Google Cloud Datalab vs Tableau Enterprise comparison

Google and Salesforce are both solutions in the Data Visualization category. Google is ranked #18 with an average rating of 7.8, while Salesforce is ranked #1 with an average rating of 8.3. Google holds a 0.8% mindshare in DV, compared to Salesforce’s 19.2% mindshare. Additionally, 80% of Google users are willing to recommend the solution, compared to 89% of Salesforce users who would recommend it.

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

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172 Comparison Views

80% willing to recommend

Tableau Enterprise

Read 307 Tableau Enterprise reviews

18,844 Views
5,653 Comparison Views

89% willing to recommend

Google Cloud Datalab

Tableau Enterprise

Comparison Buyer's Guide

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Executive SummaryUpdated on Aug 4, 2025

Tableau Enterprise and Google Cloud Datalab are both in the analytics platform category. Tableau Enterprise seems to have the upper hand due to its user-friendly interface and robust visualization capabilities, which make it ideal for non-technical users.

Features: Tableau Enterprise offers dynamic report generation, rich interactive visualizations, and simple data blending capabilities. It is known for its intuitive drag-and-drop functionality, enabling users without technical backgrounds to create complex dashboards effortlessly. Google Cloud Datalab, on the other hand, provides seamless integration with other Google Cloud services, facilitating advanced machine learning operations, big data processing, and API accessibility.

Room for Improvement: Tableau Enterprise could benefit from better integration with external big data services and improved analytics features to appeal to technical users. Additionally, more customization options for advanced users might enhance its appeal. Google Cloud Datalab could improve its user interface for beginners, offer more simplified visualization tools, and enhance its deployment ease for those unfamiliar with cloud environments.

Ease of Deployment and Customer Service: Tableau Enterprise is known for its straightforward on-premises deployment, backed by excellent customer support that facilitates quick problem resolution. Google Cloud Datalab offers cloud-based deployment, which benefits from Google’s extensive documentation and support resources, ensuring that users can leverage the platform's full capabilities.

Pricing and ROI: Tableau Enterprise's higher initial setup costs are offset by the enhanced productivity and user satisfaction it brings through its ease of use. This translates to a strong ROI as users can derive value quickly through heightened decision-making speed. Google Cloud Datalab offers competitive pricing aligned with cloud usage patterns, providing scalability and cost efficiency, leading to a greater long-term ROI for organizations heavily invested in Google Cloud solutions.

To learn more, read our detailed Google Cloud Datalab vs. Tableau Enterprise Report (Updated: September 2025).

Buyer's Guide

Google Cloud Datalab vs. Tableau Enterprise

September 2025

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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

Google Cloud Datalab

Ranking in Data Visualization

18th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Science Platforms (19th)

Tableau Enterprise

Ranking in Data Visualization

1st

Average Rating

8.4

Reviews Sentiment

6.3

Number of Reviews

307

Ranking in other categories

BI (Business Intelligence) Tools (2nd), Reporting (2nd), Embedded BI (1st)

Mindshare comparison

As of October 2025, in the Data Visualization category, the mindshare of Google Cloud Datalab is 0.8%, up from 0.5% compared to the previous year. The mindshare of Tableau Enterprise is 19.2%, down from 29.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Visualization Market Share Distribution
Product	Market Share (%)
Tableau Enterprise	19.2%
Google Cloud Datalab	0.8%
Other	80.0%

Data Visualization

Featured Reviews

Nilesh Gode

Project Manager - Data Science at Mettler-Toledo International Inc.

Easy to setup, stable and easy to design data pipelines

The scalability is average. We have not faced any issues with scalability. There are more than 500 end users using this solution in our company. It is an integral part of the daily operations. The usage pattern is not a one-time thing; employees regularly access and utilize the application. We use it at a global level with a scattered user base. This means that users don't all use the application at the same time. So, around 300 out of 500 employees use the solution, and this usage is spread out throughout the day.

Read full review

Uzair Faruqi

Head Of Analytics at Mjunction Services

Ease of developing dashboards and receiving strong technical support have enabled efficient data visualization

Introducing custom features, such as NLP-based reports, is not very good in Tableau. My MD has been asking us for a way to write in natural language to request reports that the system should generate, but that isn't very effective with Tableau. As a developer, I can develop an on-demand report in Python quite easily, but exposing a REST API on the Tableau platform is not a very easy task. AI enablement is an area for improvement for Tableau, and that is something they might have to work upon. I have heard that ThoughtSpot is quite better in this regard, but the cost of ThoughtSpot is much higher. ThoughtSpot has lots of natural language-based report generation features that Tableau lacks.

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

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

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

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

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

"The APIs are valuable."

"Google Cloud Datalab is very customizable."

"It's very easy to set everything up."

"It allows us to basically understand and evaluate our numbers in an expedient manner."

