CloverDX Designer vs Qlik Talend Cloud comparison

Why PeerSpot?

CloverDX and Qlik are both solutions in the Data Integration category. CloverDX is ranked #88, while Qlik is ranked #8 with an average rating of 7.8. CloverDX holds a 0.3% mindshare in DI, compared to Qlik’s 2.5% mindshare. Additionally, 100% of CloverDX users are willing to recommend the solution, compared to 89% of Qlik users who would recommend it.

CloverDX Designer

Read 1 CloverDX Designer review

1,048 Views
1,027 Comparison Views

100% willing to recommend

Qlik Talend Cloud

Read 56 Qlik Talend Cloud reviews

19,499 Views
7,995 Comparison Views

89% willing to recommend

CloverDX Designer

Qlik Talend Cloud

Comparison Buyer's Guide

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Executive SummaryUpdated on Feb 22, 2026

Qlik Talend Cloud and CloverDX Designer are competitors in the data integration space. CloverDX Designer seems to have the upper hand in terms of features and customization, although Qlik Talend Cloud takes the lead in pricing and support options.

Features: Qlik Talend Cloud provides comprehensive integration capabilities, scalability, and suitability for varied data environments. CloverDX Designer, however, offers advanced data transformation, workflow capabilities, and higher customization and flexibility with deeper data processing proficiency.

Ease of Deployment and Customer Service: Qlik Talend Cloud features a straightforward cloud-based deployment with robust support options. CloverDX Designer, although more complex to deploy owing to its customization, benefits from strong customer service, appealing to users with detailed data handling needs.

Pricing and ROI: Qlik Talend Cloud is cost-effective with a swift ROI, favoring budget-conscious businesses. CloverDX Designer, despite its higher initial investment, delivers long-term value and ROI for enterprises requiring sophisticated data processing.

To learn more, read our detailed Data Integration Report (Updated: September 2026).

Buyer's Guide

Data Integration

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

CloverDX Designer

Ranking in Data Integration

88th

Average Rating

7.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Qlik Talend Cloud

Ranking in Data Integration

8th

Average Rating

8.0

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Quality (2nd), Data Scrubbing Software (1st), Master Data Management (MDM) Software (2nd), Cloud Data Integration (7th), Data Governance (9th), Cloud Master Data Management (MDM) (3rd), Streaming Analytics (6th), Integration Platform as a Service (iPaaS) (7th)

Mindshare comparison

As of October 2026, in the Data Integration category, the mindshare of CloverDX Designer is 0.3%, up from 0.3% compared to the previous year. The mindshare of Qlik Talend Cloud is 2.5%, up from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Qlik Talend Cloud	2.5%
CloverDX Designer	0.3%
Other	97.2%

Data Integration

Featured Reviews

reviewer1518951

Data professional at a financial services firm with 1,001-5,000 employees

Simple, stable, and allows us to handle data from various sources, but needs enterprise features for logging, recoverability, and monitoring

If I could give any advice to the guys who are developing it, I would suggest them to really look at the enterprise features, such as being able to log what's going on, being able to capture the current state of processing, and being able to recover from error situations. So, there should be a focus on logging, recoverability, and monitoring. We should be able to monitor what's going on, and in case of any issues, we should be able to recover and restart processing and other things. For scalability and performance, I would probably suggest the Pushdown feature so that you can do the transformation directly on the data source. You do not need to do that calculation within the ETL server. For this, you should be aware of the type of data because each database or kind of storage, such as Hadoop, has its own ANSI standard or language, such as SQL. Microsoft, Oracle, and IBM have their own language. Based on the feedback that I have got, its initial setup takes some time. It could perhaps be simpler.

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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.

Read full review

Quotes from Members

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

Pros

"Its simplicity and the way it handles graphs are the most valuable features."

"Extract, Transform, and Load (ETL) transformations are open source and is a valuable feature."

"The numerous components provided by Talend mean you’re able to create jobs quickly and efficiently."

"Before, when we wanted solutions and REST APIs, we handed it over to an external company, so it took time, back and forth and all that, but now, with Qlik Talend Cloud, when we want a service, we create it, and in at most one or two days the service is in production and usable, so we save a lot of time."

"If your use case depends on heterogeneous sources like Salesforce, SAP, and some other product information systems, I would recommend Talend."

"The basic tools are easy to pick up and understand."

"If you are looking for something that is stable, cost-effective and has a great ROI, then Talend is a great choice."

"We are still in the process of evaluating them, but I love the way things look in Talend, and I'm all for Talend."

"tLogRows are also great for finding bad data."

