Software Alternatives & Reviews

dotData VS Knoldus

Compare dotData VS Knoldus and see what are their differences

dotData logo dotData

dotData is a data automation platform that enables enterprises to operationalize data science and machine learning.

Knoldus logo Knoldus

Knoldus is a data engineering and analytics platform that helps you build intelligent applications at scale.
  • dotData Landing page
    Landing page //
    2023-06-12
  • Knoldus Landing page
    Landing page //
    2023-06-12

Category Popularity

0-100% (relative to dotData and Knoldus)
Development
48 48%
52% 52
Business & Commerce
48 48%
52% 52
Technical Computing
48 48%
52% 52
Data Dashboard
50 50%
50% 50

User comments

Share your experience with using dotData and Knoldus. For example, how are they different and which one is better?
Log in or Post with

What are some alternatives?

When comparing dotData and Knoldus, you can also consider the following products

IBM ILOG CPLEX Optimization Studio - IBM ILOG CPLEX Optimization Studio is an easy-to-use, affordable data analytics solution for businesses of all sizes who want to optimize their operations.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Amadea - Amadea is the leading integrated Data Science platform, empowering data analysts and data scientists to discover the insights that drive business success.

RapidMiner Studio - Visual workflow designer for predictive analytics that brings data science and machine learning to everyone on the analytics team

Tibco Data Science - Data science is a team sport. Data scientists, citizen data scientists, business users, and developers need flexible and extensible tools that promote collaboration, automation, and...

AIXON - AIXON is an AI-powered data science solution that enables data scientists of all levels of experience to build machine learning models and deploy them into production with less code and without the need for a data science team.