"One of the most valuable features of Tableau is that it's a visual analytics solution, not just a dashboarding solution. Compared to Power BI, which is a dashboarding solution, there are no limitations with Tableau. For example, when you add a chart or a map to Power BI, it has a 3,000-point limitation. When you try to track your whole vehicle on the map, you only see the first 3,000 rows on the map, and Power BI doesn't tell you which part of the data is shown on the map. But Tableau doesn't have any limitations, which means that you can see five million data points on a map. It starts the project by creating the visuals that directly converts to SQLs. In that way, all the components have no limitations. When we compared Tableau to Power BI, we also found Tableau to be more fancy. Fancy means you can create more visual graphics and more visual dashboards. With Power BI, this isn't so—it's just some tables and some simple charts together. Tableau is more for business users who want to analyze data. Tableau can directly connect the analytics systems, like R or Titan, and get the results in screen, so it's a good solution for analytics scientists. It has some predefined capabilities to understand the data."

"Since Tableau is on the cloud, we haven't faced any challenges around scalability."

"All features are valuable. It is very user-friendly, and it is mostly drag-and-drop. If we have the dataset available, then we can develop any dashboard very quickly."

"From the data science point of view, we use it for model building purposes. For example, if we are using it for a bank and we want to understand how much loan the bank can provide, we can use visualization to show the educational qualification, salary, gender, and city of a customer, and by using this information, we can arrive at the loan amount that this person is eligible for. I can also use it to view all prospective customers, so essentially, this is going to help me in model building as well as in understanding and segmenting customers and doing forecasting and predictive analytics. We use model widgets, and we can create thousands of visualizations, such as motion charts and bubble charts. We can also create animated versions of the graphs and view the data from multiple dimensions. These are the features that we typically use and like."

"The product has the best features for analytical views and filters."

"From my perspective, it enables clients to better understand our data and make better decisions based on that information."

More Tableau Enterprise pros

Cons

"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."

"The interface should be more user-friendly."

"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."

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

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

"The performance could be better."

"I am a BI consultant. I have worked on different reporting tools, such as Power BI and MicroStrategy. As compared to other tools, Tableau lags behind in handling huge enterprise-level data in terms of robust security and the single integrated metadata concept. When we connect to large or very big databases, then performance-wise, I sometimes found Tableau a little bit slow. It can have the single metadata concept like other tools for the reusability of the objects in multiple reports."

"I also work as an SME on the platform side. Tableau is very nice and jazzy for the end-users, but there are pain points for the admins. Performance is something about which we hear a lot of complaints, such as the dashboard doesn't open in time. It performs well on the desktop but not on the server. I know that there is always a limitation when it comes to a huge amount of data or the complexity of the calculations, but we often hear from end-users about the performance on the server side. It is easy to drag and drop all the columns and do what we want, but if it is not going to load better on the server, users are not going to like it."

"The Hyper Extract functionality is not as strong as that provided by Microsoft SQL."

"Tableau's data blending feature could use some improvement. Previously, I used other tools, such as Alteryx, for data blending because Tableau had limitations."

"Areas for improvement would be visualization and augmented analytics. In the next release, I would like to see automated insights from the data added to the dashboard."

"I would like Tableau Prep to be integrated with Tableau Desktop. I would also like more customizations for tables."

"Its price is a concern. It is more expensive than Power BI. The other thing that I never liked about Tableau is its ability to handle large sets of data. To present the data in the dashboards, we have to stage it up exactly like it is going to come into the dashboard. We use another tool called Alteryx that does that for us. So, we manipulate the data, get it staged, and then push it into Tableau. Tableau is terrible at handling large data sets, and we knew right away that we couldn't use Tableau to do data manipulation."

More Tableau Enterprise cons

Pricing and Cost Advice

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

"The product is cheap."

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

"This solution is a bit expensive. The pricing options have become more difficult over the years. I think they are bordering on pricing themselves out of the market. They need different pricing options for various-sized businesses. Where my organization is a large organization, we are happy to pay a higher price because we can leverage the products very extensively. For smaller enterprises, different pricing options would be good."

"The license is very expensive."

"Tableau is an expensive solution, though it comes with its advantages."

"The solution is expensive but it depends on the customer's needs which will determine the cost of the licensing."

"The solution's licensing is based on user-basis. It depends on the business ROI it offers. It's not on the higher side or too cheap; it falls in the medium-cost range. The price is determined by user usage, so the cost will also increase as the number of users increases."

"Tableau is free."

"I wish there was more of a subscription model with the pricing when it comes to Tableau, so you can get all the latest version upgrades/features if you pay monthly/annually."

"It is a bit difficult for some people when they hear $70.00 per month, as some solutions are available for less than $10.00 or for free."

