Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Retool Reviews & Ratings
    577 Ratings
    Company Website
  • Devin Desktop Reviews & Ratings
    171 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    26 Ratings
    Company Website
  • JetBrains Junie Reviews & Ratings
    12 Ratings
    Company Website
  • DbVisualizer Reviews & Ratings
    572 Ratings
    Company Website
  • Teradata VantageCloud Reviews & Ratings
    1,120 Ratings
    Company Website
  • Google Cloud BigQuery Reviews & Ratings
    2,016 Ratings
    Company Website
  • SciSure Reviews & Ratings
    298 Ratings
    Company Website
  • Source Defense Reviews & Ratings
    7 Ratings
    Company Website
  • Parasoft Reviews & Ratings
    147 Ratings
    Company Website

What is JupyterLab?

Project Jupyter is focused on developing open-source tools, standards, and services that enhance interactive computing across a variety of programming languages. Central to this effort is JupyterLab, an innovative web-based interactive development environment tailored for Jupyter notebooks, programming, and data handling. JupyterLab provides exceptional flexibility, enabling users to tailor and arrange the interface according to different workflows in areas such as data science, scientific inquiry, and machine learning. Its design is both extensible and modular, allowing developers to build plugins that can add new functionalities while working harmoniously with existing features. The Jupyter Notebook is another key component, functioning as an open-source web application that allows users to create and disseminate documents containing live code, mathematical formulas, visualizations, and explanatory text. Jupyter finds widespread use in various applications, including data cleaning and transformation, numerical simulations, statistical analysis, data visualization, and machine learning, among others. Moreover, with support for over 40 programming languages—such as popular options like Python, R, Julia, and Scala—Jupyter remains an essential tool for researchers and developers, promoting collaborative and innovative solutions to complex computing problems. Additionally, its community-driven approach ensures that users continuously contribute to its evolution and improvement, further solidifying its role in advancing interactive computing.

What is Code Ocean?

The Code Ocean Computational Workbench significantly improves usability, coding, data tool integration, and DevOps lifecycle processes by effectively closing technology gaps with an intuitive, ready-to-use interface. Users have immediate access to essential tools such as RStudio, Jupyter, Shiny, Terminal, and Git, while also having the flexibility to choose from a range of widely-used programming languages. This platform accommodates various data sizes and storage types, allowing users to configure and easily generate Docker environments. Additionally, it facilitates one-click access to AWS compute resources, greatly enhancing workflow efficiency. Through the app panel, researchers can seamlessly share their findings by creating and publishing user-friendly web analysis applications for collaborative teams of scientists, all without requiring IT support, programming skills, or command-line expertise. The platform enables the development and deployment of interactive analyses that run effortlessly in standard web browsers. Collaboration is streamlined, and the management of resources is simplified, allowing for easy reuse. By offering an organized application and repository, researchers can efficiently manage, publish, and protect project-based Compute Capsules, data assets, and their findings, fostering a more collaborative and productive research environment. The Code Ocean Computational Workbench’s adaptability and user-friendly nature make it an essential resource for scientists aiming to expand their research capabilities, ultimately paving the way for innovative discoveries. With its powerful features and ease of use, this tool not only enhances research productivity but also encourages interdisciplinary collaboration among researchers.

Media

Media

Integrations Supported

Docker
Jupyter Notebook
Amazon EC2
Arize Phoenix
Baidu AI Cloud Machine Learning (BML)
Fosfor Decision Cloud
Git
Google Cloud Deep Learning VM Image
HTML
JSON
Java
Julia
Kubernetes
Octave
Pieces
Python
R
Scheme
Thunder Compute
esDynamic

Integrations Supported

Docker
Jupyter Notebook
Amazon EC2
Arize Phoenix
Baidu AI Cloud Machine Learning (BML)
Fosfor Decision Cloud
Git
Google Cloud Deep Learning VM Image
HTML
JSON
Java
Julia
Kubernetes
Octave
Pieces
Python
R
Scheme
Thunder Compute
esDynamic

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

Jupyter

Date Founded

2014

Company Website

jupyter.org

Company Facts

Organization Name

Code Ocean

Company Location

United States

Company Website

codeocean.com/product/

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

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Popular Alternatives

Popular Alternatives

R Markdown Reviews & Ratings

R Markdown

RStudio PBC
Jupyter Notebook Reviews & Ratings

Jupyter Notebook

Project Jupyter