Try our new research platform with insights from 80,000+ expert users

Informatica Data Engineering Streaming [EOL] vs Qlik Talend Cloud comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 11, 2025

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

Informatica Data Engineerin...
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Qlik Talend Cloud
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
55
Ranking in other categories
Data Integration (6th), Data Quality (2nd), Data Scrubbing Software (1st), Master Data Management (MDM) Software (3rd), Cloud Data Integration (7th), Data Governance (8th), Cloud Master Data Management (MDM) (4th), Streaming Analytics (8th), Integration Platform as a Service (iPaaS) (8th)
 

Featured Reviews

DK
BI Practice Lead at a tech services company with 51-200 employees
Helps with real-time data processing and improves decision-making overall
It improves decision-making overall for the company. Informatica is usually the tool for setting up the data, streaming the data into your data warehouse from your source, transforming the data, and preparing and modeling it into some desired format. It improves the performance. You need to know how to use it and how to implement it, but it improves performance.
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

"It improves the performance."
"The best features Qlik Talend Cloud offers include the fact that it is built on Java, which gives me the chance to customize my requirements and write my own Java code to achieve my logic."
"We can develop our own code if we do not see the functionality we need."
"The features that I like the most are the simplicity of the interface, and the ability to quickly develop with a predefined component."
"​It lowers the amount of time in development from weeks to a day.​"
"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."
"It is saving a lot of time. Today, we can mask around a hundred million records in 10 minutes. Masking is one of the key pieces that is used heavily by the business and IT folks. Normally in the software development life cycle, before you project anything into the production environment, you have to test it in the test environment to make sure that when the data goes into production, it works, but these are all production files. For example, we acquired a new company or a new state for which we're going to do the entire back office, which is related to claims processing, payments, and member enrollment every year. If you get the production data and process it again, it becomes a compliance issue. Therefore, for any migrations that are happening, we have developed a new capability called pattern masking. This feature looks at those files, masks that information, and processes it through the system. With this, there is no PHI and PII element, and there is data integrity across different systems. It has seamless integration with different databases. It has components using which you can easily integrate with different databases on the cloud or on-premise. It is a drag and drop kind of tool. Instead of writing a lot of Java code or SQL queries, you can just drag and drop things. It is all very pictorial. It easily tells you where the job is failing. So, you can just go quickly and figure out why it is happening and then fix it."
"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."
"The basic tools are easy to pick up and understand."
 

Cons

"Skill requirement is required. There is a learning curve."
"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. This would make things even easier."
"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."
"You can't join more than two tables for analysis."
"Qlik Talend Cloud could be improved with more advanced monitoring and flexible alerts, as well as better job performance visibility."
"Processing large volumes of data sometimes consumes a lot of resources."
"There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions."
"When we upgraded to Version 6.4.1, we tried using a GIT repository instead of a SVN repository. After a few incidents where things disappeared and changes were not saved, we decided to go back to a SVN repository."
"I'd be interested in seeing the running of Python programs and transformations from within the studio itself."
 

Pricing and Cost Advice

Information not available
"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 tool is cheap."
"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."
"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."
"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 pricing is a little higher than what I had expected, but it's comparable with I-PASS competitors."
"I have been using the open-source version."
"The solution's pricing is very reasonable and half the cost of Informatica."
report
Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.
882,606 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
27%
Computer Software Company
8%
Retailer
7%
Construction Company
5%
Financial Services Firm
13%
Computer Software Company
10%
Comms Service Provider
7%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business20
Midsize Enterprise11
Large Enterprise20
 

Questions from the Community

What needs improvement with Informatica Data Engineering Streaming?
Skill requirement is required. There is a learning curve.
What is your primary use case for Informatica Data Engineering Streaming?
We implement business intelligence solutions, including data warehousing tools, data integration to load data into warehouses, and then creating reports.
What advice do you have for others considering Informatica Data Engineering Streaming?
Overall, I would rate the solution an eight out of ten. Usually, Informatica is for big clients because of its pricing, and it also requires some skill sets. It requires investment into a proper da...
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

Big Data Streaming, Informatica Intelligent Streaming, Intelligent Streaming
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

Jewelry TV
Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Apache and others in Streaming Analytics. Updated: February 2026.
882,606 professionals have used our research since 2012.