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

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

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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

17th

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

7.8

Reviews Sentiment

6.8

Number of Reviews

182

Ranking in other categories

Data Quality (1st), 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)

Mindshare comparison

As of March 2025, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.8%, up from 1.7% compared to the previous year. The mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 4.8%, down from 7.7% 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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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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Quotes from Members

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

Pros

"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."

"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."

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

"Scalability-wise, I rate the solution a nine or ten out of ten."

"Its data preparation capabilities are highly valuable."

"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."

"DataStage allows me to connect to different data sources."

"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."

More IBM Cloud Pak for Data pros

"The product seems stable enough."

"Informatica MDM stands out as a tool that can give you the flexibility needed for doing channel-specific data quality or business validation."

"Informatica Cloud Data Integration is stable."

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

"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."

"It has been leading the market with hierarchy management and all the different match concepts and algorithms. They're very robust."

"The scalability is very high."

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

More Informatica Intelligent Data Management Cloud (IDMC) pros

Cons

"The solution could have more connectors."

"The technical support could be a little better."

"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."

"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."

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

"The interface could improve because sometimes it becomes slow. Sometimes there is a delay between clicks when using the software, which can make the development process slow. It can take a few seconds to complete one action, and then a few more seconds to do the next one."

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

"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."

More IBM Cloud Pak for Data cons

"When it comes to UI look and feel and user experience, Informatica is not as good as other solutions."

"Currently, there are limitations in processing and the interface."

"It would be helpful if there was a GenAI feature integrated into the system, especially regarding the data quality."

"I would also like to have profiling functionalities and quality transformations in the cloud."

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

"Inserting the GenAI into the master data management will reduce the overall effort of operational activities."

"It would be great if the cloud version could match the full range of capabilities available on-premise."

"The vendor should have more training resources: online classes, free tutorial videos, etc."

More Informatica Intelligent Data Management Cloud (IDMC) cons

Pricing and Cost Advice

"The solution is expensive."

"It's quite expensive."

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

"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."

"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."

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

"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."

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

"You pay for this solution based on IPUs, Informatica Processing Units. This depends on how much data you process and how much memory you consume from the cloud provider, and you pay as you go."

"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."

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

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

"Cost-wise, I think it is on the higher side, and that is why we are looking for some better options. Licensing costs are huge compared to other players in the market and for my company."

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

"Informatica MDM's pricing is not cheap but comparable to other vendors."

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

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

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Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

11%

Manufacturing Company

10%

Government

Financial Services Firm

17%

Computer Software Company

12%

Manufacturing Company

10%

Government

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.

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.

What needs improvement with IBM Cloud Pak for Data?

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...

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...

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 ...

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Comparisons

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Azure Data Factory vs IBM Cloud Pak for Data

Compared 15% of the time

Denodo vs IBM Cloud Pak for Data

Compared 11% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 7% of the time

Informatica PowerCenter vs IBM Cloud Pak for Data

Compared 4% of the time

More IBM Cloud Pak for Data Competitors

Informatica PowerCenter vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 6% of the time

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

Compared 6% of the time

Reltio Cloud vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 5% of the time

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

Compared 4% of the time

Apache Airflow vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 2% of the time

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Product Reports

IBM Cloud Pak for Data

Download IBM Cloud Pak for Data product report

Informatica Intelligent Data Management Cloud (IDMC)

Download Informatica Intelligent Data Management Cloud (IDMC) product report

Informatica Intelligent Data Management Cloud (IDMC) 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

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