Domo vs Google Cloud Datalab comparison

Why PeerSpot?

Domo and Google are both solutions in the Data Visualization category. Domo is ranked #8 with an average rating of 7.8, while Google is ranked #26. Domo holds a 3.5% mindshare in DV, compared to Google’s 1.3% mindshare. Additionally, 85% of Domo users are willing to recommend the solution, compared to 80% of Google users who would recommend it.

Domo

Read 48 Domo reviews

11,269 Views
3,944 Comparison Views

85% willing to recommend

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

2,881 Views
1,296 Comparison Views

80% willing to recommend

Domo

Google Cloud Datalab

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 1, 2025

Domo and Google Cloud Datalab are competing in the data analysis and visualization category. Domo tends to have the upper hand in usability and cost-effectiveness, while Google Cloud Datalab stands out for advanced data processing and machine learning capabilities.

Features: Domo offers rich dashboard capabilities, multiple integrations, and a user-friendly interface for business intelligence. It supports customizable data visualization, allowing for easy manipulation and real-time data integration. Google Cloud Datalab provides robust computational tools, collaborative data handling, and integration with other Google services, ideal for data exploration and large data set management.

Room for Improvement: Domo's areas for improvement include enhancing some advanced analytical capabilities and expanding support for machine learning functions. It also could benefit from more customizable data solutions. Google Cloud Datalab might focus on easing deployment complexity, making the system more accessible for non-technical users and improving customer support responsiveness.

Ease of Deployment and Customer Service: Domo is known for its rapid deployment and robust customer service which offers quick problem resolutions, ensuring smooth onboarding. In contrast, Google Cloud Datalab requires more technical expertise during deployment but integrates effectively with other Google Cloud services.

Pricing and ROI: Domo features flexible pricing options that prove cost-effective for businesses seeking simple solutions and tangible ROI. Google Cloud Datalab incurs higher costs due to its advanced infrastructural needs but offers significant ROI for companies investing in data-driven analytics strategies.

To learn more, read our detailed Domo vs. Google Cloud Datalab Report (Updated: September 2026).

Buyer's Guide

Domo vs. Google Cloud Datalab

September 2026

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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

Domo

Ranking in Data Visualization

8th

Average Rating

7.8

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Integration (17th), BI (Business Intelligence) Tools (6th), Business Performance Management (7th), Reporting (4th)

Google Cloud Datalab

Ranking in Data Visualization

26th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Science Platforms (22nd)

Mindshare comparison

As of October 2026, in the Data Visualization category, the mindshare of Domo is 3.5%, down from 7.7% compared to the previous year. The mindshare of Google Cloud Datalab is 1.3%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Visualization Mindshare Distribution
Product	Mindshare (%)
Domo	3.5%
Google Cloud Datalab	1.3%
Other	95.2%

Data Visualization

Featured Reviews

Ruban Prasanna Dass SP

Assistant Manager at a tech services company with 10,001+ employees

Have improved workflow efficiency through custom reports but encountered formatting limitations

The downsides of Domo are that we don't have a feature in the same column. When data comes in a time format, text format, and number format, we cannot segregate and create conditional formatting in that column. If in the future they develop this feature, it will benefit more users. Domo requires maintenance on my end, such as updates. I am maintaining some dashboards on a weekly basis and monthly basis daily reports. Because we need to upload in SFTP, we cannot schedule or auto-schedule due to rate purposes. We manually handle the data sets. If there were an option to reduce the cost, it would be easier to access.

Read full review

LijomonJose

System Architect at UST Global EspaÃ±a

dashboards are good and data visualization is more meaningful for the end-user

Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a faster network, it would be easier. In a big data environment, like when forcing your database with over a billion records, it can be tough for the end-user to manage the data. You need to have a single entity system in each environment. It's not because of GCP, but it would be great to have options like MongoDB or other similar tools in GCP. Then, we wouldn't always need to connect to the cloud and execute SQL queries. Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated. Once the data is collected, it should be easily sorted.

Read full review

Quotes from Members

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

Pros

"What makes me really fond of Domo is the ETL because it enables us to maximize a single platform for pulling reports and automating things. We can send the raw data from a third-party platform and do the rest of the ETL in Domo, including transforming data, adding columns, etc."

"Unlike some other visualization tools, users can log in and directly view the data without needing to play around or do more steps, like with Tableau or Power BI, making Domo quite helpful."

"In my 15 years of professional experience in IT and Project Controls, this system is truly the one that is the unicorn."

