Gartner 2019 year data science and machine learning platform Magic Quadrant (as of November 2018)
The 2019 report assesses the 17 vendors (one more than usual), based on forward-looking (referred to as forward) and ability to execute (referred to as capacity), and as usual they are listed in the four quadrants.
Please note, Gartner has included only commercial licensed product supplier. Although these purely as Python and R open-source platform in machine learning and data scientists popularity among professionals, but not included.
Gartner data science and machine learning platform Magic Quadrant for 2019 compared with 2018. 2018 Magic Quadrant (gray background) and the results of 2019 Magic Quadrant (foreground), the arrows connecting the circles on behalf of the same company. If the company significantly improved position (away from the original position), marked with a green arrow, if the company lowered position, marked with a red arrow. Green circles represent two new companies (Google and DataRobot), a red X marks this year, dropped out of the quadrant vendors (Teradata).
Open source scientific data analysis platform KNIME
KNIME is an open source, enterprise-class analytics platform, designed specifically for data scientists. KNIME visual interface that contains all the nodes from extraction to present the data, and stressed that statistical model. KNIME data analysis platform, the most striking is its powerful data integration capabilities and tools, KNIME data with several other scientific tools (including R, Python, Hadoop and H2O) as well as many types of structured and unstructured data integration.
Recommend this software main advantages are:
1-Knime open source software, with a large number of cases the data can be learned
2-Knime support graphical interface, very small segment of nodes and processes
3-knime support Python, R and Weka language, of course, native Java programming language is easy to integrate
4-Knime have community and laboratories, Community Nodes and Knime Labs constantly updated to handle new things
RapidMiner Fast Mining [ræpɪd] [maɪnər]
RapidMiner is the world's leading data mining solution, by dragging the image modeling interface, easy data preparation, machine learning and predictive model deployment, without programming, easy to use. The following figure shows its workflow
Which has the following advantages:
- 统一的平台：
一个平台，一个用户界面，一个系统，支持从数据准备，模型部署到正在进行的模型管理的完整工作流程。
- 可视化工作流设计：
快速易学和方便使用的拖放方法加速了端到端的数据科学，从而提高生产力。
- 广泛的功能：
超出其他可视化平台更多的预定义机器学习函数和第三方库。
- 开源创新：
广泛接受的开源语言和技术，超过250K的数据科学专家的社区和强大的marketplace与不断发展的数据科学需求保持同步。
- 广泛的连接：
超过60种connectors可以轻松访问所有类型的数据：结构化、非结构化和大数据。
- 各种规模的数据科学：
在内存中或hadoop中运行工作流，为各种规模的项目提供最佳选择。
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