head to head · open source

Cube vs metorikku

Cube has 20,860 GitHub stars, 2,140 forks, 1,185 open issues and last shipped today. metorikku has 589 stars, 156 forks, 65 open issues and last shipped 17 days ago. Cube leads on adoption by 3,442% (20,860 vs 589 stars). Cube is written in Rust under a custom or non-standard licence; metorikku is written in Scala under MIT. Cube has attracted 10% as many forks as stars, metorikku 26%. Cube was the more recently maintained of the two, and both are self-hostable with no licence fee.

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 metorikku ★ 589 category Data & Analytics

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Side by side

Cube metorikku
GitHub stars ★ 21K ★ 589
License Custom / other MIT
Written in Rust Scala
Last push 2026-09-18 2026-09-01
Forks ⑂ 2.1K ⑂ 156
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 metorikku if

  • You want the metorikku feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches Scala
  • You evaluated both and metorikku fits your workflow better

full metorikku 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 metorikku

Metorikku is a library that simplifies writing and executing ETLs on top of Apache Spark. It is based on simple YAML configuration files and runs on any Spark cluster. The platform also includes a simple way to write unit and E2E tests. Getting started To run Metorikku you must first define 2 files. Metric file A metric file defines the steps and queries of the ETL as well as where and what to output. For example a simple configuration YAML (JSON is also supported) should be as follows: yaml metric: "/path/to/metric" mocks: name: table 1 path: mocks/table 1.jsonl tests: df2: id: 200 name: test id: 300 name: test2…

read the full metorikku overview →

More in Data & Analytics

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

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More Data Engineering & Integration projects

Compare either of these against the rest of the Data Engineering & Integration field.

Cube vs Airbyte Cube vs shardingsphere Cube vs debezium Cube vs CocoIndex Cube vs seatunnel Cube vs steampipe Cube vs realtime Cube vs CloudQuery Cube vs flink-cdc Cube vs Lightdash Cube vs fluvio Cube vs whodb

Frequently asked questions

Is Cube or metorikku more popular?

Cube has 20,860 GitHub stars and metorikku has 589. Cube has the larger community by that measure.

Are Cube and metorikku free?

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

What is the difference between Cube and metorikku?

Cube is written in Rust and metorikku in Scala. 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 metorikku?

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