GoatCounter vs Plausible: Minimalist Analytics Compared

The Problem Both Solve

If you need website analytics without handing visitor data to Google, GoatCounter and Plausible are the two most popular privacy-first options. Both skip cookies entirely, both avoid GDPR consent banners, and both give you traffic data that actually matters. The difference is in how much infrastructure you want to run and how much polish you need in the dashboard.

Updated February 2026: Verified with latest Docker images and configurations.

Feature Comparison

Feature	GoatCounter	Plausible
Language	Go	Elixir/Phoenix
Database	SQLite or PostgreSQL	PostgreSQL + ClickHouse
Tracking script	~3.5 KB	~1 KB
Cookies	None	None
GDPR consent required	No	No
Real-time dashboard	Yes	Yes
Custom events	Yes (via data attributes)	Yes (goals/funnels)
API	Yes (REST)	Yes (REST + Stats)
Multi-site	Yes (separate subsites)	Yes (native multi-site)
Funnels	No	Yes
Revenue tracking	No	Yes
UTM tracking	Basic	Full
Email reports	No	Yes (weekly/monthly)
CSV export	Yes	Yes
Minimum RAM	~25 MB	~2 GB (ClickHouse)
License	EUPL 1.2	AGPL 3.0

Installation Complexity

GoatCounter is a single container with SQLite — one service, one volume, done:

services:
  goatcounter:
    image: arp242/goatcounter:2.7
    container_name: goatcounter
    ports:
      - "8080:8080"
    volumes:
      - goatcounter-data:/home/goatcounter/goatcounter-data
    restart: unless-stopped

volumes:
  goatcounter-data:

After startup, create your first site via CLI:

docker exec -it goatcounter goatcounter db create site \
  -vhost=stats.example.com \
  [email protected]

Plausible Community Edition requires three services — the app itself, PostgreSQL, and ClickHouse. You clone the official repository and configure a .env file with secrets and your domain:

git clone -b v3.2.0 --single-branch \
  https://github.com/plausible/community-edition plausible-ce
cd plausible-ce

ClickHouse alone needs 1–2 GB of RAM and a CPU with SSE 4.2 support. The stack is well-documented but substantially heavier than GoatCounter’s single binary.

Performance and Resource Usage

Resource	GoatCounter	Plausible CE
Idle RAM	~25 MB	~1.5–2 GB
Disk (application)	~15 MB	~500 MB
Container count	1	3 (app + PostgreSQL + ClickHouse)
CPU architecture	Any (ARM, x86)	x86_64 required (ClickHouse SSE 4.2)
Startup time	<1 second	15–30 seconds

GoatCounter runs on a Raspberry Pi. Plausible needs a proper server. On a VPS with 1 GB of RAM, GoatCounter fits comfortably alongside other services. Plausible needs the whole machine.

For high-traffic sites (100K+ pageviews/month), ClickHouse gives Plausible faster query performance on large datasets. GoatCounter with SQLite handles this volume fine but PostgreSQL is recommended beyond ~500K monthly pageviews.

Dashboard and Features

Plausible’s dashboard is polished — single-page, real-time, with filterable graphs, source/medium breakdowns, goal conversions, and funnel visualization. It looks like a SaaS product because it is one (the self-hosted Community Edition shares code with the commercial offering).

GoatCounter’s dashboard is functional but utilitarian. It shows pageviews, referrers, browsers, screen sizes, and locations. The interface works, but it won’t impress a marketing team. What it lacks in visual polish, it makes up for in speed — pages load instantly because there’s almost nothing to render.

Plausible wins on:

• Funnels and goal tracking
• Revenue attribution
• Full UTM parameter support
• Automated email reports
• Shared dashboard links with access controls

GoatCounter wins on:

• No-JavaScript tracking (image pixel fallback)
• Log file import (Apache, Nginx, Caddy, CloudFront)
• API-based counting (backend middleware)
• Minimal resource footprint

Community and Support

Metric	GoatCounter	Plausible
GitHub stars	~4.5K	~21K
Primary maintainer	Single developer (Martin Tournoij)	Company (Plausible HQ)
Update frequency	Monthly patches	Monthly releases
Documentation	Good, developer-written	Excellent, product-quality
Commercial offering	goatcounter.com (hosted)	plausible.io (hosted SaaS)
Community size	Small, focused	Large, active

Plausible has a larger team and faster feature development. GoatCounter is a one-person project with deliberate choices about what not to add. Both are actively maintained.

Use Cases

Choose GoatCounter If…

• You run a personal blog or small site and want the lightest possible analytics
• Your server has limited RAM (512 MB or less)
• You want to run on ARM hardware (Raspberry Pi, Oracle free tier)
• You prefer log file analytics or no-JavaScript tracking
• You value simplicity over features — knowing pageview counts and referrers is enough

Choose Plausible If…

• You need goal tracking, funnels, or revenue attribution
• You run multiple websites and need a unified dashboard
• You want automated email reports for stakeholders
• Your server has at least 2 GB of RAM to spare
• You want a polished UI that non-technical team members can navigate

Final Verdict

If you just want to know how many people visit your site and where they come from, GoatCounter does that in 25 MB of RAM with zero dependencies. If you need marketing-grade analytics with conversions, funnels, and team features, Plausible is the right tool — but budget 2 GB of RAM for the ClickHouse stack. Neither requires cookies, neither needs a GDPR banner, and both respect visitor privacy.

FAQ

Can I migrate from GoatCounter to Plausible or vice versa?

Both support CSV export. GoatCounter exports via goatcounter db export, Plausible via Settings > Export. Neither has a direct import tool for the other’s format, but the data is simple enough to transform with a script.

Does GoatCounter support custom events?

Yes. Add data-goatcounter-click attributes to HTML elements. It’s simpler than Plausible’s goals system but covers basic event tracking.

Can Plausible run on a Raspberry Pi?

No. ClickHouse requires SSE 4.2 CPU instructions, which ARM chips don’t have. GoatCounter is the only option for ARM hardware.

Which is better for GDPR compliance?

Both are equivalent — neither uses cookies or stores personal data. No consent banner needed for either.

Is GoatCounter’s single-developer model a risk?

It’s a consideration. The codebase is simple Go with SQLite, so forks are feasible. But if bus factor matters to you, Plausible’s company-backed development is more resilient.

Related

• How to Self-Host GoatCounter
• How to Self-Host Plausible
• GoatCounter vs Umami
• Plausible vs Umami
• Plausible vs Matomo
• Best Self-Hosted Analytics
• Self-Hosted Alternatives to Google Analytics