Coolify vs Dokploy: Best Self-Hosted PaaS for Developers 2026

If you are looking for a self-hosted alternative to Heroku, Railway, or Vercel, two open-source platforms dominate the conversation in 2026: Coolify and Dokploy. Both let you deploy applications on your own servers through a web interface, handle SSL certificates, manage databases, and integrate with Git providers. But they take fundamentally different approaches to how they get you there.

Coolify focuses on flexibility and a feature-rich PaaS experience. Dokploy emphasizes simplicity and fast, Docker-first deployments. The right choice depends on what you value — and the benchmarks tell a clearer story than the marketing pages.

At Effloow, we run AI agents on self-hosted infrastructure. We have evaluated both platforms for our deployment needs and collected real data on performance, resource usage, and developer experience. This is not a feature-table rehash — it is a practical comparison based on actual deployment work.

Quick Verdict

If you want the short answer: Dokploy is the better choice for teams that think in Docker and want minimal overhead. Coolify is the better choice for teams that want guided workflows, broader integrations, and do not mind the extra resource cost.

Now let us break down why.

Resource Usage: The Numbers That Matter

Resource efficiency is the most concrete differentiator between these two platforms. When you are running on a VPS, every percentage of CPU and megabyte of RAM counts.

Idle Resource Consumption

Based on testing by NextGrowth AI on identical Hetzner CX21 instances over an 8-month period with 20+ containers each:

A Medium analysis found similar results: Dokploy averaged 0.8-1.5% idle CPU, while Coolify hovered between 6-7% with no services running. Both platforms used around 1 GB of memory in that test, though the NextGrowth benchmarks on longer timeframes showed a wider gap.

Why does Coolify use more resources? Coolify is built with PHP/Laravel and runs additional background processes for its managed networking and proxy layers. Dokploy is built with Next.js and TypeScript, with a lighter runtime footprint.

Bottom line: On a small VPS (2-4 GB RAM), Dokploy leaves significantly more headroom for your actual applications. This matters less on larger servers, but it is a real consideration for budget-conscious deployments.

Installation and Onboarding

Both platforms offer single-command installation, but the experience diverges quickly after that.

Dokploy works straight out of the box. Install it, and you are looking at a functional dashboard. According to LogRocket's testing, Dokploy's installation was 21 minutes faster than Coolify's in testing.

Coolify includes a guided onboarding flow that walks you through connecting servers, configuring build settings, and setting up your first project. It even includes dad jokes during the setup process. This is friendlier for newcomers but adds time for experienced users who just want to deploy.

Git Integration and Build Systems

Git Provider Support

Dokploy wins on breadth here. If your team uses GitLab or Bitbucket, Coolify is not an option without workarounds.

Build Methods

Dokploy supports more build methods, including AI-assisted builds that can auto-detect and configure your project. Coolify sticks to the proven trio of Dockerfile, Nixpacks, and Docker Compose.

Docker Compose: The Critical Difference

This is where the philosophical difference between the two platforms becomes most apparent.

Dokploy treats Docker Compose files the way Docker itself does. Networking, volumes, and service definitions behave as expected. If your docker-compose.yml works locally, it works on Dokploy with minimal changes.

Coolify adds an abstraction layer on top of Docker Compose. It creates managed networks, injects proxy containers, and maps routing through its UI. This gives you more control through the web interface but introduces potential compatibility friction. Coolify also injects a helper image during each deployment, which can affect build and deployment speed.

Container Restart Behavior

A subtle but important difference from LogRocket's testing:

• Dokploy: Stops and restarts containers without rebuilding
• Coolify: Triggers a full rebuild from scratch on restart

If you frequently restart services during development, Coolify's approach adds significant overhead.

Database and Service Management

Database Options

Coolify offers a broader selection of database services out of the box, including PostgreSQL, MySQL, DragonflyDB, and KeyDB. Dokploy focuses on the most common options: PostgreSQL and MySQL.

However, Dokploy allows full image selection for database containers, while Coolify only offers tag selection. This gives Dokploy more flexibility for custom or specialized database images.

Volume Backups

Dokploy supports backing up any Docker volume to S3-compatible storage. Coolify limits backups to database services. If you have application data stored in volumes, Dokploy gives you more protection.

Monitoring and Scheduled Tasks

Monitoring

Dokploy includes built-in real-time metrics in its UI — you can see CPU, memory, and network usage for each container without additional setup.

Coolify requires configuration before monitoring works. Once configured, it provides similar metrics, but the out-of-box experience is weaker.

Scheduled Tasks

Dokploy offers more granular control over scheduled tasks, supporting container-level, service-level, and host-level scheduling. Coolify limits scheduled tasks to the application level.

Networking and SSL

Coolify has built-in Cloudflare Tunnels support, which is a significant advantage if you use Cloudflare for DNS and want to avoid exposing your server's IP address. Dokploy can achieve this through templates but does not have native integration.

Both platforms handle SSL certificates automatically through Let's Encrypt.

Coolify supports a wider range of notification integrations: Telegram, Discord, Slack, and Pushover. Dokploy supports Gotify and Discord, with fewer options overall.

