Top Machine Learning vendors recommended by Gartner

Gartner’s Magic Quadrant for Data Science and Machine Learning Platforms (2019) has published a list of top 17 vendors in data science and machine learning.

Previously titled the Magic Quadrant for Data Science Platforms and the Magic Quadrant for Advanced Analytics Platforms, the report evaluated the vendors for their completeness of vision and ability to execute.

Here are the top 17 Data Science and Machine Learning vendors shortlisted by Gartner.

1. Alteryx

Alteryx is based in Irvine, California, the U.S. It provides four software products, including its data science platform. It includes Alteryx Connect, Alteryx Designer, Alteryx Server, and Alteryx Promote.

2. Anaconda

Anaconda is based in Austin, Texas, the U.S. It offers Anaconda Enterprise 5.2, a data science development environment based on an interactive notebook concept (this analysis excludes Conda Distribution Packages) that sees users using Python and R-based open-source packages.

3. Databricks

Databricks is based in San Francisco, the U.S. Its Apache Spark-based Unified Analytics Platform combines data Its Apache Spark-based Unified Analytics Platform combines data engineering and data science capabilities using various open-source languages. In addition to Spark, Amazon Web Services (AWS) offers proprietary features for security, reliability, operationalization, performance, and real-time implementation.

4. Dataiku

Headquartered in New York City, USA, Dataiku is headquartered in Paris, France. It offers a Data Science Studio (DSS) focused on cross-disciplinary collaboration and usability.

5. DataRobot

DataRobot is based in Boston, Massachusetts, the U.S. It provides augmented data science and ML platform. The platform automates critical tasks, enabling data scientists to work efficiently and citizen data scientists to build models quickly.

6. Datawatch (Angoss)

Datawatch is based in Bedford, Massachusetts, the U.S. In January 2018, it acquired Angoss and its primary data science product components. These include KnowledgeSEEKER, aimed at citizen data scientists in a desktop context; KnowledgeSTUDIO, which provides many additional models and capabilities than KnowledgeSEEKER; and KnowledgeENTERPRISE, a flagship product that includes the full range of abilities.

7. Domino

Domino (Domino Data Lab) is a company headquartered in San Francisco, California. Their Domino Data Science Platform is a comprehensive end-to-end solution for data scientists. The platform includes both open-source and proprietary tools while providing collaborative, reproductive, and model development and deployment capabilities.

8. Google

Google, an Alphabet subsidiary, is based in Mountain View, California, U.S. Its core ML platform offerings include Cloud ML Engine, Cloud AutoML, Open Source TensorFlow, and recently announced BigQuery ML. Its ML components require other end-to-end Google components such as Google Cloud Dataprep, Google Datalab, Google BigQuery, Google Cloud Dataflow, and Google Cloud Dataprep.U.S.

9. H2O.ai

H2O.ai is based in Mountain View, California, USA and offers free, open-source H2O Open-Source Machine Learning (H2O, Sparkling Water, and H2O4GPU) and a commercial product, called H2O Driverless A.I. The core strength of H2O is its high-performance ML components, which are closely integrated into several competing platforms assessed in this Magic Quadrant.

10. IBM

IBM is based in Armonk, New York, the U.S. This Magic Quadrant evaluated two of their platforms: SPSS (including SPSS Modeler and SPSS Statistics) and Watson Studio, which includes IBM’s previous Data Science Experience (DSX) product.

11. KNIME

Based in Zurich, Switzerland, KNIME provides the KNIME Analytics Platform free on a fully open-source basis, while KNIME Server, a commercial extension, offers more advanced features such as team, automation, and deployment capabilities.

12. Microsoft

Microsoft provides data science and ML software products that include Azure Machine Learning (including Azure Machine Learning Studio), Azure HDInsight, Azure Data Factory, Azure Databricks, and Power B.I. in the cloud. Microsoft offers Machine Learning Server for on-site workloads.

13. RapidMiner

RapidMiner, based in Boston, has a U.S.platform that includes RapidMiner Studio, RapidMiner Server, RapidMiner Cloud, RapidMiner Real-Time Scoring and RapidMiner Radoop.

14. SAP

SAP, based in Walldorf, Germany, offers SAP Predictive Analytics (P.A.). This platform has several components, including Data Manager for dataset preparation and feature engineering, Automated Modeler for citizen data scientists, Expert Analytics for more advanced ML, and Predictive Factory for operationalization. SAP PA is tightly integrated with SAP HANA.

15. SAS

SAS, based in Cary, North Carolina, U.S.provides many software products for analytics and data science. For this Magic Quadrant, we evaluated SAS Enterprise Miner (EM) and SAS Visual Data Mining and Machine Learning (VDMML).

16. TIBCO Software

TIBCO Software, based in Palo Alto, California, has built a well-rounded and robust analytics platform, tU.S.hrough the acquisition of enterprise reporting and modern B.I. Platform vendors (Jaspersoft and Spotfire), descriptive and predictive analytics platform vendors (Statistica and Alpine Data), and a streaming analytics vendor (StreamBase Systems).

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