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 20.6% mindshare in DQ, compared to Melissa’s 2.8% 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 182 Informatica Intelligent Data Management Cloud (IDMC) reviews

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1,853 Comparison Views

93% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

436 Views
229 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: March 2025).

Buyer's Guide

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

March 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

7.8

Reviews Sentiment

6.8

Number of Reviews

182

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) (1st), 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 April 2025, in the Data Quality category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 20.6%, down from 25.5% compared to the previous year. The mindshare of Melissa Data Quality is 2.8%, down from 3.0% 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

"The application integration will give you more flexibility when dealing with APIs."

"The solution is applicable for both technical and business users."

"The OAuth feature is the most valuable feature for authentication."

"It is quite easy to use and flexible."

"The solution's initial setup is quite straightforward."

"The product is stable."

"The most valuable features are the structure masking and platform masking."

"The features I find most valuable is the synchronization, verification, functionalities and all the data integration features."

More Informatica Intelligent Data Management Cloud (IDMC) pros

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

"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."

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

"SSIS integration."

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

"Provides quality accurate data that our downstream solutions depend on."

"We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database."

"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."

More Melissa Data Quality pros

Cons

"The tool should provide a unified user interface to manage the data objects."

"It is complicated to establish the lineage in EDC using PowerCenter mappings."

"Informatica Axon needs more integration connectors so that it can connect to systems and different kinds of datasets."

"Data integration should be improved."

"The biggest challenge I see is the IDE's for the cloud and automization are different."

"The cloud version of the Informatica, it's a very substandard product. They might say it's enterprise-ready but it's not at all ready. They need to add more features, such as improved data replication features. If you look at other tools, such as Matillion they are now cloud-native and flexible. Additionally, Informatica Cloud Data Integration should have a good migration strategy from Informatica PowerCenter to Informatica Cloud Data Integration."

"IEDC can improve the comparison of lineages."

"The regions in which the data resides are still limited. This could be an issue in terms of the data residency laws of some of the countries. They should get more regions."

More Informatica Intelligent Data Management Cloud (IDMC) cons

"One thing I would want to have, when you're doing a property search, you can do it either on the FIPS in the APN number or the address itself. For some entries, I'll have the APN number, and some I'll have the address. Apparently it cannot process something when both the FIPS-APN and the address are on there. I have to sort, once with one and once with the other, which is a little bit of a pain."

"The SSIS component setup seems a little klunky."

"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."

"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."

"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."

"It could always be cheaper."

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

More Melissa Data Quality cons

Pricing and Cost Advice

"The price is comparable."

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

"On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing nine and a half out of ten."

"Informatica is very expensive."

"Informatica MDM recently changed its pricing model. It's usage-based but I don't have much insight into the current pricing."

"It is expensive. That's probably the biggest drawback. The business has heartache paying the license, but that's mainly because they don't realize what value it brings. The key thing about the MDM solution is that it is in the backend, and no one sees what it is actually doing. You don't know it is a problem until it is not there."

"The product is very expensive"

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

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

"Understand how may transactions you will be processing so that you can get the right tier pricing."

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

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

"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."

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

"It's affordable."

"Trial subscriptions (via cloud) are very cheap and easy to use. It’s a great way to test Listware to see if you want to go deeper with integration."

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

10%

Insurance Company

14%

Manufacturing Company

13%

Financial Services Firm

12%

Computer Software Company

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?

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 6% of the time

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Compared 5% of the time

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Compared 41% of the time

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Product Reports

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC)

March 2025

Informatica Intelligent Data Management Cloud (IDMC) report

Download Informatica Intelligent Data Management Cloud (IDMC) product report

Buyer's Guide

Melissa Data Quality

March 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

March 2025

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