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Qlik Talend Cloud vs Starburst Galaxy comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Feb 22, 2026

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

Qlik Talend Cloud
Ranking in Streaming Analytics
6th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
56
Ranking in other categories
Data Integration (7th), Data Quality (2nd), Data Scrubbing Software (1st), Master Data Management (MDM) Software (3rd), Cloud Data Integration (6th), Data Governance (9th), Cloud Master Data Management (MDM) (3rd), Integration Platform as a Service (iPaaS) (6th)
Starburst Galaxy
Ranking in Streaming Analytics
9th
Average Rating
9.4
Reviews Sentiment
2.6
Number of Reviews
12
Ranking in other categories
Data Science Platforms (7th)
 

Mindshare comparison

As of September 2026, in the Streaming Analytics category, the mindshare of Qlik Talend Cloud is 3.3%, up from 1.1% compared to the previous year. The mindshare of Starburst Galaxy is 1.7%, up from 1.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Qlik Talend Cloud3.3%
Starburst Galaxy1.7%
Other95.0%
Streaming Analytics
 

Featured Reviews

HJ
IT Consultant at a tech services company with 201-500 employees
Has automated recurring data flows and improved accuracy in reporting
The best features of Talend Data Integration are its rich set of components that let you connect to almost any data design intuitive and its strong automation and scheduling capabilities. The TMap component is especially valuable because it allows flexible transformation, joins, and filtering in a single place. I also rely a lot on context variables to manage different environments like Dev, Test, and production, without changing the code. The error handling and logging tools are very helpful for monitoring and troubleshooting, which makes the workflow more reliable. Talend Data Integration has helped our company by automating and standardizing data processes. Before, many of these tasks were done manually, which took more time and often led to errors. With Talend Data Integration, we built automated pipelines that extract, clean, and load data consistently. This not only saves hours of manual effort, but also improves the accuracy and reliability of data. As a result, business teams had faster access to trustworthy information for reporting and decision making, which directly improved efficiency and productivity. Talend Data Integration has had a measurable impact on our organization. By automating daily data loading processes, we reduced manual effort by around three or four hours per day, which saved roughly 60 to 80 hours per month. We also improved data accuracy. Error rates dropped by more than 70% because validation rules were built into the jobs. In addition, reporting teams now receive fresh data at least 50% faster, which means they can make decisions earlier and with more confidence. Overall, Talend Data Integration has increased both efficiency and reliability in our data workflows.
Pedromachado Ventura - PeerSpot reviewer
Data Analyst at a financial services firm with 5,001-10,000 employees
Unified SQL layer has streamlined access to distributed historical data for analytics and reporting
One area that I think could be improved is the experience when performance issues occur. When a query is slow, it is not always immediately obvious to me whether the bottleneck comes from Starburst Galaxy itself, the underlying data source, the query design, or the reporting tool. Better visibility into query performance and easier diagnostics for non-administrators would be useful. Another potential improvement would be enhancing the experience with BI tools to make it more seamless. I work a lot with Power BI, and when you are working with larger data sets, performance can sometimes depend on several different layers. Having more visibility into what is happening between the BI tool, Starburst Galaxy, and the underlying source would be helpful. I also think onboarding could be a little more accessible for analysts. There is good technical documentation, but sometimes I just need to understand the best way to approach a common use case without diving too deep into the platform architecture. The main improvement would be troubleshooting. I have not used the AI capabilities extensively, so I cannot give a detailed assessment. I am not sure if my organization has the full capabilities of Starburst Galaxy, but I think adding AI on top of the data layer is interesting, especially if it can help users discover data, understand data sets, and interact with them more naturally. For governance and security, one of the strengths of Starburst Galaxy is that you can centralize access to data while still controlling what different users are allowed to see. Role-based access, fine-grained permissions, and data masking are important because giving people easier access to data should not mean giving everyone access to everything. I think that is even more important than any AI capabilities that are introduced. If you do introduce AI, I think it should respect exactly the same data permissions and governance rules as the user that is accessing the data.

