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Amazon SageMaker pros and cons

Vendor: Amazon Web Services (AWS)

3.9 out of 5

38 reviews
91% willing to recommend

Pros & Cons summary

Amazon SageMaker offers an extensive feature set, including AutoML, automated tuning, and seamless AWS integration, essential for managing ML workloads. Users appreciate its one-touch deployment and technical support. However, it's viewed as costly for large workloads, and monitoring capabilities need enhancement. Integration with serverless architectures and improved security features are desired. Despite these critiques, its comprehensive support across the ML lifecycle makes SageMaker a strong option for ambitious tech projects.

Buyer's Guide

Get pricing advice, tips, use cases and valuable features from real users of this product.

Prominent pros & cons

PROS

Amazon SageMaker provides valuable features such as automated hyperparameter tuning, simplifying the process of testing and saving time through parallel computing capabilities.

It allows users to perform machine learning activities, including building, training, and deploying AI models from scratch, offering a comprehensive platform for ML projects.

SageMaker Studio is highly regarded for its overall package of deployment and management features, enabling efficient ML model development within a single environment.

The technical support for Amazon SageMaker is rated highly, with well-trained engineers offering substantial assistance and insights for ML workloads.

Additionally, Amazon SageMaker supports one-touch deployment, making it easier to manage and access models expediently.

CONS

Amazon SageMaker's pricing is often considered high, particularly for large workloads, driving some companies to seek alternative cloud options.

Scalability and integration with big data networks like Hadoop and Apache Spark could be enhanced.

Documentation and support materials require improvement, with clearer guidance and more comprehensive training modules needed.

The complexity of use and need for substantial data to train models are challenges for users, especially those with basic coding skills.

Better support for data flow management, security, and policy integration would enhance user experience and data protection.

Amazon SageMaker Pros review quotes

SaravananThiagarajan

Data Scientist at a computer software company with 5,001-10,000 employees

Jul 17, 2024

The technical support of the tool was good.

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Data Scientist at a computer software company with 501-1,000 employees

Nov 13, 2023

The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework.

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Leshmi Giridharan

Data specialist at a mining and metals company with 11-50 employees

Jan 22, 2024

The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate.

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Amazon SageMaker

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SP

Data Scientist at a tech vendor with 10,001+ employees

Dec 16, 2019

They are doing a good job of evolving.

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Big Data Solution Architect - Spatial Data Specialist at SCIERA, INC

Aug 10, 2023

The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides.

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Software Engineer at Sportsbet

Jul 10, 2023

The solution is easy to scale...The documentation and online community support have been sufficient for us so far.

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Subrata Mukherjee

Senior Technical Architect; Head of Platform at Blenheim Chalcot IT Services India

Nov 13, 2024

The most valuable features in Amazon SageMaker are its AutoML, feature store, and automated hyperparameter tuning capabilities.

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VP, Principal at Axtria - Ingenious Insights

Jan 26, 2024

The most valuable feature of Amazon SageMaker for me is the model deployment service.

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Senior Actuary at Accelerant Holdings

Oct 28, 2024

The intuitive interface and streamlined user experience make it easy to navigate and set up various tools like Visual Studio Code or Jupyter Notebook.

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Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

Apr 28, 2025

The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use.

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Amazon SageMaker Cons review quotes

SaravananThiagarajan

Data Scientist at a computer software company with 5,001-10,000 employees

Jul 17, 2024

For any cloud provider, the cost has to be substantially reduced, especially in the case of Amazon SageMaker, which is extremely expensive for huge workloads.

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Data Scientist at a computer software company with 501-1,000 employees

Nov 13, 2023

The solution is complex to use.

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Leshmi Giridharan

Data specialist at a mining and metals company with 11-50 employees

Jan 22, 2024

The training modules could be enhanced. We had to take in-person training to fully understand SageMaker, and while the trainers were great, I think more comprehensive online modules would be helpful.

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Amazon SageMaker

Free Report: Amazon SageMaker Reviews and More

Learn what your peers think about Amazon SageMaker. Get advice and tips from experienced pros sharing their opinions. Updated: August 2025.

865,295 professionals have used our research since 2012.

SP

Data Scientist at a tech vendor with 10,001+ employees

Dec 16, 2019

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.

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Big Data Solution Architect - Spatial Data Specialist at SCIERA, INC

Aug 10, 2023

In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user.

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reviewer2315208

Data Lake and MLOps Lead at a energy/utilities company with 10,001+ employees

Jul 29, 2025

They could add features such as managing environments, experiment management across those environments, and the integration with training datasets as you go through those experiments.

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Software Engineer at Sportsbet

Jul 10, 2023

The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV.

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Subrata Mukherjee

Senior Technical Architect; Head of Platform at Blenheim Chalcot IT Services India

Nov 13, 2024

Improvements are needed in terms of complexity, data security, and access policy integration in Amazon SageMaker.

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VP, Principal at Axtria - Ingenious Insights

Jan 26, 2024

Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process.

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Senior Actuary at Accelerant Holdings

Oct 28, 2024

When starting a new session, the waiting time can be quite long, ranging from two to five minutes.

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Show 10 more reviews (out of 38)

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