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 #6 with an average rating of 8.0. Melissa holds a 3.1% mindshare in DQ, compared to Talend’s 4.3% 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

403 Views
134 Comparison Views

95% willing to recommend

Talend Data Quality

Read 20 Talend Data Quality reviews

676 Views
167 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: June 2025).

Buyer's Guide

Melissa Data Quality vs. Talend Data Quality

June 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

3rd

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

6th

Ranking in Data Scrubbing Software

2nd

Average Rating

8.0

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Data Quality category, the mindshare of Melissa Data Quality is 3.1%, up from 2.7% compared to the previous year. The mindshare of Talend Data Quality is 4.3%, up from 4.3% 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

"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."

"It has a straightforward, easy setup."

"We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database."

"Allows us to delete and correct incorrect data to make the searching of our applicant tracking system more consistent and relevant."

"Extremely easy to install and setup."

"We like having the ability to write our own utilities/software to process our records and store the final output the way we want."

"Decreases chances of incorrect shipping addresses and, thus, returned packages."

"Our customer database is now significantly more accurate and reliable."

More Melissa Data Quality pros

"We are able to get emails from URLs very easily using this function when others fail."

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

"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."

"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 Studio is easy to understand."

"The numerous components provided by Talend mean you’re able to create jobs quickly and efficiently."

"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."

More Talend Data Quality pros

Cons

"Did not work as advertized. Needs better results in address parsing, as described on the website."

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

"The custom software solution we still use in-house makes Excel a lot slower than usual."

"Tech support at Melissa Data was very quick to wash their hands of an issue and say it's IT policies on my side that are causing the issue. There was no offer to try and find a work-around. Just an overwhelming attitude of "it’s not our problem.""

"It would be helpful if a list of the codes and explanations could be included."

"We encounter failed batch processes once in a while, but their team is quick to rectify issues."

"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."

"Needs better email append coverage (but every vendor struggles with this)."

More Melissa Data Quality cons

"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."

"There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions."

"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."

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

"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."

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

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

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

More Talend Data Quality cons

Pricing and Cost Advice

"This vendor has no equal in pricing for equivalent functionality."

"You should have a good idea of the size of your data and the amount of cleansing you will be doing, so you will purchase the appropriate size bundle."

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

"Buy a lot more credits than you think you’re going to need."

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

"Pricing is very reasonable."

"NCOA address verification was a requirement from USPS to send out the mailers. This was the only option that charged per address which was extremely helpful since we are a small non-profit school."

"Understand how may transactions you will be processing so that you can get the right tier pricing."

More Melissa Data Quality pricing and cost advice

"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."

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

"Moreover, the pricing structure stands out as highly competitive compared to other offerings in the market, making it a cost-effective choice for users."

"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."

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Top Industries

By visitors reading reviews

Insurance Company

16%

Financial Services Firm

11%

Manufacturing Company

11%

Computer Software Company

10%

Financial Services Firm

15%

Computer Software Company

15%

Manufacturing Company

10%

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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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.

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...

See all answers

Comparisons

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Compared 42% of the time

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

Compared 32% of the time

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Compared 26% of the time

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

Compared 28% of the time

Ataccama ONE Platform vs Talend Data Quality

Compared 21% of the time

Precisely Trillium vs Talend Data Quality

Compared 13% of the time

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Product Reports

Buyer's Guide

Melissa Data Quality

May 2025

Download Melissa Data Quality product report

Buyer's Guide

Talend Data Quality

May 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

June 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: June 2025.

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