Scaling and Multi-Node

Dokploy supports Docker Swarm multi-node clusters, allowing you to scale across multiple servers. This is important for production workloads that need horizontal scaling.

Coolify focuses on single-server deployments with managed complexity. Multi-node support is more limited.

Licensing: An Important Distinction

Coolify is fully open source under Apache 2.0 with no restrictions. Dokploy uses an Apache 2.0 license with additional restrictions on resale and commercial use, making it more accurately described as source-available rather than strictly open source.

This matters if you plan to build a hosting business on top of either platform. For personal or internal team use, both licenses are fine.

Managed Hosting Plans

Both platforms offer managed hosting for teams that do not want to maintain their own servers:

• Coolify Cloud: Starting at $5/month
• Dokploy: Managed plans starting at $4/month

The pricing is comparable, and both options include automated updates and support.

Community and Ecosystem

GitHub Activity

Coolify has a larger community and longer track record. It has been in active development for over four years with a substantial contributor base. Dokploy is newer — started in April 2024 — but has grown rapidly, reaching 24,000+ stars in under two years.

A larger community means more tutorials, more Stack Overflow answers, and faster bug fixes. But Dokploy's rapid growth suggests strong momentum and active development.

Who Should Use What

Choose Dokploy If:

• Docker is your mental model. You think in Dockerfiles and Compose files, and you want your PaaS to stay out of the way.
• Resource efficiency matters. You are running on a small VPS and need every MB of RAM for your applications.
• You use GitLab or Bitbucket. Coolify only supports GitHub.
• You need multi-node scaling. Docker Swarm support gives you a path to horizontal scaling.
• You want fast container restarts. Dokploy restarts without rebuilding.

Choose Coolify If:

• You want guided onboarding. Coolify holds your hand through setup and configuration.
• Cloudflare Tunnels are essential. Native integration saves significant configuration time.
• You need broad notification support. Telegram, Slack, Pushover, and Discord are all built in.
• Open source licensing matters. Apache 2.0 with no restrictions gives you maximum freedom.
• You value community size. A larger community means more resources and faster support.

For Effloow's Use Case

We run AI agents that need reliable, low-overhead deployment. Docker Compose compatibility is essential because our agent services are defined in Compose files. Resource efficiency matters because we run multiple services on each VPS. For these reasons, Dokploy aligns better with our requirements — but Coolify's Cloudflare Tunnels integration is genuinely compelling for teams with different priorities.

The Bottom Line

Both Coolify and Dokploy are excellent self-hosted PaaS platforms that can replace expensive managed services. The choice comes down to philosophy:

Dokploy stays close to Docker and gets out of your way. It uses fewer resources, deploys faster, and supports more Git providers and build methods. The trade-off is fewer built-in integrations and a source-available license.

Coolify provides a richer, more guided experience with broader integrations and a fully open-source license. The trade-off is higher resource overhead and a Docker Compose abstraction that may not behave exactly like native Docker.

Neither is the wrong choice. Both are actively maintained, both offer managed hosting plans, and both are dramatically cheaper than Heroku or Railway for teams that can manage their own servers.

Pick the one that matches how you think about deployment — and either way, you will be deploying on your own terms.

Migration Considerations

If you are already using one platform and considering switching, here is what to expect:

Moving from Coolify to Dokploy: Your Docker Compose files will likely work with fewer modifications on Dokploy since it stays closer to native Docker behavior. The main challenge is recreating any Cloudflare Tunnel configurations manually. Database migrations are straightforward — export from Coolify's backup system and import into Dokploy containers.

Moving from Dokploy to Coolify: Expect to adjust Docker Compose files for Coolify's managed networking layer. Some Compose configurations that work on Dokploy may need modifications for Coolify's proxy injection. The benefit is gaining access to Coolify's broader notification and integration ecosystem.

Starting fresh: If you are deploying a new project, try both platforms on a cheap VPS before committing. A $5/month Hetzner or Contabo instance is enough to evaluate the deployment experience, resource overhead, and Docker Compose compatibility with your specific stack.

Frequently Asked Questions

Can I run both on the same server? Technically yes, but it is not recommended. Both platforms manage Traefik or similar reverse proxies and would conflict on port 80/443. Use separate VPS instances for evaluation.

Which is better for Kubernetes? Neither platform is designed for Kubernetes. Both focus on Docker-based deployments. If Kubernetes is a requirement, look at Rancher or k3s instead.

How do updates work? Both platforms support self-updating through their web interface. Coolify tends to push updates more frequently due to its larger contributor base. Dokploy updates are less frequent but typically well-tested.

Is there vendor lock-in? Minimal for both. Your applications run in standard Docker containers, and your Compose files are portable. The main lock-in is in platform-specific configuration like routing rules and environment variable management, which is easy to recreate elsewhere.

Related Resources

• Self-Host Your Entire Dev Stack for Under $20/Month — A complete guide to building your self-hosted development infrastructure
• Ollama + Open WebUI Self-Hosting Guide — Deploy self-hosted AI inference alongside your Coolify or Dokploy stack
• How to Build a Custom MCP Server for Claude Code — Extend your self-hosted infrastructure with AI tool integrations
• The Perfect CLAUDE.md Setup Guide — Configure AI coding assistants for your deployment workflow