
Stay Updated
Subscribe to our newsletter for the latest news and updates about Alternatives
Subscribe to our newsletter for the latest news and updates about Alternatives

Open source alternative to Looker, AtScale and Tableau Embedded Analytics
Cube is an open source semantic layer and headless BI platform that centralizes metric definitions and delivers consistent data to any BI tool, API, or AI model. Apache-2.0 licensed.

Cube provides governed metrics and cached APIs for product analytics features shown inside an application.
Skip if all analytics are internal and your BI tool already handles performance well.
Use Cube to keep revenue, usage, and operational metrics consistent across BI, notebooks, and application APIs.
Skip if your organization is not ready to maintain semantic models in code.
Models cubes, measures, dimensions, joins, and access rules in code so metrics can be reviewed and versioned.
Exposes REST, GraphQL, SQL, and client SDK paths for building dashboards and data apps on top of the same metric definitions.
Supports pre-aggregations and query acceleration so high-traffic embedded analytics do not hit the warehouse for every request.
Cube has an open source core and publishes its code on GitHub.
Cube is used as a semantic layer and API layer for analytics, especially embedded dashboards and customer-facing data apps.
Connect to any data source, query, visualize, and share
Turn any website into clean markdown or structured JSON for LLMs
Open source personalization and search ranking engine
Open source embeddings and rerankers for semantic search and RAG
Open source AI search engine that retrieves cited sources
AI-driven research automation for complex tasks
Analytics teams often define the same metric in dashboards, notebooks, warehouse SQL, and application code. Revenue, activation, and retention numbers drift because each tool has its own formulas, filters, and joins.
The pain grows when product teams embed analytics into customer-facing apps. Developers need fast APIs and caching, while data teams need metric definitions that stay consistent across tools.
Cube and Looker both help teams centralize metric definitions. Looker bundles modeling, exploration, dashboards, and governance into a proprietary BI platform; Cube focuses on an open semantic API layer that developers can embed in products.
Cube is better when analytics must appear inside your application or across multiple tools. Looker is still better when the organization wants a managed BI suite with mature analyst workflows and vendor support.
Looker is a proprietary BI platform with its own semantic modeling layer. Cube focuses on an open source, API-first semantic layer that can power many frontends.