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We Docker-Deployed Every n8n Alternative. The Results Don't Match the Listicles.

deployment

Search “n8n alternatives” and you’ll find the same article rewritten a dozen times: a feature table copied from vendor docs, a screenshot of each homepage, and a verdict that reads like it was written by whoever answered the sponsorship email first. What none of them tell you is the thing that actually decides whether a tool works on your server: what happens when you run docker compose up.

So we ran it. All six of the most-recommended self-hosted automation tools, one after another, on the same machine, with the same procedure: write a compose file from official docs, deploy, wait for HTTP 200, record idle RAM, and write down everything that went wrong. The results cut against several pieces of conventional listicle wisdom — including which “easiest n8n alternative” actually deploys easiest.

Tested on: Ubuntu 26.04 LTS, Xeon W-2155, 128 GB RAM, Docker CE 29.7.2 / Compose v5.5.0. Cold-pull time excluded except where noted; every stack was measured to its first working page (HTTP 200). Versions were latest images as of 2026-08-23.

The matrix

ToolContainersExternal DBIdle RAM (app)Total stack RAMDeployed first try?License
Node-RED1none91 MiB91 MiB✅ yesApache-2.0
Automatisch4Postgres + Redis116 MiB~259 MiB❌ two fixes neededApache-2.0
n8n1none (embedded SQLite)356 MiB356 MiB❌ one fix neededSustainable Use (fair-code)
Activepieces3Postgres + Redis724 MiB~914 MiB❌ three config iterationsMIT (core)
Huginn2MySQL 8 (bundled)741 MiB~1.2 GiB❌ restart neededMIT
Windmill3Postgres + worker327 MiB~1.46 GiB✅ yesAGPL

Idle numbers are steady-state after boot, measured with docker stats. Full raw notes are in the methodology section below.

What the numbers actually say

Activepieces is the hardest “easy alternative” to self-host

This was our biggest surprise. Activepieces markets itself as the open-source Zapier alternative, and listicles consistently rank it the friendliest n8n swap. On our box it took three config iterations to get running:

  1. First attempt with SQLite config failed at boot — current releases no longer support SQLite.
  2. Adding Redis wasn’t enough; the app crash-looped demanding AP_POSTGRES_DATABASE and friends.
  3. Only the full Postgres + Redis + app stack came up healthy.

Final footprint: three containers, roughly 914 MiB combined, with the app itself the single hungriest process we measured (724 MiB idle). None of this means you shouldn’t use it — the UX is genuinely good — but if your mental model of self-hosting is “one container and go,” Activepieces is the furthest thing from it among these six.

Node-RED is the featherweight — with an asterisk

One container, 91 MiB idle, serving pages in under eight seconds, zero configuration issues. It’s four times lighter than anything else here. The asterisk: Node-RED isn’t trying to be Zapier. It’s a flow-based wiring tool with an IoT heritage and a node palette rather than an integration app catalog. If your automations are device-and-API plumbing, nothing else in this test comes close on efficiency. If you want prebuilt connectors for SaaS apps with OAuth flows handled for you, the lightness won’t matter — you’ll spend the saved RAM building what other tools ship.

n8n hits the deployment sweet spot

The baseline everyone compares against is also the best-balanced: a single container with embedded SQLite, 356 MiB idle, no external database to babysit. Our only issue was self-inflicted-adjacent — a bind-mounted data directory created by root caused an EACCES crash loop until we chowned it to UID 1000 (the container’s node user). That’s a five-second fix once you know it, but it’s exactly the kind of thing that produces a GitHub issue titled “container exits immediately.”

Worth noting the license column too: n8n’s Sustainable Use license is fair-code, not OSI open source. For personal and internal business use it changes nothing; if you’re embedding it into a product you sell, read it before you build.

Windmill: the best-engineered deploy, aimed at developers

Windmill runs the biggest stack — Postgres plus separate server and worker containers, ~1.46 GiB all-in — and it was the only multi-container tool that worked on the very first compose up. No missing environment variables, no crash loops, no permission surprises. That’s not luck; the official compose file is complete.

It’s also the least Zapier-like tool here besides Node-RED. Windmill treats workflows as code (TypeScript, Python, Go) with a UI on top. If you think in scripts and version control, it may be the best fit on this list. If you think in drag-and-drop nodes, it won’t.

Automatisch: honest Apache-2.0 licensing, two small traps

Four containers (app, worker, Postgres, Redis) but a modest ~259 MiB total. Two things bit us:

Both are documented if you read carefully; both are easy to miss. Automatisch remains notable as the fully-open-source option (Apache-2.0, no fair-code caveats), though its connector catalog is smaller than n8n’s or Activepieces’.

Huginn: alive, but showing its age

The oldest project here still works. Bundled MySQL 8, ~1.2 GiB total, and a first-boot race where the Rails app started before MySQL finished initializing — one manual restart fixed it. Huginn’s agent model (scheduled, composable agents rather than flow canvases) remains genuinely distinctive for data-scraping style automations. But nothing about the deployment experience has modernized, and the RAM cost is second-highest per unit of polish.

Methodology and reproducibility

Every tool got the same treatment on the same box, in order: n8n → Activepieces → Windmill → Node-RED → Automatisch → Huginn.

The full results table, ports, and raw gotchas live in our repo notes; every claim above traces to a logged container error or a docker stats line.

Which one should you actually run?

Self-hosted automation tools differ less on features than listicles imply and more on operational shape: how many processes you run, how much RAM they drink at idle, and how many times compose up fails before it works. Those are the columns nobody publishes — so we did.

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