Guide

The best self-hosted analytics tools in 2026

Self-hosting analytics means your data stays on your own servers, but it’s an operational decision as much as a feature one. Here’s an honest look at the strongest options and what running each actually involves.

Self-hosting is an ops decision

Every tool here is open source and self-hostable, so the question isn’t whether you can own your data; it’s what running the tool costs you in operations. Weigh three things:

  • Footprint: how many services you have to stand up and keep alive.
  • Infrastructure: a lightweight script + one database, or a columnar event store and a queue.
  • Maintenance: updates, backups, and scaling as your volume grows.

This roundup focuses on the self-hosting experience. For a feature-by-feature look at what each tool measures, see the best open source analytics tools.

Web analytics, lightest to run

Umami

A simple, cookieless web-analytics tool on Node with a single Postgres or MySQL database, among the easiest to run, comfortably on a small VPS. Umami v2 added funnels, retention, and journeys, but it stays aggregate (no per-person profiles). MIT-licensed. Best for: a minimal, low-maintenance traffic dashboard. If you outgrow aggregate stats, see Umami vs product analytics.

Plausible

Privacy-first, cookieless web analytics with a famously light script. The Community Edition self-hosts on Elixir with Postgres and ClickHouse, a bit more to run than Umami, still modest. AGPL-3.0. Best for: clean traffic analytics without cookie banners. Compare it as a Plausible alternative.

Matomo

The most full-featured open-source web analytics platform and the closest direct Google Analytics replacement, on PHP + MySQL. More capability means more to operate, and heatmaps and recordings are paid plugins. Best for: a complete GA replacement for web and marketing. See the Matomo alternative.

Product analytics, heavier, but behavioral

PostHog

Open-source (MIT) and very broad, analytics, replay, flags, experiments. The catch for self-hosters: the open-source build is a community “hobby” Docker Compose deployment (one project per instance, no commercial support), and PostHog steers production users to its cloud. Operationally it’s the heaviest option here. Best for: teams that want breadth and will accept the ops. Details: PostHog alternative.

Pug

Open-source (AGPL-3.0) product analytics with unified profiles and autocapture. It’s built to be self-hosted: the API and every worker run as a single Go binary, backed by Postgres, ClickHouse, and NATS, fewer moving parts than a multi-service platform, so the operational surface stays small. Self-hosting is free forever, with no event caps, and tracking defaults to cookieless. Nothing is written to the device until you grant consent. It’s new, out of beta since October 2026. Best for: product analytics you own without service sprawl. See self-hosting Pug and the setup guide.

How to choose

If you only need website traffic, the lightest tools (Umami, Plausible) are the easiest to run; Matomo is the fullest GA replacement if you accept more ops. If you need product behavior: funnels, retention, and a profile per person: you’re into product analytics, where the event store makes the stack heavier; Pug keeps that footprint smaller by shipping as one binary. Whatever you choose, self-hosting keeps every event on your own infrastructure. Moving off Google specifically? Our free Google Analytics replacement guide walks through it.

FAQ

Common questions

What is the best self-hosted analytics tool?

It depends on what you’re measuring and how much ops you want. For website traffic, Umami and Plausible are the lightest to run; Matomo is the fullest but heavier. For product analytics (funnels, retention, profiles), PostHog is the broadest but operationally heavy, while Pug runs as a single Go binary to keep the footprint small.

How much does it cost to self-host analytics?

The software is free, you pay for infrastructure. Lightweight web-analytics tools run on a $5-12/month VPS. Product-analytics tools need a columnar event store (ClickHouse) and more memory, so budget more compute, plus the time to maintain and update the stack.

Is self-hosting analytics worth it?

If data ownership, privacy, or avoiding per-event SaaS bills matters, yes. The cost you take on is operational: provisioning, updates, and scaling. Tools with a smaller footprint (one binary, fewer services) lower that cost.

Which self-hosted analytics is easiest to run?

For web analytics, Umami is among the simplest (Node + a single database). For product analytics, Pug keeps things lean by running the API and every worker as one Go binary, backed by Postgres, ClickHouse, and NATS, fewer moving parts than a multi-service platform.

Self-host product analytics, the lean way.

Pug runs as a single Go binary and is free forever under AGPL-3.0. Its cloud is free up to 100k events a month.

Questions? Email hello@pug.sh