GA4 vs. Matomo: Google Stack or Open Source?
Both are free of licence fees; you pay differently: GA4 with data in the US cloud, Matomo with running it yourself. Where each trade is worth it.
| Criterion | Google Analytics 4 (GA4) | Matomo |
|---|---|---|
| Category | Web & Marketing Analytics | Web & Marketing Analytics |
| Editorial score | 3.5 / 5 | 3.9 / 5 |
| Status | US-Cloud | EU region |
| Hosting | US-Cloud | EU-Region |
| Vendor | USA | New Zealand |
| Pricing model | Free; GA360 as enterprise license | Open source; cloud subscription by traffic |
| Tracking without consent | Modelled only (Consent Mode) | Configurable anonymised mode |
| Data ownership | Google cloud, settled by contract | Complete, your own servers |
| Ads connection | Google Ads native | No native connection |
Last reviewed: 2026-07-03 · Scores: editorial review. How we rate →
Google Analytics 4 (GA4) is a fit when
- Conversion data has to flow back into Google Ads.
- BigQuery is the set warehouse; the native export saves pipeline work.
- Nobody should operate servers, not even an analytics server.
Matomo is a fit when
- Data ownership is in the requirements: data stays on your infrastructure.
- The data protection officer has effectively ruled out US services.
- Zero licence cost with ops capacity available.
Decision matrix
| Your situation | Pick | Why |
|---|---|---|
| Google Ads and Shopping as the core channels | GA4 | Conversion import and audiences only work natively there. |
| US services are ruled out internally | Matomo | On-premise keeps every request on your infrastructure. |
| Reporting runs through a warehouse | GA4 | The free BigQuery export is the shortest path there. |
| Internal compliance view plus marketing view needed | Both in parallel | GTM Server-Side serves both from one event stream. |
Privacy & GDPR
Matomo on-premise keeps every request on your infrastructure, without US transfer and without the third-country debate. GA4 remains a US cloud service despite EU endpoints, with consent duty and modelled gaps. In a pure privacy assessment this is not a close call.
Implementation effort
GA4 is productive via GTM in days and familiar to every agency in the market. Matomo demands an operating decision up front: your own server with sizing and update discipline, or Matomo Cloud. Both hang behind GTM Server-Side at our end, so a tag switch needs no website change.
Pricing and TCO
GA4 costs no licence; you pay with consent dependence and ongoing data-quality work. Self-hosted Matomo costs servers and ops time, and the database grows with every event. At high volume, Matomo sizing is the biggest single line on the bill.
Migration
Historical GA4 data cannot be imported into Matomo; the BigQuery export stays on as the archive. We set up a fresh event schema, run both systems in parallel for four weeks, and validate the core metrics against each other. Then the shutdown decision is made.
Two philosophies, one measurement problem
GA4 is the default because it feels free and serves the Google advertising ecosystem directly. Matomo is the antithesis: software in your own house, data in your own house, responsibility in your own house.
In DACH projects we rarely see an either-or on principle. The decision falls at two points almost every time: how important Google Ads is, and what the data protection officer says. The matrix above maps exactly those cases.
Our setup around it
Related services
Sources
- Google Analytics help center (accessed 2026-07-03)
- Matomo on-premise (accessed 2026-07-03)
Where your tracking loses conversions today is what the Measurement Audit shows.
Request a Measurement Audit →Is Matomo a full GA4 replacement?
For web analytics, yes; for the Google ecosystem, no. Funnels, segments, and e-commerce reporting are covered by Matomo; conversion import and audiences for Google Ads exist only with GA4.
Does Matomo work without your own server?
Yes, as Matomo Cloud hosted by the vendor. That removes the ops burden, and billing runs by traffic.
What happens to GA4 data after a shutdown?
Inside the GA4 interface the configured retention period applies. The BigQuery export preserves the history permanently, which is why we enable it before any migration.