We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"They are doing a good job of evolving."
"The most valuable feature of Amazon SageMaker is that you don't have to do any programming in order to perform some of your use cases."
"Allows you to create API endpoints."
"The deployment is very good, where you only need to press a few buttons."
"The scalability of the solution is good; I'd rate it four out of five."
"I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox."
"AI is a new area and AWS needs to have an internship training program available."
"Lacking in some machine learning pipelines."
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"The predictive analysis feature needs improvement."
"The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation."
"The support costs are 10% of the Amazon fees and it comes by default."
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.
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.
Amazon SageMaker is ranked 13th in Data Science Platforms with 4 reviews while Domino Data Science Platform is ranked 20th in Data Science Platforms with 1 review. Amazon SageMaker is rated 8.0, while Domino Data Science Platform is rated 7.0. The top reviewer of Amazon SageMaker writes "A solution with great computational storage, has many pre-built models, is stable, and has good support". On the other hand, the top reviewer of Domino Data Science Platform writes "Good scalability and stability but the predictive analysis feature needs improvement". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, H2O.ai and KNIME, whereas Domino Data Science Platform is most compared with Databricks, Dataiku Data Science Studio, Alteryx, Microsoft Azure Machine Learning Studio and KNIME.
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.