Melissa Data Quality vs SQL Power Data Quality comparison

Why PeerSpot?

Melissa and SQL Power are both solutions in the Data Scrubbing Software category. Melissa is ranked #4, while SQL Power is ranked #7. Melissa holds a 9.3% mindshare in DSS, compared to SQL Power’s 3.4% mindshare. Additionally, 95% of Melissa users are willing to recommend the solution, compared to 100% of SQL Power users who would recommend it.

Melissa Data Quality

Read 40 Melissa Data Quality reviews

3,805 Views
2,321 Comparison Views

95% willing to recommend

SQL Power Data Quality

Read 4 SQL Power Data Quality reviews

880 Views
827 Comparison Views

100% willing to recommend

Melissa Data Quality

SQL Power Data Quality

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Melissa Data Quality and SQL Power Data Quality based on real PeerSpot user reviews.

Find out in this report how the two Data Scrubbing Software solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Melissa Data Quality vs. SQL Power Data Quality Report (Updated: November 2026).

Buyer's Guide

Melissa Data Quality vs. SQL Power Data Quality

November 2026

Download the complete report

Helped 920,769 peers since 2012

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

Ranking in other categories

Data Quality (13th)

SQL Power Data Quality

Ranking in Data Scrubbing Software

7th

Average Rating

8.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2026, in the Data Scrubbing Software category, the mindshare of Melissa Data Quality is 9.3%, up from 6.9% compared to the previous year. The mindshare of SQL Power Data Quality is 3.4%, up from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Scrubbing Software Mindshare Distribution
Product	Mindshare (%)
Melissa Data Quality	9.3%
SQL Power Data Quality	3.4%
Other	87.3%

Data Scrubbing Software

Featured Reviews

GaryM

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.

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reviewer2091297

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.…

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Quotes from Members

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

Pros

"When we plugin the contact verify component in the ETL from Source Systems, it will greatly help in standardizing and cleansing the source data and help keep the downstream systems clean."

"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."

"Decreases chances of incorrect shipping addresses and, thus, returned packages."

"Allows us to delete and correct incorrect data to make the searching of our applicant tracking system more consistent and relevant."

"I was able to dedupe millions of records in the past, and append the most recent email."

"Address verification ensures our customers get their packages, and we aren’t charged for incomplete address information."

"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."

"We now have less errors on catalog address labels."

More Melissa Data Quality pros

"The solution is very easy to use and it's quite flexible."

"SQL Power Data Quality is truly a proven product that makes the work of cleaning data in both source and target data easy yet efficient."

"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."

"The solution is able to integrate with many systems and other products."

Cons

"Did not work as advertized. Needs better results in address parsing, as described on the website."

"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."

"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"

"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."

"Needs to provide more phone numbers, even cell numbers (scrubbed numbers)."

"One thing I would want to have, when you're doing a property search, you can do it either on the FIPS in the APN number or the address itself. For some entries, I'll have the APN number, and some I'll have the address. Apparently it cannot process something when both the FIPS-APN and the address are on there. I have to sort, once with one and once with the other, which is a little bit of a pain."

More Melissa Data Quality cons

"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."

"Integrating SQL Power with the system is challenging especially in places where no tutorials found and new versions continue to be released with varying requirements."

Pricing and Cost Advice

"Buy a lot more credits than you think you’re going to need."

"Pricing is very reasonable, no licensing required."

"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."

"This vendor has no equal in pricing for equivalent functionality."

"It's affordable."

"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."

"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."

More Melissa Data Quality pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Construction Company

16%

Outsourcing Company

14%

Comms Service Provider

10%

Insurance Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	3
Large Enterprise	14

