Qlik Talend Cloud vs Starburst Galaxy comparison

Why PeerSpot?

Qlik and Starburst are both solutions in the Streaming Analytics category. Qlik is ranked #11 with an average rating of 7.9, while Starburst is ranked #9 with an average rating of 9.3. Qlik holds a 3.5% mindshare in SA, compared to Starburst’s 1.7% mindshare. Additionally, 89% of Qlik users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

Qlik Talend Cloud

Read 56 Qlik Talend Cloud reviews

21,375 Views
1,924 Comparison Views

89% willing to recommend

Starburst Galaxy

Read 12 Starburst Galaxy reviews

2,464 Views
1,133 Comparison Views

100% willing to recommend

Qlik Talend Cloud

Starburst Galaxy

Comparison Buyer's Guide

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Executive SummaryUpdated on Feb 22, 2026

Qlik Talend Cloud and Starburst Galaxy compete in data integration and analytics. Qlik Talend Cloud holds an advantage in operational and analytical integration with vast customization, whereas Starburst Galaxy excels in federated querying and adaptability across data warehouses.

Features: Qlik Talend Cloud offers comprehensive data integration tools supporting real-time data sharing among business users, developers, and IT staff. It handles large data volumes with advanced job monitoring and tailored development environments. Starburst Galaxy excels at federated querying for seamless SQL queries across data sources, integrating and executing in environments like Iceberg and Kafka.

Room for Improvement: Qlik Talend Cloud faces challenges with installation errors, memory usage, and stability. Users need improved documentation and data governance frameworks. Starburst Galaxy struggles with cluster spin-up times and lacks robust query monitoring. Users seek better ease of use through AI, seamless data lake exploration, and improved documentation.

Ease of Deployment and Customer Service: Qlik Talend Cloud offers deployment flexibility across on-premises, public, and private clouds with strong customer service and technical support. Starburst Galaxy focuses on cloud-centric deployments and is acknowledged for excellent customer service, though Talend users report occasional support inconsistencies.

Pricing and ROI: Qlik Talend Cloud is cost-effective with an open-source version, yielding ROI through reduced manual work, but users note licensing cost concerns. Starburst Galaxy has transparent, usage-based pricing with potential savings via autoscaling, justifying higher costs for advanced features and specific use cases.

To learn more, read our detailed Qlik Talend Cloud vs. Starburst Galaxy Report (Updated: September 2026).

Buyer's Guide

Qlik Talend Cloud vs. Starburst Galaxy

September 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

Qlik Talend Cloud

Ranking in Streaming Analytics

11th

Average Rating

8.0

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Integration (7th), Data Quality (2nd), Data Scrubbing Software (1st), Master Data Management (MDM) Software (4th), Cloud Data Integration (6th), Data Governance (8th), 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

Ranking in other categories

Data Science Platforms (7th)

Mindshare comparison

As of November 2026, in the Streaming Analytics category, the mindshare of Qlik Talend Cloud is 3.5%, up from 1.2% compared to the previous year. The mindshare of Starburst Galaxy is 1.7%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Starburst Galaxy	1.7%
Qlik Talend Cloud	3.5%
Other	94.8%

Streaming Analytics

Featured Reviews

Henrique Fsantos

Data & Analytics Engineer at PicPay

Automated data pipelines have improved analytics workflows and provide trusted reporting data

The best features of Qlik Talend Cloud are its connectors to many systems, databases, APIs, and files, including both SQL and NoSQL databases. The scheduling feature allows me to run jobs automatically in the cloud, and the built-in data quality tools help clean and check data. The reusable components enable me to reuse jobs and parts, which saves time, making it easy to build good data pipelines. The feature that has made the biggest difference for me in Qlik Talend Cloud is the scheduling and automation, which helps me run ETL jobs automatically without manual work. This saves time, reduces errors, and makes the pipelines more stable. In my daily work, I can trust that the data is updated on time and ready for reports and analytics. Qlik Talend Cloud has had a positive impact on my organization by automating data integration processes, reducing manual errors, and ensuring reliable and up-to-date data for reports and business decisions. This has improved operational stability, productivity, and trust in the data. Since using Qlik Talend Cloud, we have reduced manual work, resulting in approximately 20% to 30% time savings in data load processes. We have also seen a reduction in operational errors, mainly due to automation and the data quality checks, and a clear improvement in data reliability since the pipelines became more standardized and monitored.

