Amazon SageMaker Reviews

Name: Amazon SageMaker
Brand: Amazon Web Services (AWS)
Rating: 3.9 (30 reviews)

Vendor: Amazon Web Services (AWS)

3.9 out of 5

30 reviews
89% willing to recommend

1,268 followers

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What is Amazon SageMaker?

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.

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Amazon SageMaker is the #4 ranked solution in top AI Development Platforms and #5 ranked solution in top Data Science Platforms. PeerSpot users give Amazon SageMaker an average rating of 7.8 out of 10. Based on the analysis of the 30 most recent Amazon SageMaker reviews, the overall sentiment is positive, with a sentiment score of 9.1. (The highest in the category). Amazon SageMaker is most commonly compared to Databricks: Amazon SageMaker vs Databricks. Amazon SageMaker is popular among the large enterprise segment, accounting for 65% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 18% of all views.

Helped 816,660 peers since 2012

Featured reviews

Natu Lauchande

Tech Lead - Sanlam Fintech Cluster - Data,ML,AI Eng. at Sanlam

SageMaker Studio sounds very interesting. Feature Store and data pipeline features are very interesting. The product is a one-stop shop. It allows people without much engineering knowledge to try out and deploy models in environments similar to the production environments. The tool makes our ML model development a bit more efficient because everything is in one environment. It is easy to manage compared to when things were in different components of AWS. Amazon SageMaker is in AWS, so I need not pay two bills. It is one less system to manage, so it is easier.

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AnupKumar3

Executive Specialists at LineData

The product provides the ability to develop AI models relatively quickly. My team develops the models using the tool. We use AI quite extensively in our business. We use the tool for predictive analytics. It helps predict which trade might fail based on historical data. Automatic Model Tuning helps improve the productivity of the investment operation team. Typically, an analyst spends about 45% of their time collecting, organizing, and ingesting data. We were able to use the product to automate processes.

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Ethan Kang

Senior Actuary at Accelerant Holdings

There are two areas in SageMaker that need improvement. Firstly, when starting a new session, the waiting time can be quite long, ranging from two to five minutes. Secondly, the integration with Snowflake is not optimal. I face challenges in authentication, requiring multiple steps to achieve single sign-on. This process feels somewhat cumbersome.

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Amazon SageMaker mindshare

Product category:

As of November 2024, the mindshare of Amazon SageMaker in the Data Science Platforms category stands at 7.7%, down from 10.4% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Data Science Platforms

Key learnings from peers

Last updated Nov 22, 2024

Valuable Features

"One of the most valuable features of Amazon SageMaker for me is the one-touch deployment, which simplifies the process greatly."
"SageMaker is a comprehensive platform where I can perform all machine learning activities."
"The feature I found most valuable is the data catalog, as it assists with the lineage of data through the preparation pipeline."

Room for Improvement

"The dashboard could be improved by including more features and providing more information about deployed models, their drift, performance, scaling, and customization options."
"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."
"The platform could be more accessible to users with basic coding skills, making it more intuitive and easier for beginners to use comfortably."

Pricing

"On average, customers pay about $300,000 USD per month."
"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."
"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."