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What is Rocket Open AppDev for Z?

Rocket Open AppDev for Z empowers businesses to enhance their mainframe DevOps by leveraging secure open-source software, allowing for quicker application launches, cost savings, and reduced risk. This solution goes beyond simply offering a set of open-source ports for z/OS; it incorporates years of committed investment in automation frameworks, various packaging and delivery methods, and an experienced support team. It successfully combines the stringent security requirements of mainframe users with an intuitive interface for both developers and system administrators. Supported by leading banks, insurance companies, and government entities, Open AppDev for Z provides a suite of open-source programming languages and tools specifically designed for z/OS, all while meticulously scanning for security vulnerabilities and ensuring compliance with licensing standards. Regular updates are aligned with the NIST National Vulnerability Database, with open-source ports managed through multiple avenues, including both public and private conda channels, on-premises conda file channels, or SMP/E. This comprehensive strategy not only fosters innovation but also guarantees adherence to security protocols and compliance throughout the development lifecycle, ensuring that organizations can navigate the complexities of modern software development with confidence. As a result, companies can focus on delivering high-quality applications while mitigating the potential risks associated with software development.

What is Hopsworks?

Hopsworks is an all-encompassing open-source platform that streamlines the development and management of scalable Machine Learning (ML) pipelines, and it includes the first-ever Feature Store specifically designed for ML. Users can seamlessly move from data analysis and model development in Python, using tools like Jupyter notebooks and conda, to executing fully functional, production-grade ML pipelines without having to understand the complexities of managing a Kubernetes cluster. The platform supports data ingestion from diverse sources, whether they are located in the cloud, on-premises, within IoT networks, or are part of your Industry 4.0 projects. You can choose to deploy Hopsworks on your own infrastructure or through your preferred cloud service provider, ensuring a uniform user experience whether in the cloud or in a highly secure air-gapped environment. Additionally, Hopsworks offers the ability to set up personalized alerts for various events that occur during the ingestion process, which helps to optimize your workflow. This functionality makes Hopsworks an excellent option for teams aiming to enhance their ML operations while retaining oversight of their data environments, ultimately contributing to more efficient and effective machine learning practices. Furthermore, the platform's user-friendly interface and extensive customization options allow teams to tailor their ML strategies to meet specific needs and objectives.

Media

Media

Integrations Supported

Bash
Git
IBM Z
IBM z/OS
OpenSSL
PHP
Perl
Python
Sudo

Integrations Supported

Amazon EC2
Amazon Web Services (AWS)
IBM watsonx.data
Onehouse

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

$1 per month
Free Version
Free Trial Offered?

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Rocket Software

Date Founded

1990

Company Location

United States

Company Website

www.rocketsoftware.com/en-us/products/open-source/appdev-z

Company Facts

Organization Name

Logical Clocks

Date Founded

2016

Company Location

Sweden

Company Website

www.logicalclocks.com/hopsworks

Categories and Features

Categories and Features

Artificial Intelligence

For Healthcare
For eCommerce
Predictive Analytics
Process/Workflow Automation

Big Data

Collaboration
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
Templates

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Regression Analysis

Data Management

Customer Data
Data Analysis
Data Integration
Data Migration
Data Quality Control
Data Security
Master Data Management

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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