanly onto intent. If you expect to live on one box for a long time, Coolify’s direct-Docker model is simpler to reason about — when a container misbehaves, docker ps and docker logs tell you the whole story. If you think you will outgrow one server and want horizontal scaling to be a configuration change rather than a migration, Dokploy’s Swarm foundation is already pointed in that direction.

What setup and daily operation actually feel like

Both install the same way: SSH into a clean Ubuntu VPS and run a single curl-piped shell script. On a 2 vCPU / 2 GB box, each was reachable on its dashboard port within a few minutes. From there the loop is familiar to anyone who has used a hosted PaaS — connect a GitHub repo, point at a branch, and pushes trigger builds.

Resource overhead is the first thing a solo dev should check, because the control plane eats into the same RAM your apps need. Coolify’s own documentation recommends 2 GB of RAM as a floor and is comfortable at 4 GB; the control plane plus its Postgres and Redis sit resident even when nothing is deploying. Dokploy carries similar baseline requirements — the docs point at 2 GB minimum — with Swarm and Traefik adding their own footprint. In practice, a 2 GB server runs either tool plus one or two small apps, but build steps are memory-hungry. A Next.js or Rust build can OOM-kill a 1 GB box outright.

Feature parity is closer than the marketing suggests. Both give you automatic Let’s Encrypt certificates, environment-variable management, scheduled backups to S3-compatible storage, database provisioning (Postgres, MySQL, MongoDB, Redis), webhook-driven deploys, and a one-click service catalog for things like Plausible or Umami. Coolify has been shipping longer and its catalog and integration list are broader; the community is larger, which mostly matters when you are searching for someone who hit the same error you did. Dokploy is younger and leaner, and some users prefer that its surface area is smaller and easier to hold in your head.

Where you will feel the difference is debugging. Because Coolify maps onto raw Docker, the mental model is short. Dokploy’s Swarm layer adds an indirection — when a service will not converge, you are reading docker service output and Swarm task states, which is more concepts to learn if you have never run Swarm before.

Writing the Dockerfiles and Compose files these tools deploy is its own small chore, and an AI-native editor turns it from reference-hunting into autocomplete.

Picking one as a solo developer

The honest recommendation splits on one question: do you want a single server to stay simple, or do you want a path to scale already built in?

Choose Coolify if your priority is the shortest distance between a push and a running container, you will likely stay on one or two servers, and you value a larger pool of community answers when you get stuck. Its direct-Docker model is the easier thing to debug at 2 a.m., and its head start shows in breadth.

Choose Dokploy if you genuinely expect to add nodes, you are comfortable with Swarm concepts (or want a reason to learn them), and you prefer a smaller, more focused tool. The Swarm foundation means scaling out later is a configuration step rather than a re-platforming project.

Both are free to self-host, both deploy portable Docker workloads, and both will save you real money against a hosted PaaS once you have more than a toy running. The cost of switching later is low precisely because your app packaging stays the same — so pick the one whose mental model you would rather live inside, and move on to shipping.