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Pedromachado Ventura

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.

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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

"The solution can run on any machine and that is a big advantage."

"The process of upgrading the software is quite easy."

"Better control and flexibility to add/custom define features, to tailor to your needs by modifying its Java generated code."

"It is saving a lot of time. Today, we can mask around a hundred million records in 10 minutes. Masking is one of the key pieces that is used heavily by the business and IT folks. Normally in the software development life cycle, before you project anything into the production environment, you have to test it in the test environment to make sure that when the data goes into production, it works, but these are all production files. For example, we acquired a new company or a new state for which we're going to do the entire back office, which is related to claims processing, payments, and member enrollment every year. If you get the production data and process it again, it becomes a compliance issue. Therefore, for any migrations that are happening, we have developed a new capability called pattern masking. This feature looks at those files, masks that information, and processes it through the system. With this, there is no PHI and PII element, and there is data integrity across different systems. It has seamless integration with different databases. It has components using which you can easily integrate with different databases on the cloud or on-premise. It is a drag and drop kind of tool. Instead of writing a lot of Java code or SQL queries, you can just drag and drop things. It is all very pictorial. It easily tells you where the job is failing. So, you can just go quickly and figure out why it is happening and then fix it."

"Talend's most valuable feature is its ability to generate code and packages efficiently."

"We’re also able to respond much more quickly to changes and demands from the business, as we can create and change jobs quickly and provide new data for reports within hours."

"Talend Data Integration has positively impacted my organization because it is used for master management data, which I think most other components lack, but Talend Data Integration has that capability for using master management data as standard data."

"The solution is very user-friendly and easy to understand."

More Qlik Talend Cloud pros

"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."

"<p>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.</p>"

"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 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 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 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."

"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."

More Starburst Galaxy pros

Cons

"In terms of the solution's technical support, the interactions were satisfactory, but there is room for improvement, especially in managing expectations."

"Sometimes there are bugs which are unidentified and we have to follow-up with the Talend team to resolve them. In a critical situation, it takes time for them to update patches."

"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."

"Not enough material is available for beginners."

"Qlik Talend Cloud is doing well, but one improvement could be the integration of development functionalities we use in Talend Studio directly onto the Talend browser."

"Once you get past the basic tools, it gets pretty complicated."

"NullPointerExceptions are going to be the death of me and are a big reason for our transition away from Talend. One day, it is fine with a 1000 blank rows, then the next day, it will find one blank cell and it breaks down."

"The stability is good, but the performance is slower when I work on a huge amount of data."

More Qlik Talend Cloud 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."

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

"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."

"As a hosted option, I wish I had more control over the cluster configuration, specifically regarding some of the more advanced options."

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

"I would like to see better alerting integrations for failures and errors in scheduled tasks and maintenance jobs."

"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."

More Starburst Galaxy cons

Pricing and Cost Advice

"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."

"License renewal is on a yearly basis."

"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 product pricing is considered very good, especially compared to other data integration tools in the market."

"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."

"The pricing is a little higher than what I had expected, but it's comparable with I-PASS competitors."

"I would advise to first take a look and at the Open Studio edition. Figure out what you need and purchase the appropriate license."

"We did not purchase a separate license for DQ. It is part of our data platform suite, and I believe it is well-priced."

More Qlik Talend Cloud pricing and cost advice

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

Financial Services Firm

29%

Computer Software Company

10%

Manufacturing Company

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	21
Midsize Enterprise	12
Large Enterprise	20

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

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 ...

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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...

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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...

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?

See all answers

What is your primary use case for Starburst Galaxy?

I have mainly used Starburst Galaxy as a query and access layer for analytical data, as my current work involves dealing with data stored across different platforms, including Hive and SingleStore....

See all answers

Comparisons

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Compared 2% of the time

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Compared 2% of the time

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Compared 19% of the time

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Compared 10% of the time

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Compared 6% of the time

Altair RapidMiner vs Starburst Galaxy

Compared 5% of the time

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Product Reports

Buyer's Guide

Qlik Talend Cloud

October 2026

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Buyer's Guide

Starburst Galaxy

October 2026

Download Starburst Galaxy product report

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

Qlik Talend Cloud provides robust data integration tools tailored for efficient management of large volumes, offering real-time data access, Java integration, and custom code capabilities for developers.

