IBM Watson Studio vs Starburst Galaxy comparison

IBM and Starburst are both solutions in the Data Science Platforms category. IBM is ranked #17 with an average rating of 7.3, while Starburst is ranked #6 with an average rating of 9.5. IBM holds a 2.2% mindshare in Data Science Platforms, compared to Starburst’s 1.5% mindshare. Additionally, 100% of IBM users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

IBM Watson Studio

Read 19 IBM Watson Studio reviews

3,415 Views
2,254 Comparison Views

100% willing to recommend

Starburst Galaxy

Read 11 Starburst Galaxy reviews

1,681 Views
1,328 Comparison Views

100% willing to recommend

IBM Watson Studio

Starburst Galaxy

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between IBM Watson Studio and Starburst Galaxy based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed IBM Watson Studio vs. Starburst Galaxy Report (Updated: June 2026).

Buyer's Guide

IBM Watson Studio vs. Starburst Galaxy

June 2026

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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

IBM Watson Studio

Ranking in Data Science Platforms

17th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

AI Development Platforms (16th)

Starburst Galaxy

Ranking in Data Science Platforms

6th

Average Rating

9.4

Reviews Sentiment

2.5

Number of Reviews

Ranking in other categories

Streaming Analytics (8th)

Mindshare comparison

As of June 2026, in the Data Science Platforms category, the mindshare of IBM Watson Studio is 2.2%, up from 2.1% compared to the previous year. The mindshare of Starburst Galaxy is 1.5%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Starburst Galaxy	1.5%
IBM Watson Studio	2.2%
Other	96.3%

Data Science Platforms

Featured Reviews

reviewer2715654

Director and Marketing Consultant at a non-tech company with 1-10 employees

Collaborative analytics workspace has improved campaign insights and saves weekly manual effort

One of the best features IBM Watson Studio offers is the ability to collaborate across teams using a centralized workspace. The centralized workspace helps my team collaborate because we did not need to spend excessive time on manual processes. This helped us collaborate across teams by selecting which data and which channels should be reflected in IBM Watson Studio. In this way, we saved time and could easily see campaign outcomes and make better data-driven marketing decisions. IBM Watson Studio has positively impacted my organization by being time-efficient and enabling collaboration, as we can see everything in one screen. It helped improve our efficiency and provided deeper customer insights that enable better decision-making. It definitely helped our weekly time efficiency by saving manual workload because we have a lot of work going on. It really helped us in analyzing the data and analytics.

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Niketan Kumar

Advisory Solutions Architect at Dell Technologies

Unified data querying has accelerated petabyte-scale analytics and simplified dashboard delivery

Starburst Galaxy offers me several best features, which include very fast querying results, automatic indexing of data for long tables, a cost-based optimizer which reduces the time to query large tables, and an agentic feature that lets me talk to my data.I find myself relying most on querying from different databases as well as automatic indexing in my day-to-day work, as I am a data science architect who needs to get the queries in a very short period of time. Starburst Galaxy serves the best purpose for me because if my SLAs are not met with my customers, they will raise a case, and I have tried many other tools, but Starburst Galaxy fits the best. Starburst Galaxy has positively impacted my organization since we were struggling with Denodo and Dremio, which had their own features but were not helpful in querying large amounts of data, especially semi-structured or unstructured data. Starburst Galaxy addresses this with many YAML files and manifest files for automated maintenance, and it helps reduce the small file problem in different HDFS systems. Additionally, Starburst Galaxy has an MCP server that connects to various agentic pipelines, reducing the time to market for data consumption.

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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

"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."

"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."

"The features I find most valuable in IBM Watson Studio are machine learning support and testing different models for a use case, which is one of the best features on the system."

"The solution was a deployed model and I was just installing the API, sending some data and returning some data from REST API, and it was very easy to use."

"In my experience, AutoML is the most valuable feature of IBM Watson Studio."

"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."

"It has greatly improved the performance because it is standardized across the company."

"IBM Watson Studio has positively impacted my organization by being time-efficient and enabling collaboration, as we can see everything in one screen."

More IBM Watson Studio pros

"Starburst Galaxy has improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."

