Thanks! That’s a great combo — manifold-sql + duckdb gives you strong typing with powerful SQL under the hood. Fahmatrix is aiming to complement that approach for cases where you want quick, native Java code without SQL — e.g., when building data flows or custom logic inline. Would love to hear if you’ve hit any pain points that a Java-native approach could help with.

Totally agree that SQL can be the best tool for many jobs. My goal with Fahmatrix is to serve the opposite niche: where devs want something that's Java-native, procedural, and simple without reaching for an external engine. SQL support or DSL might come later though — I see the appeal.

Sure. So maybe notehr comment would be to make it (particularly the Series class), as compatible with Java Streams as possible.

Next step would likely be compatibility with popular libraries such as Apache Commons Math: https://commons.apache.org/proper/commons-math/userguide/sta...

Good question. I’ll publish benchmarks soon, but the core difference is that Fahmatrix is fully Java, no JNI, and minimalistic — ideal for small projects or environments like Android. Tablesaw and Arrow are more powerful, but heavier. Fahmatrix aims to be the “just enough” middle ground.

Thanks so much! Yep, I’ve seen the Kotlin DataFrame lib — very elegant. Fahmatrix is meant for plain Java users who want similar capabilities without switching ecosystems. Appreciate the support!

Thanks! I'm aware of those great projects. Fahmatrix aims to offer a lightweight, dependency-free alternative that’s easy to embed in any Java app. DuckDB is super impressive, especially for SQL-heavy tasks — but my goal is more about a native, fluent API for those who prefer direct Java code over SQL.