"The fact that you can add any data source is valuable. The entire data handling suite they have, all the apps, etc., is pretty amazing. One of the key things, not being a techie or a data-warehouse guy, is that you can connect data sources, and do all kinds of pretty amazing things."

"In Workbench 5, they have come up with a very useful feature called Upsert. When you're pushing data into the data set, if the data is already available it will update the data, and if that the data is not there it will insert it. That is a beneficial feature that they introduced in the latest version."

"All our client SLAs and daily and weekly dashboards are tracked on Domo."

"Overall, Domo really transformed how we worked with data."

"The user interface is quite good."

More Domo pros

"The infrastructure is highly reliable and efficient, contributing to a positive experience."

"Google Cloud Datalab is very customizable."

"For me, it has been a stable product."

"All of the features of this product are quite good."

"The APIs are valuable."

"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."

Cons

"The ETL way of storing is not up to mark. You have to rely on the naming convention that you're using in Domo because there are no folder systems where you can collate all your workflows and put them into separate folders. A folder system should be there so you can easily identify how you are working. Once you want to make some changes to your ETL, then you can see the whole lineage, identifying what is there and not there."

"All of it. Sometimes it doesn't calculate correctly, it runs slowly, and doesn't offer a solution to things I'm used to doing."

"It is expensive."

"One of the improvements that could be made is related to improved storage options."

"In Tableau, you can create virtually any kind of visualization. Based on your creativity, you can create a visualization on a human body structure, you can create a visualization on anything that you want. But Domo is limited to a few kinds of visualization views: standard things like bar, pie, and some other charts... I would like to see them add new views for presenting the data in the visualization space."

"Sometimes the tool tends to be a little laggy, but it depends on what kind of volume of data that we are working in."

"It's quite slow. We are using about 2,000,000 rows of data. Creating certain reports takes almost a couple of minutes, which should not be the case."

"In Domo, sometimes it takes too much time to upload data. If improvements can happen in this area, that would be better."

More Domo cons

"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."

"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."

"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."

"The interface should be more user-friendly."

"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."

"The product must be made more user-friendly."

Pricing and Cost Advice

"The solution is expensive compared to one of its competitors."

"They've built an "app economy." Some of them are really expensive, so they're not for startups and smaller companies. They're more like enterprise tools. We couldn't afford some of them, because they were so crazy expensive. But if I was working for a bank, insurance company, or some bigger corporation then, for sure, you could justify those prices... It was silly expensive back then and it probably still is, or even more expensive."

"Because it's software as a service, it's more expensive on the face of it. But there are a lot of variables. I don't have to pay for servers or for infrastructure. I don't have to pay labor for my IT organization to set up or maintain the environment. I don't have to pay for them to upgrade the software, and test it, etc., because when it rolls out, it is transparent and seamless for us. But, because of that, it costs more, I imagine, than Sisense, or Yellowfin, or Power BI. A lot of those make it sound like they're inexpensive, but when you add in all the hidden costs and all of the overhead, it's probably comparable."

"The pricing differs from customer to customer, depending on the package."

"I believe that the investment in Domo was worthwhile because it allowed for the organization to jump in quickly, with little training. There are different plans available based on the requirements."

"I think it is reasonable."

"The price that they offered was around $200 per user license. It was pretty cheap at that time compared to other companies. I think they have revamped their pricing structure since then."

"We are making money from Domo, and all our clients are happy with the information that they receive from it."

More Domo pricing and cost advice

"It is affordable for us because we have a limited number of users."

"The pricing is quite reasonable, and I would give it a rating of four out of ten."

"The product is cheap."

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Top Industries

By visitors reading reviews

Manufacturing Company

10%

Financial Services Firm

Outsourcing Company

University

Construction Company

18%

Comms Service Provider

13%

Financial Services Firm

11%

Outsourcing Company

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	17
Midsize Enterprise	13
Large Enterprise	20

No data available

Questions from the Community

What is your experience regarding pricing and costs for Domo?

My experience with pricing, setup cost, and licensing is that there was very little.

See all answers

What needs improvement with Domo?

I'm not sure how Domo can be improved overall, as it's a really good experience.

See all answers

What is your primary use case for Domo?

My main use case for Domo involves building different tables and different cards so I can look at different data points. A quick specific example of a table I have built or a data point I often loo...

