We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"Allows you to create API endpoints."
"They are doing a good job of evolving."
"The deployment is very good, where you only need to press a few buttons."
"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."
"The most valuable feature is the ease of setting up visualizations."
"The most valuable feature is the performance."
"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."
"The idea that you don't have to generate reports each day but they are sent automatically is great."
"AI is a new area and AWS needs to have an internship training program available."
"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."
"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."
"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."
"I would like the visualization for the map of countries to be more easily configurable."
"Additional templates would help to get things moving more quickly in terms of getting the reports out."
"The scripting for customization could be improved."
"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."
Earn 20 points
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.
TIBCO Spotfire Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.
Amazon SageMaker is ranked 11th in Data Science Platforms with 4 reviews while TIBCO Data Science is ranked 19th in Data Science Platforms with 4 reviews. Amazon SageMaker is rated 8.0, while TIBCO Data Science is rated 7.6. 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 TIBCO Data Science writes "A straightforward initial setup and good reporting but needs better documentation". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, Domino Data Science Platform and H2O.ai, whereas TIBCO Data Science is most compared with TIBCO Statistica, KNIME, Dataiku Data Science Studio and Alteryx. See our Amazon SageMaker vs. TIBCO Data Science report.
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.