Struggling to choose between Enthought and Anaconda? Both products offer unique advantages, making it a tough decision.
Enthought is a Ai Tools & Services solution with tags like python, data-science, analytics, deployment.
It boasts features such as Enthought Deployment Manager for deploying Python environments, Canopy Python distribution with scientific and analytic packages, Training and support services for Python and data science, Platform for building and deploying analytics web applications and pros including Eases Python environment management and deployment, Comes with many pre-installed scientific and data science packages, Good technical support available, Integrated web framework for building analytics apps.
On the other hand, Anaconda is a Ai Tools & Services product tagged with python, data-science, machine-learning, deep-learning, analytics.
Its standout features include Python and R distribution, Over 720 open source packages for data science, conda package and virtual environment manager, Spyder IDE for Python development, Jupyter notebook for interactive computing and data visualization, and it shines with pros like Simplifies Python and R package management, Good for managing data science environments, Bundled with commonly used data science packages, Good for beginners getting started with Python/R for data science.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
Enthought is a Python-centered software company that provides tools and solutions for scientific computing, data analytics, and machine learning. Their flagship product is the Enthought Deployment Manager, which allows deployment of Python environments across an organization.
Anaconda is an open source distribution of the Python and R programming languages for large-scale data processing, predictive analytics, and scientific computing. It aims to simplify package management and deployment.