LDA.js
Node.js library for Latent Dirichlet Allocation topic modeling
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is LDA.js?
LDA.js is a Node.js implementation of Latent Dirichlet Allocation, enabling developers to perform topic modeling on text data directly within their JavaScript applications.
Key differentiator
“LDA.js stands out as the only Node.js library providing an efficient and customizable implementation of Latent Dirichlet Allocation, making it ideal for integrating topic modeling directly into JavaScript applications.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
The official repository lacks comprehensive guides or tutorials for new users, making it difficult to understand how to configure and use the tool effectively.
LDA.js can struggle with memory management when processing extensive text corpora, leading to slower execution times or even crashes in extreme cases.
While LDA.js provides basic topic modeling functionality, it lacks advanced features and optimizations available in more mature libraries like Gensim or scikit-learn for Python.
Fit analysis
Who is it for?
✓ Best for
Developers building text analysis tools who need a Node.js-based LDA implementation
Projects requiring efficient and customizable topic modeling within JavaScript applications
✕ Not a fit for
Applications that require real-time streaming processing of text data
Teams looking for a cloud-hosted service with managed infrastructure
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
Works well with
Integrations
Next step
Get Started with LDA.js
Step-by-step setup guide with code examples and common gotchas.