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Description
Helidon is an open-source suite of Java libraries tailored for developing microservices, utilizing a high-performance web core that is driven by Netty. The introduction of Helidon Níma marks the first Java microservices framework that leverages virtual threads to enhance performance. With a focus on user-friendliness, Helidon offers comprehensive tooling and a variety of examples to facilitate a swift onboarding process. Since it is essentially a collection of Java libraries operating on a rapid Netty core, Helidon avoids unnecessary overhead or bloat. It fully supports MicroProfile and includes well-known APIs such as JAX-RS, CDI, and JSON-P/B. The Helidon Reactive WebServer serves as the backbone for our implementation, boasting a contemporary functional programming model that sits atop Netty. This lightweight, adaptable, and reactive web server provides an efficient and straightforward base for your microservices. In addition, Helidon comes equipped with essential features like health checks, metrics, tracing, and fault tolerance, ensuring you have all the necessary tools to build cloud-ready applications that seamlessly integrate with systems like Prometheus and Jaeger/Zipkin. Overall, Helidon's capabilities and performance make it an ideal choice for developers looking to create efficient and scalable cloud-native applications.
Description
Developing machine learning applications should be effortless and seamless. UnionML is an open-source framework in Python that enhances Flyte™, streamlining the intricate landscape of ML tools into a cohesive interface. You can integrate your favorite tools with a straightforward, standardized API, allowing you to reduce the amount of boilerplate code you write and concentrate on what truly matters: the data and the models that derive insights from it. This framework facilitates the integration of a diverse array of tools and frameworks into a unified protocol for machine learning. By employing industry-standard techniques, you can create endpoints for data retrieval, model training, prediction serving, and more—all within a single comprehensive ML stack. As a result, data scientists, ML engineers, and MLOps professionals can collaborate effectively using UnionML apps, establishing a definitive reference point for understanding the behavior of your machine learning system. This collaborative approach fosters innovation and streamlines communication among team members, ultimately enhancing the overall efficiency and effectiveness of ML projects.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Docker
Google Cloud Platform
GraphQL
IntelliJ IDEA
JCov
JSON
Java
Kubernetes
Microsoft Azure
Integrations
Amazon Web Services (AWS)
Docker
Google Cloud Platform
GraphQL
IntelliJ IDEA
JCov
JSON
Java
Kubernetes
Microsoft Azure
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Helidon
Country
United States
Website
helidon.io
Vendor Details
Company Name
Union
Founded
2021
Country
United States
Website
www.union.ai/unionml
Product Features
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization