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Amazon SageMaker vs Starburst Enterprise comparison

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Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Ranking in Data Science Platforms
10th
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
Amazon SageMaker
Ranking in Data Science Platforms
5th
Average Rating
7.6
Reviews Sentiment
9.1
Number of Reviews
27
Ranking in other categories
AI Development Platforms (4th)
Starburst Enterprise
Ranking in Data Science Platforms
14th
Average Rating
8.6
Number of Reviews
2
Ranking in other categories
Streaming Analytics (12th)
 

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Amazon SageMaker is 7.7%, down from 10.4% compared to the previous year. The mindshare of Starburst Enterprise is 2.1%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

AbakarAhmat - PeerSpot reviewer
Sep 21, 2023
Enhancing survey analysis that provides valued insightfulness
I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…
Natu Lauchande - PeerSpot reviewer
Feb 27, 2024
Easy to use and manage, but the documentation does not have a lot of information
We use the product for deploying machine learning models. We use it for the machine learning model development process We're currently implementing a project on a cross-selling model. It is like a standard XGBoost model. I’m evaluating the tool to see whether it will improve the workflow.…
KamleshPant - PeerSpot reviewer
Aug 22, 2024
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.

Quotes from Members

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

Pros

"The software offers consistency across multiple research projects helping us with predictive analytics capabilities."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."
"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"It is perfectly adequate if all you need are the results and not the trail of evidence."
"Most of the product features are good but I particularly like the linear regression analysis."
"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."
"Amazon SageMaker is highly valuable for managing ML workloads. It connects to AWS cloud resources, making it easy to deploy algorithms and collaborate using tools like GitLab. It offers a wide range of Python libraries and other necessary tools for modelling and algorithms."
"SageMaker offers functionalities like Jupyter Notebooks for development, built-in algorithms, model tuning, and options to deploy models on managed infrastructure."
"The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."
"The tool makes our ML model development a bit more efficient because everything is in one environment."
"We've had no problems with SageMaker's stability."
"The technical support of the tool was good."
"The most valuable features are the ability to store artifacts and gather reports and measures from experiments."
"It's very scalable, fast performing, and supports many catalogs."
"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."
 

Cons

"The technical support should be improved."
"The solution needs to improve forecasting using time series analysis."
"In some cases, the product takes time to load a large dataset. They could improve this particular area."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"It could provide even more in the way of automation as there are many opportunities."
"Improvements are needed in the user interface, particularly in terms of user-friendliness."
"The statistics should be more self-explanatory with detailed automated reports."
"It could allow adding color to data models to make them easier to interpret."
"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."
"There are other better solutions for large data, such as Databricks."
"The product must provide better documentation."
"The solution needs to be cheaper since it now charges per document for extraction."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"Lacking in some machine learning pipelines."
"AI is a new area and AWS needs to have an internship training program available."
"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."
"There should be support for REST API data sources to access data from the web."
"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."
 

Pricing and Cost Advice

"It's quite expensive, but they do a special deal for universities."
"More affordable training for new staff members."
"I rate the tool's pricing a five out of ten."
"The price of IBM SPSS Statistics could improve."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"We think that IBM SPSS is expensive for this function."
"The price of this solution is a little bit high, which was a problem for my company."
"There is no license required for the solution since you can use it on demand."
"The solution is relatively cheaper."
"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."
"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."
"The pricing could be better, especially for querying. The per-query model feels expensive."
"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."
"SageMaker is worth the money for our use case."
"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
16%
University
10%
Computer Software Company
9%
Manufacturing Company
8%
Financial Services Firm
18%
Educational Organization
14%
Computer Software Company
11%
Manufacturing Company
8%
Financial Services Firm
44%
Computer Software Company
10%
Healthcare Company
5%
Energy/Utilities Company
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
While the pricing of the product may be higher, the accompanying service and features justify the investment. However...
What needs improvement with IBM SPSS Statistics?
In some cases, the product takes time to load a large dataset. They could improve this particular area.
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 designe...
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 Cha...
What is your experience regarding pricing and costs for Amazon SageMaker?
The license cost for Amazon SageMaker ranges between seven thousand to fifteen thousand dollars per month depending o...
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...
What needs improvement with Starburst Enterprise?
There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the f...
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 ...
 

Also Known As

SPSS Statistics
AWS SageMaker, SageMaker
No data available
 

Learn More

 

Overview

 

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
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Find out what your peers are saying about Amazon SageMaker vs. Starburst Enterprise and other solutions. Updated: October 2024.
814,649 professionals have used our research since 2012.