IBM Cloud Pak for Data vs Informatica Intelligent Data Management Cloud (IDMC) comparison

IBM and Informatica are both solutions in the Data Integration category. IBM is ranked #24 with an average rating of 8.0, while Informatica is ranked #3 with an average rating of 7.7. IBM holds a 2.0% mindshare in DI, compared to Informatica’s 4.2% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 93% of Informatica users who would recommend it.

IBM Cloud Pak for Data

Read 13 IBM Cloud Pak for Data reviews

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2,349 Comparison Views

86% willing to recommend

Informatica Intelligent Dat...

Read 185 Informatica Intelligent Data Management Cloud (IDMC) reviews

24,254 Views
7,761 Comparison Views

93% willing to recommend

IBM Cloud Pak for Data

Informatica Intelligent Dat...

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Executive SummaryUpdated on Dec 19, 2024

Informatica Intelligent Data Management Cloud (IDMC) and IBM Cloud Pak for Data are competitors in the data management and analytics sector. IDMC seems to have the upper hand in deployment flexibility, while IBM Cloud Pak for Data excels in machine learning capabilities.

Features:IDMC provides seamless integration across various data management modules, efficient data cleansing, and flexible architecture options. IBM Cloud Pak for Data offers advanced machine learning capabilities, a modular design, and integration with enterprise solutions, facilitating data governance.

Room for Improvement:IDMC requires an improved UI, better integration with platforms like SAP, and more preconfigured rules. IBM Cloud Pak for Data faces challenges with initial deployment, demands on infrastructure, and connectivity issues, with a need for more integrated connectors.

Ease of Deployment and Customer Service:IDMC supports versatile deployment options providing flexibility but complexity in setup, and is praised for customer support. IBM Cloud Pak for Data is mainly deployed on cloud environments, although its customer service can be slow.

Pricing and ROI:IDMC and IBM Cloud Pak for Data both have high license costs. IDMC offers comprehensive functionality for larger enterprises, providing strong ROI when fully utilized. IBM Cloud Pak for Data is considered expensive, particularly when machine learning modules are added, and shows better ROI for organizations with complex data needs.

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

Buyer's Guide

IBM Cloud Pak for Data vs. Informatica Intelligent Data Management Cloud (IDMC)

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

IBM Cloud Pak for Data

Ranking in Data Integration

24th

Average Rating

7.8

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

Informatica Intelligent Dat...

Ranking in Data Integration

3rd

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

185

Ranking in other categories

Data Quality (1st), 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 (2nd), Metadata Management (1st), Test Data Management Services (3rd), Product Information Management (PIM) (1st), Data Observability (2nd)

Mindshare comparison

As of July 2025, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 2.0%, up from 1.7% compared to the previous year. The mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 4.2%, down from 6.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Michelle Leslie

Data asset management engineer at a tech services company with 1-10 employees

Starts strong with data management capabilities but needs a demo database

What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE models. The data modeling component is available in Cloud Pak. Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.

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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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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data."

"Its data preparation capabilities are highly valuable."

"You can model the data there, connect the data models with the business processes and create data lineage processes."

"The most valuable features are data virtualization and reporting."

"It is a scalable solution, and we have had no issues with its scalability in our company. I rate the solution's scalability a nine out of ten."

"The most valuable features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models."

"The most valuable feature of IBM Cloud Pak for Data is the Modeler flows. The ability to develop models using a graphical approach and the capability to connect to various sources, as well as the data virtualization capabilities, allow me to easily access and utilize data that is dispersed across different sources."

"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."

More IBM Cloud Pak for Data pros

"The metadata management of Informatica is great."

"The solution's most valuable features are its data quality, match-merge engine, and CLAIRE AI engine, which helps with AI automation."

"The most valuable feature of Informatica MDM is hierarchy management. It's not something that's typically available and effective within ERPs."

"The most important features are the mastering of the data and the UI intuitiveness."

"The user interface which is very easy to use if we have any problems to solve."

"The Provisioning tool is something that is really handy for everyone. It is my pick as the best feature."

