Melissa Data Quality vs Talend Data Quality comparison

Melissa and Talend are both solutions in the Data Quality category. Melissa is ranked #8 with an average rating of 9.0, while Talend is ranked #5 with an average rating of 8.0. Melissa holds a 3.2% mindshare in DQ, compared to Talend’s 5.5% mindshare. Additionally, 95% of Melissa users are willing to recommend the solution, compared to 89% of Talend users who would recommend it.

Melissa Data Quality

Read 40 Melissa Data Quality reviews

653 Views
372 Comparison Views

95% willing to recommend

Talend Data Quality

Read 20 Talend Data Quality reviews

1,296 Views
1,037 Comparison Views

89% willing to recommend

Melissa Data Quality

Talend Data Quality

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 6, 2025

Talend Data Quality and Melissa Data Quality compete in data management, with Talend offering greater features for data integration, while Melissa excels in data validation accuracy.

Features:Talend Data Quality is known for strong data profiling, data cleansing, and monitoring, making it a comprehensive data management solution. Melissa Data Quality specializes in address verification, geocoding, and real-time contact data enhancement, making it ideal for businesses focusing on accurate data verification.

Room for Improvement:Talend could improve on ease of setup and address better data visualization tools. It also lacks out-of-the-box components for some applications. Melissa could enhance its integration capabilities with third-party platforms, provide more flexible customization, and improve its batch processing speed for large datasets.

Ease of Deployment and Customer Service:Talend supports both cloud and on-premises deployment, offering flexibility and adaptability. It is characterized by a steeper learning curve. Melissa offers a straightforward installation process with robust customer service, allowing for quicker integration and support.

Pricing and ROI:Talend’s higher initial cost is balanced by its extensive features that deliver high ROI for comprehensive data solutions. Melissa provides a cost-effective setup with a rapid ROI, focusing on specific data-quality functions essential for companies needing accuracy and precision.

To learn more, read our detailed Melissa Data Quality vs. Talend Data Quality Report (Updated: July 2025).

Buyer's Guide

Melissa Data Quality vs. Talend Data Quality

July 2025

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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

Melissa Data Quality

Ranking in Data Quality

8th

Ranking in Data Scrubbing Software

4th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Talend Data Quality

Ranking in Data Quality

5th

Ranking in Data Scrubbing Software

3rd

Average Rating

8.0

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2025, in the Data Quality category, the mindshare of Melissa Data Quality is 3.2%, up from 2.4% compared to the previous year. The mindshare of Talend Data Quality is 5.5%, down from 6.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality

Featured Reviews

GaryM

Data Architect at World Vision

SSIS MatchUp Component is Amazing

- Scalability is a limitation as it is single threaded. You can bypass this limitation by partitioning your data (say by alphabetic ranges) into multiple dataflows but even within a single dataflow the tool starts to really bog down if you are doing survivorship on a lot of columns. It's just very old technology written that's starting to show its age since it's been fundamentally the same for many years. To stay relavent they will need to replace it with either ADF or SSIS-IR compliant version. - Licensing could be greatly simplified. As soon as a license expires (which is specific to each server) the product stops functioning without prior notice and requires a new license by contacting the vendor. And updating the license is overly complicated. - The tool needs to provide resizable forms/windows like all other SSIS windows. Vendor claims its an SSIS limitation but that isn't true since pretty much all SSIS components are resizable except theirs! This is just an annoyance but needless impact on productivity when developing new data flows. - The tool needs to provide for incremental matching using the MatchUp for SSIS tool (they provide this for other solutions such as standalone tool and MatchUp web service). We had to code our own incremental logic to work around this. - Tool needs ability to sort mapped columns in the GUI when using advanced survivorship (only allowed when not using column-level survivorship). - It should provide an option for a procedural language (such as C# or VB) for survivor-ship expressions rather than relying on SSIS expression language. - It should provide a more sophisticated ability to concatenate groups of data fields into common blocks of data for advanced survivor-ship prioritization (we do most of this in SQL prior to feeding the data to the tool). - It should provide the ability to only do survivor-ship with no matching (matching is currently required when running data through the tool). - Tool should provide a component similar to BDD to enable the ability to split into multiple thread matches based on data partitions for matching and survivor-ship rather than requiring custom coding a parallel capable solution. We broke down customer data by first letter of last name into ranges of last names so we could run parallel data flows. - Documentation needs to be provided that is specific to MatchUp for SSIS. Most of their wiki pages were written for the web service API MatchUp Object rather than the SSIS component. - They need to update their wiki site documentation as much of it is not kept current. Its also very very basic offering very little in terms of guidelines. For example, the tool is single-threaded so getting great performance requires running multiple parallel data flows or BDD in a data flow which you can figure out on your own but many SSIS practitioners aren't familiar with those techniques. - The tool can hang or crash on rare occasions for unknown reason. Restarting the package resolves the problem. I suspect they have something to do with running on VM (vendor doesn't recommend running on VM) but have no evidence to support it. When it crashes it creates dump file with just vague message saying the executable stopped running.

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WesamHabboub

Chief Consultant at Insight360

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.

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Quotes from Members

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

Pros

"We only use the one feature for the NAICS code. This allows our product users to know what industry a business is in."

"There have been tangible benefits in combating fraudulent transactions. The information from Melissa Data is fed straight into our fraud system. This creates efficiency but also removes the need for manual address checks."

"It has a straightforward, easy setup."

"Address parsing. Our other software does not have this functionality."

"Helps our organization provide accurate address information to our customers for direct mailing (household) and other campaigns they want to do."

