No more typing reviews! Try our Samantha, our new voice AI agent.

Informatica Data Quality vs Melissa Data Quality comparison

 

Comparison Buyer's Guide

Executive Summary

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 Quality
Ranking in Data Quality
25th
Average Rating
8.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Melissa Data Quality
Ranking in Data Quality
10th
Average Rating
8.4
Reviews Sentiment
7.6
Number of Reviews
40
Ranking in other categories
Data Scrubbing Software (4th)
 

Featured Reviews

Hemanthreddy Vakiti - PeerSpot reviewer
Data engineer at a tech vendor with 10,001+ employees
Data quality checks have reduced manual monitoring but still face cost and performance issues
Some of the best features Informatica Data Quality offers include AI automation using CLAIRE, which integrates AI with Informatica Data Quality, and its user-friendly drag-and-drop interface. All of this is simply usable to any person who has minimal knowledge of ETL. Rather than querying every table to check for any duplicate entries or null values, it is impossible to query for each site. Once we integrate it with Informatica Data Quality and use the drag-and-drop function to specify the conditions we need and connect to the databases, it directly checks if the values are within the threshold or if we can set conditions, such as not entering records with null values. It also features a match and merge condition, from which data profiling and data cleansing can be done.
GM
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.

Quotes from Members

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

Pros

"About Informatica Data Quality, I do not think that I have any questions because the product is very good."
"Since we integrated Informatica Data Quality in our project, the amount of human interaction has reduced, so the team has decreased, resulting in cost savings for our project and improved time by automating checks for missing or null values."
"Extremely easy to install and setup."
"Provides simplicity, ease of use, combined with overall accuracy of data."
"Melissa Data is cost effective and efficient."
"Melissa offer a high quality product with great service."
"It saves a huge amount of time. Before using this service, we used a vendor that manually ran our lists through this NCOA list, which might have taken one to three business days to return the file. This was a huge bottleneck in our process, and the data returned was not always accurate. After switching to Melissa Data’s SmartMover, the process has been reduced to between ten minutes and three hours, depending on the amount of records sent."
"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."
"We have only been using this for about two months, but it has sped up our processing significantly, making data mining easy and fast so we no longer have to spend an entire month gathering correct information on leads, as all we need is a list of home addresses and in minutes we have names and phone numbers to increase our chance of these leads becoming customers."
"Be confident that the scalability and load are not going to be an issue with the services. ​"
 

Cons

"The scalability is not up to mark in my view because even a small increase in data, like the number of rows, can cause the server to crash, requiring a reboot."
"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."
"An area for improvement is where an end customer's address is not found in the Melissa Data database, even though it is a valid address."
"Speed of delivery/ease of use. They advertise a 24-hour, next business day turn time on data annotation, but I’ve found it is usually closer to 72 hours. This is still excellent, just make sure you add in the appropriate fluff to your delivery timelines."
"It would be nice if it also had a user interface, as it did in years past."
"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."
"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."
"One of the problems that we ran into this year was we probably spent over 40 hours finding and trying to drill down to where specific bugs were in the program, which was a tremendous waste of time for us. There were a couple of updates to Windows this year, the program kept crashing. It happened on two different occasions over a period of a few months. Once we told them what the problem was - even though their tech support is great to work with - it literally took probably about two months to fix the issue where we could actually use the program the way we needed to use it."
"MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version."
 

Pricing and Cost Advice

Information not available
"Buy a lot more credits than you think you’re going to need."
"Be sure to determine how the data is priced (record-based versus credit-based or some hybrid of data and services)."
"The only complaint that I have towards it is they sell licenses based on a range of usage, and I feel those ranges are too large."
"​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."
"Generally, the cost is ROI positive, depending on your shipping volume."
"Cloud version is very cheap. On-premise version is expensive."
"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."
"​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.​"
report
Use our free recommendation engine to learn which Data Quality solutions are best for your needs.
902,988 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
No data available
Construction Company
18%
Healthcare Company
7%
Educational Organization
6%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise3
Large Enterprise14
 

Questions from the Community

What is your experience regarding pricing and costs for Informatica Data Quality?
I have been informed by our management team that the pricing is high, but I am not sure about the specific figures regarding what the pricing is.
What needs improvement with Informatica Data Quality?
One thing is that, compared to the features provided by Informatica Data Quality, when compared to other tools offering similar features, it is somewhat costly. The scalability is not up to mark co...
What is your primary use case for Informatica Data Quality?
We are using Informatica PowerCenter for ETL, and simultaneously we are using Informatica Data Quality for data profiling, validation, to remove duplicate entries, and for data cleansing. Ours is a...
Ask a question
Earn 20 points
 

Overview

 

Sample Customers

Information Not Available
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, Qlik, SAP and others in Data Quality. Updated: June 2026.
902,988 professionals have used our research since 2012.