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

"It has improved our organization because it has made our data more reliable. Data is the most important asset these days, and in order to trust your data, you need these tools to make sure that your data is clean and reliable."

More Informatica Intelligent Data Management Cloud (IDMC) pros

Cons

"What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated."

"The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem."

"The solution's user experience is an area that has room for improvement."

"The solution's catalog searching or map search needs to be improved."

"Cloud Pak would be improved with integration with cloud service providers like Cloudera."

"There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement."

"The solution could have more connectors."

"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."

More IBM Cloud Pak for Data cons

"The configuration process is pretty lengthy and challenging and could be made easier to understand."

"The main issue preventing Brazilian companies from migrating to Informatica Cloud Data Integration from on-prem is the price."

"The scalability is tough."

"We cannot sell the product directly with an additional layer."

"Informatica MDM could be improved by adding drag and drop options, business data insights, and visualization reporting."

"Informatica's issue is the licensing. Right now, there are a lot of new gen MDMs that are offering a lot in a single licensing model."

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

"This solution is hard to set up and its interface is not user-friendly. It's also not as stable, and the technical support takes a lot of time to solve simple problems."

More Informatica Intelligent Data Management Cloud (IDMC) cons

Pricing and Cost Advice

"I think that this product is too expensive for smaller companies."

"I don't have the exact licensing cost for IBM Cloud Pak for Data, as my company is still finalizing requirements, including monthly, yearly, and three-year licensing fees. Still, on a scale of one to five, I'd rate it a three because, compared to other vendors, it's more complicated."

"The solution is expensive."

"IBM Cloud Pak for Data is expensive. If we include the training time and the machine learning, it's expensive. The cost of the execution is more reasonable."

"For the licensing of the solution, there is a yearly payment that needs to be made. Also, since it is expensive, cost-wise, I rate the solution an eight or nine out of ten."

"Cloud Pak's cost is a little high."

"It's quite expensive."

"The solution's pricing is competitive with that of other vendors."

"The price is high, but the competitors are even higher, like Collibra."

"I rate the product's pricing a nine on a scale of one to ten, where one is low price, and ten is high price."

"Informatica MDM's price could be lower."

"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."

"Informatica Axon is expensive."

"The pricing is quite flexible."

"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."

"Informatica Axon is a costly solution. I rate Informatica Axon a four out of ten for its pricing."

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

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Top Industries

By visitors reading reviews

Financial Services Firm

31%

Manufacturing Company

10%

Computer Software Company

Government

Financial Services Firm

16%

Computer Software Company

11%

Manufacturing Company

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about IBM Cloud Pak for Data?

DataStage allows me to connect to different data sources.

See all answers

What is your experience regarding pricing and costs for IBM Cloud Pak for Data?

The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem.

See all answers

What needs improvement with IBM Cloud Pak for Data?

See all answers

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

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 40% of the time

Denodo vs IBM Cloud Pak for Data

Compared 12% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 10% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 8% of the time

Informatica PowerCenter vs IBM Cloud Pak for Data

Compared 4% of the time

More IBM Cloud Pak for Data Competitors

Microsoft Purview Data Governance vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 5% of the time

Informatica PowerCenter vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 4% of the time

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

Compared 4% of the time

Reltio Cloud vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 4% of the time

Collibra Governance vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 4% of the time

More Informatica Intelligent Data Management Cloud (IDMC) Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

July 2025

Download IBM Cloud Pak for Data product report

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC)

April 2025

Informatica Intelligent Data Management Cloud (IDMC) report

Download Informatica Intelligent Data Management Cloud (IDMC) product report

Also Known As

Cloud Pak for Data

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

Overview

IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.

Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.

IBM

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

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

The Travel Company, Carbonite

Buyer's Guide

IBM Cloud Pak for Data vs. Informatica Intelligent Data Management Cloud (IDMC)

July 2025

Free Report: IBM Cloud Pak for Data vs. Informatica Intelligent Data Management Cloud (IDMC)

Find out what your peers are saying about IBM Cloud Pak for Data vs. Informatica Intelligent Data Management Cloud (IDMC) and other solutions. Updated: July 2025.

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