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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
5th
Ranking in Streaming Analytics
8th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
55
Ranking in other categories
Data Quality (2nd), Data Scrubbing Software (1st), Master Data Management (MDM) Software (3rd), Cloud Data Integration (6th), Data Governance (8th), Cloud Master Data Management (MDM) (4th), Integration Platform as a Service (iPaaS) (6th)
Upsolver
Ranking in Data Integration
36th
Ranking in Streaming Analytics
20th
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 May 2026, in the Data Integration category, the mindshare of Qlik Talend Cloud is 2.4%, up from 2.1% compared to the previous year. The mindshare of Upsolver is 0.7%, up from 0.1% 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

"Flexibility is a key feature I appreciate about Talend Data Integration, especially the integration of Java within it and the ease of integrating with multiple source repositories such as GitHub and Bitbucket."
"It’s easy to monitor the processes. Every morning I’ll open the Talend Administration Center to check the status of the process. Within seconds I’m able to see which process ran successfully and which have failed and why they failed."
"Talend Studio has the ability to connect to almost anything to integrate data from files, databases, web services, etc."
"The solution enables robust data matching, merging, survivorship, and Data Stewardship that can be a part of data quality workflows or true master data management."
"The numerous components provided by Talend mean you’re able to create jobs quickly and efficiently."
"It offers advanced features that allow you to create custom patterns and use regular expressions to identify data issues."
"The features that I like the most are the simplicity of the interface, and the ability to quickly develop with a predefined component."
"What I like about the Talend MDM Platform is that it's a good vendor diagnostic tool."
"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."
"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."
"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."
"Customer service is excellent, and I would rate it between eight point five to nine out of ten."
 

Cons

"There are no concurrent licenses, they only have seat licenses on cloud. For example, if in any project your headcount increases or decreases, you do not have that concurrence and you have a seat license, you run into challenges because you have to procure a few more licenses for getting the job done."
"In redundancy analysis, the query is failing to bring non-matched records. This query is an internal script."
"SQL for displaying underlying data in non-match results does not work."
"I would like to sync a project and do an upload from that current version, and then from GitLab, be able to download the latest one."
"Qlik Talend Cloud could be improved with more advanced monitoring and flexible alerts, as well as better job performance visibility."
"Data management could also encompass APIs and real-time streaming data integration."
"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."
"If the SQL input controls could dynamically determine the schema-based on the SQL alone, it would simplify the steps of having to use a manually created and saved schema for use in the TMap for the Postgres and Redshift components."
"I would say Upsolver's scalability is eight out of 10 because of pricing."
"There is room for improvement in query tuning."
"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."
"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."
 

Pricing and Cost Advice

"The pricing is a little higher than what I had expected, but it's comparable with I-PASS competitors."
"The product pricing is considered very good, especially compared to other data integration tools in the market."
"It's a subscription-based platform, we renew it every year."
"The licensing cost is about 40,000 Euros a year."
"I have been using the open-source version."
"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."
"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 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."
"Upsolver is affordable at approximately $225 per terabyte per year."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Comms Service Provider
8%
Computer Software Company
8%
Government
5%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business20
Midsize Enterprise11
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 was a very good experience, but it is not a direct experience because it was not my responsibility. It was in charge of the customer. However, ...
What needs improvement with Upsolver?
I think that Upsolver can be improved in orchestration because it is not a full orchestration tool. I believe it could be better in this regard. The cost needs attention at a very large scale. I th...
What is your primary use case for Upsolver?
My main use case for Upsolver is during an IT consulting project for a large enterprise running a cloud-native data platform on AWS. I used Upsolver to ingest and process high-volume stream data fr...
 

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: April 2026.
893,164 professionals have used our research since 2012.