Informatica Cloud Data Quality vs Melissa Data Quality comparison

Informatica and Melissa are both solutions in the Data Quality category. Informatica is ranked #3 with an average rating of 8.0, while Melissa is ranked #8 with an average rating of 9.0. Informatica holds a 4.4% mindshare in DQ, compared to Melissa’s 2.9% mindshare. Additionally, 75% of Informatica users are willing to recommend the solution, compared to 95% of Melissa users who would recommend it.

Informatica Cloud Data Quality

Read 17 Informatica Cloud Data Quality reviews

896 Views
896 Comparison Views

75% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

750 Views
405 Comparison Views

95% willing to recommend

Informatica Cloud Data Quality

Melissa Data Quality

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 6, 2025

Melissa Data Quality and Informatica Cloud Data Quality are competing products in the data cleansing and enhancement category. Informatica Cloud Data Quality has the upper hand with its advanced features and comprehensive integration capabilities, which justify its higher price for many users.

Features: Melissa Data Quality is known for data verification, enrichment, and ease of use, ideal for businesses prioritizing data accuracy. It offers a straightforward installation and configuration with components like Contact Verify and MatchUp. Informatica Cloud Data Quality is favored for its advanced integration and automation features, Master Data Management, and a user-friendly interface, making it suitable for enterprises needing scalable solutions.

Room for Improvement: Melissa Data Quality could benefit from enhanced support for more complex data needs, increased flexibility in integration, and advanced rule creation capabilities. Informatica Cloud Data Quality may improve by simplifying its deployment complexity, offering more cost-effective pricing options, and enhancing user training resources for its comprehensive features.

Ease of Deployment and Customer Service: Melissa Data Quality provides a straightforward deployment process with strong customer support, making it convenient for smaller teams. On the other hand, Informatica Cloud Data Quality, while having a complex deployment, is backed by comprehensive customer service, suiting organizations with intricate data requirements.

Pricing and ROI: Melissa Data Quality offers a cost-effective setup, allowing for quick ROI, appealing to businesses looking to minimize initial expenses. Informatica Cloud Data Quality involves a higher upfront cost, viewed as a valuable long-term investment due to its extensive capabilities and scalable solutions.

To learn more, read our detailed Informatica Cloud Data Quality vs. Melissa Data Quality Report (Updated: September 2025).

Buyer's Guide

Informatica Cloud Data Quality vs. Melissa Data Quality

September 2025

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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

Informatica Cloud Data Quality

Ranking in Data Quality

3rd

Average Rating

8.0

Reviews Sentiment

5.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Melissa Data Quality

Ranking in Data Quality

8th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Scrubbing Software (5th)

Mindshare comparison

As of October 2025, in the Data Quality category, the mindshare of Informatica Cloud Data Quality is 4.4%, down from 8.7% compared to the previous year. The mindshare of Melissa Data Quality is 2.9%, up from 2.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality Market Share Distribution
Product	Market Share (%)
Informatica Cloud Data Quality	4.4%
Melissa Data Quality	2.9%
Other	92.7%

Data Quality

Featured Reviews

Mehmet SukruKaya

Senior Data Analytics Manager at Esan

Improved data quality significantly enhances project efficiency and effectiveness

I am not utilizing the data quality rules management part yet. We had a bad experience before Informatica Cloud Data Quality. We started a data analytics project that took more than three months of wasted time because we couldn't use the data to create the optimization model. If we have an application like Informatica Cloud Data Quality or a data quality platform, we can finish the project in less than three months. This is the on-prem data that we ingested. We don't use any cloud data that we have. For now, we are just using the on-prem data, and we don't have any integration from the data outside of the on-prem. I would recommend it to other users. On a scale of 1-10, I rate this solution a 9.

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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

"The most beneficial feature of Informatica Cloud Data Quality is it's cloud-based."

"We primarily used Cloud Data Profiling to connect with Cloud Data Governance, a tool also used by Teva. This integration allowed users to access data quality results within the data governance catalog."

"The reusability factors are nice. The Cloud Data Quality is much better. A major flaw in the previous version was integration with the catalog, which is now seamless."

