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Couchbase Capella 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

Couchbase Capella
Ranking in AI Data Analysis
27th
Average Rating
7.6
Reviews Sentiment
7.5
Number of Reviews
2
Ranking in other categories
Database as a Service (DBaaS) (15th)
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 Couchbase Capella is 0.4%. The mindshare of Cube is 0.3%. It is calculated based on PeerSpot user engagement data.
AI Data Analysis Mindshare Distribution
ProductMindshare (%)
Cube0.3%
Couchbase Capella0.4%
Other99.3%
AI Data Analysis
 

Featured Reviews

SupriyaKulkarni - PeerSpot reviewer
Devops Specialist at Amdocs
Good GUI, easy to learn, and simple to install
The architecture is complex. I do understand that. However, the GUI is very user-friendly. Sometimes all these things are a little difficult to understand for a person who is not experienced in Couchbase. There is a constant requirement to upgrade the versions. We need to constantly keep on upgrading the latest version for the newest one. Currently, we are dealing with an issue where some of the servers are on the 6.5 version, and a few have moved to 7.5. So we are in a mixed mode right now. We are having a high IO issue on our servers, which we are already dealing with. We have these cases with Couchbase, with Red Hat, et cetera. We feel like this constant need to upgrade is something that is very mundane yet a very difficult task. If you have three clusters, which have around thirty nodes, the data is quite sensitive. Whenever there is Couchbase upgrade that is going on, we see that our SR is dropped. The purchase rate and success rate drop. This affects our business and the clients. Rebalancing could be improved. I find it to be a very slow process when it comes to rebalancing the clusters. If you talk about other architectures like Oracle, they are pretty fast. Couchbase is a little slower. Rebalancing, taking the node out, doing the upgrade, putting it back, rebalancing it, is a very difficult and cumbersome. For Oracle, we have been running on version 19.5 for the past five years. There were absolutely no issues. Yet for Couchbase, every six months, we have to go do the upgrade.
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

"The way the nodes are managed is interesting."
"The initial setup was straightforward."
"Implementation was super smooth, and within two weeks we were up and running and the metrics were exposed in our app."
"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."
 

Cons

"The product could be improved by including a log section for tracking activities, enhancing database integration, and providing more transparency regarding pricing and monitoring activities."
"Rebalancing could be improved."
"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."
"Cube can be improved by enhancing data refresh over multiple tabs."
"I did not see any return on investment from Cube."
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Top Industries

By visitors reading reviews
Construction Company
18%
Computer Software Company
11%
Manufacturing Company
11%
Performing Arts
8%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

What needs improvement with Couchbase Capella?
The architecture is complex. I do understand that. However, the GUI is very user-friendly. Sometimes all these things are a little difficult to understand for a person who is not experienced in Cou...
What is your primary use case for Couchbase Capella?
The solution is basically used to support our ordering system, which generates a huge number of orders for our customers.
What advice do you have for others considering Couchbase Capella?
We are Counchbase customers. Depending on your application, it is good to use Couchbase where you have high OLTP systems where you know there will be constant data loading, deleting, et cetera, hap...
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 ...
 

Interactive Demo

Demo not available
 

Overview

Find out what your peers are saying about Couchbase Capella vs. Cube and other solutions. Updated: June 2026.
909,725 professionals have used our research since 2012.