Google Cloud Datalab vs IBM Watson Studio comparison

Google and IBM are both solutions in the Data Science Platforms category. Google is ranked #16 with an average rating of 7.8, while IBM is ranked #11 with an average rating of 8.5. Google holds a 1.0% mindshare in Data Science Platforms, compared to IBM’s 2.1% mindshare. Additionally, 80% of Google users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

850 Views
763 Comparison Views

80% willing to recommend

IBM Watson Studio

Read 14 IBM Watson Studio reviews

2,237 Views
1,406 Comparison Views

100% willing to recommend

Google Cloud Datalab

IBM Watson Studio

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

IBM Watson Studio and Google Cloud Datalab are products competing in advanced data analysis. IBM Watson Studio has an advantage in support and usability, while Google Cloud Datalab excels in feature richness justified by its cost.

Features: IBM Watson Studio offers comprehensive data visualization, easy integration with IBM products, and robust data analysis capabilities. Google Cloud Datalab provides powerful data exploration, seamless integration with Google Cloud, and excellent scalability for cloud-native applications.

Room for Improvement: IBM Watson Studio can improve in scalability for larger datasets, reduce complexity in its interface, and offer more flexible pricing models. Google Cloud Datalab could expand its customer support options, simplify its deployment processes, and increase user-friendliness for those new to cloud ecosystems.

Ease of Deployment and Customer Service: IBM Watson Studio offers a robust deployment model with extensive customer support, making it easier for enterprises with dedicated resources. Google Cloud Datalab, while flexible, provides fewer direct support options and requires more self-service deployment efforts, suiting those already invested in Google Cloud.

Pricing and ROI: IBM Watson Studio comes with a higher initial setup cost, offset by extensive features and support for large enterprises, offering a strong ROI. Google Cloud Datalab provides a more affordable entry point with competitive long-term ROI, benefiting those using Google Cloud services already.

To learn more, read our detailed Google Cloud Datalab vs. IBM Watson Studio Report (Updated: January 2025).

Buyer's Guide

Google Cloud Datalab vs. IBM Watson Studio

January 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

16th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Visualization (19th)

IBM Watson Studio

Ranking in Data Science Platforms

11th

Average Rating

8.4

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

AI Development Platforms (9th)

Mindshare comparison

As of January 2025, in the Data Science Platforms category, the mindshare of Google Cloud Datalab is 1.0%, down from 1.3% compared to the previous year. The mindshare of IBM Watson Studio is 2.1%, down from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

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

Abilio Duarte

Senior Solutions Architect at Self-employed

A highly robust and well-documented platform that simplifies the complex world of AI

The main challenge lies in visibility and ease of use. Providing training sessions can be immensely helpful in helping users navigate and understand the tool's potential. This approach would empower users to explore and make the most of the tools and technologies at their disposal. Another area where IBM could enhance its offering is by providing more visibility to end users regarding the vast potential that Watson offers.

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."

"Google Cloud Datalab is very customizable."

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

"The APIs are valuable."

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

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

"Watson Studio is very stable."

"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."

"It has greatly improved the performance because it is standardized across the company."

"It is a very stable and reliable solution."

"Stability-wise, it is a great tool."

"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."

"The scalability of IBM Watson Studio is great."

"The system's ability to take a look at data, segment it and then use that data very differently."

More IBM Watson Studio pros

Cons

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

"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."

"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 product must be made more user-friendly."

"The interface should be more user-friendly."

"The decision making in their decision making feature is less good than other options."

"Watson Studio would be improved with a clearer path for the deployment of docker images."

"I want IBM's technical support team to provide more specific answers to queries."

"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."

"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."

"One area that could be improved is the backup and restoration of the database and the overall database configuration."

"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."

"I think maybe the support is an area where it lacks."

More IBM Watson Studio cons

Pricing and Cost Advice

"The product is cheap."

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

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

"Watson Studio's pricing is reasonable for what you get."

"IBM Watson Studio is a reasonably priced product"

"IBM Watson Studio is an expensive solution."

"The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Computer Software Company

14%

University

10%

Manufacturing Company

Financial Services Firm

15%

Computer Software Company

12%

Manufacturing Company

University

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.

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

What do you like most about IBM Watson Studio?

Stability-wise, it is a great tool.

See all answers

What is your experience regarding pricing and costs for IBM Watson Studio?

The pricing of Watson Studio is justified by the benefits and power it offers.

See all answers

What needs improvement with IBM Watson Studio?

One area that could be improved is the backup and restoration of the database and the overall database configuration. There were also challenges with programming the network extension in the last p...

See all answers

Comparisons

IBM SPSS Statistics vs Google Cloud Datalab

Compared 34% of the time

Databricks vs Google Cloud Datalab

Compared 34% of the time

Cloudera Data Science Workbench vs Google Cloud Datalab

Compared 20% of the time

IBM SPSS Modeler vs Google Cloud Datalab

Compared 11% of the time

More Google Cloud Datalab Competitors

Databricks vs IBM Watson Studio

Compared 26% of the time

Google Vertex AI vs IBM Watson Studio

Compared 17% of the time

Azure OpenAI vs IBM Watson Studio

Compared 15% of the time

Microsoft Azure Machine Learning Studio vs IBM Watson Studio

Compared 14% of the time

Amazon Comprehend vs IBM Watson Studio

Compared 4% of the time

More IBM Watson Studio Competitors

Product Reports

Buyer's Guide

Google Cloud Datalab

January 2025

Download Google Cloud Datalab product report

Buyer's Guide

IBM Watson Studio

January 2025

Download IBM Watson Studio product report

Also Known As

No data available

Watson Studio, IBM Data Science Experience, Data Science Experience, DSx

Learn More

Google

Video not available

IBM

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.

IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.

Sample Customers

Information Not Available

GroupM, Accenture, Fifth Third Bank

Buyer's Guide

Google Cloud Datalab vs. IBM Watson Studio

January 2025

Free Report: Google Cloud Datalab vs. IBM Watson Studio

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