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Qlik Talend Cloud vs Upsolver 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

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
39th
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 August 2026, in the Data Integration category, the mindshare of Qlik Talend Cloud is 2.4%, up from 2.0% compared to the previous year. The mindshare of Upsolver is 0.7%, up from 0.2% 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

"Overall, from 2017 to 2020, we have almost saved around 140,000 to 160,000 hours, which is only with respect to the 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."
"We have used value frequency and patterns. We have been it impressed with these functions as they have helped us in making decisions in transformation work."
"With its frequency function, we were able to pick a line of business to be addressed first in one of our conversion projects."
"I like the way that you can use the context variables, and how you can work those context variables to give you values and settings for every development environment, such as PROD, TEST, and DEV."
"We are still in the process of evaluating them, but I love the way things look in Talend, and I'm all for Talend."
"Talend is user-friendly and has many components and connectors, which makes it a great choice."
"The process of upgrading the software is quite easy."
"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."
"I have saved 50 to 60% on maintaining pipelines since using Upsolver."
"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."
"Customer service is excellent, and I would rate it between eight point five to nine out of ten."
"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."
 

Cons

"The documentation from version to version could be more accurate."
"Heap space issues plague us consistently. We maxed it out and it runs fine, then it doesn’t, then it does."
"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."
"They lack in memory capacity."
"The usage of memory. This tool uses a huge amount of memory."
"In terms of the solution's technical support, the interactions were satisfactory, but there is room for improvement, especially in managing expectations."
"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."
"Once you get past the basic tools, it gets pretty complicated."
"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."
"There is room for improvement in query tuning."
"I would say Upsolver's scalability is eight out of 10 because of pricing."
"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."
 

Pricing and Cost Advice

"The tool is cheap."
"Moreover, the pricing structure stands out as highly competitive compared to other offerings in the market, making it a cost-effective choice for users."
"It's a subscription-based platform, we renew it every year."
"I have been using the open-source version."
"The licensing cost is about 40,000 Euros a year."
"I would advise to first take a look and at the Open Studio edition. Figure out what you need and purchase the appropriate license."
"The product pricing is considered very good, especially compared to other data integration tools in the market."
"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."
"Upsolver is affordable at approximately $225 per terabyte per year."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Comms Service Provider
10%
Construction Company
9%
Outsourcing Company
8%
Real Estate/Law Firm
14%
Manufacturing Company
14%
Retailer
11%
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: August 2026.
908,800 professionals have used our research since 2012.