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Comparisons

Tableau Enterprise vs Domo

Compared 15% of the time

Microsoft Power BI vs Domo

Compared 13% of the time

Google Data Studio vs Domo

Compared 3% of the time

Zendesk vs Domo

Compared 2% of the time

Palantir Foundry vs Domo

Compared 2% of the time

More Domo Competitors

Tableau Enterprise vs Google Cloud Datalab

Compared 8% of the time

Databricks vs Google Cloud Datalab

Compared 7% of the time

Qlik Sense vs Google Cloud Datalab

Compared 7% of the time

Dataiku vs Google Cloud Datalab

Compared 5% of the time

Anaconda Platform vs Google Cloud Datalab

Compared 5% of the time

More Google Cloud Datalab Competitors

Product Reports

Buyer's Guide

Domo

October 2026

Download Domo product report

Buyer's Guide

Google Cloud Datalab

September 2026

Download Google Cloud Datalab product report

Also Known As

corda

No data available

Overview

Domo provides self-service BI, enabling users to generate reports without needing a data warehouse. Its cloud-based nature enhances accessibility and performance, while offering customizable dashboards for data-driven decision-making.

Domo stands out for its robust data integration, featuring Magic ETL to streamline processes. Its AI-driven insights, extensive data connectors, and collaboration tools promote secure sharing and analytical proficiency. Although users note room for improvement in visualization, pricing, and data integration, its capabilities in generating executive dashboards and unified analytics remain prominent. Performance and user experience enhancements are desired, including improved support for large data volumes and richer data transformation tools.

What are the key features of Domo?

Self-Service BI: Generate reports without a data warehouse for simplified analysis.
Data Integration: Leverage Magic ETL for easy data management.
Customizable Dashboards: Tailor dashboards to specific needs.
AI-Driven Insights: Gain automated insights for better decision-making.
Extensive Data Connectors: Access a wide range of data sources.

What benefits should users look for when evaluating Domo?

Accessibility: Cloud-based structure ensures data access anywhere.
Performance: Enhanced performance with seamless data processing.
Collaboration: Facilitate secure sharing and collaboration for collective insights.
Decision-Making: Enable data-driven decisions with real-time analytics.

In industries like finance, marketing, project management, and retail, organizations use Domo for crafting executive dashboards, integrating data sources, and conducting advanced analytics. Its capabilities allow them to transform data into insightful dashboards, aiding in performance tracking and actionable insights.

Domo

Google Cloud Datalab offers an integrated environment for seamless data processing and analysis. It combines robust infrastructure with free call-up features to enhance user experience, making it a go-to choice for data-driven tasks.

Google Cloud Datalab is geared towards users seeking efficient data handling solutions. It provides a seamless setup with robust infrastructure, focusing on enhancing APIs and offering meaningful data visualization through its dashboards. Notable AI capabilities include auto-completion and data logging, although some minor configuration challenges exist. While transitioning from AWS can be complex, the platform supports dynamic data pipeline design that suits Python development, offering an end-user friendly environment.

What are the key features of Google Cloud Datalab?

Robust Infrastructure: Provides seamless setup with strong backend support.
Free Call-Up: Allows use without extra costs, enhancing accessibility.
Data Visualization: Dashboards offer meaningful insights into data trends.
AI Capabilities: Features auto-completion and data logging for efficiency.
Customizable Architecture: Adapts to different data handling needs effectively.

What benefits should users expect from Google Cloud Datalab?

Efficient Data Analysis: Streamlines exploratory data analysis in machine learning.
Enhanced API Value: API integrations add significant value to data handling.
Friendly Python Environment: Suitable for end-users looking for ease in Python development.
Adaptive Pipeline Design: Supports complex data transitions from AWS.
Global Availability: Helps overcome time lag issues with server location selection.

In specific industries, Google Cloud Datalab is instrumental in managing data analysis, machine learning exploration, and dataset preprocessing. It facilitates the transfer of workloads from AWS and ensures efficient daily data processing. Organizations benefit from its capability to provision machine learning models into Vertex AI, bolstering research and development efforts. The global availability feature plays a significant role in selecting optimal server locations, addressing time lag and connectivity challenges.

Google

Sample Customers

Capco, SABMiller, Stance, eBay, Sage North America, Goodwill Industries of Central Indiana, Telus, The Cliffs, OGIO International Inc., and many more!

Information Not Available

Buyer's Guide

Domo vs. Google Cloud Datalab

September 2026

Free Report: Domo vs. Google Cloud Datalab

Find out what your peers are saying about Domo vs. Google Cloud Datalab and other solutions. Updated: September 2026.

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