AMIDST Toolbox
A Java Toolbox for Scalable Probabilistic Machine Learning
- Status
- UnmaintainedNo commits in 2091 days.
- Last checked
- Checked · Oct 5, 2026
- License
- Open source
- Pricing
- Free tier
What it is
AMIDST Toolbox is an open-source Java library designed for scalable probabilistic machine learning. It focuses on Bayesian methods, providing tools for Bayesian networks and latent variable models. The toolbox is particularly suited for handling streaming data, making it a valuable resource for real-time data analysis. Despite its last update in 2020, it remains a relevant tool for specific machine learning tasks, especially those involving graphical models.
Focus on scalable Bayesian methods for streaming data.
When it fits — and when it doesn’t
A good fit for
Developers working with Bayesian networks
The toolbox provides specialized tools for Bayesian methods.
Projects requiring real-time data analysis
Its capability to handle streaming data is beneficial for such tasks.
Look elsewhere if
Teams needing frequent updates and support
The project has not been updated since 2020.
Developers using languages other than Java
The toolbox is Java-specific, limiting cross-language integration.
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Last updated in 2020
GitHub last commit date
- 02
High number of open issues
47 open issues on GitHub
- 03
Limited to Java
Primary language is Java
What it does well
Supports Bayesian networks
Listed under GitHub topics
Handles streaming data
Mentioned in GitHub topics
Open-source under Apache-2.0 license
GitHub license information
Pricing
- Free tier
- Yes
- Paid from
- —
- Model
- N/A
- Enterprise plan
- No
Pricing last confirmed Sep 27, 2026.
Performance benchmarks
How Fast Is It?
Set up AMIDST Toolbox
Setup steps, common gotchas and what to check after 30 days.