cube: what it is, what problem it solves & why it's gaining traction

What it solves

Cube Core provides a standalone, open-source semantic layer that eliminates the need to redefine business logic (metrics, dimensions, and joins) across multiple BI tools or AI agents. It prevents the fragmentation of data definitions by allowing users to define their logic once in code and reuse it across any downstream application.

How it works

Cube Core acts as a headless middle layer between your data sources and your consumption layer. It connects to SQL data sources (such as Snowflake, BigQuery, Databricks, Postgres, and Amazon Athena) and exposes the defined semantic model via SQL, REST, and GraphQL APIs. To ensure high performance, it includes a built-in relational caching engine to provide sub-second latency for API requests.

Who it’s for

Developers building custom BI experiences, teams implementing deeply integrated embedded analytics, and developers of AI agents that require a governed, consistent semantic foundation for data analysis.

Highlights

• Headless Architecture: No built-in UI, allowing for complete control over the analytics experience.
• Multi-Source Support: Works with all SQL data sources, including cloud warehouses and application databases.
• Multi-API Access: Exposes data through SQL, REST, and GraphQL APIs.
• Caching Engine: Built-in relational caching for high concurrency and low latency.