Amazon SageMaker vs. Oracle Machine Learning

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon SageMaker
Score 8.3 out of 10
N/A
Amazon SageMaker 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.N/A
Oracle Machine Learning
Score 8.0 out of 10
N/A
Oracle Machine Learning (formerly Oracle Advanced Analytics) combines the Oracle database with Oracle Data Miner and SQL as well as R programming language functionality, providing a complete predictive analytics suite.N/A
Pricing
Amazon SageMakerOracle Machine Learning
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Amazon SageMakerOracle Machine Learning
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon SageMakerOracle Machine Learning
Top Pros
Top Cons
Best Alternatives
Amazon SageMakerOracle Machine Learning
Small Businesses
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
Posit
Posit
Score 9.3 out of 10
Enterprises
Dataiku
Dataiku
Score 8.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon SageMakerOracle Machine Learning
Likelihood to Recommend
9.0
(5 ratings)
8.0
(10 ratings)
User Testimonials
Amazon SageMakerOracle Machine Learning
Likelihood to Recommend
Amazon AWS
It allows for one-click processes and for things to be auto checked before they are moved through the process but through the system. It also makes training easy. I am able to train users on the basic fundamentals of the tool and how it is used very easily as it is fully managed on its own which is incredible.
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Oracle
OAC doesn't require software to be installed since it is browser based. This allows for easier deployment since a local client software is not required to be installed for each user. OAC can be used for the casual light user who mainly consumes data to the power user who can created sophisticated dashboard with advanced analytics. OAC is not meant to replace Essbase reporting.
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Pros
Amazon AWS
  • Machine Learning at scale by deploying huge amount of training data
  • Accelerated data processing for faster outputs and learnings
  • Kubernetes integration for containerized deployments
  • Creating API endpoints for use by technical users
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Oracle
  • Analyzing heaps of data dumped into the machine learning tool.
  • Giving the researcher an insight on which direction to proceed in order to get the desired results.
  • Can help perform a functional analysis before doing a deep dive.
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Cons
Amazon AWS
  • It's very good for the hardcore programmer, but a little bit complex for a data scientist or new hire who does not have a strong programming background.
  • Most of the popular library and ML frameworks are there, but we still have to depend on them for new releases.
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Oracle
  • As mentioned by others the formatting of reports constantly has issues
  • Once your initial contract terms are up be prepared for a significant increase
  • Pricing needs to be inline with what other competitors are offering
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Alternatives Considered
Amazon AWS
Amazon SageMaker took the heavy lifting out of building and creating models. It allowed for our organization to use our current system for integration and essentially added on a feature to help all levels of Data scientists and IT professionals in our department and company as a whole. The training was simple as well.
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Oracle
Sorry this product was not selected by me, but was a legacy install that was upgraded. I see the value in the product, however, I was not involved in the selection process.
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Return on Investment
Amazon AWS
  • We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
  • We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
  • For our use-cases, serving models is less expensive with SageMaker than bespoke servers.
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Oracle
  • Our ROI has been great since we have been able to get a birdseye view of our business operations.
  • Shows your areas within your company that needs attention and improvements.
  • Oracle has had a positive impact on all of our business objectives since it provides a clear view of your business operations.
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ScreenShots