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 10.8% mindshare in DQ, compared to Melissa’s 2.9% 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

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1,851 Comparison Views

93% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

750 Views
405 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: September 2025).

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC) 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 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 (3rd), Business Process Management (BPM) (10th), 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 (1st), 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 (5th)

Mindshare comparison

As of October 2025, in the Data Quality category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 10.8%, down from 21.9% 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 Intelligent Data Management Cloud (IDMC)	10.8%
Melissa Data Quality	2.9%
Other	86.3%

Data Quality

Featured Reviews

SaurabhGaonshindhe

Principle Cloud Engineer at Sector 125

Modular structure and AI features stream new reporting processes

One of my clients has a requirement; they want to integrate metadata into the process, which means, for example, if I just want to implement a new field into my database, that field needs to be reflected throughout, let's say, 200 mappings. This highlights the need for a data-driven approach. My experience with technical support from Informatica is quite interesting; I would rate it as nine out of ten for Informatica PowerCenter kind of products or the Informatica integration products, because my team can do some hands-on using their free licenses or one-month kind of products. However, for products Master Data Management or related to MDM or Data Governance, there is no way by which we can directly practice, and my team struggles at that point.

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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

"It comes with lot of features and is a one-stop-shop solution for integration, data modeling, and data governance. Everything can be built under one particular umbrella. If any issues come up, then there won't be any blame game saying that it could be an integration issue or an MDM hub issue because it's wholly owned by Informatica. That's the biggest advantage of Informatica MDM over that of any other tools that are available on the market."

"The best part about the Informatica Intelligent Data Management Cloud (IDMC) is the modularity; when I say modularity, I mean the things get easier by working into different modules."

"Informatica is good for integrating data and cloud applications. We have connectors for integrating cloud applications like Salesforce. You can quickly integrate anything with an exposed API or a REST API. The industry is increasingly shifting to the cloud, so we need more products that can connect to cloud-based applications. The integration is seamless and works in real time. It's also secure because you don't need to expose databases or tables."

"It is a scalable solution. Scalability-wise, I rate the solution a nine out of ten."

"It gives you accountability to centralize your data and have it available to different applications."

"Axon has a marketplace that allows you to showcase all the assets the data owner has, so they can request access. That's one feature we use extensively. Axon also offers great visibility and intuitive searchability, allowing you to easily search data assets. You can check the lineage and see the work EDC does. EDC handles all the classification, cataloging, and lineage. It's integrated with Axon, and anyone can see that."

"I think the integration feature is probably one of the key features in Informatica MDM...Stability-wise, I rate the solution a ten out of ten."

"The MDM solution is capable of integrating multiple systems, so it helped us to solve the purpose of centralizing the depository as well as the standardization of mass data. It takes away all the ambiguity around data integrity issues or all the process challenges which happen when every stage of a process uses a different source as master data."

More Informatica Intelligent Data Management Cloud (IDMC) pros

"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."

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

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

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

"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."

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

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

"SSIS integration."

More Melissa Data Quality pros

Cons

"Some functionalities can be a challenge in the cloud."

"The solution doesn't directly connect to any of the analytical tools."

"Exploring the possibility of incorporating AI capabilities that can suggest additional rules would significantly streamline our data analysis process following data profiling."

"One area that could use improvement is the speed of the web interfaces. At present, they are very slow. I think it is essential that we are original and robust on-premises."

"The integration with other data management tools can be enhanced. For instance, there is no integration with tools like Collibra or Hubview."

"The customer servive and support could be faster. There is a slow turnaround."

"Informatica Cloud Data Integration can improve by being more user-friendly. When you're working with the solution a lot of technical knowledge is required. It's not a solution that anyone can use properly, you need knowledge of what's happening at the back end, such as SQL. When you get stuck, you need to look into your logic. For other tools, such as Dell Boomi, anyone can use them."

"With the solution, we had some issues, and we have every day, and we used to open a ticket. Sometimes, there are data issues and transformation issues."

More Informatica Intelligent Data Management Cloud (IDMC) cons

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

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

"MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version."

"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."

"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."

"To continually update the database with NAICS codes on businesses."

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

More Melissa Data Quality cons

Pricing and Cost Advice

"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."

"It's offers value for money. They're more competitive with respect to pricing and offerings."

"The price is very high and has become a big concern for our customers who require the solution in order for their business to function smoothly."

"The solution's pricing model is easy, but it is very expensive."

"We have licenses, and we are provided with certain particular services in the solution."

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

"Informatica MDM's pricetag should come down. They have to cut some costs."

"I have heard from customers that the product comes with a huge license cost."

More Informatica Intelligent Data Management Cloud (IDMC) pricing and cost advice

"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."

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

"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."

"Melissa pricing is competitive."

"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."

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

"It is 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

16%

Computer Software Company

10%

Manufacturing Company

10%

Insurance Company

13%

Manufacturing Company

13%

Healthcare Company

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	42
Midsize Enterprise	24
Large Enterprise	134

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

Questions from the Community

How does Azure Data Factory compare with Informatica Cloud Data Integration?

Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...

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Which Informatica product would you choose - PowerCenter or Cloud Data Integration?

Complex transformations can easily be achieved using PowerCenter, which has all the features and tools to establish a real data governance strategy. Additionally, PowerCenter is able to manage huge...

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What are the biggest benefits of using Informatica Cloud Data Integration?

When it comes to cloud data integration, this solution can provide you with multiple benefits, including: Overhead reduction by integrating data on any cloud in various ways Effective integration ...

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Comparisons

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Compared 5% of the time

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Compared 4% of the time

Azure Data Factory vs Informatica Intelligent Data Management Cloud (IDMC)

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Product Reports

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC)

September 2025

Informatica Intelligent Data Management Cloud (IDMC) report

Download Informatica Intelligent Data Management Cloud (IDMC) product report

Buyer's Guide

Melissa Data Quality

September 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) integrates data quality, governance, and integration with flexible architecture. It supports multiple domains and a data models repository, delivering AI-enhanced data management across cloud-native platforms.

IDMC provides seamless integration and governance capabilities that support diverse data environments. Its comprehensive suite includes customizable workflows, data profiling, and metadata management. AI features, a data marketplace, and performance scalability enhance data management. While its interface poses challenges, its robust matching and cloud-native integration facilities are essential for complex data ecosystems. Users employ IDMC for connecting systems, ensuring data quality, and supporting data compliance but seek better pre-built rules, services, and improved connectivity, especially with platforms like Salesforce. Licensing, cost, and added AI functionalities are areas for potential refinement.

What are the key features of IDMC?

Data Quality and Integration: Seamless integration ensures data accuracy across platforms.
Metadata Management: Comprehensive metadata management supports data governance.
AI Capabilities: AI features enhance automation and decision-making processes.
Data Marketplace: Facilitates easy access to data across the organization.
Performance Scalability: Scales performance efficiently to meet growing data demands.

What benefits should be expected from IDMC?

Enhanced Data Management: Offers robust tools for data governance and quality.
Improved Integration: Connects disparate systems seamlessly, reducing data silos.
Cost Efficiency: Streamlines data processes, potentially reducing operational costs.
Data Compliance: Supports compliance with data privacy regulations.
Agility and Scalability: Adapts quickly to changing data environments.

IDMC is implemented across industries for data integration, metadata management, and governance. Organizations use it to connect systems, migrate data to cloud environments, and maintain data quality. They manage master data and automate business processes, facilitating data lineage and ensuring compliance with privacy regulations.

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

September 2025

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