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Cube vs Google Data Studio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 23, 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 Embedded BI
10th
Average Rating
8.4
Reviews Sentiment
6.2
Number of Reviews
5
Ranking in other categories
AI Data Analysis (19th)
Google Data Studio
Ranking in Embedded BI
8th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
21
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Embedded BI category, the mindshare of Cube is 0.8%, up from 0.5% compared to the previous year. The mindshare of Google Data Studio is 5.2%, down from 8.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Embedded BI Mindshare Distribution
ProductMindshare (%)
Google Data Studio5.2%
Cube0.8%
Other94.0%
Embedded BI
 

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.
Hemanthreddy Vakiti - PeerSpot reviewer
Data engineer at a tech vendor with 10,001+ employees
Automated dashboards have transformed daily trend analysis and now drive faster business decisions
One of the best features that Looker offers is LookML, which allows us to develop dashboards directly rather than dragging and dropping. We can also customize some fields that are not available in the table by combining different tables using LookML. Compared to other reporting tools, Looker is somewhat more customizable and interactive. With the help of Views and Explore in Looker, we can combine different tables and create a unique column that is not available in the table, and then use that column in our reporting dashboard. Since we brought Looker into our project, it has improved data visibility and enabled faster interaction between us and our client. Rather than simply using free form or Essbase, seeing customizable and visualized data in Looker allows the business users to understand the trends in the data more easily rather than just seeing numbers. It has helped us save a lot of time. The automated dashboards that we develop allow us to run the dashboard for the coming years with only some modifications, which has reduced some manpower and working hours. When I joined this project, there were around eight to nine people for developing Looker dashboards. Once the development part is completed for almost all cases, the next part is just monitoring the dashboards and making some minor changes required to align with business goals. After development, the team was reduced to three or four people, so the manpower has significantly reduced, and time taken has decreased as well. For a business user to understand data from free form or Essbase, it usually takes thirty minutes to an hour to go through the previous day's trend. However, with the visualization tools in Looker, they can easily understand the data and compare it to the previous one or two years using a bar graph, pie chart, or other graphs. The return on investment has been very good. The number of employees has reduced to half, and time is saved by nearly two to three hours a day because of automated reports. We are just monitoring the reports to ensure they are released. This has saved nearly two hours per day, and the team has been reduced to half.

Quotes from Members

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

Pros

"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."
"Cube's caching mechanism impacts my database query loads and response times significantly."
"Technical support is the best ever."
"The most valuable features are the ability to create visualizations for non-technical employees, as well as the ability to provide ways to dynamically slice the data."
"In the past, adding a new dashboard to our product was a multi-week development effort, now our nontechnical product management and client success teams can create, launch, and maintain high quality dashboards with no interruption to the development team."
"It is a pretty stable solution because it is a cloud-based product."
"Empowering every employee to make smarter decisions in less time easily pushes us into the black on ROI."
"With respect to buy solutions, cost is relevant. However, the Looker solution would have outmatched the ongoing multi-million budget spending with respect to cost-efficiency."
"It's quite effortless to navigate through various applications and review their updated data in real-time."
"Looker offers incredible business visualization and analytical tools: graphs, charts, tables, and single numbers."
 

Cons

"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'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."
"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."
"The integration with different databases must be improved."
"The pricing model makes sense, but can be very expensive, potentially prohibitively so for smaller companies."
"Integrations with other BI tools could be better."
"There have a been a few minor bugs, including a security bug that did not affect us."
"The biggest friction point or frustration I have encountered with Google Data Studio is the lack of automatic integrations."
"The main area of concern in Looker is probably related to blending the data from the different sources, including the data present internally in the company and on the cloud."
"The visualization capability of the product is limited."
"One thing is that Looker is not user-friendly to non-technical users."
 

Pricing and Cost Advice

Information not available
"I do not have to make any payments to use the solution."
"The price of Looker usually depends on the solution's provider, but it is usually cheaper than the other products in the market. Looker is offered at different prices for different companies."
"It's not cheap, but it's not expensive for big companies."
"Looker is expensive and could be made better by reducing it."
"It is cheap."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
12%
Media Company
8%
Retailer
7%
Construction Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise8
Large Enterprise7
 

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 Looker?
The biggest friction point or frustration I have encountered with Google Data Studio is the lack of automatic integrations. For example, with Meta, you have to pay for a premium integration for it ...
What is your primary use case for Looker?
My main use case for Google Data Studio is dashboards and reporting. For every month, in some cases, it pulls fresh data from a brand new campaign that got launched and ensures that it is visually ...
What advice do you have for others considering Looker?
My advice for someone considering Google Data Studio who has a similar workflow to mine is to start off from one of the templates that are available. It is a good place to start so you can understa...
 

Also Known As

No data available
Looker
 

Overview

 

Sample Customers

Information Not Available
Yahoo!, Etsy, Kohler, Hipcamp, Hubspot, Kickstarter, Venmo, Dollar Shave Club, 600+ customer
Find out what your peers are saying about Cube vs. Google Data Studio and other solutions. Updated: August 2026.
909,725 professionals have used our research since 2012.