Amazon SageMaker vs. Google Cloud AI

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
Google Cloud AI
Score 8.3 out of 10
N/A
Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.N/A
Pricing
Amazon SageMakerGoogle Cloud AI
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Amazon SageMakerGoogle Cloud AI
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 SageMakerGoogle Cloud AI
Considered Both Products
Amazon SageMaker
Chose Amazon SageMaker
Amazon SageMaker comes with other supportive services like S3, SQS, and a vast variety of servers on EC2. It's very comfortable to manage the process and also support the end application by one click hosting option. Also, it charges on the base of what you use and how long you …
Chose Amazon SageMaker
Amazon SageMaker is the best option for machine learning if you are already using the Amazon data science ecosystem. The software integrates nicely with MapReduce and most of the other Amazon tools. Additionally, MapReduce does a fairly good job of making the development of …
Google Cloud AI

No answer on this topic

Top Pros
Top Cons
Best Alternatives
Amazon SageMakerGoogle Cloud AI
Small Businesses
Google Cloud AI
Google Cloud AI
Score 8.3 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 8.3 out of 10
Posit
Posit
Score 9.1 out of 10
Enterprises
Dataiku
Dataiku
Score 7.9 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon SageMakerGoogle Cloud AI
Likelihood to Recommend
9.0
(6 ratings)
10.0
(6 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(1 ratings)
Usability
-
(0 ratings)
10.0
(1 ratings)
Support Rating
-
(0 ratings)
7.3
(3 ratings)
Implementation Rating
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
Amazon SageMakerGoogle Cloud AI
Likelihood to Recommend
Amazon AWS
Amazon SageMaker is a great tool for developing machine learning models that take more effort than just point-and-click type of analyses. The software works well with the other tools in the Amazon ecosystem, so if you use Amazon Web Services or are thinking about it, SageMaker would be a great addition. SageMaker is great for consumer insights, predictive analytics, and looking for gems of insight in the massive amounts of data we create. SageMaker is less suitable for analysts who do generally "small" data analyses, and "small" data analyses in today's world can be billions of records.
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Google
Google Cloud AI is a wonderful product for companies that are looking to offset AI and ML processing power to cloud APIs, and specific Machine Learning use cases to APIs as well. For companies that are looking for very specific, customized ML capabilities that require lots of fine-tuning, it may be better to do this sort of processing through open-source libraries locally, to offset the costs that your company might incur through this API usage.
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Pros
Amazon AWS
  • Provides enough freedom for experienced data scientists and also for those who just need things done without going much deeper into building models.
  • Customization and easy to alter and change.
  • If you already are an Amazon user, you do not need to transition over to another software.
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Google
  • good conversion from the voice to the text
  • speed in the conversion from voice to text
  • time-saving in the conversion activity
  • analysis of the results of the conversion in real time
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Cons
Amazon AWS
  • The UI can be eased up a bit for use by business analysts and non technical users
  • For huge amount of data pull from legacy solutions, the platform lags a bit
  • Considering ML is an emerging topic and would be used by most of the organizations in future, the pipeline integrations can be optimized
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Google
  • Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time.
  • Customization of existing modules and libraries is harder and it does need time and experience to learn.
  • Google Cloud AI can do a better job in providing better support for Python and other coding languages.
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Likelihood to Renew
Amazon AWS
No answers on this topic
Google
We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.
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Usability
Amazon AWS
No answers on this topic
Google
So far we have not had any problems with the application, it is extremely easy to use and it is also easy to install. It does not require much training since the instruction is quite clear for its execution and application in the procedures of the company. The team in charge of this application is very pleased to work with this app.
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Support Rating
Amazon AWS
No answers on this topic
Google
Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.
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Implementation Rating
Amazon AWS
No answers on this topic
Google
In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.
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Alternatives Considered
Amazon AWS
Amazon SageMaker comes with other supportive services like S3, SQS, and a vast variety of servers on EC2. It's very comfortable to manage the process and also support the end application by one click hosting option. Also, it charges on the base of what you use and how long you use it, so it becomes less costly compared to others.
Read full review
Google
These are basic tools although useful, you can't simply ignore them or say they are not good. These tools also have their own values. But, Yes, Google is an advanced one, A king in the field of offering a wide range of tools, quality, speed, easy to use, automation, prebuild, and cost-effective make them a leader and differentiate them from others.
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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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Google
  • Artificial intelligence and automation seems 'free' and draws the organization in, without seeming to spend a lot of funds. A positive impact, but who is actually tracking the cost?
  • We want our employees to use it, but many resist technology or are scared of it, so we need a way to make them feel more comfortable with the AI.
  • The ROI seems positive since we are full in with Google, and the tools come along with the functionality.
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ScreenShots