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 7.7, while Melissa is ranked #8 with an average rating of 9.0. Informatica holds a 19.2% mindshare in DQ, compared to Melissa’s 3.0% 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 183 Informatica Intelligent Data Management Cloud (IDMC) reviews

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1,751 Comparison Views

93% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

414 Views
211 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: April 2025).

Buyer's Guide

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

April 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

183

Ranking in other categories

Data Integration (3rd), Business Process Management (BPM) (13th), Business-to-Business Middleware (4th), API Management (8th), 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 May 2025, in the Data Quality category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 19.2%, down from 25.3% compared to the previous year. The mindshare of Melissa Data Quality is 3.0%, up from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality

Featured Reviews

Raj Sethupathi

Data Integration Consultant GCP/AWS at Infogrators Inc

Offers profiling and address standardization but can be complicated

Informatica Data Quality has its data warehouse, primarily using Oracle and some SQL databases. You need a database to host the data. The cleansed version of the data is stored in the data warehouse. It integrates with PowerCenter and other Informatica tools. The integration details can be complex, but a regional setup is involved in this process. Profiling smaller datasets, such as 10,000-50,000 records, worked fine. However, unexpected issues could arise with larger datasets, such as thousands of records or more, especially with tables containing many columns. Handling tables with fifty or more columns can be challenging, even in Excel. A mismatch in data types could cause the entire system to crash. Continual enhancements are being made to address these issues, which can be unique to specific industries like finance and healthcare.

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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

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

"Multifeatured and easily scalable data catalog, with good data domain discovery and data profiling features."

"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."

"We've used the solution for quite some time, so in our organization, the product is pretty mature."

"I like that Informatica MDM has robust matching technology. Informatica MDM is also porting the external Java applications for validations. I can consider that a must-have. It is also exposed to Rest API calls, and we can engage in real-time integrations with any third-party systems."

"MDM is very stable - it can handle millions of hits daily and still run 24/7."

"It can automatically connect or associate business terms with various options, providing flexibility beyond general capabilities."

"I am impressed by the solution's interface."

More Informatica Intelligent Data Management Cloud (IDMC) pros

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

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

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

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

"We only use the one feature for the NAICS code. This allows our product users to know what industry a business is in."

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

"There have been tangible benefits in combating fraudulent transactions. The information from Melissa Data is fed straight into our fraud system. This creates efficiency but also removes the need for manual address checks."

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

More Melissa Data Quality pros

Cons

"Error reporting and debugging need improvement."

"The UX and UI of the solution are areas with certain shortcomings where improvements can be made in the future."

"Informatica Data Quality has its data warehouse, primarily using Oracle and some SQL databases. You need a database to host the data."

"The on-prem solution is harder to learn than the cloud-based versions."

"Its cloud-based version has a few limitations compared to the on-premise version."

"Managing the licenses with the on-premises version was difficult."

"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."

"There's no direct way to connect to Amazon APIs from Informatica Cloud."

More Informatica Intelligent Data Management Cloud (IDMC) cons

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

"Address validation and parsing in a few countries have room for improvement."

"We encounter failed batch processes once in a while, but their team is quick to rectify issues."

"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."

"One of the problems that we ran into this year was we probably spent over 40 hours finding and trying to drill down to where specific bugs were in the program, which was a tremendous waste of time for us. There were a couple of updates to Windows this year, the program kept crashing. It happened on two different occasions over a period of a few months. Once we told them what the problem was - even though their tech support is great to work with - it literally took probably about two months to fix the issue where we could actually use the program the way we needed to use it."

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

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

"Pricing model."

More Melissa Data Quality cons

Pricing and Cost Advice

"We got a 50% discount."

"We switched to Informatica PIM because it was cheaper than the Oracle solution. It is cheaper initially, but they will bundle it later. This is what happens in the industry."

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

"It is an expensive solution. I would say it is the most expensive solution in the market."

"There is no doubt that it is very expensive, but the brand value comes at a cost. Other MDM solutions in the market that haven't proven themselves like Informatica are also pretty expensive. We need to understand that MDM itself is very expensive to implement. So, Informatica is also pretty expensive. I would rate it a two out of five for being pretty expensive."

"Pricing is determined by the number of licensed users as well as the number of Core CPUs."

"The platform has a premium cost. I rate the pricing as seven out of ten."

"The product is not very pocket-friendly for small and medium-sized businesses, and it is understandable because of the kind of features the tool gives."

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

"Pricing is very reasonable."

"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."

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

"Melissa pricing is competitive."

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

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

"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."

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

12%

Manufacturing Company

Insurance Company

15%

Manufacturing Company

12%

Financial Services Firm

11%

Computer Software Company

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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

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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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Product Reports

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC)

April 2025

Informatica Intelligent Data Management Cloud (IDMC) report

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Buyer's Guide

Melissa Data Quality

April 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

April 2025

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