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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
4th
Average Rating
8.4
Reviews Sentiment
7.6
Number of Reviews
40
Ranking in other categories
Data Quality (8th)
SQL Power Data Quality
Ranking in Data Scrubbing Software
7th
Average Rating
8.8
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the Data Scrubbing Software category, the mindshare of Melissa Data Quality is 6.8%, up from 4.5% compared to the previous year. The mindshare of SQL Power Data Quality is 0.7%, down from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Scrubbing Software
 

Featured Reviews

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.
Ayinde Hammed - PeerSpot reviewer
Helps you cleanse your data, validate and correct addresses, and identify and remove duplicates
I use SQL most of the time to clean up the data, transform it, and then push it into the database. We extract data from apps and from websites using a lot of applications. We do that using Python. We used Outlook before to pull data from, the source and then log into Snowflake.  The Nomo, select…

Quotes from Members

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

Pros

"Our customer database is now significantly more accurate and reliable."
"Services for all manner of data-driven organizations, no matter their size or budget."
"​Allows us to identify cell phones before dialing, and giving us data about callers."
"​We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database.​"
"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."
"It gives me an assessed value of the property in question. My partner and I are property investors, and it's good to get an assessed value to cull out properties that we're not interested in."
"Address verification ensures our customers get their packages, and we aren’t charged for incomplete address information."
"It is a scalable solution. We have over 1,000 SQL Power Data Quality users in our organization."
"The solution is able to integrate with many systems and other products."
"The Nomo, select form, and so on are the most valuable features."
 

Cons

"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."
"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."
"We have noticed that some of the emails and addresses return with confusing or incorrect codes, but for the most part, it is accurate.​"
"I wish there was a way to do a "test run" and see what a particular format will give you."
"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 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."
"Address validation and parsing in a few countries have room for improvement."
"There are some hitches in setup, especially with the new encoding, but otherwise it’s relatively simple."
"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."
"The normalization factor should be improved so that it is better scaled. It should be more user-friendly."
"Downtime issues should be improved."
 

Pricing and Cost Advice

"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."
"Pricing is very reasonable."
"​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."
"Cloud version is very cheap. On-premise version is expensive."
"Understand how may transactions you will be processing so that you can get the right tier pricing."
"Depends on situation. We prefer to have data onsite, but some might prefer web access."
"They were willing to work with our preferred vendors, though it involved extra steps to get the license."
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Top Industries

By visitors reading reviews
Insurance Company
14%
Manufacturing Company
13%
Financial Services Firm
12%
Computer Software Company
8%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

Ask a question
Earn 20 points
What do you like most about SQL Power Data Quality?
The Nomo, select form, and so on are the most valuable features.
What advice do you have for others considering SQL Power Data Quality?
It is a very good solution and I recommend it. I rate the overall solution an eight out of ten.
 

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: March 2025.
845,406 professionals have used our research since 2012.