If you run a website and rely on Google Analytics, you likely deal with two recurring problems: visitors must accept cookie banners before they are tracked, and visitor data is sent to a third party. Self-hosted, privacy-friendly web analytics solves both. Tools in the Web Apps category such as Umami, Plausible Analytics and Matomo let you measure traffic, campaigns and conversions while keeping data on infrastructure you control.

The problem with Google Analytics

Google Analytics typically requires a consent mechanism in many jurisdictions because it sets cookies and transfers visitor data to a third-party service. For site owners this creates concrete work:

  • Maintaining a cookie banner and making sure tracking respects the visitor's choice.
  • Documenting where analytics data is processed and who has access to it.
  • Explaining to users why their browsing is measured by an external company.

For IT teams and technical founders, the question is less about analytics features and more about control: where the data lives, who can read it, and how much code has to run in the visitor's browser.

How privacy-first, self-hosted analytics solves it

The three products below are open-source web analytics platforms built around a different model. Each is positioned as a cookie-free or privacy-friendly alternative that can run on your own server.

Umami

Umami is a privacy-first web analytics app that tracks traffic, campaigns, behavior and conversions without cookies. It is available self-hosted or in the cloud. It is published under the MIT license, which is permissive and allows broad reuse, and it has a large community with about 39,000 GitHub stars. The publisher is umami-software.

Plausible Analytics

Plausible Analytics is an open-source, privacy-first tool that presents itself as a cookie-free alternative to Google Analytics, available self-hosted or in the cloud. It is licensed under AGPL-3.0, a copyleft license that requires modified versions run as a network service to make their source available. The project is published by plausible and has about 29,000 GitHub stars.

Matomo

Matomo is an open-source web analytics platform described as a self-hosted alternative to Google Analytics that keeps visitor data privacy-friendly and under your control. It is licensed under GPL-3.0 and published by matomo-org, with about 22,000 GitHub stars. Matomo covers a broad feature set, which makes it a fit when you need more than page-level traffic reports.

Choosing between them

  • Pick Umami if you want a lightweight, MIT-licensed tool focused on traffic, campaigns and conversions.
  • Pick Plausible Analytics if you want a simple, cookie-free dashboard and can accept the AGPL-3.0 terms.
  • Pick Matomo if you need a full-featured platform under GPL-3.0 and are prepared to operate a larger system.

All three are listed under Web Apps in the catalog, so you can compare them side by side in the Web Apps category and browse self-hosted web apps more broadly.

How to get started

A practical rollout for a small team looks like this:

  1. Decide between self-hosting and the vendor's cloud offering. Self-hosting keeps data on your infrastructure; the cloud option removes operational work.
  2. Check the license against your plans. MIT (Umami), AGPL-3.0 (Plausible Analytics) and GPL-3.0 (Matomo) differ in what you must share when you modify and redistribute the software.
  3. Deploy one tool on a staging domain and add its tracking snippet to a test page.
  4. Compare the reported numbers with your current analytics for a week to confirm the data looks plausible.
  5. Update your privacy notice to describe the new setup, then remove the Google Analytics tag and, where your consent flow depended on it, adjust the cookie banner.

If you also manage developers' tooling, the developer tools and libraries and SDKs sections list adjacent components you may need.

Recommendation

For most teams replacing Google Analytics, start with a single cookie-free tool and run it side by side with the current setup. Umami suits teams that want a minimal, permissively licensed option. Plausible Analytics suits teams that value a simple dashboard and accept AGPL terms. Matomo suits teams that need the widest feature set and can run a heavier platform. Whichever you choose, confirm the license and hosting model against your legal and operational requirements before going live.