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Qlik Talend Cloud vs Starburst Galaxy comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Nov 18, 2025

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
9th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
54
Ranking in other categories
Data Integration (9th), Data Quality (3rd), Data Scrubbing Software (1st), Master Data Management (MDM) Software (3rd), Cloud Data Integration (7th), Data Governance (8th), Cloud Master Data Management (MDM) (4th), Integration Platform as a Service (iPaaS) (9th)
Starburst Galaxy
Ranking in Streaming Analytics
13th
Average Rating
9.8
Reviews Sentiment
1.0
Number of Reviews
9
Ranking in other categories
Data Science Platforms (10th)
 

Mindshare comparison

As of January 2026, in the Streaming Analytics category, the mindshare of Qlik Talend Cloud is 1.8%, up from 0.9% compared to the previous year. The mindshare of Starburst Galaxy is 1.5%, up from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Qlik Talend Cloud1.8%
Starburst Galaxy1.5%
Other96.7%
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.
reviewer2750097 - PeerSpot reviewer
VP, Business Intelligence at a outsourcing company with 501-1,000 employees
Unified data access improves analytics and simplifies complex processes
I would like to see better alerting integrations for failures and errors in scheduled tasks and maintenance jobs. I also want support for more connectors such as Kinesis and Firehose, support for more file types such as Avro and JSON, and object storage message queue integration for object storage integrations. A single view of query execution and optimization details, rather than needing to toggle between the Galaxy and Trino UI, would be helpful. Additionally, enhanced control over account and environment variables that would be available in the Enterprise edition would be beneficial.

Quotes from Members

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

Pros

"The numerous components provided by Talend mean you’re able to create jobs quickly and efficiently."
"The most valuable features of the Talend Data Management Platform are the components."
"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."
"It’s easy to monitor the processes. Every morning I’ll open the Talend Administration Center to check the status of the process. Within seconds I’m able to see which process ran successfully and which have failed and why they failed."
"tLogRows are also great for finding bad data."
"With its frequency function, we were able to pick a line of business to be addressed first in one of our conversion projects."
"The tool was mainly used for ETL processes to apply governance rules on data."
"They're very competitive in terms of performance, which is a good selling point. It has very rich features. It provides a very rich feature set in the application."
"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."
"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 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 Galaxy is becoming a cornerstone of our data platform, empowering us to make smarter and faster decisions across the organization."
"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."
"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 has provided us with virtually guaranteed performance on complex queries across datasets that are in the tens of gigabytes which complete in seconds."
"Starburst has provided us with virtually guaranteed performance on complex queries across datasets that are in the tens of gigabytes which complete in seconds."
 

Cons

"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."
"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 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."
"Talend Data Integration can be improved by reducing the license cost, as it is a bit high compared to other tools, which can be a burden for small-scale companies wanting to buy a license."
"The stability is good, but the performance is slower when I work on a huge amount of data."
"You can't join more than two tables for analysis."
"Processing large volumes of data sometimes consumes a lot of resources."
"The solution's memory sometimes bottlenecks and that can be challenging."
"I would like Starburst to leverage AI to improve usability. Data lakes are complicated and difficult for users to explore."
"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."
"The most persistent issue is the cluster spin-up time."
"Cluster startup time can be slow, sometimes taking over a minute."
"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."
 

Pricing and Cost Advice

"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 pricing is a little higher than what I had expected, but it's comparable with I-PASS competitors."
"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."
"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."
"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."
"The licensing cost is about 40,000 Euros a year."
"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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
10%
Comms Service Provider
7%
Manufacturing Company
7%
Financial Services Firm
26%
Computer Software Company
14%
Government
8%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business20
Midsize Enterprise11
Large Enterprise20
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise1
 

Questions from the Community

What do you like most about Talend Data Quality?
The most valuable feature lies in the capability to assign data quality issues to different stakeholders, facilitating the tracking and resolution of defective work.
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 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?
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. On the AWS side this ...
What is your primary use case for Starburst Galaxy?
I use the solution for processing large simulation datasets into aggregated datasets that can either be used for real-time data analysis or stored for later analysis.
 

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: December 2025.
881,082 professionals have used our research since 2012.