Cube Semantic Layer

Define metrics once and serve them everywhere with Cube. Models cubes, dimensions, measures, and joins, exposes a headless semantic layer over REST, GraphQL, and SQL, and tunes pre-aggregations, caching, and multi-tenant security.

This skill builds a headless semantic layer with Cube: modeling cubes, dimensions, measures, segments, and joins in the data model, exposing consistent metrics over the REST, GraphQL, and SQL APIs, defining pre-aggregations and rollups for sub-second queries, and configuring caching and multi-tenant row-level security so every tool computes the same numbers.

When to use

Use when modeling a Cube semantic layer, defining measures and dimensions, adding pre-aggregations, or exposing consistent metrics to BI tools over REST, GraphQL, or SQL.

Examples

Model a revenue cube

Measures and dimensions

Model a Cube data model for orders with revenue and order-count measures and dimensions for date, plan, and region

Add pre-aggregations

Speed up dashboards

Add Cube pre-aggregations so our daily revenue rollup returns in under a second instead of scanning raw orders

Expose metrics over SQL

Headless BI API

Expose our Cube metrics through the SQL API so a BI tool can query the semantic layer directly