Amazon SageMaker Overview

Amazon SageMaker is the #13 ranked solution in our list of top Data Science Platforms. It is most often compared to Databricks: Amazon SageMaker vs Databricks

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.

Amazon SageMaker is also known as AWS SageMaker, SageMaker.

Amazon SageMaker Buyer's Guide

Download the Amazon SageMaker Buyer's Guide including reviews and more. Updated: January 2021

Amazon SageMaker Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit

Amazon SageMaker Video

Pricing Advice

What users are saying about Amazon SageMaker pricing:
  • "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."
  • "The support costs are 10% of the Amazon fees and it comes by default."

Amazon SageMaker Reviews

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Sandeep_Pandey
Data Scientist at a tech vendor with 10,001+ employees
Real User
Top 20
Dec 22, 2019
A solution with great computational storage, has many pre-built models, is stable, and has good support

What is our primary use case?

I know about SageMaker and its capabilities, and what it can do, but I have not had any hands-on experience. It's a machine learning platform for developers to create models.

Pros and Cons

  • "They are doing a good job of evolving."
  • "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."

What other advice do I have?

I am not exposed to Amazon SageMaker but I know it's capabilities. I know exactly what we can do and how we can do it. We have been provided with several solutions for image processing, speech processing, and text processing. They have provided a built-in solution for every task. You can use tools for deploying your model, you just have to plug and play. There is no cessation from what I can see. Whatever they have in the industry, they can solve 98% of the use cases. There is also data engineering which is quite important. It's where the real work is done. Amazon has already provided a free…
PankajUrmaliya
Lead Data Scientist at a tech services company with 201-500 employees
Real User
Top 5
Sep 18, 2020
Good deployment and monitoring features, but the interface could use some improvement

What is our primary use case?

This is a solution that we have provided to one of our clients. The client is in the business of consumer goods and they wanted to get accurate demand forecasts to evaluate performance of campaigns and optimize inventory. The solution is an ensemble of regression models and is deployed on their AWS Cloud and all of the data is on Amazon Redshift.

Pros and Cons

  • "The deployment is very good, where you only need to press a few buttons."
  • "Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

What other advice do I have?

My advice to anybody who is considering this solution is to think about using multiple cloud services. This solution is good but for complex business problems and big data, it gets a bit trickier. In terms of deployment, it is a clear winner. From the cost point of view, it's relatively on the higher side. Overall, there are a few improvements that I want but SageMaker is pretty good. I would rate this solution a seven out of ten.
Learn what your peers think about Amazon SageMaker. Get advice and tips from experienced pros sharing their opinions. Updated: January 2021.
455,301 professionals have used our research since 2012.
Jaison Jose
Cloud Architect & Support Service Delivery Manager at Almoayyed Computers
Reseller
Top 5
Feb 27, 2020
Straightforward setup, scalable, and the technical support is good

What is our primary use case?

We are a solution provider that is concentrating on migrating our customers from on-premises to the cloud, and Amazon SageMaker is one of the products that we implement for our customers. SageMaker is an AI platform, and I have been working on creating a solution that uses SageMaker and DeepLens to recognize people for access control. It will automatically log people who are coming and leaving. The second use case that we are working on is a system that recognizes cars by reading license plates and then opening a gate automatically to let them into the parking area. AI, in general, has not yet… more »

Pros and Cons

  • "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."
  • "AI is a new area and AWS needs to have an internship training program available."

What other advice do I have?

Myself and certain people in my team have just begun the training. There is an eight-hour training video to assist with learning how to use this solution. I would rate this solution an eight out of ten.
reviewer1318050
Consultant at a tech services company with 501-1,000 employees
Consultant
Top 5
Apr 21, 2020
Great for automating pipelines and creation of API endpoints

What is our primary use case?

Our primary use case for SageMaker is for developing end to end machine learning solutions and ready solutions for things such as computer vision or speech recognition or speech to text. It's basically providing off-the-shelf solutions. Our customers are generally medium to enterprise size companies. We're a partner of Amazon.

Pros and Cons

  • "Allows you to create API endpoints."
  • "Lacking in some machine learning pipelines."

What other advice do I have?

I think for anyone using SageMaker it will help automate pipelines, and make it easier than doing the process manually. For anyone already on the AWS platform, they should definitely make use of it. I would rate this product an eight out of 10.
reviewer1178424
Vice President & CIO at a logistics company with 201-500 employees
Real User
Top 5
Sep 3, 2019
The Random Cut Forest Algorithm is helpful, but the IDE is immature and needs enhancing

What is our primary use case?

We use this solution for Outlier Detection using Random Cut Forest. We intend to implement a Predictive modeling project starting in October and have not yet decided on the platform(s) we will utilize. The challenge for us is balancing the Data Scientists, Technical vs. Analyst.

How has it helped my organization?

We are still learning the platform and will conduct more training as we evaluate it for other projects. The few projects we have done have been promising.

What is most valuable?

The most valuable features of this solution are the Random Cut Forest and the IDE.

What needs improvement?

I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time.

For how long have I used the solution?