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Performance numbers require identical hardware/workload.
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There are no invented “37% faster” claims here. Without fixed hardware and workloads, such benchmarks are meaningless. Instead we compare operating model, deployment flow, databases/backups, networking and troubleshooting surface.
The scorecard is not a synthetic benchmark and does not declare a universal winner. It weights your priorities. Real CPU/RAM/build performance must be measured on identical VPS hardware and repositories.
If Git-centric app deployment, broad service workflows and platform ergonomics dominate, Coolify may fit; if Dokploy’s Docker/Swarm model and its database/backup/network workflows match your operations better, evaluate it. Make the final choice with your own staging workload.
If Git-centric app deployment, broad service workflows and platform ergonomics dominate, Coolify may fit; if Dokploy’s Docker/Swarm model and its database/backup/network workflows match your operations better, evaluate it. Make the final choice with your own staging workload.
Compare Coolify and Dokploy by operational model rather than feature checklists: deployment, databases, backups, networking, debugging, resource needs and an interactive decision scorecard.
Performance numbers require identical hardware/workload.
Both support Git/container workflows with different operational models.
Persistent-data lifecycle matters more than UI preference.
How quickly your team diagnoses failure is a critical selection criterion.
A solo developer, agency, DevOps team and multi-client hosting operation have different priorities. Start by defining the operator profile.
| Profile | Priority |
|---|---|
| Solo developer | Low maintenance, fast deploy |
| Agency | Many projects/domains, backup |
| DevOps team | Network, observability, runbooks |
| SaaS | Rollback, secrets, database reliability |
Before feature lists, understand the Docker/orchestration primitives, remote-server model and failure domains on the host.
For a real comparison, clone identical VPS snapshots and use the same repository, database fixture and health checks.
| Metric | How to measure |
|---|---|
| First deploy | Repo connect → healthy URL |
| Incremental deploy | Commit → healthy new release |
| Rollback | Failure → previous healthy release |
| Disk growth | docker system df after 20 deploys |
“One-click database” is convenient; the real questions are point-in-time recovery, remote backup, credential rotation and restore testing.
A public application domain and a private management network are different problems. List edge and management networking separately.
When panel errors are insufficient, evaluate how clearly you can move through host, Docker, service/task, reverse proxy and application logs.
| Failure | Measurement |
|---|---|
| Build fail | Time to root cause |
| 502 | Proxy→container chain |
| DB down | Health + dependency visibility |
| Disk full | Alert → cleanup → recovery |
Instead of judging installation day, run two weeks of deployments, backups, updates and one controlled failure drill. The lowest total operational friction is often the better choice.
Move the sliders according to your priorities. The result is a decision aid, not a benchmark.
Use two VPS instances with identical CPU/RAM/NVMe to test your real repository and workload for 14 days and make a data-based platform choice.
Primary documentation and technical references used by this guide.
Continue with related infrastructure and implementation guides.
Coolify vs Dokploy
There is no universal answer without identical hardware, repository and build/runtime method. That is why this guide avoids fabricated benchmark numbers.
It varies by version, internal services and workload. Measure idle and deployment usage on identical clean VPS snapshots.
For fair testing, use separate identical VPS snapshots to avoid port, network and volume interference.
No. It is a preference-weighted decision aid; performance testing is separate.