Quotes from Members

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

Pros

"Talend is a good product and I recommend it."
"It offers advanced features that allow you to create custom patterns and use regular expressions to identify data issues."
"The solution is very user-friendly and easy to understand."
"We have used value frequency and patterns. We have been it impressed with these functions as they have helped us in making decisions in transformation work."
"I really like the fact that there are no out-of-the-box solutions regarding the development of jobs. Other vendors may have modules which cleanse your addresses. In Talend, you have the freedom to completely develop the process yourself. This can be tricky, but it also makes it fun."
"The best features Qlik Talend Cloud offers include the fact that it is built on Java, which gives me the chance to customize my requirements and write my own Java code to achieve my logic."
"Talend Data integration has a wide library of connectors."
"Extract, Transform, and Load (ETL) transformations are open source and is a valuable feature."
"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."
"I am now able to answer questions in a couple of minutes that would otherwise take hours or days of time for my data engineering teams."
"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."
"Starburst Galaxy is becoming a cornerstone of our data platform, empowering us to make smarter and faster decisions across the organization."
"The main positive impact Starburst Galaxy has made is making data more accessible for analytics and reporting."
"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 improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."
 

Cons

"If I am designing something in Talend Data Integration, I cannot backtrack in the flow. For example, if I read data from a source and transform it before applying complex aggregation in the third step, I cannot join this data with the second step."
"In terms of the solution's technical support, the interactions were satisfactory, but there is room for improvement, especially in managing expectations."
"The tool's technical support needs to be better. It doesn't have a local data center but pushes everything to the cloud. They need to check in with customers to see if they're happy and how well the solutions work. They need to assign a customer success manager for the accounts they sell."
"If we encounter issues, it’s most likely when using the Talend Open Studio. The studio can be slow, get stuck, or crash. But again, it can be caused by the resources of your machine or your connection with the repository. If we encounter issues with the Studio we restart the Studio. In emergencies, we create and use a new workspace."
"I wonder if, at the same price, the API component could be added, which would be beneficial."
"The documentation from version to version could be more accurate."
"Not enough material is available for beginners."
"In redundancy analysis, the query is failing to bring non-matched records. This query is an internal script. There is no way (that I know of) to fix this syntax error for future runs."
"I would like to see better alerting integrations for failures and errors in scheduled tasks and maintenance jobs."
"The most persistent issue is the cluster spin-up time."
"As a hosted option, I wish I had more control over the cluster configuration, specifically regarding some of the more advanced options."
"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."
"I would like Starburst to leverage AI to improve usability. Data lakes are complicated and difficult for users to explore."
"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."
 

Pricing and Cost Advice

"I would advise to first take a look and at the Open Studio edition. Figure out what you need and purchase the appropriate license."
"The pricing is a little higher than what I had expected, but it's comparable with I-PASS competitors."
"We did not purchase a separate license for DQ. It is part of our data platform suite, and I believe it is well-priced."
"The tool is cheap."
"The licensing cost for the Talend MDM Platform is paid yearly, but I'm unable to give you the figure. I would rate its price as four out of five because it's on the cheaper side. I'm not aware of any extra costs in addition to the standard licensing fees for the Talend MDM Platform."
"The price of the Talend Data Management Platform is reasonable. The other competing solutions are priced high. Gartner Magic Quadrant identified other solutions, such as Informatica, that are far more expensive."
"I have been using the open-source version."
"It is cheaper than Informatica. Talend Data Quality costs somewhere between $10,000 to $12,000 per year for a seat license. It would cost around $20,000 per year for a concurrent license. It is the same for the whole big data solution, which comes with Talend DI, Talend DQ, and TDM."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Outsourcing Company
12%
Comms Service Provider
11%
Construction Company
8%
Financial Services Firm
25%
Computer Software Company
11%
Manufacturing Company
7%
Construction Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business21
Midsize Enterprise12
Large Enterprise20
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise4
 

Questions from the Community

What needs improvement with Talend Data Quality?
I don't use the automated rule management feature in Talend Data Quality that much, so I cannot provide much feedback. I may not know what Talend Data Quality can improve for data quality. I'm not ...
What is your primary use case for Talend Data Quality?
It is for consistency, mainly; data consistency and data quality are our main use cases for the product. Data consistency is the primary purpose we use it for, as we have written rules in Talend Da...
What advice do you have for others considering Talend Data Quality?
Currently, I'm working with batch jobs and don't perform real-time data quality monitoring because of the large data volume. For real-time, we use a different product. I cannot provide details abou...
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.
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...
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...
 

Also Known As

Talend Data Quality, Talend Data Management Platform, Talend MDM Platform, Talend Data Streams, Talend Data Integration, Talend Data Integrity and Data Governance
No data available
 

Overview

 

Sample Customers

Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group
Information Not Available
Find out what your peers are saying about Qlik Talend Cloud vs. Starburst Galaxy and other solutions. Updated: September 2026.
913,924 professionals have used our research since 2012.