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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
39th
Ranking in Integration Platform as a Service (iPaaS)
26th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
1
Ranking in other categories
Business-to-Business Middleware (13th)
Qlik Talend Cloud
Ranking in Cloud Data Integration
6th
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 (7th), Data Quality (2nd), Data Scrubbing Software (1st), Master Data Management (MDM) Software (3rd), Data Governance (9th), Cloud Master Data Management (MDM) (3rd), Streaming Analytics (6th)
 

Mindshare comparison

As of August 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."
"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."
"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."
"It reduces the QA effort immensely by handling most of the test scenarios in a reusable way."
"The most valuable feature is the data loading and scripting language"
"The most valuable feature lies in the capability to assign data quality issues to different stakeholders, facilitating the tracking and resolution of defective work."
"The tool was mainly used for ETL processes to apply governance rules on data."
"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."
"Talend's most valuable feature is its ability to generate code and packages efficiently."
 

Cons

"Technical support needs to be better."
"Technical support isn't the greatest. The transparency is less than you sometimes need."
"What's missing in the Talend MDM Platform is that it's not maintaining technology references. For example, my company needs a reference case if the platform has been implemented for a configuration that's similar to the client's required configuration. Currently, the client is still reluctant to roll out the Talend MDM Platform at a wider level because there's still no reference received from the Talend team."
"I encountered scalability issues."
"They don't have any AI capabilities. Talend DQ is specifically for data quality, which only has data profiling."
"I'd be interested in seeing the running of Python programs and transformations from within the studio itself."
"Qlik Talend Cloud could be improved with more advanced monitoring and flexible alerts, as well as better job performance visibility."
"The product's setup process could be simpler."
"We'd like to see more connectors it the future."
"The documentation from version to version could be more accurate."
 

Pricing and Cost Advice

Information not available
"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."
"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 pricing is a little higher than what I had expected, but it's comparable with I-PASS competitors."
"License renewal is on a yearly basis."
"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."
"The licensing cost is about 40,000 Euros a year."
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Top Industries

By visitors reading reviews
Manufacturing Company
14%
Construction Company
11%
Outsourcing Company
10%
Wholesaler/Distributor
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

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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: July 2026.
908,834 professionals have used our research since 2012.