"The most fundamental feature is the query engine, which is much faster than any of the competitors; Starburst is able to finish most queries within 10 seconds, which is especially important for many non-technical employees."

"Starburst Galaxy serves the best purpose for me because if my SLAs are not met with my customers, they will raise a case, and I have tried many other tools, but Starburst Galaxy fits the best."

"Starburst Galaxy is becoming a cornerstone of our data platform, empowering us to make smarter and faster decisions across the organization."

"Starburst Galaxy serves as our primary SQL-based data processing engine, a strategic decision driven by its seamless integration with our AWS cloud infrastructure and its ability to deliver high performance with low-latency responses."

"Starburst has provided us with virtually guaranteed performance on complex queries across datasets that are in the tens of gigabytes which complete in seconds."

"I use Starburst as a cost-efficient hosted option for Trino for data integration and ad-hoc analysis across a broad range of data sources."

"Starburst Galaxy has positively impacted my organization by allowing us to rethink the strategy for data and architect data differently; instead of having multiple data marts and siloed data marts, we have a unified vision, and that is how it is changing."

More Starburst Galaxy pros

Cons

"Some of the solutions are really good solutions but they can be a little too costly for many."

"The initial setup was complex."

"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."

"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."

"We would like to see it more web-based with more functionality."

"IBM Watson Studio can be improved because there is currently a learning curve."

"One area that could be improved is the backup and restoration of the database and the overall database configuration."

"I want IBM's technical support team to provide more specific answers to queries."

More IBM Watson Studio cons

"I think there are areas of improvement with respect to AI adaptability, and also in general, the amount of connectors working with other tools are areas where it can be expanded."

"Cluster startup time is another pain point, typically 3 to 5 minutes, which is not the worst with proper planning but can be annoying for ad-hoc work."

"The most persistent issue is the cluster spin-up time."

"Starburst Galaxy can be improved by discovering unstructured data and building in streaming ingestion because we are currently using Kafka for that purpose."

"Multi-tenancy could be improved. In order to have multiple environments for SSO, we maintain multiple tenants that are connected to different AWS accounts via the Marketplace."

"I would like Starburst to leverage AI to improve usability. Data lakes are complicated and difficult for users to explore."

"Cluster startup time can be slow, sometimes taking over a minute."

Pricing and Cost Advice

"IBM Watson Studio is an expensive solution."

"IBM Watson Studio is a reasonably priced product"

"The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."

"Watson Studio's pricing is reasonable for what you get."

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Manufacturing Company

10%

Construction Company

University

Financial Services Firm

29%

Computer Software Company

12%

University

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	14
Midsize Enterprise	2
Large Enterprise	12

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	3

Questions from the Community

What is your experience regarding pricing and costs for IBM Watson Studio?

The pricing for IBM Watson Studio is very high, but we are talking about an enterprise solution. Most of the time we try to convince the customer with the price because it is a robust and enterpris...

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What needs improvement with IBM Watson Studio?

I have not used the AutoAI feature yet, if it is a feature in IBM Watson Studio. I think the user experience of IBM Watson Studio can be improved, as I am trying to use other products outside IBM a...

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What is your primary use case for IBM Watson Studio?

IBM Watson Studio is used primarily with our customers, though we have also tested it in our company and laboratories. I am also dealing with products like IBM Watson Studio and IBM Cognos.

See all answers

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

I recommend experimenting with different cluster sizes to determine what works best for your particular use case.

See all answers

What needs improvement with Starburst Galaxy?

Starburst Galaxy can be improved by discovering unstructured data and building in streaming ingestion because we are currently using Kafka for that purpose. We rely on third-party tools for ingesti...

See all answers

What is your primary use case for Starburst Galaxy?

My main use case for Starburst Galaxy is querying petabytes of data across vast data sources, and I use a federated query engine to join data sources from different databases and then join them usi...