More Qlik Talend Cloud pros

Cons

"If I could give any advice to the guys who are developing it, I would suggest them to really look at the enterprise features, such as being able to log what's going on, being able to capture the current state of processing, and being able to recover from error situations. So, there should be a focus on logging, recoverability, and monitoring. We should be able to monitor what's going on, and in case of any issues, we should be able to recover and restart processing and other things. For scalability and performance, I would probably suggest the Pushdown feature so that you can do the transformation directly on the data source. You do not need to do that calculation within the ETL server. For this, you should be aware of the type of data because each database or kind of storage, such as Hadoop, has its own ANSI standard or language, such as SQL. Microsoft, Oracle, and IBM have their own language. Based on the feedback that I have got, its initial setup takes some time. It could perhaps be simpler."

"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."

"Qlik Talend Cloud has impacted my organization by increasing the license cost, leading many companies to decide to decommission Talend, as they find the cost too high."

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

"They don't have any AI capabilities. Talend DQ is specifically for data quality, which only has data profiling. With Talend DQ, I cannot generate any reports today, so I need an ETL tool. It provides general Excel files, or I have to create some views. If instead of buying a new tool, Talend provides a reporting capability or solution, it would be great. It will reduce the development effort for creating these kinds of reports. We also manage the infrastructure for Talend. From the licensing perspective, for cloud, they only have seat licenses where one person is tied to one license, but for on-premise, they have concurrent licenses. It would be really awesome if they can provide concurrent licenses for the cloud so that if one person is not there, somebody else can use that license. Currently, it is not possible unless a person deactivates his or her license and moves the same seat license to someone else. We are one of the biggest customers in the central zone of the US for Talend, and this is the feedback that we have provided them again and again, but they come back and say that they aren't able to provide concurrent licenses on the cloud. In version 7.3, there is a feature for tokenization and de-tokenization of data. This is the feature that we are looking for. It is useful if somebody wants to see what we have masked and how do we demask it. This feature is not there in version 7.1. There are also a few other capabilities on the cloud, but we don't yet have a big footprint in the cloud."

"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."

"There are too many functions which could be streamlined."

"The biggest challenge with Talend was its performance."

"SQL for displaying underlying data in non-match results does not work."

More Qlik Talend Cloud cons

Pricing and Cost Advice

"Its price and value for money would be okay for our purpose if there were some additional features."

"The solution's pricing is very reasonable and half the cost of Informatica."

"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."

"License renewal is on a yearly basis."

"The licensing cost is about 40,000 Euros a year."

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

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

"It's a subscription-based platform, we renew it every year."

More Qlik Talend Cloud pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

14%

Outsourcing Company

12%

Comms Service Provider

11%

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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

Questions from the Community

Ask a question

Earn 20 points

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...

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Comparisons

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Compared 41% of the time

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Compared 9% of the time

Qlik Compose vs CloverDX Designer

Compared 7% of the time

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Compared 6% of the time

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Compared 3% of the time

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Compared 2% of the time

Ataccama ONE Platform vs Qlik Talend Cloud

Compared 2% of the time

SSIS vs Qlik Talend Cloud

Compared 2% of the time

Melissa Data Quality vs Qlik Talend Cloud

Compared 2% of the time

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Product Reports

Buyer's Guide

Data Integration

September 2026

Download CloverDX Designer product report

Buyer's Guide

Qlik Talend Cloud

October 2026

Download Qlik Talend Cloud product report

Also Known As

No data available

Talend Data Quality, Talend Data Management Platform, Talend MDM Platform, Talend Data Streams, Talend Data Integration, Talend Data Integrity and Data Governance

Overview

CloverDX Designer is a robust data integration platform offering advanced capabilities for data transformation and workflow automation, making it a versatile choice for those with intricate data management tasks.

Designed for users looking to streamline complex data processes, CloverDX Designer provides an intuitive yet powerful interface for designing, testing, and deploying data pipelines. Its primary functions include data integration, transformation, and managing intricate data workflows, catering to professionals who require flexibility and reliability in data handling.

What are the key features of CloverDX Designer?

Data Transformation: Enables conversion and mapping of data between formats.
Workflow Automation: Streamlines repetitive tasks for efficiency.
Scalability: Adapts to growing data volumes with ease.
Debugging Tools: Offers efficient ways to test and troubleshoot data flows.

What benefits or ROI aspects should be evaluated?

Cost Efficiency: Reduces manual data handling expenses.
Time Saving: Accelerates data processing and project deployment.
Customization: Offers flexibility tailored to specific needs.
Improved Data Accuracy: Ensures accurate processes with validation features.

In industries like finance, healthcare, and retail, CloverDX Designer is implemented to handle complex data transformations, automate regulatory reporting, and manage customer insights efficiently. Its versatility makes it suitable for any sector requiring reliable data integration solutions.

CloverDX

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

Sample Customers

Allant Group, NDP, Porch, GoodData

Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group

Find out what your peers are saying about Informatica, Palantir, Microsoft and others in Data Integration. Updated: September 2026.

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