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What is Nitric?

Nitric is an adaptable, open-source backend framework designed to function across multiple cloud environments, enabling developers to efficiently articulate their infrastructure using code while optimizing deployment workflows with a range of customizable plugins. It supports numerous programming languages, including JavaScript, TypeScript, Python, Go, and Dart. Key features include the creation of APIs (encompassing REST and HTTP), serverless functions, routing, and the management of authentication and authorization through OIDC. Moreover, it caters to various storage options such as object and file storage, signed URLs, and bucket events, alongside database capabilities like managed Postgres with migration support. The framework also incorporates messaging functionalities, including queues, topics, and pub/sub systems, while offering support for websockets, scheduled tasks, and secure handling of sensitive data. Nitric can integrate smoothly with infrastructure management solutions like Terraform and Pulumi, or you can create custom plugins tailored to your needs; it is compatible with major cloud providers such as AWS, Azure, and Google Cloud. In addition, it features a local development setup that mimics cloud environments, allowing developers to prototype, test, and enhance their applications without incurring cloud costs. The framework prioritizes declarative security and efficient resource management, ensuring smooth portability between different environments, which positions it as a robust option for contemporary application development, especially in a rapidly evolving technological landscape.

What is Horovod?

Horovod, initially developed by Uber, is designed to make distributed deep learning more straightforward and faster, transforming model training times from several days or even weeks into just hours or sometimes minutes. With Horovod, users can easily enhance their existing training scripts to utilize the capabilities of numerous GPUs by writing only a few lines of Python code. The tool provides deployment flexibility, as it can be installed on local servers or efficiently run in various cloud platforms like AWS, Azure, and Databricks. Furthermore, it integrates well with Apache Spark, enabling a unified approach to data processing and model training in a single, efficient pipeline. Once implemented, Horovod's infrastructure accommodates model training across a variety of frameworks, making transitions between TensorFlow, PyTorch, MXNet, and emerging technologies seamless. This versatility empowers users to adapt to the swift developments in machine learning, ensuring they are not confined to a single technology. As new frameworks continue to emerge, Horovod's design allows for ongoing compatibility, promoting sustained innovation and efficiency in deep learning projects.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Microsoft Azure
Python
AWS Lambda
Azure Databricks
Dart
Docker
GitLab
Go
Google Cloud Platform
JavaScript
Keras
OpenAI
PostgreSQL
Pulumi
PyTorch
React
TensorFlow
Terraform

Integrations Supported

Amazon Web Services (AWS)
Microsoft Azure
Python
AWS Lambda
Azure Databricks
Dart
Docker
GitLab
Go
Google Cloud Platform
JavaScript
Keras
OpenAI
PostgreSQL
Pulumi
PyTorch
React
TensorFlow
Terraform

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Nitric

Company Location

United States

Company Website

nitric.io

Company Facts

Organization Name

Horovod

Company Website

horovod.ai/

Categories and Features

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

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