"By using Melissa Data, we are able to scrub and verify, then better validate the end customer's address to ensure a more consistent delivery of products."

"It cuts down significantly on time in trying to match names to addresses. I can do in a few hours what would otherwise take days to accomplish."

"Getting the most up to date address for our members. We like to keep in touch with membership a few times a year so we want to maintain up to date addresses to be sure they receive any information that we mail to them."

More Melissa Data Quality pros

"It lowers the amount of time in development from weeks to a day."

"The solution is customizable."

"The features that I find to be the most valuable are the extensibility, the integration, and the ease of integration with multiple platforms."

"I really like the fact that there are no out-of-the-box solutions regarding the development of jobs. Other vendors may have modules which cleanse your addresses. In Talend, you have the freedom to completely develop the process yourself. This can be tricky, but it also makes it fun."

"The Studio is easy to understand."

"It reduces the QA effort immensely by handling most of the test scenarios in a reusable way."

"The jobs are visual and this has improved collaboration between colleagues. It’s much easier to understand a visual job than a piece of Java code."

"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."

More Talend Data Quality pros

Cons

"Many issues, sometimes I have to completely log out and start over."

"It really hasn't given us a phone number for the owner of the property, and that's one thing I'd really like to be getting. Either a phone number or email."

"Pricing is based on tiers, with each tier capped at a specified number of records processed. Once you go over the cap at one tier, you are automatically bumped to the next tier. However, they seem to count failed batch processes so it’s good to keep track of the number of records sent. They’ll fix the count when notified, but their system fails to detect actual successful processes versus failed processes."

"MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version."

"It will mix up family members at times, so we will change addresses at times that shouldn’t be changed."

"One thing I would want to have, when you're doing a property search, you can do it either on the FIPS in the APN number or the address itself. For some entries, I'll have the APN number, and some I'll have the address. Apparently it cannot process something when both the FIPS-APN and the address are on there. I have to sort, once with one and once with the other, which is a little bit of a pain."

"More countries should be supported by Melissa."

"We are no longer using Melissa Data to clean up our address information as there are free tools that we can use to do the same thing."

More Melissa Data Quality cons

"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."

"I would say that some of the support elements need improvement."

"You can't join more than two tables for analysis."

"SQL for displaying underlying data in non-match results does not work."

"Heap space issues plague us consistently. We maxed it out and it runs fine, then it doesn’t, then it does."

"In terms of the solution's technical support, the interactions were satisfactory, but there is room for improvement, especially in managing expectations."

"In redundancy analysis, the query is failing to bring non-matched records. This query is an internal script. There is no way (that I know of) to fix this syntax error for future runs."

"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."

More Talend Data Quality cons

Pricing and Cost Advice

"Pricing is very reasonable, no licensing required."

"Generally, the cost is ROI positive, depending on your shipping volume."

"Fully understand your volume, both monthly and annually. Speak with a Melissa account manager, they will put together an effective solution to meet your needs."

"Depends on situation. We prefer to have data onsite, but some might prefer web access."

"Cloud version is very cheap. On-premise version is expensive."

"It's affordable."

"It is affordable."

"I think it's worth the value for me to run it."

More Melissa Data Quality pricing and cost advice

"We did not purchase a separate license for DQ. It is part of our data platform suite, and I believe it is well-priced."

"It's a subscription-based platform, we renew it every 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."

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Top Industries

By visitors reading reviews

Insurance Company

14%

Manufacturing Company

11%

Financial Services Firm

Computer Software Company

13%

Financial Services Firm

10%

Government

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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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.

See all answers

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...

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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...

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Comparisons

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Compared 19% of the time

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Compared 17% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Melissa Data Quality

Compared 17% of the time

Anchor Software Data Quality vs Melissa Data Quality

Compared 17% of the time

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Ataccama ONE Platform vs Talend Data Quality

Compared 28% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Talend Data Quality

Compared 23% of the time

ibi Data Quality vs Talend Data Quality

Compared 14% of the time

DQ Global Data Quality vs Talend Data Quality

Compared 12% of the time

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Product Reports

Buyer's Guide

Melissa Data Quality

August 2025

Download Melissa Data Quality product report

Buyer's Guide

Talend Data Quality

July 2025

Download Talend Data Quality product report

Overview

Data Quality Components for SSIS

This suite of data transformations for Microsoft SQL Server Integration Services (SSIS) delivers the full spectrum of data quality including data profiling, data verification, data enrichment and data matching. With an intuitive interface and drag/drop capabilities, this powerful toolkit makes it easy to unify data into a single version of the truth for Master Data Management (MDM) success.

Melissa

The data quality tools in Talend Open Studio for Data Quality enable you to quickly take the first big step towards better data quality for your organization: getting a clear picture of your current data quality. Without having to write any code, you can perform data quality analysis tasks ranging from simple statistical profiling, to analysis of text fields and numeric fields, to validation against standard patterns (email address syntax, credit card number formats) or custom patterns of your own creation.

Talend

Sample Customers

Boeing Co., FedEx, Ford Motor Co, Hewlett Packard, Meade-Johnson, Microsoft, Panasonic, Proctor & Gamble, SAAB Cars USA, Sony, Walt Disney, Weight Watchers, and Intel.

Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group

Buyer's Guide

Melissa Data Quality vs. Talend Data Quality

July 2025

Free Report: Melissa Data Quality vs. Talend Data Quality

Find out what your peers are saying about Melissa Data Quality vs. Talend Data Quality and other solutions. Updated: July 2025.

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