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Qlik Talend Cloud vs Upsolver 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 Data Integration
7th
Ranking in Streaming Analytics
6th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
56
Ranking in other categories
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)
Upsolver
Ranking in Data Integration
38th
Ranking in Streaming Analytics
21st
Average Rating
8.6
Reviews Sentiment
7.6
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of September 2026, in the Data Integration category, the mindshare of Qlik Talend Cloud is 2.4%, up from 1.8% compared to the previous year. The mindshare of Upsolver is 0.7%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Qlik Talend Cloud2.4%
Upsolver0.7%
Other96.9%
Data Integration
 

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.
reviewer2784462 - PeerSpot reviewer
Software Engineer at a tech vendor with 10,001+ employees
Streaming pipelines have become simpler and onboarding new data sources is now much faster
One of the best features Upsolver offers is the automatic schema evolution. Another good feature is SQL-based streaming transformations. Complex streaming transformations such as cleansing, deduplication, and enrichment were implemented using SQL and drastically reduced the need for custom Spark code. My experience with the SQL-based streaming transformations in Upsolver is that it had a significant positive impact on the overall data engineering workflow. By replacing custom Spark streaming jobs with declarative SQL logic, I simplified development, review, and deployment processes. Data transformations such as parsing, filtering, enrichment, and deduplication could be implemented and modified quickly without rebuilding or redeploying complex code-based pipelines. Upsolver has impacted my organization positively because it brings many benefits. The first one is faster onboarding of new data sources. Another one is more reliable streaming pipelines. Another one is near-real-time data availability, which is very important for us. It also reduced operational effort for data engineering teams. A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days. Custom Spark code reduction reached 50 to 40 percent. Pipeline failures are reduced by 70 to 80 percent. Data latency is improved from hours to minutes.

Quotes from Members

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

Pros

"If you are looking for something that is stable, cost-effective and has a great ROI, then Talend is a great choice."
"What I like about the Talend MDM Platform is that it's a good vendor diagnostic tool."
"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."
"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."
"The solution is connected to various phones. It retrieves the configuration from the system."
"If your use case depends on heterogeneous sources like Salesforce, SAP, and some other product information systems, I would recommend Talend."
"I like idea of storing the results of Data Quality jobs in a DB and having the ability to run reports in the DB to show a dashboard of quality metrics."
"We can develop our own code if we do not see the functionality we need."
"A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days, custom Spark code reduction reached 50 to 40 percent, pipeline failures are reduced by 70 to 80 percent, and data latency is improved from hours to minutes."
"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."
"I have saved 50 to 60% on maintaining pipelines since using Upsolver."
"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."
"Customer service is excellent, and I would rate it between eight point five to nine out of ten."
 

Cons

"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."
"Processing large volumes of data sometimes consumes a lot of resources."
"There are no natural connections for some of the applications that I use more regularly."
"Not enough material is available for beginners."
"Heap space issues plague us consistently. We maxed it out and it runs fine, then it doesn’t, then it does."
"Data management could also encompass APIs and real-time streaming data integration."
"Lots of errors and system crashes during installation and IMHO we didn’t receive good enough technical support and guidance from Talend to solve the issues."
"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."
"I would say Upsolver's scalability is eight out of 10 because of pricing."
"There is room for improvement in query tuning."
"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."
"On the stability side, I would rate it seven out of ten. Using multiple cloud providers and data engineering technologies creates complexity, and managing different plugins is not always easy, but they are working on it."
"Upsolver excels in ETL and data aggregation, while ThoughtSpot is strong in natural language processing for querying datasets. Combining these tools can be very effective: Upsolver handles aggregation and ETL, and ThoughtSpot allows for natural language queries. There’s potential for highlighting these integrations in the future."
 

Pricing and Cost Advice

"I have been using the open-source version."
"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."
"Moreover, the pricing structure stands out as highly competitive compared to other offerings in the market, making it a cost-effective choice for users."
"License renewal is on a yearly basis."
"It's a subscription-based platform, we renew it every 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."
"The licensing cost is about 40,000 Euros a year."
"Upsolver is affordable at approximately $225 per terabyte per year."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Outsourcing Company
12%
Comms Service Provider
10%
Construction Company
8%
Real Estate/Law Firm
14%
Manufacturing Company
14%
Retailer
13%
Construction Company
11%
 

Company Size

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

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 Upsolver?
My experience with pricing, setup cost, and licensing is that the pricing is nine out of 10.
What needs improvement with Upsolver?
I think Upsolver can be improved with deeper integration with external orchestration out of the box. I would appreciate more clear dashboards with billing in real time as a needed improvement.
What is your primary use case for Upsolver?
My main use case for Upsolver is to operate with changes in the structure of new data without a pipeline disrupting. I write SQL queries in Upsolver, and the platform takes care of the data itself,...
 

Comparisons

 

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. Upsolver and other solutions. Updated: September 2026.
913,683 professionals have used our research since 2012.