Amazon SageMaker vs Starburst Enterprise comparison

Amazon Web Services (AWS) and Starburst are both solutions in the Data Science Platforms category. Amazon Web Services (AWS) is ranked #3 with an average rating of 8.0, while Starburst is ranked #14 with an average rating of 8.5. Amazon Web Services (AWS) holds a 7.3% mindshare in Data Science Platforms, compared to Starburst’s 2.2% mindshare. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

Amazon SageMaker

Read 36 Amazon SageMaker reviews

6,112 Views
4,892 Comparison Views

91% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

1,176 Views
1,011 Comparison Views

100% willing to recommend

Amazon SageMaker

Starburst Enterprise

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

Amazon SageMaker and Starburst Enterprise are competing products in advanced data analytics and machine learning. Amazon SageMaker seems to have an upper hand in pricing and support, while Starburst Enterprise offers a strong feature set, making it appealing despite higher costs.

Features: Amazon SageMaker provides comprehensive machine learning tools such as model training, deployment, and management, along with scalable infrastructure. It integrates tightly with AWS services. Starburst Enterprise is strong with its SQL engine and data federation capabilities, enabling cross-platform analytics and handling queries from different data sources efficiently.

Ease of Deployment and Customer Service: Amazon SageMaker facilitates seamless deployment within the AWS ecosystem, simplifying setup and scaling. It offers extensive AWS support and resources. Starburst Enterprise can run on various platforms including on-premises and cloud, but may involve more complex setup. It provides tailored support and consultancy services, emphasizing direct customer interaction, which benefits complex deployments.

Pricing and ROI: Amazon SageMaker offers a pay-as-you-go pricing model, making it cost-effective for variable usage and providing significant AWS credits for startups, resulting in a favorable ROI. Starburst Enterprise requires a higher initial setup cost, however, it offers a compelling ROI by efficiently querying data across multiple sources, which reduces the need for costly data migration and duplication.

To learn more, read our detailed Amazon SageMaker vs. Starburst Enterprise Report (Updated: March 2025).

Buyer's Guide

Amazon SageMaker vs. Starburst Enterprise

March 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 Data Science Platforms

3rd

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

AI Development Platforms (5th)

Starburst Enterprise

Ranking in Data Science Platforms

14th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Streaming Analytics (12th)

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 7.3%, down from 9.8% compared to the previous year. The mindshare of Starburst Enterprise is 2.2%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Hemant Paralkar

Lead Consultant at Saama

Improves team collaboration with advanced feature sharing but needs a better user experience

Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker. This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background. Additionally, dealing with frequent UI updates can be challenging, especially for infrastructure architects like myself. It involves effort to migrate to new UIs, making the updates not seamless. User auditing requires enhancements as tracking operations performed by users can be difficult due to dynamic IP validation and role propagation.

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KamleshPant

Senior Software Architect at USEReady

Connects to any data source from any region and offers unified access

There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the future, if we have all the data available, we can definitely capitalize on AI/ML and LLM capabilities to summarize data and gain insights. That's our future goal, but we haven't reached that point yet. There should be support for REST API data sources to access data from the web. We often have data coming in and communicate with data sources via REST API calls. I don't see that capability in Starburst currently; everything is through JDBC or ODBC. If Starburst could seamlessly access data using REST API capabilities, it would be a game-changer. The self-service data management features, like self-service materialized views, are great, but they can be a bit complex for basic users to understand.

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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 evolution from SageMaker Classic to SageMaker Studio, particularly the UI part of Studio, is commendable."

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

"They offer insights into everyone making calls in my organization."

"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 support is very good with well-trained engineers whose training curriculum is rigorous."

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

"I appreciate the ease of use in Amazon SageMaker."

"SageMaker is a comprehensive platform where I can perform all machine learning activities."

More Amazon SageMaker pros

"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."

"It's very scalable, fast performing, and supports many catalogs."

Cons

"The solution is complex to use."

"The main challenge with Amazon SageMaker is the integrations."

"The user interface (UI) and user experience (UX) of SageMaker and AWS, in general, need improvement as they are not intuitive and require substantial time to learn how to use specific services."

"The documentation must be made clearer and more user-friendly."

"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."

"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."

"Amazon SageMaker can make it simpler to manage the data flow from start to finish, such as by integrating data, usingthe machine, and deploying models. This process could be more user-friendly compared to other tools. I would also like to improve integration with Bedrock and the LLM connection for AWS."

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

More Amazon SageMaker cons

"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."

"There should be support for REST API data sources to access data from the web."

Pricing and Cost Advice

"There is no license required for the solution since you can use it on demand."

"SageMaker is worth the money for our use case."

"Amazon SageMaker is a very expensive product."

"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."

"The solution is relatively cheaper."

"The product is expensive."

More Amazon SageMaker pricing and cost advice

"I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of using Starburst Enterprise can vary based on the amount of data you're processing and the type of machines you opt for, whether on AWS or another cloud platform."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Educational Organization

13%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

44%

Computer Software Company

10%

Energy/Utilities Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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...

See all answers

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?

Before deploying SageMaker, I reviewed the pricing, especially for notebook instances. The cost for small to medium instances is not very high.

See all answers

What is your experience regarding pricing and costs for Starburst Enterprise?

I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of us...

See all answers

What needs improvement with Starburst Enterprise?

See all answers

What is your primary use case for Starburst Enterprise?

We use Starburst with one client who is exploring their ecosystem to remove data silos and enable data access across departments. It's a very big ecosystem, like a finance institute. They are curre...

See all answers

Comparisons

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Compared 17% of the time

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Compared 12% of the time

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Compared 10% of the time

Google Vertex AI vs Amazon SageMaker

Compared 9% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

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Databricks vs Starburst Enterprise

Compared 42% of the time

Starburst Galaxy vs Starburst Enterprise

Compared 17% of the time

Dremio vs Starburst Enterprise

Compared 14% of the time

Alteryx vs Starburst Enterprise

Compared 10% of the time

Apache Spark Streaming vs Starburst Enterprise

Compared 4% of the time

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Product Reports

Buyer's Guide

Amazon SageMaker

March 2025

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Buyer's Guide

Data Science Platforms

March 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)

Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems.

By providing a unified view, Starburst Enterprise helps organizations make better-informed decisions and improve operational efficiency, leading to better customer insights and more accurate forecasting. Overall, Starburst Enterprise is a powerful tool for organizations looking to unlock the full potential of their data.

Starburst

Sample Customers

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

Information Not Available

Buyer's Guide

Amazon SageMaker vs. Starburst Enterprise

March 2025

Free Report: Amazon SageMaker vs. Starburst Enterprise

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