Ixsight Data Quality vs Melissa Data Quality comparison

Ixsight and Melissa are both solutions in the Data Scrubbing Software category. Ixsight is ranked #9, while Melissa is ranked #3 with an average rating of 9.0. Ixsight holds a 1.5% mindshare in DSS, compared to Melissa’s 7.9% mindshare. Additionally, 100% of Ixsight users are willing to recommend the solution, compared to 95% of Melissa users who would recommend it.

Ixsight Data Quality

Read 1 Ixsight Data Quality review

126 Views
123 Comparison Views

100% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

656 Views
348 Comparison Views

95% willing to recommend

Ixsight Data Quality

Melissa Data Quality

Comparison Buyer's Guide

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Executive Summary

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

Find out what your peers are saying about Experian, Talend, Melissa and others in Data Scrubbing Software.

To learn more, read our detailed Data Scrubbing Software Report (Updated: July 2025).

Buyer's Guide

Data Scrubbing Software

July 2025

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Helped 863,429 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

Ixsight Data Quality

Ranking in Data Scrubbing Software

9th

Average Rating

8.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Melissa Data Quality

Ranking in Data Scrubbing Software

3rd

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Quality (8th)

Mindshare comparison

As of July 2025, in the Data Scrubbing Software category, the mindshare of Ixsight Data Quality is 1.5%, down from 2.4% compared to the previous year. The mindshare of Melissa Data Quality is 7.9%, up from 3.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Scrubbing Software

Featured Reviews

it_user826683

EVP & Head SDG

Dedupe helps us identify customer relationships as well as non-performing assets

We are using it primarily as a dedupe application. Our bank has multiple customer onboarding applications (different ones for trade products, non-trade, micro finance products, consumer finance products) and we use Ixsight to dedupe the customer across applications so that we know the customer's…

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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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Quotes from Members

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

Pros

"We are using it primarily as a dedupe application... We use Ixsight to dedupe the customer across applications so that we know the customer's relationship across the bank."

"Enables us to send out bulk mailings when we need to verify NCOA."

"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."

"Ability to keep our data set clean and usable for our community searches."

"We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database."

"Our customer database is now significantly more accurate and reliable."

"Be confident that the scalability and load are not going to be an issue with the services. "

"Allows us to identify cell phones before dialing, and giving us data about callers."

"Initial setup was fairly straightforward. The documentation was very good in terms of how to integrate and consume the service(s) that we use. It did not take an abundance of time to set up things on our side to use the service."

More Melissa Data Quality pros

Cons

"I would like them to evolve the product's online strategy, as more and more the need is for a "prefacto" dedupe (before creating the customer)."

"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"

"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."

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

"It would be nice if it also had a user interface, as it did in years past."

"If I had multiple Excel files open and ran Listware it would crash Excel, charge the credits, and not save the results."

"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."

"It will mix up family members at times, so we will change addresses at times that shouldn’t be changed."

More Melissa Data Quality cons

Pricing and Cost Advice

Information not available

"Pricing is very reasonable, no licensing required."

"It's affordable."

"They were willing to work with our preferred vendors, though it involved extra steps to get the license."

"You should have a good idea of the size of your data and the amount of cleansing you will be doing, so you will purchase the appropriate size bundle."

"Generally, the cost is ROI positive, depending on your shipping volume."

"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."

"Depends on situation. We prefer to have data onsite, but some might prefer web access."

"Be sure to determine how the data is priced (record-based versus credit-based or some hybrid of data and services)."

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Insurance Company

14%

Manufacturing Company

11%

Computer Software Company

10%

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Comparisons

No data available

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

Compared 32% of the time

Experian Data Quality vs Melissa Data Quality

Compared 30% of the time

Precisely Trillium vs Melissa Data Quality

Compared 21% of the time

Talend Data Quality vs Melissa Data Quality

Compared 17% of the time

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Product Reports

Buyer's Guide

Data Scrubbing Software

July 2025

Download Ixsight Data Quality product report

Buyer's Guide

Melissa Data Quality

July 2025

Download Melissa Data Quality product report

Overview

Ixsightâs data cleansing tool handles the customer data domain â by turning data that is just âMere Textâ to meaningful, standardized and validated output. Ixsightâs data cleansing tool works withÂ names, addresses, text data, contact dataÂ in form of emails, contact numbers and custom data to parse, validate, correct, populate, standardise enrich to give enhanced Ixsights.

Ixsight

Data Quality Components for SSIS

This suite of data transformations for Microsoft SQL Server Integration Services (SSIS) delivers the full spectrum of data quality including data profiling, data verification, data enrichment and data matching. With an intuitive interface and drag/drop capabilities, this powerful toolkit makes it easy to unify data into a single version of the truth for Master Data Management (MDM) success.

Melissa

Sample Customers

Axis Bank, Barclays, IndusInd Bank, Oriental Bank of Commerce, Tata Sky, Save the Children, Merkle Inc., Naaptol, Volkswagen, Voltas, Schneider Electric, Future Generali, HDFC Life, Bajaj Finserv, Indiabulls, Ranbaxy Laboratories

Boeing Co., FedEx, Ford Motor Co, Hewlett Packard, Meade-Johnson, Microsoft, Panasonic, Proctor & Gamble, SAAB Cars USA, Sony, Walt Disney, Weight Watchers, and Intel.

Buyer's Guide

Data Scrubbing Software

July 2025

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Find out what your peers are saying about Experian, Talend, Melissa and others in Data Scrubbing Software. Updated: July 2025.

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