Analytics and monitoring decision

Vemetric

Self-hosting is realistic because Vemetric's AGPL-3.0 repository is available; a technical user should self-host rather than reimplement the product to avoid recreating core functionality.

Visit website
You pay

$5/mo

$60/yr

Read off the official pricing page.

You’d pay instead

$20one-off6 h to build

$0/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 1 seat.

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Vemetric alternatives, with the arithmetic →

What a replacement has to do

  • 1) Receive events from a JS/HTTP SDK endpoint and validate payloads; 2) Persist events and user/profile records in Postgres (and short-term cache in Redis); 3) Sessionize events into sessions and user journeys (batch or streaming job); 4) Build query endpoints that aggregate events into funnels, top pages, referrers and event streams; 5) Minimal web UI to display dashboard, funnels, event streams and user detail pages (React + API).

What it still won’t have

  • Hosted infrastructure, uptime SLA and backups managed by vendor
  • Vendor support, onboarding, and product roadmap/feature updates
  • Automatic upgrades and hosted analytics optimizations

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 1 seat.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a self-hosted Vemetric deployment using Docker Compose (or Kubernetes) with Postgres (primary event store), Redis (cache/sessionization), a Node.js or Go ingestion API, and a React frontend. Core features in scope: ingest Pageviews and Custom Events via a JS snippet and HTTP API; durable event storage in Postgres; a background sessionization and aggregation job; API endpoints for dashboards, funnels, top pages, referrers, event streams and individual user timelines; minimal RBAC for one org and project; TLS via Let's Encrypt and reverse proxy (Nginx). Out of scope: multi-tenant billing, advanced long-term cold storage, and premium managed-hosting. Include error handling, input validation, DB migrations, basic tests (unit for ingestion and integration test for end-to-end event→dashboard flow), and deployment/run instructions.
How we checked4 sources · 2/2 runs agreed · evidence score 99

How the score was reached

  • Self-host verdict base92
  • An open-source build was found+5
  • 4 cited sources+3
  • Price verified on pricing page+3
  • 2/2 assessment runs agreed+4
  • Evidence score99

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 4

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 2 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded