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

Informatica and Melissa are both solutions in the Data Quality category. Informatica is ranked #1 with an average rating of 7.8, while Melissa is ranked #8 with an average rating of 9.0. Informatica holds a 16.6% mindshare in DQ, compared to Melissa’s 3.2% mindshare. Additionally, 93% of Informatica users are willing to recommend the solution, compared to 95% of Melissa users who would recommend it.

Informatica Intelligent Dat...

Read 185 Informatica Intelligent Data Management Cloud (IDMC) reviews

22,748 Views
2,047 Comparison Views

93% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

653 Views
372 Comparison Views

95% willing to recommend

Informatica Intelligent Dat...

Melissa Data Quality

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Executive SummaryUpdated on Jan 6, 2025

Informatica Intelligent Data Management Cloud and Melissa Data Quality compete in the data management and quality domain. Informatica IDMC has an advantage due to its robust data integration capabilities.

Features: IDMC offers extensive data integration with a variety of connectors and automation tools, AI-driven insights, and flexible scalability. Melissa Data Quality provides precise data verification and cleansing, focusing on address validation, geocoding, and contact data verification.

Room for Improvement: IDMC could enhance its initial cost-effectiveness, simplify setup processes, and expand support for more specialized data validation features. Melissa Data Quality might improve by enhancing its integration capabilities, developing more robust cloud-based features, and offering a wider range of automated data insights.

Ease of Deployment and Customer Service: IDMC supports a cloud-based approach, ensuring efficient integration with multiple platforms and offering strong customer support. Melissa Data Quality offers both on-premises and cloud options, providing personalized customer service despite potentially complex deployments.

Pricing and ROI: IDMC is a higher upfront investment with long-term ROI benefits through its scalability and comprehensive features. Melissa Data Quality is more cost-effective initially, offering essential data quality functions at a lower setup cost.

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

Buyer's Guide

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

July 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 Intelligent Dat...

Ranking in Data Quality

1st

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

185

Ranking in other categories

Data Integration (4th), Business Process Management (BPM) (9th), Business-to-Business Middleware (5th), API Management (7th), Cloud Data Integration (3rd), Data Governance (2nd), Test Data Management (3rd), Cloud Master Data Management (MDM) Solutions (1st), Data Management Platforms (DMP) (2nd), Data Masking (2nd), Metadata Management (1st), Test Data Management Services (3rd), Product Information Management (PIM) (1st), Data Observability (2nd)

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 (4th)

Mindshare comparison

As of August 2025, in the Data Quality category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 16.6%, down from 23.2% compared to the previous year. The mindshare of Melissa Data Quality is 3.2%, up from 2.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality

Featured Reviews

Saikat Ghosh

Consulting Principal & Founder at Digital Data Consultancy

Match and merge functionality is still the best but cloud version needs more functionality

There are various areas for improvement in IDMC. Enhancements on basic data management functionality and the UI front, such as multiple templates and improved grid views, would be beneficial. Bulk data management features could be improved from the UI perspective to get to the level of the on prem versions of Informatica MDM. The tool needs to mature but missing small but important features, like restricted dynamic attributes functionality, data inheritance rules in master hierachies, identifiers not being passed in jobs is a drawback.

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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

"In the latest version, I like the outlay of the business roles creation. I like seeing that visualization as you're building it, as opposed to going through metatables or XML mappings. We liked that piece, and it makes it more intuitive for the business."

"I do find Informatica Data Quality is stable. It generally maintains a high level of reliability and stability, making it an asset."

"The most valuable features of Informatica MDM are it is cloud-enabled and has all the elements that are supposed to have in terms of MDM as a solution. All the features that are there. It is very well-integrated with any of the SAP and non-SAP applications. It is quite user-friendly. The user experience that you receive in Informatica MDM is quite good."

"There are a couple of valuable features. One is that it is very quick on the profiling. So, you get a very fast snapshot of the type of data that you're looking at from the profiling perspective. It can highlight anomalies in the data."

"Its data cleansing capabilities are very valuable. The match and merge and the audit trail functionalities are very good."

"Seeing the data in the mapping itself is really nice."

"It provides all the typical MDM capabilities like deduplication and machine survivorship."

"Replication allows us to fully replicate all objects from Shop Floor Data Collection (SFDC) to in-house/on-premises database in one job."

More Informatica Intelligent Data Management Cloud (IDMC) pros

"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."

"We ran a standard name, address, and zip code, internal dedupe between the different files we had purchased, and we were able to quickly notify our vendor that they had tens of thousands of duplications that they were not even aware of."

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

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

"The customers' addresses are now complete, correct and follow one consistent format."

"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."

"Provides simplicity, ease of use, combined with overall accuracy of data."

