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Cloudera DataFlow vs Qlik Talend Cloud comparison

 

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

Cloudera DataFlow
Ranking in Streaming Analytics
20th
Average Rating
7.4
Reviews Sentiment
6.5
Number of Reviews
5
Ranking in other categories
No ranking in other categories
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)
 

Mindshare comparison

As of August 2026, in the Streaming Analytics category, the mindshare of Cloudera DataFlow is 2.8%, up from 1.1% compared to the previous year. The mindshare of Qlik Talend Cloud is 3.2%, up from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Qlik Talend Cloud3.2%
Cloudera DataFlow2.8%
Other94.0%
Streaming Analytics
 

Featured Reviews

Mohamed-Saied - PeerSpot reviewer
Senior Data Architect at Teradata Corporation
Efficient data integration and workflow scheduling elevate project performance
Cloudera DataFlow is used as an ETL or ELT solution within Cloudera's data pipeline. Our organization heavily relies on it for data ingestion, transformation, and warehousing. It is also used daily for operational tasks, and it integrates well within Cloudera's ecosystem for high performance and…
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.

Quotes from Members

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

Pros

"Cloudera DataFlow is fully compatible with Cloudera's ecosystem and offers high efficiency through native connectors for various ecosystems."
"This solution is very scalable and robust."
"The most effective features are data management and analytics."
"The initial setup was not so difficult"
"DataFlow's performance is okay."
"You move data from one source to another without problem and apply some business rules in data."
"What I like about the Talend MDM Platform is that it's a good vendor diagnostic tool."
"The most valuable features of the Talend Data Management Platform are the components."
"The tool was mainly used for ETL processes to apply governance rules on data."
"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."
"I would definitely recommend others to implement this product as it is really helpful, easy to learn, user friendly, provides lot of enhanced features, etc."
"Talend Data Integration has had a measurable impact on our organization by automating daily data loading processes, reducing manual effort by around three or four hours per day, improving data accuracy with error rates dropping by more than 70%, and enabling reporting teams to receive fresh data at least 50% faster for earlier and more confident decision-making."
"It reduces the QA effort immensely by handling most of the test scenarios in a reusable way."
 

Cons

"It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists."
"It is not easy to use the R language. Though I don't know if it's possible, I believe it is possible, but it is not the best language for machine learning."
"Although their workflow is pretty neat, it still requires a lot of transformation coding; especially when it comes to Python and other demanding programming languages."
"Cloudera DataFlow's UI interface could be enhanced significantly. Memory handling can also be improved to be better than it is today."
"We'd like to see more connectors it the future."
"Finding assistance with issues can be spotty. With Python, there are literally millions of open source answers which are recent and apply to the version that we are using."
"For us in New Zealand, it is quite expensive."
"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."
"First, We faced problems with stability of the products."
"With M rows, it runs too slowly and has memory issues."
"I encountered scalability issues."
"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."
 

Pricing and Cost Advice

"DataFlow isn't expensive, but its value for money isn't great."
"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."
"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."
"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 pricing is a little higher than what I had expected, but it's comparable with I-PASS competitors."
"It's a subscription-based platform, we renew it every year."
"The solution's pricing is very reasonable and half the cost of Informatica."
"License renewal is on a yearly basis."
"The licensing cost is about 40,000 Euros a year."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Construction Company
13%
Manufacturing Company
10%
Comms Service Provider
8%
Financial Services Firm
15%
Comms Service Provider
10%
Construction Company
9%
Outsourcing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business21
Midsize Enterprise12
Large Enterprise20
 

Questions from the Community

What needs improvement with Cloudera DataFlow?
Cloudera DataFlow's UI interface could be enhanced significantly. Memory handling can also be improved to be better than it is today.
What is your primary use case for Cloudera DataFlow?
Cloudera DataFlow is used as an ETL or ELT solution within Cloudera's data pipeline. Our organization heavily relies on it for data ingestion, transformation, and warehousing. It is also used daily...
What advice do you have for others considering Cloudera DataFlow?
Cloudera DataFlow is fully compatible with Cloudera's ecosystem and offers high efficiency through native connectors for various ecosystems. However, the learning curve is high, and there is a shor...
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...
 

Also Known As

CDF, Hortonworks DataFlow, HDF
Talend Data Quality, Talend Data Management Platform, Talend MDM Platform, Talend Data Streams, Talend Data Integration, Talend Data Integrity and Data Governance
 

Overview

 

Sample Customers

Clearsense
Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group
Find out what your peers are saying about Cloudera DataFlow vs. Qlik Talend Cloud and other solutions. Updated: August 2026.
909,948 professionals have used our research since 2012.