Amazon SageMaker vs Prem Studio comparison

Amazon Web Services (AWS) and Prem are both solutions in the AI Development Platforms category. Amazon Web Services (AWS) is ranked #4 with an average rating of 8.0, while Prem is ranked #16 with an average rating of 10.0. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Prem users who would recommend it.

Amazon SageMaker

Read 38 Amazon SageMaker reviews

6,422 Views
2,826 Comparison Views

91% willing to recommend

Prem Studio

Read 2 Prem Studio reviews

14 Views
0 Comparison Views

100% willing to recommend

Amazon SageMaker

Prem Studio

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Executive Summary

We performed a comparison between Amazon SageMaker and Prem Studio based on real PeerSpot user reviews.

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October 2025

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Review summaries and opinions

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

Categories and Ranking

Amazon SageMaker

Ranking in AI Development Platforms

4th

Average Rating

7.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Science Platforms (2nd)

Prem Studio

Ranking in AI Development Platforms

16th

Average Rating

10.0

Reviews Sentiment

1.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Featured Reviews

Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

Create innovative assistants with seamless data integration for large-scale projects

The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use. Tools like AWS Glue integrate well for data transformations. The Databricks integration aids data scientists and engineers. SageMaker is fully managed, offers high availability, flexibility with TensorFlow, PyTorch, and MXNet, and comes with pre-trained algorithms for forecasting, anomaly detection, and more.

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reviewer2760291

Head of AI at a consultancy with 1,001-5,000 employees

Has accelerated AI solution development through automated evaluation and fine-tuning

Prem Studio allowed me to easily automate and solve the complicated problem of exploring and identifying the best AI architecture for our problems. Prem Studio has a straightforward yet powerful approach to evaluate disparate AI architectures on our business problems and to accurately fine-tune the most promising ones. This significantly reduced time-to-market, almost by a factor of ten in my case, for solutions tailored and optimized for customer requirements and KPIs.

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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

"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."

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

"We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for these models, making accessing them convenient as needed."

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

"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 most valuable features include the ML operations that allow for designing, deploying, testing, and evaluating models."

"SageMaker offers functionalities like Jupyter Notebooks for development, built-in algorithms, model tuning, and options to deploy models on managed infrastructure."

"They are doing a good job of evolving."

More Amazon SageMaker pros

"The dataset management feature and the managed finetuning are the most valuable because they save the most time."

Cons

"The solution is complex to use."

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

"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."

"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."

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

"The dashboard could be improved by including more features and providing more information about deployed models, their drift, performance, scaling, and customization options."

"Having all documentation easily accessible on the front page of SageMaker would be a great improvement."

"There is room for improvement in the collaboration with serverless architecture, particularly integration with AWS Lambda."

More Amazon SageMaker cons

"The inference should be faster."

Pricing and Cost Advice

"Amazon SageMaker is a very expensive product."

"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."

"You don't pay for Sagemaker. You only pay for the compute instances in your storage."

"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."

"Databricks solution is less costly than Amazon SageMaker."

"The pricing is comparable."

"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."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a six out of ten."

More Amazon SageMaker pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

11%

Manufacturing Company

University

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	11
Large Enterprise	16

No data available

Questions from the Community

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

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What do you like most about Amazon SageMaker?

We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for t...

See all answers

What is your experience regarding pricing and costs for Amazon SageMaker?

If you manage it effectively, their pricing is reasonable. It's similar to anything in the cloud; if you don't manage it properly, it can be expensive, but if you do, it's fine.

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What is your experience regarding pricing and costs for Prem Studio?

To maximize the effectiveness of fine-tuning, I would suggest using the parallelism features of the platform. This allows fine-tuning and evaluating multiple models at the same time, making compari...

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What needs improvement with Prem Studio?

Prem Studio is perfect for text input and output. We requested support for vLM, which should be available soon.

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What is your primary use case for Prem Studio?

I use Prem Studio to automate fine-tuning and evaluation of AI solutions.

See all answers

Comparisons

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Compared 10% of the time

Databricks vs Amazon SageMaker

Compared 9% of the time

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Compared 8% of the time

Azure OpenAI vs Amazon SageMaker

Compared 8% of the time

Google Vertex AI vs Amazon SageMaker

Compared 8% of the time

More Amazon SageMaker Competitors

No data available

Product Reports

Buyer's Guide

Amazon SageMaker

October 2025

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Buyer's Guide

AI Development Platforms

October 2025

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Also Known As

AWS SageMaker, SageMaker

No data available

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.

Amazon Web Services (AWS)

Information not available

Prem

Sample Customers

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

Information Not Available

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October 2025

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