Gaur and traditional BI.
Tableau, Looker and Power BI are dashboarding apps. We're the governed backend underneath. The honest comparison is when each one matters, and how they sit together.
Different layers, different jobs.
Dashboards and visual exploration.
Tableau, Looker and Power BI let analysts build visual dashboards and explore data interactively. They connect to a source (a warehouse, an extract, or both) and render charts on top of it. Their primary audience is the person looking at the screen.
The serving layer underneath.
We ingest from your sources into our own engine, let your team publish contracts (named, governed interfaces) and serve them to every consumer through one endpoint family. Our primary audience is the system asking the question.
We're not a Tableau replacement. We're a backend.
You can keep Tableau, Looker or Power BI, and put them on top of one of our contracts. The dashboard reads from the same governed definition your app and your AI agent read from. We replace the ad-hoc SQL and the per-tool semantic layers that sit between your warehouse and your BI tool, not the BI tool itself.
The honest table.
Empty cells are honest. They mean the tool isn't built for that job.
Coming from Tableau or Looker: keep them. Point them at a Gaur contract instead of raw warehouse tables, and the same definition serves your apps and agents too.
Tighter peers, sharper contrasts.
vs Metabase
Metabase is a BI app with a built-in semantic layer. Where it overlaps with Gaur, and where it doesn't.
vs Cube
Both are semantic layers. The split is ingest-and-serve vs push-down on your warehouse.
vs dbt Semantic Layer
dbt SL is tied to dbt models on the warehouse. Gaur is decoupled and ingests.
You run your business.
We run your analytics.
Hop on a 30-minute call. We'll connect a sandbox to your warehouse and show you Gaur on your numbers.
