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Cloud · head to head

Beam Cloud vs Dokku

Beam Cloud logo

Beam Cloud

Cloud

Serverless GPU computing with sub-second cold starts and multi-cloud support

From
Free
Rated
-
Full reviewWebsite
Dokku logo

Dokku

Cloud

Single-server platform that accepts a git push and runs Heroku buildpacks on Docker

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Beam Cloud free tier limited to $30 monthly credits with 5 GPU containers; Dokku one maintainer accounts for nearly all human commit activity and the project records roughly 10,500 US dollars of annual income on Open Collective, which is not enough to fund a maintainer, so continuity rests on one person continuing to volunteer.
  • They diverge on capability: Beam Cloud covers Sub-second cold starts, Dokku covers Git push deploy.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Beam Cloud and Dokku actually diverge.

Attributes where Beam Cloud and Dokku differ
AttributeBeam CloudDokku
Pricing modelFreemium with pay-per-millisecond usage chargesOpen source, no licence fee
PlatformsCloud, PythonLinux, Docker, CLI, Self-hosted

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Cloud).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Beam Cloud

  • Sub-second cold starts
  • Inference endpoints
  • Task queues
  • Sandboxes
  • Multi-cloud support
  • Python SDK
  • Global distribution
  • Massive parallelization

Only in Dokku

  • Git push deploy
  • Heroku buildpacks
  • Datastore plugins
  • Automatic certificates
  • Zero downtime deploys
  • Pluggable schedulers

What people use each for

The jobs each tool is most often brought in to do.

Beam Cloud

  • Deploying ML models with minimal latency and setup timenot Dokku
  • Large-scale batch processing across thousands of concurrent tasksnot Dokku
  • Cost-effective inference serving with bursty workloadsnot Dokku
  • Multi-cloud AI deployments with global low-latency accessnot Dokku
  • Serverless AI development for rapid experimentationnot Dokku

Dokku

  • Running a dozen side projects and client applications on one virtual private server with Heroku style deploymentnot Beam Cloud
  • Moving off a managed platform when the monthly bill has grown faster than the traffic hasnot Beam Cloud
  • A consultancy that wants buildpack deployments without teaching every client team Kubernetesnot Beam Cloud
  • Keeping a legacy Procfile application alive on hardware you control after a managed platform deprecates its stacknot Beam Cloud

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Beam Cloud

  • Free tier limited to $30 monthly credits with 5 GPU containers
  • Massive parallelization complexity may require DevOps expertise
  • Per-millisecond pricing model requires careful cost monitoring
  • Smaller team relative to established cloud providers

Dokku

  • One maintainer accounts for nearly all human commit activity and the project records roughly 10,500 US dollars of annual income on Open Collective, which is not enough to fund a maintainer, so continuity rests on one person continuing to volunteer.
  • Dokku Pro asks 849 US dollars for a lifetime licence from a project with no disclosed legal entity behind the promise and no published refund terms, while the product is still described as in development at early bird pricing.
  • Dokku is single-server by design, and the k3s scheduler that provides multi-node support is missing log retrieval, process inspection and content-based health checks, with a post-run hook the documentation says does not consistently fire.
  • Supported operating systems are limited to Ubuntu 22.04 or 24.04 and Debian 11 or later, so organisations standardised on Red Hat, Rocky or Alma Linux cannot run it on their approved base image.
  • Backups are separate commands per datastore plugin that you schedule yourself, with no unified snapshot, no point-in-time recovery and no tested restore path, so verifying that a restore works is entirely your responsibility.

Pricing, plan by plan

Beam Cloud

Free
  • DeveloperFree
    • $30 monthly free credits
    • 5 GPU containers, 30 CPU containers
    • Community support
  • Team$89/month
    • $30 monthly free credits included
    • 50 GPU containers, 1,000 CPU containers
    • 3 seats included, $25 per additional
  • Growth$undefined/custom
    • 1,000+ GPU containers
    • Unlimited CPU containers
    • Unlimited seats
  • Serverless GPUs$undefined/per-millisecond
    • RTX 4090: $0.00019/sec

Dokku

Free
  • DokkuFree
    • MIT licensed, no usage limits
    • Command line and SSH only
    • All datastore and certificate plugins
  • Dokku Pro$849/one-time
    • Lifetime licence with free upgrades and no subscription
    • Covers 1 production and 2 pre-production servers
    • Web dashboard and JSON REST API

Which should you pick?

Choose Beam Cloud if

  • You need sub-second cold starts.
  • You want to start without paying.
  • You work on Cloud, Python.
  • You also want inference endpoints.
Beam Cloud review

Choose Dokku if

  • You need git push deploy.
  • You want to start without paying.
  • You work on Linux, Docker, CLI, Self-hosted.
  • You also want heroku buildpacks.
Dokku review

Questions people ask

Is Beam Cloud or Dokku better?
Neither clearly leads. Beam Cloud starts at Free and Dokku at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Beam Cloud or Dokku?
Beam Cloud starts at Free and Dokku at Free.
Does Beam Cloud or Dokku run on more platforms?
Beam Cloud runs on Cloud, Python. Dokku runs on Linux, Docker, CLI, Self-hosted.
Can I use Beam Cloud for free?
Both have a free tier, so you can try either at no cost before committing.
What is Beam Cloud best used for?
Beam Cloud is most often used for deploying ml models with minimal latency and setup time, large-scale batch processing across thousands of concurrent tasks, cost-effective inference serving with bursty workloads, multi-cloud ai deployments with global low-latency access. Of those, deploying ml models with minimal latency and setup time and large-scale batch processing across thousands of concurrent tasks are not what Dokku is typically brought in for.
What can Beam Cloud do that Dokku cannot?
Beam Cloud covers Sub-second cold starts, Inference endpoints, Task queues, Sandboxes. Dokku covers Git push deploy, Heroku buildpacks, Datastore plugins, Automatic certificates.

Answered from the vendors’ own pages

Beam Cloud: What is included in the Developer plan?

The Developer plan includes $30 monthly free credits, 5 GPU containers, 30 CPU containers, and community support. No upfront commitment is required.

Source
Dokku: Is Dokku still maintained?

Yes. Version 0.38.27 shipped in August 2026 with roughly six releases in the preceding two months. The caveat is that one maintainer writes nearly all of it.

Beam Cloud: How fast are the cold starts?

Beam Cloud achieves sub-second cold starts through memory snapshots that restore GPU containers 35x faster than traditional cold boots.

Source
Dokku: What does Dokku Pro give me over the free edition?

A web dashboard, a JSON REST API, git push over HTTPS, browser log tailing, team management and email support from the maintainers. It costs 849 US dollars once for one production and two pre-production servers.

Beam Cloud: Can I deploy across multiple cloud providers?

Yes, Beam Cloud supports multi-cloud deployment across AWS, GCP, Azure, Hetzner, and other providers with 30+ global regions available.

Source
Dokku: Can Dokku run across multiple servers?

Only through the k3s or Nomad schedulers. The k3s path is missing several commands and health check types, and the older Kubernetes scheduler is deprecated and no longer developed.

Dokku: Will my Heroku application run on it unchanged?

Usually. Dokku runs the same buildpacks and reads a Procfile, so the application layer normally moves across. Add-ons, scaling behaviour and backups are the parts you have to rebuild.

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