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

More Melissa Data Quality pros

Cons

"There may be some types of limitations with the performance."

"The cloud version of Axon is far behind the on-prem, and many of my clients want to go fully to the cloud. However, Axon has to be an on-prem installation. I would like to see their cloud products catch up with their on-prem capabilities."

"The configurations could be better. It is a bit confusing because we must develop two tools when building a data model in Informatica MDM. Even though Informatica MDM is a single tool, we have our hub console plus the provisioning tool within that. Whatever data model we are building in the hub console, we have to develop it in the provisioning tool again. It is double the work to create a data model. We are also using external calls or the Java custom plans functions. This can be both positive and negative. Since MDM as a client does not support any complex validation, we have to depend on the external call or a Java call. Every time we deployed, the entire solution was impacted if something went wrong."

"I would like to see better visuals for business users, such as a dashboard where they can precisely track where problems are."

"It would be helpful if there was a GenAI feature integrated into the system, especially regarding the data quality."

"They need more feature flexibility, as it is not fully developed."

"There are some limitations with Informatica Axon when one tries to connect or integrate it with Jira."

"The product isn't mature enough to provide suitable connectors to various data engines."

More Informatica Intelligent Data Management Cloud (IDMC) cons

"It would be helpful if a list of the codes and explanations could be included."

"Pricing model."

"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."

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

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

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

"Many issues, sometimes I have to completely log out and start over."

More Melissa Data Quality cons

Pricing and Cost Advice

"Comparatively, their prices are a little bit too high."

"We saw an ROI. We have been able to get data from various sources and consolidate it into a data lake, which is helping us in data analytics."

"It's pretty high for us. It's more on the higher side, like low to middle high."

"The pricing is high compared to other tools on the market."

"The solution is very expensive."

"Licensing is difficult to understand, but the team is always available to explain anything. They are very helpful."

"So, there are plans for licensing. There are subscription-based and usage-based licenses. Also, there are licenses for exceptional analytics, etc. In short, there are different models of licensing for every enterprise."

"The price is comparable."

More Informatica Intelligent Data Management Cloud (IDMC) 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."

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

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

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

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

"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."

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

"It is affordable."

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Computer Software Company

11%

Manufacturing Company

10%

Insurance Company

14%

Manufacturing Company

11%

Financial Services Firm

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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Product Reports

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC)

August 2025

Informatica Intelligent Data Management Cloud (IDMC) report

Download Informatica Intelligent Data Management Cloud (IDMC) product report

Buyer's Guide

Melissa Data Quality

August 2025

Download Melissa Data Quality product report

Also Known As

ActiveVOS, Active Endpoints, BPM, Address Verification, Persistent Data Masking, Cloud Test Data Management, PIM, , Enterprise Data Catalog, Data Integration Hub, Cloud Data Integration, Data Quality, Cloud API and App Integration

No data available

Overview

Informatica Intelligent Data Management Cloud (IDMC) is a robust platform used by banks, financial institutions, and health sector organizations for data management, governance, and compliance.

IDMC provides comprehensive tools for data discovery, profiling, masking, and transformation. It supports Salesforce integration, real-time data streaming, and scalable data management solutions. Health organizations manage national product catalogs while financial entities focus on data protection and regulatory compliance. Its intuitive interface, flexible features, and robust tools make it valuable across sectors, though enhancements in data integration and human workflow are being sought.

What are the most important features?

Data discovery: Facilitates identifying and understanding data sources.
Data profiling: Analyzes old databases for data quality.
Data and platform masking: Ensures data protection.
Salesforce integration: Seamless connectivity with Salesforce.
Mastering data: Centralizing and standardizing data.
UI intuitiveness: User-friendly interface.
Feature map flexibility: Adapts to user needs.
Business glossary creation: Defines business terms.
Data lineage: Tracks data flow and transformations.
Automation: Streamlines data processes.
Enterprise data cataloging: Organizes extensive data assets.
Scalability: Supports expanding data requirements.
Easy setup: Quick deployment process.
Bulk upload: Efficiently handles large data volumes.
Customizable data management: Tailors data solutions.
Real-time data streaming: Manages live data streams.
Integration with Hadoop and NoSQL: Connects with big data platforms.

What benefits and ROI should be considered?

Regulatory compliance: Ensures adherence to regulations.
Data protection: Safeguards sensitive information.
Enhanced data quality: Improves accuracy and reliability.
Centralized data: Consolidates data for better management.
Process automation: Reduces manual tasks and errors.

Banks and financial institutions use IDMC for data masking, transformation, and compliance, while health sector organizations leverage it for national product catalogs. Industry applications focus on automating business processes, centralizing data, and managing data catalogs to meet regulatory demands and ensure data protection.

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

The Travel Company, Carbonite

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

July 2025

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