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OpenText Trading Grid vs Qlik Talend Cloud 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

OpenText Trading Grid
Ranking in Cloud Data Integration
39th
Ranking in Integration Platform as a Service (iPaaS)
25th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
1
Ranking in other categories
Business-to-Business Middleware (14th)
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 (4th), Data Governance (8th), Cloud Master Data Management (MDM) (3rd), Streaming Analytics (11th)
 

Mindshare comparison

As of November 2026, in the Cloud Data Integration category, the mindshare of OpenText Trading Grid is 0.9%, up from 0.6% compared to the previous year. The mindshare of Qlik Talend Cloud is 4.7%, up from 3.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
Qlik Talend Cloud4.7%
OpenText Trading Grid0.9%
Other94.4%
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.
Henrique Fsantos - PeerSpot reviewer
Data & Analytics Engineer at PicPay
Automated data pipelines have improved analytics workflows and provide trusted reporting data
The best features of Qlik Talend Cloud are its connectors to many systems, databases, APIs, and files, including both SQL and NoSQL databases. The scheduling feature allows me to run jobs automatically in the cloud, and the built-in data quality tools help clean and check data. The reusable components enable me to reuse jobs and parts, which saves time, making it easy to build good data pipelines. The feature that has made the biggest difference for me in Qlik Talend Cloud is the scheduling and automation, which helps me run ETL jobs automatically without manual work. This saves time, reduces errors, and makes the pipelines more stable. In my daily work, I can trust that the data is updated on time and ready for reports and analytics. Qlik Talend Cloud has had a positive impact on my organization by automating data integration processes, reducing manual errors, and ensuring reliable and up-to-date data for reports and business decisions. This has improved operational stability, productivity, and trust in the data. Since using Qlik Talend Cloud, we have reduced manual work, resulting in approximately 20% to 30% time savings in data load processes. We have also seen a reduction in operational errors, mainly due to automation and the data quality checks, and a clear improvement in data reliability since the pipelines became more standardized and monitored.

Quotes from Members

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

Pros

"The solution is easy to implement."
"The good thing about OpenText is that we have the mapping specification guideline available, which is not there in a solution like SEEBURGER."
"Better control and flexibility to add/custom define features, to tailor to your needs by modifying its Java generated code."
"What I like about the Talend MDM Platform is that it's a good vendor diagnostic tool."
"​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.​"
"With its frequency function, we were able to pick a line of business to be addressed first in one of our conversion projects."
"The product's integration with PostgreSQL and Jira has been helpful for us. Its performance is good. However, we do not use it for large data sets."
"The solution is connected to various phones. It retrieves the configuration from the system."
"Extract, Transform, and Load (ETL) transformations are open source and is a valuable feature."
"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."
 

Cons

"Technical support isn't the greatest. The transparency is less than you sometimes need."
"Technical support needs to be better."
"Data management could also encompass APIs and real-time streaming data integration."
"Including either XML or JSON in the next release would definitely be a good transformation. I'm not sure if Talend has that feature, but it's one of those requirements that we are working around and have to do some parsing of XML so this could make it easier."
"I would say that some of the support elements need improvement."
"I wonder if, at the same price, the API component could be added, which would be beneficial."
"The sales and market department could improve the Talend Data Management Platform."
"In the Philippines, there's only a handful of Talend support. The support is very helpful, but it's very limited."
"The tool's technical support needs to be better. It doesn't have a local data center but pushes everything to the cloud. They need to check in with customers to see if they're happy and how well the solutions work. They need to assign a customer success manager for the accounts they sell."
"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."
 

Pricing and Cost Advice

Information not available
"We did not purchase a separate license for DQ. It is part of our data platform suite, and I believe it is well-priced."
"I have been using the open-source version."
"The solution's pricing is very reasonable and half the cost of Informatica."
"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."
"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."
"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."
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Top Industries

By visitors reading reviews
Manufacturing Company
12%
Construction Company
12%
Outsourcing Company
12%
Comms Service Provider
9%
Financial Services Firm
14%
Outsourcing Company
12%
Comms Service Provider
11%
Construction 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

Ask a question
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), SnapLogic, Informatica and others in Cloud Data Integration. Updated: October 2026.
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