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

Cohesity DataProtect vs Cube 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

Cohesity DataProtect
Ranking in AI Data Analysis
18th
Average Rating
9.0
Reviews Sentiment
7.2
Number of Reviews
77
Ranking in other categories
Backup and Recovery (12th), Cloud Backup (14th)
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)
 

Mindshare comparison

As of August 2026, in the AI Data Analysis category, the mindshare of Cohesity DataProtect is 0.5%, down from 0.6% compared to the previous year. The mindshare of Cube is 0.3%. It is calculated based on PeerSpot user engagement data.
AI Data Analysis Mindshare Distribution
ProductMindshare (%)
Cohesity DataProtect0.5%
Cube0.3%
Other99.2%
AI Data Analysis
 

Featured Reviews

Kalaiarasan Meganathan - PeerSpot reviewer
Specialist at HCLSoftware
Backup operations have become faster and daily recoveries run smoothly for on‑prem workloads
When compared to other tools, the deduplication in Cohesity DataProtect is very fast, and the restore performance is better than other tools. Global deduplication ensures that only unique data blocks are stored, significantly reducing storage consumption. Cohesity DataProtect's dashboard displays options and errors clearly, making it easy to access and understand how to fix issues. Cohesity DataProtect's ability to start processes automatically without manual selections enhances its reliability. Cohesity DataProtect's architecture ensures that agent installations automatically reflect in the dashboard, allowing for seamless integration into backup jobs. This improves operational efficiency, ensuring backups can be triggered without manual refreshes. Additionally, the user interface is intuitive, and the respect of the N-1 rule during updates helps prevent client-affecting issues.
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.

Quotes from Members

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

Pros

"We are saving valuable datacenter rack space, which is critical as we evaluate co-location options."
"It's stable."
"It has a lightning fast restore."
"The ability to essentially instantly recover a VM and have it run on the Cohesity Platform while all those bits are technically being recovered in the background is useful to us."
"Backups and restores are much faster and we were able to increase our backup frequency where it made sense to do so in order to have lower RPO."
"Cohesity has made the pain of doing restores disappear with the ability to open recovery and select files and folders, then have the ability to type in the file or document name and have it show up."
"Cohesity is powerful and simple!"
"The product is easy to put in place, all backups are done very quickly, and it's easy to perform restores."
"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."
 

Cons

"Cohesity DataProtect takes hours to restore a single file, even a small one."
"Many of the reports are basic, at most, and at times we had to open a support ticket to help find or develop a report for our needs."
"They could always keep up with continuous interface refinements."
"Features I would like to see include a more visible data lifecycle monitoring tab, and an easier to read backup status dashboard."
"Reducing storage capacity requirements and improving security features are also areas that could be enhanced."
"The marketplace app stability is still an issue at times."
"If someone were to change an admin account password, I would like an alert raised for that, which is not available at the moment."
"In terms of what could be improved, their UI requires a manual refresh. It doesn't seem like it updates itself sometimes when you're moving from screens or waiting for a change to take effect, so you have to manually refresh."
"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."
"There is no way to create a real template that is not exposed directly in the UI."
"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."
 

Pricing and Cost Advice

"From my last assessment, the pricing for Cohesity DataProtect was reasonable. Compared to its closest competitor, Rubrik, I found Rubrik's pricing to be somewhat high-end. While Rubrik may have more advanced security features than Cohesity DataProtect currently, Cohesity DataProtect is releasing a new solution in the near future that will compete directly with Rubrik."
"On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing a seven out of ten."
"The tool's licensing costs are yearly. It is cheaper than other backup solutions."
"It has reasonable pricing, and we know they can give discounts. If you look at the primary pricing or the list pricing, it conforms to the market pricing, but you have to have a discount on it. Otherwise, it is way too expensive."
"Cohesity came in at the best price. Setup was included and done in half a day."
"We purchased support from Cohesity to ensure that should we face an issue, we don't have to deal with different service providers."
"The pricing model is impressive and very effective."
"My advice is to always negotiate for better pricing."
Information not available
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
Financial Services Firm
11%
Manufacturing Company
9%
Construction Company
8%
Computer Software Company
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business21
Midsize Enterprise22
Large Enterprise43
No data available
 

Questions from the Community

What needs improvement with Cohesity DataProtect?
There are several areas that have room for improvement, and I believe there are other aspects that could be enhanced as well.
What is your primary use case for Cohesity DataProtect?
I use Cohesity DataProtect for backup, analysis, and recovery purposes.
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 ...
 

Also Known As

Cohesity
No data available
 

Overview

 

Sample Customers

Tribune Media
Information Not Available
Find out what your peers are saying about Cohesity DataProtect vs. Cube and other solutions. Updated: June 2026.
909,725 professionals have used our research since 2012.