No more typing reviews! Try our Samantha, our new voice AI agent.

Cube vs Informatica Intelligent Data Management Cloud (IDMC) comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 15, 2026

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

Cube
Ranking in AI Data Analysis
19th
Average Rating
8.4
Reviews Sentiment
6.2
Number of Reviews
5
Ranking in other categories
Embedded BI (10th)
Informatica Intelligent Dat...
Ranking in AI Data Analysis
1st
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
215
Ranking in other categories
Data Integration (1st), Data Quality (1st), Business Process Management (BPM) (6th), Business-to-Business Middleware (2nd), API Management (7th), Cloud Data Integration (3rd), Data Governance (3rd), Test Data Management (2nd), Cloud Master Data Management (MDM) (1st), Data Management Platforms (DMP) (2nd), Data Masking (2nd), Metadata Management (2nd), Integration Platform as a Service (iPaaS) (3rd), Test Data Management Services (3rd), Product Information Management (PIM) (1st), Data Observability (2nd)
 

Mindshare comparison

As of August 2026, in the AI Data Analysis category, the mindshare of Cube is 0.3%. The mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 0.9%, down from 22.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Data Analysis Mindshare Distribution
ProductMindshare (%)
Informatica Intelligent Data Management Cloud (IDMC)0.9%
Cube0.3%
Other98.8%
AI Data Analysis
 

Featured Reviews

Amir Hassan - PeerSpot reviewer
Data Scientist / Data Analytics Consultant at Fiverr International Ltd
Managing complex data hierarchies has improved analytics but still needs richer hierarchy types
To evaluate Cube's efficiency in handling large data volumes, I use metrics including F1 scores, AUC (Area Under the Curve), and RMC (Root Mean Squares), along with RSE (Root Square Errors). These factors help me gauge the efficiency of the algorithms clearly. Regarding improving Cube, I believe that when we are building hierarchies, I should enhance the type of hierarchies. For instance, in a few countries lacking state systems, there could be a hierarchy without proper categorization—such as continent, country, and city. Therefore, it would be beneficial if I could improve the hierarchies to retrieve data as quickly as possible from Cube.
RC
Contractor at Sanlam
Cloud data catalog has streamlined lineage and quality while leaving more automation to improve
I have not explored IDMC's automation capabilities driven by AI and metadata too much at the moment, but it is on the cards. We are basically creating the foundation, as the whole migration has taken place recently and it is still early days. I think Informatica Intelligent Data Management Cloud (IDMC) is evolving, and as the vendors move forward, they pick up new concepts from each other. I have seen that products leapfrog each other, and from my experience over the years, the big players tend to copy features or add enhancements based on industry trends. I feel whatever the tool does not have now, there is a feedback loop allowing us to request new features, and we continually ask for different ways to do things as we have a pipeline into the product management team. It is difficult to say what additional features I would prefer to see in the next release of IDMC. I would appreciate more automation on the lineage front, with more AI to seamlessly join independent sources and create seamless lineage between different technologies, such as from file into database A into a different database and landing up in a reporting system such as Cognos, Qlik, Qlik Sense, QlikView, or Power BI.

Quotes from Members

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

Pros

"Cube's caching mechanism impacts my database query loads and response times significantly."
"Cube completes my tasks very easily and takes less time, allowing me to deliver any project in a timely manner to our clients."
"NPS improved to approximately eight out of ten for our feature, and internally ticket handling times decreased, allowing reallocation of resources to higher-impact projects."
"Implementation was super smooth, and within two weeks we were up and running and the metrics were exposed in our app."
"It's helpful in integration, and it can be moved around in SharePoint. So, from the SharePoint View, data integration and reporting, it help a lot in that way."
"We had a bad experience before Informatica Cloud Data Quality, we started a data analytics project that took more than three months of wasted time because we couldn't use the data to create the optimization model."
"It is very useful for testing purposes and designing mappings for small projects."
"It's great as a unified enterprise data management platform."
"The interface is really good."
"One of the most valuable features of Informatica Cloud Data Quality is Master Data Management, and you can write code to build your logic rules to check the quality."
"The solution's technical support is pretty good, especially since the turnaround time is good."
"It is a scalable solution. Scalability-wise, I rate the solution a nine out of ten."
 

Cons

"When it comes to the initial setup of Cube, I faced some challenges, including server issues when uploading data from local sources to the Unipi servers."
"There is no way to create a real template that is not exposed directly in the UI."
"I did not see any return on investment from Cube."
"Cube can be improved by enhancing data refresh over multiple tabs."
"Cube's interface can be challenging for non-technical users, needing clearer use-case examples to ease integration into workflows."
"The tool is quite good overall, but sometimes the number of modules can be overwhelming. If the development interface could be optimized to have fewer modules, it would be greatly beneficial."
"The product could be improved in the area of architecture and technology. All the parts are old."
"Though EDC has maximum coverage, a few things were not available to scan, but I think EDC is evolving to address this issue."
"Exploring the possibility of incorporating AI capabilities that can suggest additional rules would significantly streamline our data analysis process following data profiling."
"There is room for improvement at the highest level in terms of useability and connectors for various types of new applications. The row processing performance could be better because you experience some latency dealing with high volumes of data. Most organizations will be dealing with multiple cloud applications, so you could see performance issues moving from one system to another."
"I would like to have the solution in one product and technical support needs to be better."
"It could be improved by including a buffer that saves data when there is a connectivity issue."
"The product interface could be improved to be more intuitive."
 

Pricing and Cost Advice

Information not available
"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."
"Informatica Cloud Data Quality is a costly solution."
"In terms of the licensing for Informatica Intelligent Cloud Services, we had the option of paying based on the number of users and paying based on the volume of data, and we went with the data volume licensing option. Informatica Intelligent Cloud Services isn't as expensive as CIG. The pricing for it is okay, so I'm rating it a four out of five in terms of pricing. We did use the email verification and address validation services which weren't part of the contract, so we had to pay additional fees for those services."
"We saw an ROI. We have been able to get data from various sources and consolidate it into a data lake, which is helping us in data analytics."
"The pricing is quite flexible."
"We switched to Informatica PIM because it was cheaper than the Oracle solution. It is cheaper initially, but they will bundle it later. This is what happens in the industry."
"The pricing structure is good, but having to pay for extra drivers to be used in an ICS environment makes me a little nervous."
"Comparatively, their prices are a little bit too high."
report
Use our free recommendation engine to learn which AI Data Analysis solutions are best for your needs.
909,725 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
No data available
Financial Services Firm
12%
Manufacturing Company
10%
Construction Company
9%
Outsourcing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business51
Midsize Enterprise27
Large Enterprise155
 

Questions from the Community

What is your experience regarding pricing and costs for Cube?
The cost is around $1,500 per month. The exact number is not coming to my mind, but it is approximately $1,500 or $200 per month.
What needs improvement with Cube?
To evaluate Cube's efficiency in handling large data volumes, I use metrics including F1 scores, AUC (Area Under the Curve), and RMC (Root Mean Squares), along with RSE (Root Square Errors). These ...
What is your primary use case for Cube?
In my recent projects with Cube, I was tasked with finding crashes and the reasons behind them using three datasets: people, crash, and vehicles. I had to merge them and preprocess them, clean and ...
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 ...
 

Also Known As

No data available
ActiveVOS, Active Endpoints, Address Verification, Persistent Data Masking
 

Overview

 

Sample Customers

Information Not Available
The Travel Company, Carbonite
Find out what your peers are saying about Cube vs. Informatica Intelligent Data Management Cloud (IDMC) and other solutions. Updated: June 2026.
909,725 professionals have used our research since 2012.