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Melissa Data Quality vs SQL Power 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

Melissa Data Quality
Ranking in Data Scrubbing Software
5th
Average Rating
8.4
Reviews Sentiment
7.6
Number of Reviews
40
Ranking in other categories
Data Quality (5th)
SQL Power Data Quality
Ranking in Data Scrubbing Software
9th
Average Rating
8.8
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the Data Scrubbing Software category, the mindshare of Melissa Data Quality is 9.0%, up from 6.1% compared to the previous year. The mindshare of SQL Power Data Quality is 3.0%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Scrubbing Software Market Share Distribution
ProductMarket Share (%)
Melissa Data Quality9.0%
SQL Power Data Quality3.0%
Other88.0%
Data Scrubbing Software
 

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.
reviewer2091297 - PeerSpot reviewer
Fraud Strategist(Actimize/SAS) at a financial services firm with 10,001+ employees
Is easy to deploy and is stable and scalable
I like the load balancing feature The normalization factor should be improved so that it is better scaled. It should be more user-friendly. It should be easier to export reports. I've been using SQL Power Data Quality for 10 years. SQL Power Data Quality is stable. It is a scalable solution.…

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 send out client mailings with the most accurate addresses possible."
"Ability to validate addresses, make corrections to address."
"There have been tangible benefits in combating fraudulent transactions. The information from Melissa Data is fed straight into our fraud system. This creates efficiency but also removes the need for manual address checks."
"It cuts down significantly on time in trying to match names to addresses. I can do in a few hours what would otherwise take days to accomplish."
"Extremely easy to install and setup."
"We only use the one feature for the NAICS code. This allows our product users to know what industry a business is in."
"Be confident that the scalability and load are not going to be an issue with the services. ​"
"We like having the ability to write our own utilities/software to process our records and store the final output the way we want."
"The solution is able to integrate with many systems and other products."
"The Nomo, select form, and so on are the most valuable features."
"It is a scalable solution. We have over 1,000 SQL Power Data Quality users in our organization."
 

Cons

"The custom software solution we still use in-house makes Excel a lot slower than usual."
"It would be helpful if a list of the codes and explanations could be included."
"MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version."
"The SSIS component setup seems a little klunky."
"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."
"Many issues, sometimes I have to completely log out and start over."
"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."
"Pricing model."
"The normalization factor should be improved so that it is better scaled. It should be more user-friendly."
"Downtime issues should be improved."
"The only area of improvement that we've come across within the solution was the portfolio roadmap creation. There's a bit of limitation there, but otherwise, the tool itself is very good."
 

Pricing and Cost Advice

"Cloud version is very cheap. On-premise version is expensive."
"They were willing to work with our preferred vendors, though it involved extra steps to get the license."
"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."
"​It is affordable."
"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."
"Pricing is very reasonable."
"​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."
"It's affordable."
Information not available
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Top Industries

By visitors reading reviews
Insurance Company
15%
Educational Organization
6%
Manufacturing Company
6%
Computer Software Company
6%
No data available
 

Company Size

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

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.
TimeWarner, Champion Technologies Tiscali, Oneil, Broadspire,youbet.com, Pepsi Co, Citco, John Lewes
Find out what your peers are saying about Melissa Data Quality vs. SQL Power Data Quality and other solutions. Updated: February 2026.
881,707 professionals have used our research since 2012.