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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 JetBrains Datalore?

Datalore serves as a collaborative data science and analytics platform designed to enhance the analytics workflow, making data interaction more enjoyable for both data scientists and business teams with analytical skills. This platform prioritizes the efficiency of data teams, enabling technically skilled business users to engage with data teams through no-code and low-code solutions alongside the robust capabilities of Jupyter Notebooks. With Datalore, business users can enjoy analytic self-service by utilizing SQL or no-code cells, generating reports, and exploring data in depth. This functionality also allows core data teams to concentrate on more complex tasks, thus streamlining their workflow. Moreover, Datalore facilitates seamless collaboration between data scientists and analysts, enabling them to share their findings with ML Engineers. Users can effortlessly share their code with ML Engineers who have access to powerful CPUs and GPUs, all while collaborating in real time with colleagues for improved productivity and creativity. Ultimately, Datalore seeks to bridge the gap between technical and non-technical users, fostering a truly collaborative environment in the data science field.

Media

Media

Integrations Supported

Amazon S3
Azure Marketplace
Cleanlab
Coiled
DataOps.live
EDB Postgres Advanced Server
Google Cloud Platform
Goose
JetBrains DataSpell
JetBrains Gateway
Kite
MySQL
PostgreSQL
Python
SQL
Scala
Supermaven
Timbr.ai
Vast.ai
Wizata

Integrations Supported

Amazon S3
Azure Marketplace
Cleanlab
Coiled
DataOps.live
EDB Postgres Advanced Server
Google Cloud Platform
Goose
JetBrains DataSpell
JetBrains Gateway
Kite
MySQL
PostgreSQL
Python
SQL
Scala
Supermaven
Timbr.ai
Vast.ai
Wizata

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$19.90 per month
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

JetBrains

Date Founded

2000

Company Location

Czech Republic

Company Website

www.jetbrains.com/datalore/

Categories and Features

Categories and Features

Code Collaboration

Audio Conferencing
Chat / Messaging
Code Review
Discussion Threads
IDE Integration
Remote Control
Remote Pair Programming
Screen Sharing
Video Conferencing

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

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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Popular Alternatives

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