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

Oracle Data Quality vs Talend Data Quality comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 6, 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

Oracle Data Quality
Ranking in Data Quality
15th
Average Rating
8.4
Reviews Sentiment
7.9
Number of Reviews
8
Ranking in other categories
No ranking in other categories
Talend Data Quality
Ranking in Data Quality
6th
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
20
Ranking in other categories
Data Scrubbing Software (2nd)
 

Mindshare comparison

As of April 2025, in the Data Quality category, the mindshare of Oracle Data Quality is 1.6%, down from 2.0% compared to the previous year. The mindshare of Talend Data Quality is 3.5%, down from 4.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality
 

Featured Reviews

Venkatraman Bhat - PeerSpot reviewer
Fast, has good extraction, validation, and transformation features, and provides good support
Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution.
WesamHabboub - PeerSpot reviewer
Stands out for its user-friendly interface, robust community support, competitive pricing and strategic approach to improving data accuracy
Its greatest asset lies in its user-friendly interface, specifically within the Talend Open Studio, known for its ease of use and familiarity among users. The robust community support proves invaluable when encountering challenges, providing a reliable resource for issue resolution. 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 most valuable feature lies in the capability to assign data quality issues to different stakeholders, facilitating the tracking and resolution of defective work. This functionality enables a streamlined process for identifying, assigning, and subsequently addressing data quality issues.

Quotes from Members

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

Pros

"With Oracle Data Quality, the most valuable feature is entity matching."
"Once it is set up, it is easy to use and maintain."
"I have found the most valuable features to be data cleansing and deduplication."
"The features I like most about Oracle Data Quality include extraction, transformation, and validation, which makes it a multipurpose product such as Oracle GoldenGate and Oracle Data Integrator. I also like that Oracle Data Quality is very fast, so you can use it for a large volume of data within a short period. You have to do the validation very quickly, so the solution helps in that area of data quality. Another feature of Oracle Data Quality that I like is the MDM (Master Data Management) where you'll have a single source of protection, and this makes the solution perfect and helpful to my company."
"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."
"tLogRows are also great for finding bad data."
"It offers advanced features that allow you to create custom patterns and use regular expressions to identify data issues."
"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 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."
"​It lowers the amount of time in development from weeks to a day.​"
"It has definitely streamlined certain processes.​"
"With its frequency function, we were able to pick a line of business to be addressed first in one of our conversion projects."
 

Cons

"If the length of time required for deployment was reduced then it would be very helpful."
"Oracle Data Quality should integrate with data warehousing solutions such as Azure and CWS Office. For example, having the ability to integrate with tools, such as Azure Synapse and SQL data warehousing would be a great benefit."
"Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution."
"Oracle is currently not that intuitive. We need to use programmers to write code for a lot of the procedures. We need to have them write CL SQL code and write a CL script."
"NullPointerExceptions are going to be the death of me and are a big reason for our transition away from Talend. One day, it is fine with a 1000 blank rows, then the next day, it will find one blank cell and it breaks down."
"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."
"In terms of the solution's technical support, the interactions were satisfactory, but there is room for improvement, especially in managing expectations."
"There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions."
"The performance is one area that Talend Data Quality could improve in because large volumes take a lot of time."
"If we encounter issues, it’s most likely when using the Talend Open Studio. The studio can be slow, get stuck, or crash. But again, it can be caused by the resources of your machine or your connection with the repository. If we encounter issues with the Studio we restart the Studio. In emergencies, we create and use a new workspace."
"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."
"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

"The vendor needs to revisit their pricing strategy."
"The price of this solution is comparable to other similar solutions."
"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."
"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 would advise to first take a look and at the Open Studio edition. Figure out what you need and purchase the appropriate license."
"It's a subscription-based platform, we renew it every year."
report
Use our free recommendation engine to learn which Data Quality solutions are best for your needs.
845,406 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
23%
Computer Software Company
11%
Manufacturing Company
9%
University
7%
Financial Services Firm
16%
Computer Software Company
13%
Manufacturing Company
10%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Ask a question
Earn 20 points
What do you like most about Talend Data Quality?
The most valuable feature lies in the capability to assign data quality issues to different stakeholders, facilitating the tracking and resolution of defective work.
What is your experience regarding pricing and costs for Talend Data Quality?
There are many data quality tools available, but some can be expensive. Talend Data Quality stands out because it is often provided for free if you already have Talend Data Integration, which means...
What needs improvement with Talend Data Quality?
Talend suite might have a missing product, particularly in the commercial master aspect. This would contribute to completing the overall picture, though the focus isn't necessarily on economic cons...
 

Also Known As

Datanomic
No data available
 

Overview

 

Sample Customers

Roka Bioscience, Statistics Centre _ Abu Dhabi , Raymond James Financial inc., CaixaBank, Industrial Bank of Korea, Posco, NHS Business Services Authority, RWE Power, LIFE Financial Group,
Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group
Find out what your peers are saying about Oracle Data Quality vs. Talend Data Quality and other solutions. Updated: March 2025.
845,406 professionals have used our research since 2012.