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Cube vs Informatica Intelligent Data Management Cloud comparison

 

Comparison Buyer's Guide

Executive Summary

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
297th
Average Rating
7.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

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.
RS
Senior Delivery Architect at Capgemini
Improved data migration has supported governance and AI matching yet still needs smoother self-service
I would not characterize it as a drawback, but there are a few things which were good at that time but have now become stable. The older transformations that have degraded now have to be changed. I would not say it has to be something that needs to be updated or upgraded, but the bottom line is there needs to be updates for data migration and all that. Multiple companies, including my consulting service firm, have created accelerators for upgrading those things. Ultimately, I would say that it is still stable. If there is nothing to be updated or created, then our job would be done. I would say it is mixed regarding self-service data preparation features for non-technical users, as it is a tool that has been around for a long time. There is a significant amount of information on the internet to help us out, including many KB articles. However, I would suggest to Informatica that there should be a different approach in providing KB articles and information. The information should be provided in a seamless way for the entire functions, not in bits and pieces across different places. For instance, if I need to create a data model, the entire process flow, including database objects, entity objects, business entities, entity views, and all that should be presented in that particular direction as a project situation, rather than scattered across plain sections.

Quotes from Members

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

Pros

"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."
"Cube completes my tasks very easily and takes less time, allowing me to deliver any project in a timely manner to our clients."
"Cube's caching mechanism impacts my database query loads and response times significantly."
"Implementation was super smooth, and within two weeks we were up and running and the metrics were exposed in our app."
"Ultimately, I would say Informatica is still leading in the entire MDM space with multiple different users."
"Informatica Intelligent Data Management Cloud has pretty good services to handle data governance, data lineage, and data management."
 

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."
"I did not see any return on investment from Cube."
"Cube's interface can be challenging for non-technical users, needing clearer use-case examples to ease integration into workflows."
"Cube can be improved by enhancing data refresh over multiple tabs."
"There is no way to create a real template that is not exposed directly in the UI."
"For Informatica Intelligent Data Management Cloud in general, as a product and service, I would rate it somewhere between seven to seven point five, particularly for the AI part because it is still new and still needs multiple refinements and efficiencies."
"I have not seen any return on investment at the moment or any tangible benefits so far."
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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 ...
What is your experience regarding pricing and costs for Informatica Intelligent Data Management Cloud?
I am not sure about the pricing side of Informatica Intelligent Data Management Cloud. That is something a different team works on.
What needs improvement with Informatica Intelligent Data Management Cloud?
I would like to have more AI capabilities. Looking at AI and the market AI currently has, AI capabilities will definitely help.
What is your primary use case for Informatica Intelligent Data Management Cloud?
I cannot disclose use cases because that is something confidential we have. However, services-wise, I can say that Informatica Intelligent Data Management Cloud has very good services for data gove...
 

Comparisons

No data available
 

Overview

Find out what your peers are saying about Informatica, Denodo, Cisco and others in AI Data Analysis. Updated: August 2026.
909,153 professionals have used our research since 2012.