Analytics and monitoring decision
DataRadar
A trimmed web-first real-time visitor radar is realistic for one capable developer to build and operate in ~40 hours with modest monthly upkeep; prior open-source analytics projects can be adapted instead of building from scratch.
Visit website↗Built by Marc Lou, who ships 32 products in this index
Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off40 h to build
$30/mo3 h/mo upkeep
No published price to break even against.
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 DataRadar alternatives, with the arithmetic →
What a replacement has to do
- Collect pageview events from a small client script, persist them, and stream them in real time to a dashboard that visualizes visitor locations on a map.
What it still won’t have
- Polished native macOS app download and packaging
- Hosted service convenience, uptime SLAs and attended support
- Any proprietary telemetry, demo data, or branding from the vendor
- Analytics integrations or advanced retention/aggregation features
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
DataRadar does not publish a price we could read, so there is nothing to compare against. What building costs is below.
Money you would actually spend
Time you would spend
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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
Build a self-hosted real-time visitor radar using Node.js (Express), a Postgres DB, a Redis pub/sub for real-time events, and a React + Mapbox GL frontend. Core features in scope: (1) small tracking JS snippet that POSTs pageview events (url, referrer, geo IP lookup on server), (2) an authenticated ingest API that validates and writes events to Postgres and publishes to Redis, (3) a WebSocket/SSE service that subscribes to Redis and streams recent events to connected clients, (4) a React dashboard that shows a world map with a sweeping scanner effect and live pins for visitors and a side list of recent sessions, (5) Docker Compose deployment, TLS via Let's Encrypt, and simple health checks. Out of scope: native macOS app, long-term analytics aggregation/retention policies, enterprise SSO, and multi-tenant billing. Include error handling, input validation, and unit tests for the ingest and broadcast layers.
How we checked
How the score was reached
- Build verdict base78
- An open-source build was found+5
- 3 cited sources+3
- Evidence score86
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 · 3
Every page the run actually retrieved.
- official productDATARADAR — real-time visitor radar
- open sourceumami-software/umami
- open sourcePostHog/posthog
Integrity checks
What held up, and what did not.