"I was responsible for installing Informatica Cloud Data Quality on Google infrastructure, which was straightforward."

"One of the most valuable features of Informatica Cloud Data Quality is Master Data Management. You can write code to build your logic rules to check the quality."

"Server maintenance, server hosting, backup, restoration, and DB capabilities are not needed in the cloud."

"An advantage is its seamless integration with other Informatica capabilities, making data quality a deeply embedded part of the solution."

"We had a bad experience before Informatica Cloud Data Quality, we started a data analytics project that took more than three months of wasted time because we couldn't use the data to create the optimization model."

More Informatica Cloud Data Quality pros

"Gives us the ability to offer an additional resource that other companies do not."

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

"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."

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

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

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

"By validating and parsing the addresses our customers submit to us, we have reduced the number of addressing errors encountered during our processing."

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

More Melissa Data Quality pros

Cons

"Informatica Cloud Data Quality has significant room for improvement. It is not stable, and there are several issues, especially on the cloud side, unlike the on-premise version which was very stable."

"If given the opportunity, I would like to address these concerns, particularly with regard to enhancing the end-user experience."

"Improving the UI to be more business user-friendly would also be beneficial."

"The high price of the product is an area of concern where improvements are required."

"You cannot import the data discovery rules you create in the solution to the Cloud Data Governance and Catalog (CDGC)."

"The integration with older technology and cloud quality needs improvement."

"Logical views are a little bit behind in comparison to the on-premise version."

"If a new solution has the same features and less investment, it would be worth considering."

More Informatica Cloud Data Quality cons

"Needs better email append coverage (but every vendor struggles with this)."

"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 more/better search tools are needed. Also, state and local tax data would be nice."

"More countries should be supported by Melissa."

"There are some hitches in setup, especially with the new encoding, but otherwise it’s relatively simple."

"I wish there was a way to do a "test run" and see what a particular format will give you."

"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."

More Melissa Data Quality cons

Pricing and Cost Advice

"The licensing costs attached to the solution are pretty high, but then, with the cloud model, the prices depend on what it provides for the value of money, which I feel was very high."

"Informatica Cloud Data Quality is a costly solution."

"We pay for a yearly subscription."

"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 is affordable."

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

"Cloud version is very cheap. On-premise version is expensive."

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

"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."

"It's affordable."

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

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Manufacturing Company

12%

Computer Software Company

10%

Healthcare Company

Insurance Company

13%

Manufacturing Company

13%

Computer Software Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	2
Large Enterprise	9

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

Questions from the Community

What do you like most about Informatica Cloud Data Quality?

The profiling features are much better than the on-premise version.

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What needs improvement with Informatica Cloud Data Quality?

I think it would be very useful to have the same features on the data center version available on the cloud version. I remember when I used it, there was some limitation in one of the data quality ...

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What is your primary use case for Informatica Cloud Data Quality?

I worked on a project where we had to use these tools to execute the data quality requirements from assessment perspectives to scorecards and similar tasks. I haven't used any other tools, so I can...

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Compared 16% of the time

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Compared 16% of the time

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

Compared 12% of the time

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Compared 10% of the time

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Product Reports

Buyer's Guide

Informatica Cloud Data Quality

October 2025

Download Informatica Cloud Data Quality product report

Buyer's Guide

Melissa Data Quality

September 2025

Download Melissa Data Quality product report

Also Known As

Cloud Data Quality Radar

No data available

Overview

Informatica Cloud Data Quality Radar is a cloud application that quickly identifies, fixes, and monitors data quality problems in your business applications—wherever they are, in the cloud or on-premise.

This easy-to-use, browser-based tool empowers line-of-business managers to take ownership of the data quality process so business can maximize the return on trusted data. Informatica Cloud Data Quality Radar enables you to quickly assess the strengths and weaknesses in your data, to track improvements in the data over time, and to calculate data quality scores for objects and field entities with the flexibility to filter and drill down on specific records for better detection of problems.

Informatica

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

Freddie Mac, Rabobank

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

Informatica Cloud Data Quality vs. Melissa Data Quality

September 2025

Free Report: Informatica Cloud Data Quality vs. Melissa Data Quality

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