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IBM Watson Studio vs Starburst Galaxy comparison

 

Comparison Buyer's Guide

Executive Summary

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

IBM Watson Studio
Ranking in Data Science Platforms
10th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
15
Ranking in other categories
AI Development Platforms (10th)
Starburst Galaxy
Ranking in Data Science Platforms
13th
Average Rating
10.0
Reviews Sentiment
1.0
Number of Reviews
3
Ranking in other categories
Streaming Analytics (17th)
 

Mindshare comparison

As of August 2025, in the Data Science Platforms category, the mindshare of IBM Watson Studio is 2.0%, down from 2.3% compared to the previous year. The mindshare of Starburst Galaxy is 0.8%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Abilio Duarte - PeerSpot reviewer
A highly robust and well-documented platform that simplifies the complex world of AI
The main challenge lies in visibility and ease of use. Providing training sessions can be immensely helpful in helping users navigate and understand the tool's potential. This approach would empower users to explore and make the most of the tools and technologies at their disposal. Another area where IBM could enhance its offering is by providing more visibility to end users regarding the vast potential that Watson offers.
reviewer2748021 - PeerSpot reviewer
Has a cost-effective transformation for data management as efficient querying enhances productivity
We have experienced several improvements across our organization. Our data ingestion processes previously involved copying data from S3 to Snowflake, which was fairly costly and required constant vigilance to purge old data so that our source tables would not bloat. Now we are able to move ingestion staging data to Iceberg tables, resulting in a much better experience in terms of both compute and storage costs as well as maintenance. Data transformation has also become more efficient. Starburst on Trino, combined with our SQL-native data transformation tool SQLMesh, has delivered anywhere from a two to five times improvement in compute performance across our transformation DAG. This improvement is largely due to how efficiently Trino scans relevant data without requiring any additional setup, such as defining partitions in Snowflake. In terms of cost effectiveness, we are already forecasting a 25% reduction in cloud data provider spending, even while continuing to use both Snowflake and Starburst. This is because we are able to shift a significant amount of compute to Galaxy, and the cost difference compared to our previous approach of running jobs exclusively on Snowflake is substantial.

Quotes from Members

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

Pros

"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"Watson Studio is the most complete tool for AI projects."
"Watson Studio is very stable."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"IBM Watson Studio consistently automates across channels."
"Watson Studio is the most complete tool for AI projects."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"The scalability of IBM Watson Studio is great."
"Starburst on Trino, combined with our SQL-native data transformation tool SQLMesh, has delivered anywhere from a two to five times improvement in compute performance across our transformation DAG."
 

Cons

"The initial setup was complex."
"The main challenge lies in visibility and ease of use."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"So a better user interface could be very helpful"
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"The decision making in their decision making feature is less good than other options."
"I think maybe the support is an area where it lacks."
"One area that could be improved is the backup and restoration of the database and the overall database configuration."
"The most persistent issue is the cluster spin-up time."
 

Pricing and Cost Advice

"The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."
"IBM Watson Studio is a reasonably priced product"
"IBM Watson Studio is an expensive solution."
"Watson Studio's pricing is reasonable for what you get."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
10%
Educational Organization
8%
Financial Services Firm
34%
Computer Software Company
10%
University
7%
Government
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for IBM Watson Studio?
IBM Watson Studio is considered rather expensive, with a rating of six or seven. The pricing could be optimized relative to the features and capabilities of the product.
What needs improvement with IBM Watson Studio?
IBM Watson Studio, while powerful, lacks user-friendliness. It is not easy to use, particularly for medium or small enterprises or less experienced staff. Another aspect that requires improvement i...
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Earn 20 points
 

Also Known As

Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
No data available
 

Overview

 

Sample Customers

GroupM, Accenture, Fifth Third Bank
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