Analytics and monitoring decision

BIG

With only a product name and no feature or pricing detail available, a technical user can realistically build a narrow analytics/dashboard replacement (basic SQL connectors, charts, auth) in about a week, but the full commercial product's integrations, polish, and hosting are not reproducible from the supplied page.

Visit website
You pay

Not priced

No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.

You’d pay instead

$100one-off38 h to build

$50/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 BIG alternatives, with the arithmetic →

What a replacement has to do

  • Query a data source, visualize results, save dashboards, and share links.

What it still won’t have

  • Commercial polish, design and onboarding flows provided by the vendor
  • Pre-built connectors beyond basic SQL databases
  • Hosted scaling, managed backups, and formal support SLA
  • Any proprietary datasets, integrations, or platform-level features the vendor may provide

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

BIG 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

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 small self-hosted analytics dashboard app using React for the frontend, Node.js/Express for the backend, and Postgres for metadata and user storage. Core features: (1) connect to one external SQL data source (Postgres/MySQL) and run parameterized SQL queries, (2) create and save simple visualizations (line, bar, table) mapped to query results, (3) persist dashboards and visualizations in Postgres, (4) email/password user authentication and read-only shareable dashboard links, (5) Dockerfiles for frontend/backend and a docker-compose deployment with an nginx reverse proxy and auto TLS via certbot. Out of scope: multi-tenant billing, dozens of connector types, advanced alerting, and commercial-grade analytics pipelines. Include input validation, error handling, and unit tests for backend query execution and auth flows.
How we checked3 sources · 3/3 runs agreed · evidence score 64

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 3 cited sources+3
  • 3/3 assessment runs agreed+4
  • Evidence score64

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.

Integrity checks

What held up, and what did not.

✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded