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Informatica Intelligent Data Management Cloud (IDMC) vs SAP Data Hub comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Nov 3, 2024

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 Governance
2nd
Ranking in Metadata Management
1st
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
185
Ranking in other categories
Data Integration (3rd), Data Quality (1st), Business Process Management (BPM) (10th), Business-to-Business Middleware (5th), API Management (7th), Cloud Data Integration (3rd), Test Data Management (3rd), Cloud Master Data Management (MDM) Solutions (1st), Data Management Platforms (DMP) (2nd), Data Masking (2nd), Test Data Management Services (3rd), Product Information Management (PIM) (1st), Data Observability (2nd)
SAP Data Hub
Ranking in Data Governance
29th
Ranking in Metadata Management
10th
Average Rating
7.6
Reviews Sentiment
6.8
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2025, in the Data Governance category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 5.7%, down from 8.7% compared to the previous year. The mindshare of SAP Data Hub is 1.2%, down from 1.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Governance
 

Featured Reviews

Saikat Ghosh - PeerSpot reviewer
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.
VM
The solution is seamless, but the database sometimes leads to confusion
We used to have multiple different kinds of databases, which internally, had different compliance levels. Retention management is very different now. If the policy is live and the claim has been completed, I couldn't archive the claim. I needed to keep a reference integrity of that claim and understand which policy paid out the claim. With this solution, the policy came in six months ago and qualified for archiving. The claim had been paid and in every environment, the claim had been closed, including the reporting system, the claims system, etc. With the payment set gateway, I can just go and archive. But, we had a hard time during this process. I rate the overall solution a seven out of ten.

Quotes from Members

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

Pros

"The match and merge functionality is invaluable for discovering golden master data records."
"I like the fact that you can find almost any product connection that you need and the list is always expanding."
"MDM doesn't require a separate IDQ."
"Offers data lineage feature"
"It has all the advantages of the Cloud in that you can use it without worrying about infrastructure, upkeep, or upgrades."
"I definitely would recommend the Informatica solution to other people."
"Informatica Cloud Data Integration is stable."
"The solution has the best feature for parameterization."
"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."
"The most valuable feature is the S/4HANA 1909 On-Premise"
"Its connection to on-premise products is the most valuable. We mostly use the on-premise connection, which is seamless. This is what we prefer in this solution over other solutions. We are using it the most for the orchestration where the data is coming from different categories. Its other features are very much similar to what they are giving us in open source. Their push-down approach is the most advantageous, where they push most of the processing on to the same data source. This means that they have a serverless kind of thing, and they don't process the data inside a product such as Data Hub. They process the data from where the data is coming out. If it is coming from HANA, to capture the data or process it for analytics, orchestration, or management, they go to the HANA database and give it out. They don't process it on Data Hub. This push-down approach increases the processing speed a little bit because the data is processed where it is sitting. That's the best part and an advantage. I have used another product where they used to capture the data first and then they used to process it and give it. In Data Hub, it is in reverse. They process it first and give it, and then they put their own manipulations. They lead in terms of business functions. No other solution has business functions already implemented to perform business analysis. They have a lot of prebuilt business functions for machine learning and orchestration, which we can use directly to get an analysis out from the existing data. Most of the data is sitting as enterprise data there. That's a major advantage that they have."
 

Cons

"The solution is quite expensive."
"I would like to see more API integration to have the capability to build a report using other third party reporting tools to streamline the operation."
"Some functionalities can be a challenge in the cloud."
"The tools required to migrate existing mappings and server rules through cloud data quality are not available."
"The solution still is a bit manual in its functionality. We want t to be more automation-driven."
"Managing the licenses with the on-premises version was difficult."
"Exploring the possibility of incorporating AI capabilities that can suggest additional rules would significantly streamline our data analysis process following data profiling."
"If I want to scan the metadata from the data lineage or the Python code, such areas can get tedious in the tool."
"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."
"In 2018, connecting it to outside sources, such as IoT products or IoT-enabled big data Hadoop, was a little complex. It was not smooth at the beginning. It was unstable. It took a lot of time for the initial data load. Sometimes, the connection broke, and we had to restart the process, which was a major issue, but they might have improved it now. It is very smooth with SAP HANA on-premise system, SAP Cloud Platform, and SAP Analytics Cloud. It could be because these are their own products, and they know how to integrate them. With Hadoop, they might have used open-source technologies, and that's why it was breaking at that time. They are providing less embedded integration because they want us to use their other products. For example, they don't want to go and remove SAP Analytics Cloud and put everything in Data Hub. They want us to use SAP Analytics Cloud somewhere else and not inside the Data Hub. On the integration part, it lacks real-time analytics, and it is slow. They should embed the SAP Analytics Cloud inside Data Hub or support some kind of analysis. They do provide some analysis, but it is not extensive. They are moreover open source. So, we need a lot of developers or data scientists to go in and implement Python algorithms. It would be better if they can provide their own existing algorithms and give some connections and drop-down menus to go and just configure those. It will make things really quick by increasing the embedded integrations. It will also improve the process efficiency and processing power. Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this. In terms of technology and performance, it is a little slow as compared to Microsoft and other data orchestration products. I haven't used other products, but I have read about those products, their settings, and the milliseconds that they do. In Azure Purview, they say that they can copy, manage, or transform the data within milliseconds. They say that they can transform 100 gigabytes of data within three to five seconds, which is something SAP cannot do. It generally takes a lot of time to process that much amount of data. However, I have never tested out Azure."
"The company has everything offshore."
 

Pricing and Cost Advice

"It's offers value for money. They're more competitive with respect to pricing and offerings."
"The price is high, but the competitors are even higher, like Collibra."
"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."
"Informatica MDM is a costly solution because it comes as a bundle. They are also globally positioning themselves and are definitely working on very upgraded technologies. If someone wanted to do it on the cloud, they have a lot of flexibility because they upgrade themselves according to the current needs. It definitely comes with a lot of features and that's the reason why it's costly. The licensing cost should be approximately one million dollars. It's about four to five times that of other vendors."
"The price is comparable."
"Informatica Cloud Data Integration is famously known for its high price. The vendor targets large enterprises, and not medium or small companies. These large companies, and organizations, handle large amounts of data. If you go into any large bank, such as American or Canadian banks, these banks use this solution because it is more reliable, secure, and has more functionality."
"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."
"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."
"The Cloud is very expensive, but SAP HANA previous service is okay."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
12%
Manufacturing Company
9%
Insurance Company
6%
Financial Services Firm
14%
Manufacturing Company
14%
Computer Software Company
14%
Government
12%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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...
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 ...
What do you like most about SAP Data Hub?
SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database.
What needs improvement with SAP Data Hub?
We moved from Oracle. If you're aware of your monitoring system, the RPU market, and the managed system, you should move to HANA, which is an innovative database built by SAP itself. However, this ...
What is your primary use case for SAP Data Hub?
I technically handle the database, like cycle management projects. When transaction data comes in, we see it based on the retention periods. We have to move the data to some secure storage rather t...
 

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

 

Sample Customers

The Travel Company, Carbonite
Kaeser Kompressoren, HARTMANN
Find out what your peers are saying about Informatica Intelligent Data Management Cloud (IDMC) vs. SAP Data Hub and other solutions. Updated: May 2025.
859,687 professionals have used our research since 2012.