NDScala
N-dimensional arrays in Scala with compile-time type-checking and inference.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is NDScala?
NDScala provides N-dimensional arrays for Scala 3, offering compile-time type-checking and inference over shapes, tensor/axis labels, and numeric data types. It is inspired by NumPy ndarray but tailored for the Scala ecosystem.
Key differentiator
“NDScala stands out by offering compile-time safety and efficiency for N-dimensional arrays in Scala, making it ideal for projects that require strict type-checking over shapes, labels, and numeric types.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
Being a niche library for Scala, the user base is relatively small compared to more established libraries like NumPy or TensorFlow.
Integrating NDScala into existing projects requires careful configuration of Scala 3 and potential dependency conflicts with other libraries.
While optimized, NDScala may not match the performance of native C/Fortran implementations used in libraries like NumPy due to JVM overhead.
The project's documentation lacks comprehensive guides and practical examples, making it harder for new users to get started quickly.
Fit analysis
Who is it for?
✓ Best for
Scala developers who need compile-time safety and efficiency for N-dimensional arrays.
Projects that require strict type-checking over shapes, labels, and numeric types in array operations.
✕ Not a fit for
Developers looking for a JavaScript-based solution.
Teams requiring real-time streaming capabilities.
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Works well with
Next step
Get Started with NDScala
Step-by-step setup guide with code examples and common gotchas.