Gartner 2018: List of Leading Data Science and Machine Learning Platforms on the Market

September 17, 2018 By Natalia Andueza

GARTNER 2018: Which tools are leading the way in Data Science and Machine Learning?

Once again, Gartner has published its magic quadrant, presenting a thorough study of the Data Science and Machine Learning platforms currently available on the market. As shown in the chart above, Gartner’s quadrant groups the different players into: niche players, visionaries, challengers, and leaders. Surprisingly, the three largest companies with platforms developed for data science and machine learning—SAP, IBM, and Microsoft—have failed to enter or remain in the leaders segment for yet another year.

Last year, the only one of these companies to proudly belong to the leaders group was IBM, with its IBM SPSS tool. IBM SPSS even led Gartner’s quadrant at the time; however, this year it has dropped out of the leaders quadrant, landing in a modest position among the visionaries.

Knime Tops the List of Data Science and Machine Learning Tools

It’s worth highlighting the outstanding work that the 5 platforms in the leaders zone have carried out over the years. This year, that group includes Alteryx, SAS, RapidMiner, and H2O.ai, with Knime topping Gartner’s magic quadrant.

Comparison of Gartner’s Magic Quadrants for Data Science and Machine Learning Platforms: 2018 vs. 2017

It’s worth noting that Knime, in addition to topping Gartner’s magic quadrant, is—along with H2O.ai—one of the two platforms that have advanced the most over the past year.

It’s also worth highlighting H2O.ai’s impressive rise. The improvement seen this past year has been remarkable, especially considering it only appeared in Gartner’s quadrant for the first time last year.

Here at LISDATA, we’d like to close this post by congratulating all the platforms featured in this diagram, given the effort required to earn a place on it. Of course, special congratulations go to the platforms that have managed to maintain their position as leaders in this magic quadrant, and especially to those that, for the first time, have managed to carve out a spot among the best. Want to learn more about Data Science and Machine Learning tools? Contact us.