Gartner’s 2018 Magic Quadrant Ranks Elite Machine Learning Tools

Pranav Dar 28 Feb, 2018 • 2 min read


  • Gartner’s magic quadrant for data science platforms has been released for 2018
  • moves into the ‘Leaders’ quadrant, Microsoft goes from ‘Leaders’ in 2017 to ‘Visionaries’ this year
  • RapidMiner continues to be a leader for a 5th straight year
  • The quadrant helps companies define and decide which data science platform is best for them



The question of “which tool should I use?” is an ever-present in the data science field. With the rapid pace at which new technology is being created, it’s no surprise that even experienced data scientists are always on the lookout for the “next best tool”.

Keeping that in mind, Gartner has released it’s annual ‘Magic Quadrant for Data Science and Machine-Learning Platforms’ report for 2018 this week. This magic quadrant evaluated 16 platforms to help companies to identify the right one for their respective organizations. The two criteria used in the quadrant are:

  • Completeness of vision
  • Ability to Execute

These platforms are the software data scientists use for developing and deploying machine learning solutions. Gartner defines a data science and machine learning platform as:

“A cohesive software application that offers a mixture of basic building blocks essential both for creating many kinds of data science solution and incorporating such solutions into business processes, surrounding infrastructure and products.”

Without any further ado, here is the magic quadrant for 2018: are the biggest entry in this year’s version as this is their first time on the list. IBM and Microsoft retail their status as stable platforms.

Comparing this year’s report with the 2017 version:

  • SAS , RapidMiner and KNIME remain in the ‘Leaders’ quadrant
  •, thanks to it’s ‘Driverless AI’ product, transcends into the ‘Leaders’ section while Alteryx has moved from a ‘Challenger’ to a ‘Leader’
  • Microsoft and Domino remain visionaries
  • Anaconda’s rapid rise continues with it’s inclusion here in the ‘Niche Players’ category

You can view the full report for this year on Gartner’s site here. They have listed the strengths and cautions for each platform in each quadrant in detail.


Our take on this

The report is a comprehensive overview of each platform and will help companies decide which tool suits their needs the most. We love how well defined each company is in the quadrant.’s ‘Driverless AI’ automated machine learning platform has fueled its rise into the ‘Leaders’ quadrant.

For data scientists, this report is a welcome sight. It not only helps them keep up to date with what tools are available in the industry currently, but with the comprehensive review of each one available, it helps them decide which tools can be leveraged for the different types of analysis and data available.


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Pranav Dar 28 Feb 2018

Senior Editor at Analytics Vidhya.Data visualization practitioner who loves reading and delving deeper into the data science and machine learning arts. Always looking for new ways to improve processes using ML and AI.

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