Analytics and monitoring decision
Microsoft Power BI
Build a narrow, self-hosted dashboard and sharing workflow (using Superset/Metabase ideas) if you only need core reporting and control; keep paying for Power BI if you require Fabric integrations, Copilot AI, large premium capacity, vendor SLAs, or Microsoft-managed governance.
Visit website↗$14/mo
$168/yr
Not verified against a pricing page.
$50one-off30 h to build
$150/mo20 h/mo upkeep
On cash alone, building overtakes the subscription at 12 seats.
The code exists. It is not what you are paying for.
This project is real, published, and does the core job — and this page still says keep paying. What the subscription buys is integration maintenance, proprietary models and infrastructure at scale, and none of that ships in a repository. Fork it anyway if you want to. Go in knowing what it does not carry. What stays hard ↓ · All Microsoft Power BI alternatives, with the arithmetic →
What a replacement has to do
- Ingest data → model/transform → build interactive report/dashboard → publish/share with teams → schedule refreshes.
What it still won’t have
- Deep Microsoft Fabric integration (Copilot, OneLake, Fabric features)
- Proprietary AI features (Copilot in Power BI) and Microsoft-managed semantic engine optimizations
- Scale and reserved premium capacity (large-model memory and enterprise SLAs)
- Official Microsoft licensing, support, and governance controls
What remains hard
- Integration maintenance
- Proprietary models
- Infrastructure at scale
- Brand trust
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 12 seats.
Money you would actually spend
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
Build a minimal self-hosted BI dashboard service using PostgreSQL + DuckDB + React + FastAPI + Redis. Core features in scope: (1) connectors for PostgreSQL and CSV upload, (2) a lightweight semantic layer implemented with DuckDB-based materialized models and a simple expression/calculation layer, (3) a React single-page app for authoring and viewing interactive charts (charting via Apache ECharts), (4) REST APIs for publishing/embedding reports and role-based access control using OAuth/OIDC, and (5) scheduled refresh worker using Redis + rq and health/refresh logs. Out of scope: full DAX compatibility, Microsoft Fabric/Copilot AI, enterprise reserved capacity, and every connector. Include error handling, authentication failures, and tests (unit tests for API and integration test for end-to-end ingestion→dashboard). Deploy with Docker Compose (dev) and Kubernetes manifests (prod).
How we checked
How the score was reached
- Pay verdict base20
- An open-source build was found+5
- 4 cited sources+3
- Hard moats found in the evidence-6
- Evidence score22
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.
- official docsWhat is Power BI? Overview of Components and Benefits - Microsoft Learn
- official productPower Platform / Power BI product page - Microsoft
- official docsPower BI REST API - Microsoft Learn
- open sourceApache Superset GitHub repository
Integrity checks
What held up, and what did not.
