Google Cloud Datalab vs TIBCO Data Science comparison

Google and TIBCO are both solutions in the Data Science Platforms category. Google is ranked #19 with an average rating of 7.5, while TIBCO is ranked #25. Google holds a 1.5% mindshare in Data Science Platforms, compared to TIBCO’s 1.4% mindshare. Additionally, 80% of Google users are willing to recommend the solution, compared to 100% of TIBCO users who would recommend it.

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

1,162 Views
802 Comparison Views

80% willing to recommend

TIBCO Data Science

Read 4 TIBCO Data Science reviews

720 Views
713 Comparison Views

100% willing to recommend

Google Cloud Datalab

TIBCO Data Science

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

Google Cloud Datalab and TIBCO Data Science are cloud-based data science and machine learning solutions. Google Cloud Datalab excels in ease of use and integration within the Google Cloud ecosystem, while TIBCO Data Science stands out for its advanced analytics capabilities and enterprise integration.

Features: Google Cloud Datalab offers seamless integration with Google Cloud, Jupyter Notebook support, and easy collaboration which benefit users needing straightforward deployment in cloud analytics. TIBCO Data Science showcases sophisticated data manipulation, rich predictive analytics, and robust security measures, thriving in complex model management across varied environments.

Room for Improvement: Google Cloud Datalab could enhance its data visualization capabilities and address limitations in AI configuration that may require server restarts. Increasing support for non-Google Cloud environments may also be beneficial. TIBCO Data Science can improve by offering more competitive pricing structures and simplifying the initial setup process. Enhancing user-friendly interfaces for less technical users could further improve the product.

Ease of Deployment and Customer Service: Google Cloud Datalab provides streamlined deployment via Google Cloud integration, offering simplified setup and efficient resource management. TIBCO Data Science supports on-premises and hybrid deployments, favorable for organizations with intricate infrastructure needs, providing flexibility in various deployment scenarios.

Pricing and ROI: Google Cloud Datalab is known for competitive pricing appealing to budget-conscious tech buyers focused on cloud services, with a favorable cost-to-value ratio. TIBCO Data Science involves higher setup costs justified by its advanced features and tailored enterprise solutions. While the entry cost is higher, TIBCO's ROI can be substantial due to its comprehensive features.

To learn more, read our detailed Google Cloud Datalab vs. TIBCO Data Science Report (Updated: December 2025).

Buyer's Guide

Google Cloud Datalab vs. TIBCO Data Science

December 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 Science Platforms

19th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Visualization (17th)

TIBCO Data Science

Ranking in Data Science Platforms

25th

Average Rating

7.6

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2026, in the Data Science Platforms category, the mindshare of Google Cloud Datalab is 1.5%, up from 0.9% compared to the previous year. The mindshare of TIBCO Data Science is 1.4%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Google Cloud Datalab	1.5%
TIBCO Data Science	1.4%
Other	97.1%

Data Science Platforms

Featured Reviews

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.

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JacekSierajewski

Tibco Spotfire Expert (contractor via Amaris) at GSK

Good performance, reporting, and data visualization

The two similar solutions that I have used are MicroStrategy and Tableau. Tableau is pretty similar and it would be difficult for me to point out the differences. With MicroStrategy, it has a great feature where you build the representation in the database and it then the tool creates SQL queries by itself. There are more differences between these tools but this is the one essential difference.

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Quotes from Members

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

Pros

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

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

"The APIs are valuable."

"Google Cloud Datalab is very customizable."

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

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

"The most valuable feature is the ease of setting up visualizations."

"The most valuable feature is the performance."

"The idea that you don't have to generate reports each day but they are sent automatically is great."

"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."

Cons

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

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

"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."

"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."

"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."

"I would like the visualization for the map of countries to be more easily configurable."

"The scripting for customization could be improved."

"Additional templates would help to get things moving more quickly in terms of getting the reports out."

Pricing and Cost Advice

"The product is cheap."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

24%

Computer Software Company

10%

University

Comms Service Provider

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Google Cloud Datalab?

Google Cloud Datalab is very customizable.

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What needs improvement with Google Cloud Datalab?

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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 ...

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Comparisons

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Compared 10% of the time

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FICO Decision Management vs TIBCO Data Science

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Compared 10% of the time

KNIME Business Hub vs TIBCO Data Science

Compared 9% of the time

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Product Reports

Buyer's Guide

Google Cloud Datalab

January 2026

Download Google Cloud Datalab product report

Buyer's Guide

Data Science Platforms

February 2026

Download TIBCO Data Science product report

Also Known As

No data available

Alpine Data Chorus

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

TIBCO Spotfire Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.

TIBCO

Sample Customers

Information Not Available

Havas Media, Tipping Point Community, eviCore

Buyer's Guide

Google Cloud Datalab vs. TIBCO Data Science

December 2025

Free Report: Google Cloud Datalab vs. TIBCO Data Science

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