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Compare Amazon SageMaker vs. Google Cloud Datalab

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Quotes From Members

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

Pros
"They are doing a good job of evolving.""Allows you to create API endpoints.""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 deployment is very good, where you only need to press a few buttons."

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"All of the features of this product are quite good."

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Cons
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier.""Lacking in some machine learning pipelines.""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."

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"The interface should be more user-friendly."

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Pricing and Cost Advice
"The support costs are 10% of the Amazon fees and it comes by default.""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."

More Amazon SageMaker Pricing and Cost Advice »

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Ranking
11th
Views
12,692
Comparisons
10,450
Reviews
3
Average Words per Review
596
Rating
8.0
18th
Views
3,393
Comparisons
2,989
Reviews
1
Average Words per Review
303
Rating
8.0
Comparisons
Also Known As
AWS SageMaker, SageMaker
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Overview

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.

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.

Offer
Learn more about Amazon SageMaker
Learn more about Google Cloud Datalab
Sample Customers
DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
Information Not Available
Top Industries
VISITORS READING REVIEWS
Computer Software Company24%
Media Company14%
Comms Service Provider14%
Financial Services Firm8%
VISITORS READING REVIEWS
Comms Service Provider25%
Computer Software Company18%
Financial Services Firm13%
Retailer8%
Company Size
REVIEWERS
Midsize Enterprise57%
Large Enterprise43%
No Data Available
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: November 2021.
555,358 professionals have used our research since 2012.

Amazon SageMaker is ranked 11th in Data Science Platforms with 4 reviews while Google Cloud Datalab is ranked 18th in Data Science Platforms with 1 review. Amazon SageMaker is rated 8.0, while Google Cloud Datalab is rated 8.0. 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 Google Cloud Datalab writes "Stable, feature-rich, and easy to set up". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, Domino Data Science Platform and H2O.ai, whereas Google Cloud Datalab is most compared with Databricks, IBM Watson Studio, Microsoft Azure Machine Learning Studio, Domino Data Science Platform and MathWorks Matlab.

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.