Cube
Universal semantic layer with AI agents for analytics.
About
Cube is a headless, universal semantic layer that sits between data warehouses and every consumer: BI tools, embedded apps, and AI agents. Teams define metrics once in code, and Cube serves them through SQL, REST, GraphQL, and MCP APIs with caching and access control.
In 2025 Cube launched D3, an agentic analytics platform with an AI Data Analyst for natural-language analytics and an AI Data Engineer that automates semantic model creation. Its thesis is that LLMs should query through the semantic layer, not around it, so every agent answer stays governed and metric-correct.
What it can do
- Universal semantic layer over SQL, REST, GraphQL, and MCP
- D3 AI Data Analyst for natural-language analytics
- AI Data Engineer for automated semantic modeling
- AI API and Cube Copilot for LLM integration
- Pre-aggregations and caching for fast queries
Setup
Install the open-source core via Docker or npm, or sign up for Cube Cloud.
Prerequisites
A SQL data source (warehouse, Postgres, ClickHouse, etc.) and a data model defined in YAML or JavaScript.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 129; Trending score 80/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.