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

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 15, 2026

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 Intelligent Dat...
Ranking in Data Quality
1st
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
214
Ranking in other categories
Data Integration (1st), Business Process Management (BPM) (8th), Business-to-Business Middleware (2nd), API Management (5th), Cloud Data Integration (2nd), Data Governance (3rd), Test Data Management (3rd), Cloud Master Data Management (MDM) (1st), Data Management Platforms (DMP) (2nd), Data Masking (2nd), Metadata Management (2nd), Integration Platform as a Service (iPaaS) (4th), Test Data Management Services (3rd), Product Information Management (PIM) (1st), Data Observability (1st), AI Data Analysis (1st)
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 2026, in the Data Quality category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 9.6%, down from 19.3% compared to the previous year. The mindshare of Melissa Data Quality is 4.3%, up from 2.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality Mindshare Distribution
ProductMindshare (%)
Informatica Intelligent Data Management Cloud (IDMC)9.6%
Melissa Data Quality4.3%
Other86.1%
Data Quality
 

Featured Reviews

Divya-Raj - PeerSpot reviewer
Sr. Consultant cum Assistant Manager & Offshore Lead at Deloitte
Handles large data volumes effectively and offers competitive pricing
There is a lot of improvement required, as we still face some cache issues most of the time, which is a challenge that we expect to see resolved in the future. Additionally, there is some limitation when we are working with a tool, especially regarding In and Out parameters, and I feel that this aspect should be improved going ahead. We face issues with the API side, as Cloud Application Integration cannot handle large volumes; according to the API page, there is a limitation of 500 records or 500 MB. The AI integrated into the Informatica Intelligent Cloud Services solution is called Application Integration, where we still face challenges when dealing with huge volumes, as previously explained.
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

"The product's most valuable feature is the ability to select the data flow and lineage."
"I have rated the stability a ten out of ten due to a high level of satisfaction."
"Informatica is good for integrating data and cloud applications. We have connectors for integrating cloud applications like Salesforce. You can quickly integrate anything with an exposed API or a REST API. The industry is increasingly shifting to the cloud, so we need more products that can connect to cloud-based applications. The integration is seamless and works in real time. It's also secure because you don't need to expose databases or tables."
"The most valuable features of Informatica MDM are it is cloud-enabled and has all the elements that are supposed to have in terms of MDM as a solution, very well-integrated with any of the SAP and non-SAP applications, quite user-friendly, and the user experience that you receive in Informatica MDM is quite good."
"Axon does one interesting thing that I don't think other tools do as well. It lets you rate data and incorporates Informatica's data quality feature into it. There are little indications and graphics that show you how good the data quality is, and you can drill into it to see where potential issues lie."
"A great product enrichment tool."
"Informatica is user-friendly, stable, and scalable."
"We have matured as an organization with regards to better quality management, and we have evolved over time."
"​​Allows us to delete and correct incorrect data to make the searching of our applicant tracking system more consistent and relevant.​​"
"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."
"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."
"We only use the one feature for the NAICS code. This allows our product users to know what industry a business is in."
"Trial subscriptions (via cloud) are very cheap and easy to use."
"Melissa Data is cost effective and efficient."
"Decreases chances of incorrect shipping addresses and, thus, returned packages."
"We use a Melissa API to access the data, so it easy to use, accurate, and fast."
 

Cons

"We'd like to see the microservices, which don't run yet because the solution is not yet fully cloud-based."
"Informatica's issue is the licensing."
"They have to improve their relationship discovery tool. They say that they have AI inside, but this AI did not automatically find relationships or suggested relationships between entities."
"They have too many diversified products. If you don't know Informatica, it's very confusing and feels very idiotic."
"When it comes to UI look and feel and user experience, Informatica is not as good as other solutions."
"I need to have some insight into the tool's cloud capabilities."
"We haven't had many technical issues. We don't use all of the components of the tool that are more complex and error-prone."
"When it comes to UI look and feel and user experience, Informatica is not as good as other solutions."
"Needs to provide more phone numbers, even cell numbers (scrubbed numbers)."
"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 seems to be single threaded, and limits the amount of data that can be processed automatically."
"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.""
"There are some companies out there using Google or other sources to check / confirm if addresses are residential. If Melissa is not doing this, that could be an improvement."
"There are some companies out there using Google or other sources to check/confirm if addresses are residential. If Melissa is not doing this, that could be an improvement."
"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."
"It would be nice if it also had a user interface, as it did in years past."
 

Pricing and Cost Advice

"I rate the product's pricing a seven on a scale of one to ten, where one is the lowest price and ten is the highest price."
"It's an expensive solution."
"On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing nine and a half out of ten."
"The pricing is quite flexible."
"There is no doubt that it is very expensive, but the brand value comes at a cost. Other MDM solutions in the market that haven't proven themselves like Informatica are also pretty expensive. We need to understand that MDM itself is very expensive to implement. So, Informatica is also pretty expensive. I would rate it a two out of five for being pretty expensive."
"Informatica Axon is expensive."
"It is an expensive solution. I would say it is the most expensive solution in the market."
"So, there are plans for licensing. There are subscription-based and usage-based licenses. Also, there are licenses for exceptional analytics, etc. In short, there are different models of licensing for every enterprise."
"I think it's worth the value for me to run it."
"Depends on situation. We prefer to have data onsite, but some might prefer web access."
"The price for address validation is similar in all software. However, the price for geocoding decides the actual pricing. If you get their most accurate geocoding (called GeoPoints), then it will add about $10k+ per million requests."
"Cloud version is very cheap. On-premise version is expensive."
"Melissa pricing is competitive."
"Trial subscriptions (via cloud) are very cheap and easy to use. It’s a great way to test Listware to see if you want to go deeper with integration."
"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."
"Be sure to determine how the data is priced (record-based versus credit-based or some hybrid of data and services)."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Manufacturing Company
10%
Retailer
7%
Computer Software Company
7%
Insurance Company
11%
Construction Company
10%
Healthcare Company
8%
Comms Service Provider
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business51
Midsize Enterprise27
Large Enterprise153
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise3
Large Enterprise14
 

Questions from the Community

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Also Known As

ActiveVOS, Active Endpoints, Address Verification, Persistent Data Masking
No data available
 

Overview

 

Sample Customers

The Travel Company, Carbonite
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 Intelligent Data Management Cloud (IDMC) vs. Melissa Data Quality and other solutions. Updated: April 2026.
893,244 professionals have used our research since 2012.