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Melissa Data Quality vs SAP Data Quality Management 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

Melissa Data Quality
Ranking in Data Quality
5th
Average Rating
8.4
Reviews Sentiment
7.6
Number of Reviews
40
Ranking in other categories
Data Scrubbing Software (5th)
SAP Data Quality Management
Ranking in Data Quality
9th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the Data Quality category, the mindshare of Melissa Data Quality is 4.4%, up from 2.6% compared to the previous year. The mindshare of SAP Data Quality Management is 3.3%, down from 4.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality Market Share Distribution
ProductMarket Share (%)
Melissa Data Quality4.4%
SAP Data Quality Management3.3%
Other92.3%
Data Quality
 

Featured Reviews

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.
VB
Director at Norderia
Embrace efficient data management with integrated features but anticipate some enhancement needs
This tool itself is new. SAP Data Quality Management was brought in by SAP recently, maybe a year or two years back. We just started implementing and we still have not heard exact feedback from the client. It would not be correct if I give feedback now because I don't have accurate feedback from client usage. I feel it is a good tool with some limitations. We compared it with Celonis, which is also one of the other tools in the market. I am more into SAP and S4 HANA, so I am not familiar with all the best tools available in Data Quality Management which can be compatible with SAP. We know there are issues with SAP Data Quality Management. The advantage of this tool that SAP brought is that it is already in-built. You don't need to build another application layer on top of the existing one. The compatibility and response time for these applications within the same database is faster.

Quotes from Members

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

Pros

"​We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database.​"
"This tool works better for us than using a batch processing system that we do not have enough control over as each record is being processed."
"SSIS integration."
"By validating and parsing the addresses our customers submit to us, we have reduced the number of addressing errors encountered during our processing."
"Gives us the ability to offer an additional resource that other companies do not."
"Be confident that the scalability and load are not going to be an issue with the services. ​"
"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."
"Provides quality accurate data that our downstream solutions depend on."
"Scalability is good."
"Our primary use case is for us to inspect the results from the product and material, and for releasing or leaving the status of the product."
"We work with API standards or norms for internal applications, so it's essential for SSE to have tests and pass those tests according to the criteria, which makes SAP Data Quality Management very important for our products."
 

Cons

"More countries should be supported by Melissa."
"​If I had multiple Excel files open and ran Listware it would crash Excel, charge the credits, and not save the results."
"It will mix up family members at times, so we will change addresses at times that shouldn’t be changed."
"The SSIS component setup seems a little klunky."
"Did not work as advertized. Needs better results in address parsing, as described on the website."
"Needs to validate more addresses accurately."
"Needs better email append coverage (but every vendor struggles with this)."
"The billing structure does not seem very accurate. We’ve had issues with miscounted batch records processed"
"SAP Data Quality Management would be better if it directly integrates with the ME system. Right now, the company has a lot of machines on the shop floor working as a standalone, so you have to use all methods to ensure that the data interface appears on the ME system and that SAP Data Quality Management records the QM results. It would be much easier if the ME system could be integrated directly with SAP Data Quality Management."
"There are some limitations. They are not covering complete scenarios for all the modules."
"I would like for them to develop a feature to able to record all of our inspections; so all the data can go through SAP. It's not user-friendly or easy to get further analysis, so we mostly skip this step."
 

Pricing and Cost Advice

"Cloud version is very cheap. On-premise version is expensive."
"It's affordable."
"This vendor has no equal in pricing for equivalent functionality."
"​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."
"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."
"Pricing is very reasonable."
"Pricing is very reasonable, no licensing required."
"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."
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Top Industries

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

Company Size

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

Questions from the Community

Ask a question
Earn 20 points
What needs improvement with SAP Data Quality Management?
This tool itself is new. SAP Data Quality Management was brought in by SAP recently, maybe a year or two years back. We just started implementing and we still have not heard exact feedback from the...
What is your primary use case for SAP Data Quality Management?
Currently, one of our clients is seeking SAP Data Quality Management solutions, so we are exploring options in that area. The product is not mature yet, so they need to work to improve it. We are a...
What advice do you have for others considering SAP Data Quality Management?
For smaller organizations, I don't think this much is required. If it is a bigger size client from a business point of view, I definitely recommend this tool. They can use it if they are already us...
 

Also Known As

No data available
SAP BusinessObjects Data Quality Management, BusinessObjects Data Quality Management
 

Overview

 

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.
AOK Bundesverband, Surgutneftegas Open Joint Stock Company, Molson Coors Brewing Company, City of Buenos Aires, ASR Group, Citrix, EarlySense, Usha International Limited, Automotive Resources International, Wªrth Group, Takisada-Osaka Co. Ltd., Coelba, R
Find out what your peers are saying about Melissa Data Quality vs. SAP Data Quality Management and other solutions. Updated: February 2026.
881,733 professionals have used our research since 2012.