Compare Amazon SageMaker vs. Databricks

Amazon SageMaker is ranked 13th in Data Science Platforms with 1 review while Databricks is ranked 6th in Data Science Platforms with 4 reviews. Amazon SageMaker is rated 6.0, while Databricks is rated 8.8. The top reviewer of Amazon SageMaker writes "The Random Cut Forest Algorithm is helpful, but the IDE is immature and needs enhancing". On the other hand, the top reviewer of Databricks writes "Good build-in optimization, easy to use with a good user interface". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio and Cloudera Data Science Workbench, whereas Databricks is most compared with Amazon SageMaker, Microsoft Azure Machine Learning Studio and Cloudera Data Science Workbench.
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5,088 views|4,718 comparisons
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8,028 views|7,355 comparisons
Most Helpful Review
Find out what your peers are saying about Alteryx, Knime, IBM and others in Data Science Platforms. Updated: November 2019.
384,468 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

The few projects we have done have been promising.

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Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great.Automation with Databricks is very easy when using the API.We are completely satisfied with the ease of connecting to different sources of data or pocket files in the searchThe built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly.

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I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time.

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It should have more compatible and more advanced visualization and machine learning libraries.Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems.The integration features could be more interesting, more involved.The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment.

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Pricing and Cost Advice
Information Not Available
I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly.Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful.Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery.

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Top Comparisons
Compared 29% of the time.
Compared 19% of the time.
Also Known As
AWS SageMaker, SageMakerDatabricks Unified Analytics, Databricks Unified Analytics Platform

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.

Databricks creates a Unified Analytics Platform that accelerates innovation by unifying data science, engineering, and business. It utilizes Apache Spark to help clients with cloud-based big data processing. It puts Spark on “autopilot” to significantly reduce operational complexity and management cost. The Databricks I/O module (DBIO) improves the read and write performance of Apache Spark in the cloud. An increase in productivity is ensured through Databricks’ collaborative workplace.

Learn more about Amazon SageMaker
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Sample Customers
DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing,, GE Healthcare, Tinder, IntuitElsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Top Industries
Software R&D Company32%
Media Company17%
Comms Service Provider9%
Software R&D Company39%
Media Company10%
Comms Service Provider8%
Find out what your peers are saying about Alteryx, Knime, IBM and others in Data Science Platforms. Updated: November 2019.
384,468 professionals have used our research since 2012.
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.
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