More Tableau Enterprise pricing and cost advice

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Comparison Review

it_user6330

Product Manager at a retailer with 10,001+ employees

May 2, 2013

MicroStrategy vs. Tableau

After a recent presentation, several attendees asked me about the applications of Visual Insights and Tableau. Many companies are investing in both tools and are trying to figure out the right tool for specific applications Tableau has found its sweet-spot as an agile discovery tool that analysts…

Read full review

Top Industries

By visitors reading reviews

Financial Services Firm

28%

University

Computer Software Company

Government

Financial Services Firm

15%

Manufacturing Company

10%

Computer Software Company

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	117
Midsize Enterprise	66
Large Enterprise	182

Questions from the Community

What do you like most about Google Cloud Datalab?

Google Cloud Datalab is very customizable.

See all answers

What needs improvement with Google Cloud Datalab?

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 forcin...

See all answers

What is your primary use case for Google Cloud Datalab?

It's for our daily data processing, and there's a batch job that executes it. The process involves more than ten servers or systems. Some of them use a mobile network, some are ONTAP networks, and ...

See all answers

Seeking lightweight open source BI software

It depends on the Data architecture and the complexity of your requirement. Some great tools in the market are Qlik Sense, Power BI, OBIEE, Tableau, etc. I have recently started using Cognos Enter...

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Tableau vs. Business Objects - Which is a better solution for visualization and analysis?

Both tools have their positives and negatives. First, I should mention that I am relatively new to Tableau. I have been working on and off Tableau for about a year, but getting to work on it consta...

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Which would you choose - Tableau or SAP Analytics Cloud?

Tableau is easy to set up and maintain. In about a day it is possible for the entire platform to be deployed for use. This relatively short amount of time can make all the difference for companies ...

See all answers

Comparisons

Anaconda Business vs Google Cloud Datalab

Compared 38% of the time

IBM SPSS Statistics vs Google Cloud Datalab

Compared 19% of the time

Databricks vs Google Cloud Datalab

Compared 17% of the time

Oracle Analytics Cloud vs Google Cloud Datalab

Compared 14% of the time

KNIME Business Hub vs Google Cloud Datalab

Compared 12% of the time

More Google Cloud Datalab Competitors

Microsoft Power BI vs Tableau Enterprise

Compared 19% of the time

Domo vs Tableau Enterprise

Compared 9% of the time

Amazon QuickSight vs Tableau Enterprise

Compared 5% of the time

Databricks vs Tableau Enterprise

Compared 5% of the time

SAP Analytics Cloud vs Tableau Enterprise

Compared 4% of the time

More Tableau Enterprise Competitors

Product Reports

Buyer's Guide

Google Cloud Datalab

October 2025

Download Google Cloud Datalab product report

Buyer's Guide

Tableau Enterprise

September 2025

Download Tableau Enterprise product report

Also Known As

No data available

Tableau Desktop, Tableau Server, Tableau Online

Overview

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.

Google

Tableau Enterprise offers powerful features for creating interactive visualizations, dashboards, and maps, including drag-and-drop functionality and easy integration with multiple data sources, promoting real-time collaboration and self-service analysis.

Tableau Enterprise stands out with its ability to create user-friendly, interactive visualizations, making it pivotal for business intelligence applications. Users benefit from its seamless connectivity and advanced analytical functions, facilitating data blending and storytelling. Despite a complex learning curve and high licensing costs, its features like geospatial analysis and efficient content distribution drive its indispensable value for data-driven insights. Enhancements in predictive analytics and support integration with machine learning tools further its capabilities across industries.

What are the most valuable features?

Interactive Visualizations: Enables users to create engaging reports.
Drag-and-Drop Functionality: Simplifies data analysis processes.
Data Integration: Offers seamless connectivity with multiple sources.
Real-Time Collaboration: Supports synchronous data sharing.
Advanced Analytics: Provides predictive analytics and geospatial analysis.

What benefits and ROI should users look for?

Informed Decision-Making: Facilitates data-driven insights.
Efficiency in Reporting: Streamlines dashboard and reporting tasks.
Cost-Effectiveness: Despite high licensing, value in robust analytics tools.
Customizable Options: Tailors analytics to specific needs.

Tableau Enterprise is widely used for business intelligence, supporting industries like healthcare, telecommunications, and finance. Organizations utilize it to analyze performance indicators, operational insights, and financial analytics, enhancing decision-making through interactive reports and real-time data integration.

Salesforce

Sample Customers

Information Not Available

Accenture, Adobe, Amazon.com, Bank of America, Charles Schwab Corp, Citigroup, Coca-Cola Company, Cornell University, Dell, Deloitte, Duke University, eBay, Exxon Mobil, Fannie Mae, Ferrari, French Red Cross, Goldman Sachs, Google, Government of Canada, HP, Intel, Johns Hopkins Hospital, Macy's, Merck, The New York Times, PayPal, Pfizer, US Army, US Air Force, Skype, and Walmart.

Buyer's Guide

Google Cloud Datalab vs. Tableau Enterprise

September 2025

Free Report: Google Cloud Datalab vs. Tableau Enterprise

Find out what your peers are saying about Google Cloud Datalab vs. Tableau Enterprise and other solutions. Updated: September 2025.

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