See all answers

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Compared 4% of the time

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Compared 22% of the time

Databricks vs Starburst Galaxy

Compared 10% of the time

Dremio vs Starburst Galaxy

Compared 6% of the time

Qlik Talend Cloud vs Starburst Galaxy

Compared 6% of the time

Domino Data Science Platform vs Starburst Galaxy

Compared 3% of the time

More Starburst Galaxy Competitors

Product Reports

Buyer's Guide

IBM Watson Studio

June 2026

Download IBM Watson Studio product report

Buyer's Guide

Starburst Galaxy

May 2026

Download Starburst Galaxy product report

Also Known As

Watson Studio, IBM Data Science Experience, Data Science Experience, DSx

No data available

Overview

IBM Watson Studio offers comprehensive support for machine learning lifecycles with a focus on collaboration and automation, integrating open-source tools for ease of use by developers and data scientists.

IBM Watson Studio provides end-to-end management of machine learning processes, supporting tasks from data validation to model deployment and API integration. Its integration with Jupyter Notebook is highly regarded, allowing seamless development and deployment of machine learning models. Users benefit from flexible machine-learning frameworks and strong visual tools that enhance productivity, with multi-cloud support further boosting efficiency. Despite some concerns about interface complexity and responsiveness with large datasets, Watson Studio remains a cost-effective, time-saving solution for predictive analytics and algorithm development.

What are Watson Studio's Key Features?

AutoAI and AutoML: Automates model building and deployment, saving time.
Open-source Integration: Supports popular tools like Jupyter Notebook for smoother workflows.
Seamless Deployment: Strong capabilities for deploying models across various environments.
Flexible Frameworks: Supports a wide range of machine-learning frameworks.
Multi-cloud Support: Enhances deployment and operational efficiency.

What Benefits and ROI can Users Expect?

Cost-effectiveness: Provides a budget-friendly way to manage machine learning projects.
Time Efficiency: Streamlined processes and automation reduce execution time.
Enhanced Cash Management: Predictive models assist in cash flow analysis.
User Experience: Improved data insights lead to better customer experiences.

IBM Watson Studio is implemented across industries for tasks like marketing analytics, chatbot development, and AI-driven data studies. It aids in data cleansing and algorithm development, including radar sensor applications, optimizing decision-making and enhancing experiences in fields such as operations data analysis and predictive analytics.

IBM

Starburst Galaxy offers rapid query speeds and robust cluster management, enhancing data engineering efficiency while supporting AWS integrations and cross-database functionality. Users benefit from its advanced data integration and federated querying capabilities.

Starburst Galaxy stands out with a compute-focused architecture that excels in facilitating seamless data integration. Technological innovations like autoscaling clusters and automated metadata management optimize operations in multi-tenant environments. With a keen emphasis on compatibility, the platform provides support for AWS Glue and enables federated querying across S3, Snowflake, and Redshift. This adaptability ensures comprehensive ETL processes and enhances analytics through querying SQL Server, Google Sheets, and blob stores. While noted for its robust capabilities, users seek improvements in cluster startup times, Tableau and AI support, and desire infrastructure-as-code enhancements.

What are Starburst Galaxy's key features?

Rapid Query Speeds: Enhances data processing with quick responses.
Cluster Autoscaling: Optimizes resource allocation for varying workloads.
Federated Querying: Cross-database functionality for seamless integration.
Compute-Focused Architecture: Ensures efficiency and scalability.
Automated Metadata Management: Streamlines data handling processes.
AWS Integration: Broad compatibility with AWS services.

What benefits should users evaluate in reviews?

Data Engineering Efficiency: Reduces operating expenses and improves productivity.
Cost Reduction: Highlights lower storage costs with efficient data handling.
Seamless Integration: Enables robust data integration across various platforms.
Cluster Management: Supports diverse workloads with advanced management tools.

In industries focusing on large-scale data efforts, Starburst Galaxy plays an essential role in connecting data sources like Amazon S3 and RDS, streamlining tasks in data engineering and ad-hoc analysis across complex environments. Teams leverage its cross-database querying to boost AWS analytics, with features tailored for sectors needing agile data solutions, from ETL pipelines to secure data federation.

Starburst

Sample Customers

GroupM, Accenture, Fifth Third Bank

Information Not Available

Buyer's Guide

IBM Watson Studio vs. Starburst Galaxy

June 2026

Free Report: IBM Watson Studio vs. Starburst Galaxy

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