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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

"The product's integration with PostgreSQL and Jira has been helpful for us. Its performance is good. However, we do not use it for large data sets."
"The features that I like the most are the simplicity of the interface, and the ability to quickly develop with a predefined component."
"Maybe the best thing is the product's easy start-up level when you are familiar with Java."
"Coming into the department with no knowledge of Talend, the interface has been user-friendly enough to allow me to come up to speed in four to five months on almost all its functions and use it like a pro."
"The file fetch process is impeccable."
"The primary use case is for data ingestion."
"The most valuable feature is the data loading and scripting language"
"The numerous components provided by Talend mean you’re able to create jobs quickly and efficiently."
"Starburst Galaxy has significantly improved our data architecture flexibility and performance management by solving cross-database query challenges and enabling us to utilize iceberg tables externally across our entire data ecosystem."
"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 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."
"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 has improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."
"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."
"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."
 

Cons

"I think the subscription-based model is concerning because as I mentioned, some of our other projects are migrating to different tools."
"The setup cost is very expensive."
"You can't join more than two tables for analysis."
"Sometimes when working with larger datasets (possibly due to insufficient memory)."
"I'd be interested in seeing the running of Python programs and transformations from within the studio itself."
"Qlik Talend Cloud could be improved with more advanced monitoring and flexible alerts, as well as better job performance visibility."
"The stability is good, but the performance is slower when I work on a huge amount of data."
"They don't have any AI capabilities. Talend DQ is specifically for data quality, which only has data profiling."
"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."
"There is still room for improved usability and diagnostics, especially for users who are not platform specialists."
"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."
"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 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."
"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."
 

Pricing and Cost Advice

"The solution's pricing is very reasonable and half the cost of Informatica."
"Moreover, the pricing structure stands out as highly competitive compared to other offerings in the market, making it a cost-effective choice for users."
"The tool is cheap."
"The licensing cost is about 40,000 Euros a year."
"It's a subscription-based platform, we renew it every year."
"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 product pricing is considered very good, especially compared to other data integration tools in the market."
"The price is on a per-user basis. It's a little more expensive than other tools. There aren't any additional costs beyond the standard licensing fee."
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
26%
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.
914,109 professionals have used our research since 2012.