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What is JupyterHub?

JupyterHub is a powerful tool that enables the creation of a multi-user environment, allowing for the spawning, management, and proxying of multiple instances of Jupyter notebook servers. Created by Project Jupyter, it is specifically tailored to support numerous users at once. This platform serves a wide array of functions, making it suitable for educational settings, corporate data science teams, collaborative scientific research endeavors, or groups that utilize high-performance computing resources. However, it's essential to highlight that JupyterHub does not officially support Windows operating systems. While some users may attempt to run JupyterHub on Windows using compatible Spawners and Authenticators, the default settings are not optimized for such an environment. Additionally, any issues encountered on Windows will not receive support, and the testing framework is not designed to work on Windows platforms. Minor patches that could potentially address basic compatibility issues on Windows are infrequent and not guaranteed. Consequently, for those using Windows, it is recommended to operate JupyterHub within a Docker container or a Linux virtual machine, as this ensures better performance and compatibility. This strategy not only improves functionality but also streamlines the installation process, making it easier for Windows users to access the benefits of JupyterHub. Ultimately, adopting this method can lead to a more seamless user experience.

What is Apache Zeppelin?

An online notebook tailored for collaborative document creation and interactive data exploration accommodates multiple programming languages like SQL and Scala. It provides an experience akin to Jupyter Notebook through the IPython interpreter. The latest update brings features such as dynamic forms for note-taking, a tool for comparing revisions, and allows for the execution of paragraphs sequentially instead of the previous all-at-once approach. Furthermore, the interpreter lifecycle manager effectively terminates the interpreter process after a designated time of inactivity, thus optimizing resource usage when not in demand. These advancements are designed to boost user productivity and enhance resource management in projects centered around data analysis. With these improvements, users can focus more on their tasks while the system manages its performance intelligently.

Media

Media

Integrations Supported

Timbr.ai
Alluxio
Apache Flink
Apache Geode
Apache Hive
Apache Ignite
Cleanlab
DataOps.live
Elasticsearch
Hadoop
Java
JavaScript
JupyterLab
Kite
OctoData
OpenHexa
QueryPie
Train in Data
Yandex Data Proc

Integrations Supported

Timbr.ai
Alluxio
Apache Flink
Apache Geode
Apache Hive
Apache Ignite
Cleanlab
DataOps.live
Elasticsearch
Hadoop
Java
JavaScript
JupyterLab
Kite
OctoData
OpenHexa
QueryPie
Train in Data
Yandex Data Proc

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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

JupyterHub

Date Founded

2014

Company Website

github.com/jupyterhub/jupyterhub

Company Facts

Organization Name

Apache

Date Founded

1999

Company Location

United. States

Company Website

zeppelin.apache.org

Categories and Features

Categories and Features

IDE

Code Completion
Compiler
Cross Platform Support
Debugger
Drag and Drop UI
Integrations and Plugins
Multi Language Support
Project Management
Text Editor / Code Editor

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