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 20.4% mindshare in DQ, compared to Melissa’s 2.7% 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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1,971 Comparison Views

93% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

461 Views
250 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) (11th), 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 (2nd), 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 March 2025, in the Data Quality category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 20.4%, down from 25.4% compared to the previous year. The mindshare of Melissa Data Quality is 2.7%, down from 3.1% 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

"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."

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

"I have rated the stability a ten out of ten due to a high level of satisfaction."

"Axon does one interesting thing that I don't think other tools do as well. It lets you rate data and incorporates Informatica's data quality feature into it. There are little indications and graphics that show you how good the data quality is, and you can drill into it to see where potential issues lie."

"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."

"It's good for tool management, maintaining the golden record of customer status."

"Some of Axon's valuable features include creating your business glossaries, importing DQ rules, and creating change management."

"We can see all our information on a single screen."

More Informatica Intelligent Data Management Cloud (IDMC) pros

"Getting the most up to date address for our members. We like to keep in touch with membership a few times a year so we want to maintain up to date addresses to be sure they receive any information that we mail to them."

"We use a Melissa API to access the data, so it easy to use, accurate, and fast."

"Services for all manner of data-driven organizations, no matter their size or budget."

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

"Ability to keep our data set clean and usable for our community searches."

"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."

"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."

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

More Melissa Data Quality pros

Cons

"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."

"The user interface can be a bit more functionality-aligned."

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

"The biggest pain point for us is the documentation. Typically, you have to go through knowledge forums and knowledge groups to find out about the syntax issues for interfacing with new products. Typically, you've got to deal with someone who has been through the pain before. Their documents are not really up to date with current innovations happening in the industry. As big as they are, you can't really expect it, but that's our pain point."

"The user interface of the product needs to be improved"

"Informatica's support understands the solution, but they lack the experience we need for our use case. That was one thing that we prioritized when we started searching for this kind of solution."

"Informatica Enterprise Data Catalog could improve by having a much better user interface. It is not user-friendly."

"Certain applications are not being synced with the ION."

More Informatica Intelligent Data Management Cloud (IDMC) cons

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

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

"We are no longer using Melissa Data to clean up our address information as there are free tools that we can use to do the same thing."

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

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

"The tool needs to provide resizable forms/windows like all other SSIS windows. Vendor claims its an SSIS limitation however all SSIS components are resizable so that isn't true. This is just an annoyance but needless."

"It could always be cheaper."

"More countries should be supported by Melissa."

More Melissa Data Quality cons

Pricing and Cost Advice

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

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

"I rate the licensing cost of Informatica MDM a five out of ten."

"I rate the product's price a seven on a scale of one to ten, where one is the cheapest and ten is the most expensive. The product is a bit expensive."

"My understanding is that Informatica is quite expensive compare to other tools that are available in the market."

"The pricing is quite flexible."

"I rate the product's pricing a seven on a scale of one to ten, where one is the lowest price and ten is the highest price."

"It's a very expensive solution"

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

"It's affordable."

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

"Pricing is very reasonable."

"Fully understand your volume, both monthly and annually. Speak with a Melissa account manager, they will put together an effective solution to meet your needs."

"It is affordable."

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

"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."

"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

17%

Computer Software Company

12%

Manufacturing Company

10%

Government

Insurance Company

14%

Manufacturing Company

14%

Financial Services Firm

12%

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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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 7% of the time

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Compared 6% of the time

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Compared 5% of the time

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Compared 4% of the time

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Compared 37% of the time

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Compared 24% of the time

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Product Reports

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC)

February 2025

Informatica Intelligent Data Management Cloud (IDMC) report

Download Informatica Intelligent Data Management Cloud (IDMC) product report

Buyer's Guide

Melissa Data Quality

February 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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