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Informatica Cloud Data Quality vs Melissa 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

Informatica Cloud Data Quality
Ranking in Data Quality
3rd
Average Rating
8.0
Reviews Sentiment
7.3
Number of Reviews
14
Ranking in other categories
No ranking in other categories
Melissa Data Quality
Ranking in Data Quality
8th
Average Rating
8.4
Reviews Sentiment
7.6
Number of Reviews
40
Ranking in other categories
Data Scrubbing Software (4th)
 

Mindshare comparison

As of May 2025, in the Data Quality category, the mindshare of Informatica Cloud Data Quality is 8.4%, down from 10.4% compared to the previous year. The mindshare of Melissa Data Quality is 3.0%, up from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality
 

Featured Reviews

TaherDungrawala - PeerSpot reviewer
Has good reusability and CDI features
I use Collibra Data Quality. I switched to Informatica because Collibra cannot integrate. Colibra Cloud Data Quality is a very basic tool. There is no integration capability. If you have problem records, there is no fix to remediate them using the same tool. With Informatica, you can integrate with CDI and then create a remediation plan.
GM
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.

Quotes from Members

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

Pros

"We primarily used Cloud Data Profiling to connect with Cloud Data Governance, a tool also used by Teva. This integration allowed users to access data quality results within the data governance catalog."
"Initial setup was fairly easy."
"Informatica Cloud Data Quality was most valuable for our real-time data quality monitoring needs."
"The most beneficial feature of Informatica Cloud Data Quality is it's cloud-based."
"The reusability factors are nice. The Cloud Data Quality is much better. A major flaw in the previous version was integration with the catalog, which is now seamless."
"One of the most valuable features of Informatica Cloud Data Quality is Master Data Management. You can write code to build your logic rules to check the quality."
"Stability-wise, I rate the solution a ten out of ten."
"The user-friendliness and performance of Informatica is quite impressive."
"We use their GeoPoints to get the most precise, rooftop level geocoding."
"Our customer database is now significantly more accurate and reliable."
"The customers' addresses are now complete, correct and follow one consistent format."
"​It has a straightforward, easy setup."
"I was able to dedupe millions of records in the past, and append the most recent email."
"Gives us the ability to offer an additional resource that other companies do not."
"Helps our organization provide accurate address information to our customers for direct mailing (household) and other campaigns they want to do."
"We mainly communicate with our customers via email, so we primarily use it to find a phone number so we can contact them more efficiently. This allows us to talk to them and resolve their issues much more quickly."
 

Cons

"Some capabilities from the cloud version are not included in the on-premises version."
"The downside of Informatica Cloud Data Quality is that it requires a developer to write rules and maintain the systems. This creates a significant cost and time burden."
"Accessing data as a service is essential, especially for validations requiring external data services. This goes beyond basic syntactic checks, like ensuring an email address contains the @ symbol or .com domain. Instead, it's about advanced validation, such as verifying if an email address exists or if a phone number is valid."
"The integration with older technology and cloud quality needs improvement."
"Improving the UI to be more business user-friendly would also be beneficial."
"Informatica Cloud Data Quality could improve by adding more algorithms for matching and mastering. We currently only have five or six. Additionally, the parallelism in data is better in other solutions, such as IBM."
"In certain domains, I am looking for material-level match features that are not customizable. The current solution requires code-writing and tweaking, while other solutions offer material-level matches."
"If given the opportunity, I would like to address these concerns, particularly with regard to enhancing the end-user experience."
"MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version."
"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.""
"​If I had multiple Excel files open and ran Listware it would crash Excel, charge the credits, and not save the results."
"It would be nice if it also had a user interface, as it did in years past."
"It will mix up family members at times, so we will change addresses at times that shouldn’t be changed."
"Many issues, sometimes I have to completely log out and start over."
"We would appreciate it if there was a larger database so that we could find information more often. For example, we can search for 10 people and only find the information for three of them, if we are lucky."
"Needs to validate more addresses accurately."
 

Pricing and Cost Advice

"Informatica Cloud Data Quality is a costly solution."
"We pay for a yearly subscription."
"The licensing costs attached to the solution are pretty high, but then, with the cloud model, the prices depend on what it provides for the value of money, which I feel was very high."
"Cloud version is very cheap. On-premise version is expensive."
"Be sure to determine how the data is priced (record-based versus credit-based or some hybrid of data and services)."
"Generally, the cost is ROI positive, depending on your shipping volume."
"Melissa pricing is competitive."
"​It is affordable."
"Understand how may transactions you will be processing so that you can get the right tier pricing."
"​We are concerned that our own pricing is going up every year for Melissa Data products, but we highly recommend the services for people who are routinely sending out mailings."
"Pricing is very reasonable, no licensing required."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Manufacturing Company
10%
Computer Software Company
8%
Educational Organization
6%
Insurance Company
15%
Manufacturing Company
12%
Financial Services Firm
11%
Computer Software Company
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Informatica Cloud Data Quality?
The profiling features are much better than the on-premise version.
What needs improvement with Informatica Cloud Data Quality?
Informatica Cloud Data Quality has significant room for improvement. It is not stable, and there are several issues, especially on the cloud side, unlike the on-premise version which was very stabl...
What is your primary use case for Informatica Cloud Data Quality?
We use Informatica Cloud Data Quality ( /products/informatica-cloud-data-quality-reviews ) in a medium business environment.
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Also Known As

Cloud Data Quality Radar
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Overview

 

Sample Customers

Freddie Mac, Rabobank
Boeing Co., FedEx, Ford Motor Co, Hewlett Packard, Meade-Johnson, Microsoft, Panasonic, Proctor & Gamble, SAAB Cars USA, Sony, Walt Disney, Weight Watchers, and Intel.
Find out what your peers are saying about Informatica Cloud Data Quality vs. Melissa Data Quality and other solutions. Updated: April 2025.
850,028 professionals have used our research since 2012.