head to head · open source

Cube vs sycamore

Cube has 20,860 GitHub stars, 2,140 forks, 1,185 open issues and last shipped today. sycamore has 608 stars, 72 forks, 57 open issues and last shipped 2 months ago. Cube leads on adoption by 3,331% (20,860 vs 608 stars). Cube is written in Rust under a custom or non-standard licence; sycamore is written in Python under Apache-2.0. Cube has attracted 10% as many forks as stars, sycamore 12%. Cube was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

Cube ★ 21K sycamore ★ 608 category Data & Analytics

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Side by side

Cube sycamore
GitHub stars ★ 21K ★ 608
License Custom / other Apache-2.0
Written in Rust Python
Last push 2026-09-18 2026-08-01
Forks ⑂ 2.1K ⑂ 72
Self-hosting Yes Yes
Data ownership Your server Your server

pick Cube if

  • You weight community size — 21K stars and counting
  • You want the Custom / other license terms
  • Your stack matches Rust
  • You value the larger contributor base for long-term maintenance

full Cube profile →

pick sycamore if

  • You want the sycamore feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches Python
  • You evaluated both and sycamore fits your workflow better

full sycamore profile →

About Cube

Cube Core is an open source semantic layer for AI, BI, and embedded analytics. It lives in the data analytics and data engineering ecosystem for SQL warehouses, BI tools, applications, and AI agents. It lets teams define metrics, dimensions, joins, and access rules once in code, then expose them through SQL, REST, and GraphQL APIs. It is headless and ships no user interface.

read the full Cube overview →

About sycamore

Sycamore is an open source, AI powered document processing engine for ETL, RAG, LLM based applications, and analytics on unstructured data. Sycamore can partition and enrich a wide range of document types including reports, presentations, transcripts, manuals, and more. It can analyze and chunk complex documents such as PDFs and images with embedded tables, figures, graphs, and other infographics. Check out an example notebook. For processing documents, Sycamore leverages Aryn DocParse (formerly known as the Aryn Partitioning Service), a serverless, GPU powered API for segmenting and labeling documents, doing OCR…

read the full sycamore overview →

More in Data & Analytics

Mermaid ★ 90K Crawl4AI ★ 84K Scrapling ★ 82K Apache Superset ★ 75K echarts ★ 67K scrapy ★ 64K

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Frequently asked questions

Is Cube or sycamore more popular?

Cube has 20,860 GitHub stars and sycamore has 608. Cube has the larger community by that measure.

Are Cube and sycamore free?

Both are open source. Cube has no licence declared in this registry, and sycamore is licensed under Apache-2.0. Both are free to self-host.

What is the difference between Cube and sycamore?

Cube is written in Rust and sycamore in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, Cube or sycamore?

Choose Cube if you want the larger community (20,860 stars) or its Custom / other licence terms. Choose sycamore if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.