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OpenText Trading Grid 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

OpenText Trading Grid
Ranking in Cloud Data Integration
38th
Ranking in Integration Platform as a Service (iPaaS)
27th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
1
Ranking in other categories
Business-to-Business Middleware (12th)
Qlik Talend Cloud
Ranking in Cloud Data Integration
7th
Ranking in Integration Platform as a Service (iPaaS)
6th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
56
Ranking in other categories
Data Integration (6th), Data Quality (2nd), Data Scrubbing Software (1st), Master Data Management (MDM) Software (3rd), Data Governance (9th), Cloud Master Data Management (MDM) (4th), Streaming Analytics (6th)
 

Mindshare comparison

As of June 2026, in the Cloud Data Integration category, the mindshare of OpenText Trading Grid is 0.9%, up from 0.3% compared to the previous year. The mindshare of Qlik Talend Cloud is 4.8%, up from 3.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
Qlik Talend Cloud4.8%
OpenText Trading Grid0.9%
Other94.3%
Cloud Data Integration
 

Featured Reviews

VARUNKUMAR - PeerSpot reviewer
Mgr Value Chain Integration/EDI at a non-tech company with 10,001+ employees
Industry-leading, easy to implement, and has good mapping specification guidelines
The good thing about OpenText is that we have the mapping specification guideline available, which is not there in a solution like SEEBURGER. Whenever you want to take a decision to move away from OpenText, you have already documented your mapping and what your mapping looks like. So you go to the next provider, provide them with that mapping specification, and it'll be very easy for them to develop a new map instead of just taking the data - input data, output data - and then looking for how the data is getting transformed. So you have the mapping spec level which is a very good feature of OpenText, which we do not have in SEEBURGER. It's very hard to move from SEEBURGER. The solution is easy to implement. It's stable and reliable. They are the industry leaders in the integration space.
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

"The good thing about OpenText is that we have the mapping specification guideline available, which is not there in a solution like SEEBURGER."
"The solution is easy to implement."
"They're very competitive in terms of performance, which is a good selling point. It has very rich features. It provides a very rich feature set in the application."
"​It lowers the amount of time in development from weeks to a day.​"
"Maybe the best thing is the product's easy start-up level when you are familiar with Java."
"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."
"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."
"​This product speeds up the unit testing and QA for specific test scenarios. As a result, the development output quality can be evaluated and adjusted.​"
"tLogRows are also great for finding bad data."
"The tool was mainly used for ETL processes to apply governance rules on data."
 

Cons

"Technical support needs to be better."
"Technical support isn't the greatest. The transparency is less than you sometimes need."
"The stability for Talend Data Quality can be rated around an 8; it is quite stable."
"The sales and market department could improve the Talend Data Management Platform."
"I think the subscription-based model is concerning because as I mentioned, some of our other projects are migrating to different tools."
"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."
"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."
"There are no natural connections for some of the applications that I use more regularly."
"The usage of memory. This tool uses a huge amount of memory."
"As it is a open source tool, some minor bugs are there."
 

Pricing and Cost Advice

Information not available
"The tool is cheap."
"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 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."
"Moreover, the pricing structure stands out as highly competitive compared to other offerings in the market, making it a cost-effective choice for users."
"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."
"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."
"The licensing cost is about 40,000 Euros a year."
"The pricing is a little higher than what I had expected, but it's comparable with I-PASS competitors."
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Top Industries

By visitors reading reviews
Manufacturing Company
13%
Construction Company
11%
Wholesaler/Distributor
8%
Comms Service Provider
7%
Financial Services Firm
16%
Comms Service Provider
9%
Construction Company
7%
Computer Software Company
7%
 

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

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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 ...
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

Trading Grid, GXS Trading Grid
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

Autoliv, Hella, Hutchinson, Michelin
Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group
Find out what your peers are saying about Amazon Web Services (AWS), Informatica, Palantir and others in Cloud Data Integration. Updated: June 2026.
900,644 professionals have used our research since 2012.