Qlik Talend Cloud is known for its extensive connectivity options, enabling seamless integration across different platforms, such as S3, Redshift, Oracle, and SQL Server. The central repository facilitates consistent metadata access throughout organizations, enhancing collaboration. Despite its strengths in advanced monitoring, automation, and user-friendly drag-and-drop interfaces, users face challenges with installation stability, technical support, documentation inconsistencies, and complexities in learning. Performance concerns also include multitasking limitations and excessive memory usage. The platform's licensing costs can be prohibitive for smaller companies, while demands for improved data governance and intuitive code management continue. Its applications in healthcare data parsing, ETL task automation, and diverse data platform integration demonstrate its utility, although there's a constant demand for better scalability and efficient transformations.

What are the key features?

Seamless Real-Time Data Access: Ensures that users can access the latest information across systems without delays for better decision-making.
Java Integration: Facilitates smooth incorporation of Java components into workflows, broadening development options.
Custom Code Development: Offers flexibility to develop tailored solutions to meet specific integration scenarios.
Vast Connectors: Enhances connectivity between multiple platforms, supporting comprehensive data integration strategies.
Central Repository: Allows for uniform metadata access across departments, promoting cohesive data management practices.
Automation and Monitoring: Streamlines workflows with advanced automation and monitoring, reducing manual intervention and errors.

What benefits and ROI should users evaluate?

Improved Data Quality: Tools for data matching and error handling ensure high-quality, reliable data for analytics and reporting.
Efficient Workflow Streamlining: Drag-and-drop interfaces and automation features simplify complex workflows, enhancing operational efficiency.
Enhanced Business Insights: By integrating diverse data sources, businesses can derive deeper insights and ensure compliance through better data management.
Cost Management: Although some users find licensing expensive, comprehensive feature sets aimed at improving data processes can justify costs.
Community Support: Users benefit from active community forums that provide assistance, although technical support also necessitates enhancements.

In specialized industries like healthcare, users leverage Qlik Talend Cloud for data integration and transformation, aiding in compliance and analytics. Compatibility with cloud and on-premises systems ensures adaptability to complex data tasks, facilitating business application development. Organizations focus on enhanced data ingestion and quality checks for comprehensive solutions.

Qlik

Starburst Galaxy enhances data management with fast querying, flexible data integration, and efficient cost handling, offering seamless connectivity to numerous data platforms and formats.

Starburst Galaxy stands out for its exceptional query speed and flexibility, offering effective federated querying and cluster management. It facilitates connection to multiple data warehouses and supports writing to varied formats. The intuitive interface simplifies navigation and administration while segmenting expenses for better cost management. Users can efficiently perform query federation across data systems and the compatibility with AWS Glue ensures quick onboarding. Its SQL-friendly architecture, object storage, and indexing capabilities make it highly valued.

What are the key features of Starburst Galaxy?

Federated Querying: Efficiently performs cross-database queries connecting multiple data sources like Amazon S3 and Google Sheets.
Cluster Management: Simplifies the administration and optimization of clusters, enhancing operational efficiency.
Data Integration: Supports numerous data warehouses, promoting seamless data integration and real-time analysis.
Compatibility with AWS: Offers improved user experience with quick onboarding and seamless integration services.
Object Storage: Provides robust data storage and management capabilities with effective indexing.

What benefits or ROI should users look for?

Cost Efficiency: Effectively manages expenses by segmenting costs, optimizing resource allocation.
Data Accessibility: Facilitates easy and flexible access to large datasets for analysis and reporting.
Scalability: Supports expansion and scaling to handle growing datasets and increased data sources.
Enhanced Analytics: Integrates with analytics tools like Tableau and Power BI for comprehensive insights.

Starburst Galaxy is widely used in sectors that require extensive data analysis like finance, health, and retail. It efficiently supports connecting and analyzing data from varied sources, allowing companies to perform real-time analysis and comprehensive reporting, thereby enhancing decision-making processes.

Starburst

Sample Customers

Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group

Information Not Available

Buyer's Guide

Qlik Talend Cloud vs. Starburst Galaxy

September 2026

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