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Cube vs Reltio 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)
Reltio Cloud
Ranking in AI Data Analysis
13th
Average Rating
8.2
Reviews Sentiment
6.1
Number of Reviews
16
Ranking in other categories
Cloud Master Data Management (MDM) (4th), AI Customer Experience Personalization (18th)
 

Mindshare comparison

As of August 2026, in the AI Data Analysis category, the mindshare of Cube is 0.3%. The mindshare of Reltio Cloud is 0.5%, down from 14.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Data Analysis Mindshare Distribution
ProductMindshare (%)
Reltio Cloud0.5%
Cube0.3%
Other99.2%
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.
reviewer2826747 - PeerSpot reviewer
Data Domain Lead at a government with 10,001+ employees
Unified data has created trusted golden records but complex AI matching still needs clearer control
Reltio Cloud has greatly enhanced our data management, and I acknowledge there are areas where our team continues to face challenges. Specifically, the AI-based matching feature operates like a black box, making it difficult to understand why certain records are matched or not matched accurately. If there could be better visual debugging and clarity regarding why records are matched, it would significantly aid our decision-making process. The technical configuration, particularly regarding data models and rule matching, can be overly complex for business users, hence a more user-friendly approach, with simplified guidelines, would be incredibly beneficial. Additionally, data stewardship can present complexities, and clearer actions can facilitate addressing these challenges. Performance issues can arise with larger data models and numerous data sources impacting system use, hence enhancements in optimization and ready-to-use features for complex configurations are essential. Pricing can also be convoluted; therefore, a clearer cost model would aid users in comprehending the structure. While data lineage has its merits, it is complex to interpret; thus, improved visualization would greatly benefit users. Ultimately, technical complexity emerges as the primary challenge we face, revealing opportunities for improvement.

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."
"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."
"Cube completes my tasks very easily and takes less time, allowing me to deliver any project in a timely manner to our clients."
"The cloud feature is very beneficial, and the scalability performance feature is excellent."
"The most valuable feature is real-time synchronization. You can see the events as soon as they are posted within a couple of fraction seconds."
"Reltio Cloud has positively impacted my organization because we were able to promote our data and sell data to our customers."
"We can store the data and enrich it from multiple sources."
"Its user interface is different from that of other MDM solutions like Informatica"
"It is very easy to learn. The"
"There are default limitations and considerations. For instance, Reltio can store a maximum of 200 values for a single attribute. If your data exceeds this limit, you can request Reltio support to increase the limit. However, be aware that increasing this limit may impact performance, potentially slowing down data loading times."
"The survivorship feature is great because we can define it, prioritize the sources, and only allow those sources to survive when making the golden record."
 

Cons

"Cube can be improved by enhancing data refresh over multiple tabs."
"I did not see any return on investment from Cube."
"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."
"Cube's interface can be challenging for non-technical users, needing clearer use-case examples to ease integration into workflows."
"There is no way to create a real template that is not exposed directly in the UI."
"The customer support is adequate, but not exceptional."
"The support team is slow to respond when we need assistance with workflow deployments. We must rely on their availability and contact them to receive the required JAR files."
"There are many issues. For example, sometimes, errors related to tokenization occur while creating a match rule."
"Reltio Cloud can be improved by providing the possibility to connect with other connectors and databases such as Snowflake, Databricks, and eventually with Azure Data Factory."
"What could be improved about Reltio Cloud was minimal."
"The download process can be quite slow"
"The deployment is difficult."
"AI features should be introduced in Reltio more."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
12%
Manufacturing Company
12%
Computer Software Company
9%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise2
Large Enterprise13
 

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 needs improvement with Reltio Cloud?
In future updates of Reltio Cloud, I would like to see features such as AI for match and merge, which can create predefined AI address doctors and match and merge for customer data, easily integrat...
What is your primary use case for Reltio Cloud?
I use Reltio Cloud for customer data management, specifically for C-MDM purposes.
What advice do you have for others considering Reltio Cloud?
Reltio Cloud was not purchased through AWS Marketplace or directly from the vendor. It was already available in my company at that time, so I used the system to showcase its capabilities. What coul...
 

Comparisons

 

Overview

 

Sample Customers

Information Not Available
iMiDiA, Slalom, MeritDirect, Cognizant
Find out what your peers are saying about Cube vs. Reltio Cloud and other solutions. Updated: June 2026.
909,725 professionals have used our research since 2012.