Plausible vs Fathom vs Simple Analytics: a practical 2026 comparison
- 02 Mar, 2026
Plausible, Fathom and Simple Analytics sit in the same broad category: lightweight, privacy-first web analytics for teams that do not want the complexity of GA4 or an enterprise analytics suite. They are not interchangeable, though. The right choice depends on your traffic volume, team model, reporting needs, hosting expectations and internal privacy review.
Prices and packaging change often. This comparison is based on public vendor pages checked on May 9, 2026. Always verify the current vendor page before buying.
The short version
Choose Plausible if you want an established open-source product, a clean dashboard, a self-hosting route and detailed documentation around subscription tiers.
Choose Fathom if you want a simple paid SaaS with a deliberately small feature surface and straightforward multi-site pricing.
Choose Simple Analytics if you want a Netherlands-based product with a clearly documented privacy posture, simple reports and a free entry point within the vendor’s published limits.
Choose Pomelo if your priority is multi-site reporting for European SMEs, B2B SaaS teams and agencies, with Strict collection by default and Extended collection only when explicitly configured.
Comparison table
| Criterion | Plausible | Fathom | Simple Analytics |
|---|---|---|---|
| Main fit | Teams wanting open-source credibility and simple reports | Teams wanting a compact paid SaaS | Teams prioritizing documented privacy posture |
| Pricing model | Subscription tiers by usage | Subscription tiers by pageviews | Free or paid plans depending on usage limits |
| Self-hosting | Community Edition available | Not the core model | Not the core model |
| Multi-site use | Supported | Supported | Supported by plan |
| Reporting style | Minimal dashboard, events, goals, campaigns | Minimal dashboard, events, campaigns | Minimal dashboard, goals, referrers |
| Buyer risk to verify | Plan limits, self-hosting maintenance, imported history | Plan fit and feature depth | Plan limits and event/view counting |
Privacy posture is a configuration question
All three vendors position themselves around privacy-first analytics, but a vendor promise is not the same as your live setup. Your team still needs to document:
- what the script collects;
- whether events or campaign parameters add personal or sensitive context;
- retention periods;
- provider role and data-processing terms;
- transfers and hosting location;
- whether other trackers on the same site change the consent analysis.
This is where Pomelo’s Strict/Extended split is useful as a product model. Strict should cover baseline audience reporting. Extended should be a deliberate setting for richer campaign, event, goal or technical context. The dashboard should explain the effect of that setting instead of hiding it inside marketing copy.
Pricing should be compared at your real volume
Do not compare only entry prices. Model the cost at your actual monthly pageviews, number of sites, number of users, retention needs and export/API expectations.
For example, a tool that is cheaper at 10,000 monthly pageviews may be more expensive at 500,000. A self-hosted option may reduce subscription fees but add infrastructure, backup and maintenance cost. A plan with generous site limits may be cheaper for an agency than a plan priced per site.
Reporting quality matters more than feature count
The best analytics tool is the one the team actually reads. Before buying, ask the person who will use the dashboard every week to answer three questions from a trial account:
- Which acquisition sources are working?
- Which content or pages deserve action?
- Which conversions changed materially since last period?
If the tool cannot answer those questions quickly, more reports will not fix the problem.
Sources
Sources checked on May 9, 2026.
