Zurich, January 28, 2019 - For the sixth year in a row1, Gartner has placed KNIME®, the open source platform for data driven innovation, as a leader for Data Science and Machine Learning Platforms based on ability to execute and completeness of vision.
Gartner, Inc. describes leaders as having “a strong presence and significant mind share in the data science and ML market. They demonstrate strength in depth and breadth across the full data exploration, model development and operationalization process. While providing outstanding service and support, Leaders are also nimble in responding to rapidly changing market conditions. The number of expert and citizen data scientists using Leaders’ platforms is significant and growing.
Leaders are in the strongest position to influence the market’s growth and direction. They address the majority of industries, geographies, data domains and use cases, and therefore have a solid understanding of, and strategy for, this market. Not only can they focus on executing effectively, based on current market conditions, but they also have solid roadmaps to take advantage of new developments and advancing technologies in this rapidly transforming sector. They provide thought leadership and innovative differentiation, often disrupting the market in the process.
Leaders are suitable vendors for most organizations to evaluate. They should not be the only vendors evaluated, however, as other vendors might address an organization’s unique needs more precisely. Leaders provide a benchmark of high standards to which others should be compared.”
“We have always believed it is the data science and machine learning community that ultimately decides what the leading platforms are. We are humbled by the response of KNIME users across all industries, continents, and application areas which has helped us achieve this honor,” says Michael Berthold, CEO, KNIME AG. “That community comprises not only users who use our software, but many who also contribute to it.”
The KNIME approach is unique. Its integrative, open source approach ensures all capabilities required of an individual data scientist are available for free and with no restrictions. This includes leading edge technologies such as text mining, image processing, the newest trends in machine learning / artificial intelligence, as well as integrations with other platforms and engines such as Python, R, Spark, H2O, and Keras/TensorFlow for Deep Learning. “KNIME simply does it all within one platform, allowing you to mix and match and move seamlessly from prototyping to production as required, depending on the problem you are solving,” says Phil Winters, KNIME advocate and “Father of Customer Intelligence”. “For me as an individual, everything I do - regardless of scale - is free. I strongly believe that KNIME has set the standard that others must now scramble to follow.”
“We are continuing to not only add leading edge methods, but are also placing a strong emphasis on blueprints for Guided Analytics and Guided Automation. These are an extremely practical way of helping the KNIME community get “focused AI” applications into the hands of even more users,” continues Berthold. “Our commitment to open source is unwavering. This transparent business model works for everyone and we will keep it that way.”
For further information, contact KNIME at info@knime.com, or download KNIME and discover it for yourself. KNIME – Open for Innovation®.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
1Reports referenced include: Gartner Magic Quadrant for Advanced Analytics Platforms (2014, 2015, 2016), Gartner Magic Quadrant for Data Science Platforms (2017), Gartner Magic Quadrant for Data Science and Machine Learning Platforms (2018, 2019)
