We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
Domino provides a central system of record that keeps track of all data science activity across an organization. Domino helps data scientists seamlessly orchestrate AWS hardware and software toolkits, increase flexibility and innovation, and maintain required IT controls and standards. Organizations can automatically keep track of all data, tools, experiments, results, discussion, and models, as well as dramatically scale data science investments and impact decision-making across divisions. The platform helps organizations work faster, deploy results sooner, scale rapidly, and reduce regulatory and operational risk.
Dremio is the Data-as-a-Service Platform. Created by veterans of open source and big data technologies, and the creators of Apache Arrow, Dremio is a fundamentally new approach to data analytics that helps companies get more value from their data, faster. Dremio makes data engineering teams more productive, and data consumers more self-sufficient.
Domino Data Science Platform is ranked 20th in Data Science Platforms with 1 review while Dremio is ranked 21st in Data Science Platforms. Domino Data Science Platform is rated 7.0, while Dremio is rated 0.0. The top reviewer of Domino Data Science Platform writes "Good scalability and stability but the predictive analysis feature needs improvement". On the other hand, Domino Data Science Platform is most compared with Databricks, Amazon SageMaker, Alteryx, Dataiku Data Science Studio and SAS Visual Analytics, whereas Dremio is most compared with Databricks, Alteryx, AtScale Adaptive Analytics (A3), Microsoft BI and Dataiku Data Science Studio.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.