Ixsight Data Quality vs Melissa Data Quality comparison

Ixsight and Melissa are both solutions in the Data Scrubbing Software category. Ixsight is ranked #10, while Melissa is ranked #5 with an average rating of 9.0. Ixsight holds a 2.5% 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

192 Views
190 Comparison Views

100% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

1,022 Views
613 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.

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To learn more, read our detailed Data Scrubbing Software Report (Updated: January 2026).

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Data Scrubbing Software

January 2026

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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

10th

Average Rating

8.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Melissa Data Quality

Ranking in Data Scrubbing Software

5th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Quality (5th)

Mindshare comparison

As of January 2026, in the Data Scrubbing Software category, the mindshare of Ixsight Data Quality is 2.5%, up from 1.8% compared to the previous year. The mindshare of Melissa Data Quality is 7.9%, up from 5.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Scrubbing Software Market Share Distribution
Product	Market Share (%)
Melissa Data Quality	7.9%
Ixsight Data Quality	2.5%
Other	89.6%

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."

"Standardizing allows me to more effectively check for duplicate/existing records. Verifying increases the value of the data."

"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."

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

"We like having the ability to write our own utilities/software to process our records and store the final output the way we want."

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

"Through more accurate data, our marketing department has been able to increase delivery and conversion rates through email direct marketing initiatives."

"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."

"We mainly communicate with our customers via email, so we primarily use it to find a phone number so we can contact them more efficiently. This allows us to talk to them and resolve their issues much more quickly."

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)."

"The billing structure does not seem very accurate. We’ve had issues with miscounted batch records processed"

"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."

"MatchUp seems to be single threaded, and limits the amount of data that can be processed automatically."

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

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

"The custom software solution we still use in-house makes Excel a lot slower than usual."

"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."

"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."

More Melissa Data Quality cons

Pricing and Cost Advice

Information not available

"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."

"I think it's worth the value for me to run it."

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

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

"Pricing is very reasonable, no licensing required."

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

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

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

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Insurance Company

15%

Manufacturing Company

Educational Organization

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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

Comparisons

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Compared 100% of the time

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Qlik Talend Cloud vs Melissa Data Quality

Compared 23% of the time

Experian Data Quality vs Melissa Data Quality

Compared 14% of the time

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

Compared 10% of the time

Coheris Spad Data Quality vs Melissa Data Quality

Compared 8% of the time

Anchor Software Data Quality vs Melissa Data Quality

Compared 7% of the time

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Product Reports

Buyer's Guide

Data Scrubbing Software

January 2026

Download Ixsight Data Quality product report

Buyer's Guide

Melissa Data Quality

January 2026

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

January 2026

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