No data available

Comparisons

Qlik Talend Cloud vs Melissa Data Quality

Compared 13% of the time

Experian Data Quality vs Melissa Data Quality

Compared 12% of the time

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

Compared 6% of the time

BCC Data Quality vs Melissa Data Quality

Compared 6% of the time

Ataccama ONE Platform vs Melissa Data Quality

Compared 4% of the time

More Melissa Data Quality Competitors

BCC Data Quality vs SQL Power Data Quality

Compared 14% of the time

Qlik Talend Cloud vs SQL Power Data Quality

Compared 13% of the time

Omikron Data Quality vs SQL Power Data Quality

Compared 12% of the time

Ataccama ONE Platform vs SQL Power Data Quality

Compared 12% of the time

Infoshare Data Quality vs SQL Power Data Quality

Compared 5% of the time

More SQL Power Data Quality Competitors

Product Reports

Buyer's Guide

Melissa Data Quality

October 2026

Download Melissa Data Quality product report

Buyer's Guide

Data Scrubbing Software

October 2026

Download SQL Power Data Quality product report

Overview

Melissa Data Quality delivers robust features for address validation and data standardization with seamless SSIS integration, making it a cost-effective choice for managing large datasets on-premises or in the cloud.

Emphasizing efficiency, Melissa Data Quality supports organizations in refining data accuracy through features like address validation, parsing, and cleansing. Its integration with SSIS simplifies setup and enhances operational ease, while solutions like Personator provide comprehensive contact detail acquisition. The system's match process ensures accurate deduplication, catering to extensive datasets with flexibility from on-premises to cloud deployments. Despite its strengths, there could be improvements in handling unknown addresses, phone number standardization, and international support, alongside refining processing speed and streamlining license management.

What features does Melissa Data Quality offer?

Address Validation: Ensures accurate address data
Data Parsing: Breaks data into structured components
Data Cleansing: Removes inaccuracies and standardizes
SSIS Integration: Simplifies installation and operation
Personator: Extracts names, phone numbers, and emails

What benefits can be expected from Melissa Data Quality?

Cost Efficiency: Provides value for business data needs
Accuracy: Enhances precision through deduplication
Flexibility: Adapts from on-premises to cloud solutions
Contact Verification: Streamlines onboarding processes

Organizations employ Melissa Data Quality for accurate address validation, customer data accuracy, and geocoding. It's instrumental in duplicate identification, data cleansing, and maintaining address accuracy via USPS NCOA. During customer onboarding, it verifies details while integrating seamlessly with existing data systems, using Listware and Personator for precise address entry, geocoding, and status updates, helping classify businesses by industry.

Melissa

SQL Power Data Quality enhances data management by providing an efficient platform designed for robust data quality processes. It's a comprehensive tool essential for data-driven organizations seeking accuracy and integrity in their data solutions.

Organizations leveraging SQL Power Data Quality benefit from advanced data profiling and cleansing capabilities, equipped with intuitive features that enable users to address complex data quality challenges effectively. It supports a seamless integration and automation process, allowing users to concentrate their efforts on strategic planning and decision-making by reducing manual data handling.

What are the key features of SQL Power Data Quality?

Data Profiling: Identify anomalies and patterns effortlessly for improved data accuracy.
Data Cleansing: Automatically correct and standardize data entries to ensure consistency.
Real-time Monitoring: Detect and address data quality issues promptly as they arise.
Automation Capabilities: Streamline repetitive data tasks to enhance productivity and efficiency.
Scalability: Easily adapt to expanding data sets and growing organizational data needs.

What benefits should be considered when reviewing SQL Power Data Quality?

Cost Efficiency: Reduces operational costs by automating data quality processes.
Improved Decision-Making: Enhances the reliability of business analytics through cleaner data.
Time Savings: Minimizes time spent on manual data corrections.
Data Integrity: Ensures high-quality, accurate datasets that support strategic goals.
Enhanced Compliance: Facilitates adherence to regulatory standards with comprehensive auditing features.

Industries like finance, healthcare, and telecommunications effectively integrate SQL Power Data Quality to meet stringent data standards. Finance institutions utilize its capabilities for auditing and risk management, while healthcare benefits from improved patient record accuracy. In telecommunications, the focus is on optimizing customer data for better service delivery. SQL Power Data Quality serves crucial industry-specific needs by offering versatile solutions tailored to unique challenges.

SQL Power

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

Buyer's Guide

Melissa Data Quality vs. SQL Power Data Quality

November 2026

Free Report: Melissa Data Quality vs. SQL Power Data Quality

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