Dataiku vs Google Cloud Datalab comparison

Dataiku and Google are both solutions in the Data Science Platforms category. Dataiku is ranked #4 with an average rating of 8.0, while Google is ranked #19 with an average rating of 7.5. Dataiku holds a 6.7% mindshare in Data Science Platforms, compared to Google’s 1.6% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 80% of Google users who would recommend it.

Dataiku

Read 20 Dataiku reviews

5,913 Views
5,795 Comparison Views

100% willing to recommend

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

1,246 Views
860 Comparison Views

80% willing to recommend

Dataiku

Google Cloud Datalab

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 5, 2024

Google Cloud Datalab and Dataiku are products in the data analytics domain. Dataiku holds the advantage with its comprehensive features and user-friendly analytics tools.

Features: Google Cloud Datalab offers seamless integration with Google Cloud services, rapid notebook-based exploration, and real-time collaboration. Dataiku provides robust data preparation tools, machine learning capabilities, and easy-to-use analytics supporting teamwork.

Room for Improvement: Google Cloud Datalab could enhance its advanced analytics tools, improve user support for complex setups, and expand its non-Google Cloud integrations. Dataiku could benefit from reducing its initial setup complexity, offering more detailed customization options, and optimizing system resource usage for large datasets.

Ease of Deployment and Customer Service: Google Cloud Datalab ensures straightforward deployment in Google's ecosystem, leveraging Google's support. Dataiku offers flexible deployment on-premises or in the cloud with personalized support, facilitating a smoother transition.

Pricing and ROI: Google Cloud Datalab's integration lowers setup costs, appealing to budget-conscious users. Dataiku, despite higher initial costs, offers substantial ROI with its impactful features, justifying its pricing through efficiency in complex data tasks.

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

Buyer's Guide

Dataiku vs. Google Cloud Datalab

March 2026

Download the complete report

Helped 884,797 peers since 2012

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

Dataiku

Ranking in Data Science Platforms

4th

Average Rating

8.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

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 (16th)

Mindshare comparison

As of March 2026, in the Data Science Platforms category, the mindshare of Dataiku is 6.7%, down from 12.5% compared to the previous year. The mindshare of Google Cloud Datalab is 1.6%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Dataiku	6.7%
Google Cloud Datalab	1.6%
Other	91.7%

Data Science Platforms

Featured Reviews

Shubhamkumar Gomar

Senior Data Scientist at Deloitte

Visual workflows have streamlined healthcare analytics and have reduced reporting time significantly

In terms of improvement, I cannot comment on the LLMs or the agentic view as I have not used them yet. However, I feel that better documentation is necessary. Dataiku should establish a stronger community since this is proprietary software, where users can share knowledge. Although they have some community interaction, it is often challenging to find assistance when stuck. For example, when I was new to Dataiku and trying to use an external optimization tool such as CPLEX, I struggled with resource directory linking to a project's notebook. Detailed documentation and community discussions could have significantly alleviated these issues for users such as myself.

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

"Dataiku has positively impacted my organization since we use it majorly for our day-to-day work, and it is very helpful in creating and managing ETL pipelines to create a project flow, making it easy to go back to any step and then make edits if some changes occur."

"The best features Dataiku offers include the ability for users to use the node without having to code and the functionality related to low-code/no-code."

"Data Science Studio's data science model is very useful."

"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."

"The best feature in Dataiku is that once the data is connected in the underneath layer, it flows exceptionally smoothly if you know how to tweak it."

"Our clients can easily drag and drop components and use them on the spot."

"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."

"I consider the return on investment with Dataiku valuable because for us, it is one single platform where all our data scientists come together and work on any model building, so it is collaboration, plus having everything in one place, organized, having proper project management, and then built-in capabilities which help to facilitate model building."

More Dataiku pros

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

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

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

"The APIs are valuable."

"Google Cloud Datalab is very customizable."

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

Cons

"I have not seen a return on investment with Dataiku in terms of time saved, money saved, or fewer employees needed."

"However, I feel that better documentation is necessary."

"The ability to have charts right from the explorer would be an improvement."

"One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."

"We still encounter some integration issues."

"All products have room for improvement, and I would like to see their pricing simplified, as it is somewhat complex."

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."

"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."

More Dataiku cons

"The interface should be more user-friendly."

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

"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."

"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

"Pricing is pretty steep. Dataiku is also not that cheap."

"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."

"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."

"The product is cheap."

See which vendors are best for you

Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.

See recommendations

884,797 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

10%

Computer Software Company

Energy/Utilities Company

Financial Services Firm

25%

University

Outsourcing Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	2
Large Enterprise	13

No data available

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?

I am not the person involved in the process regarding pricing, setup cost, and licensing.

See all answers

What needs improvement with Dataiku Data Science Studio?

To improve Dataiku, it could enhance its visualization features, as it is not possible in Dataiku to create direct visualizations or to integrate a web app directly or in a simpler way as it is pos...

See all answers

What is your primary use case for Dataiku Data Science Studio?

My main use case for Dataiku is for data science and AI projects. I use Dataiku for a demand forecasting use case where the objective is to predict the demand for each product for the next four mon...

See all answers

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?

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

Comparisons

Databricks vs Dataiku

Compared 21% of the time

KNIME Business Hub vs Dataiku

Compared 13% of the time

Alteryx vs Dataiku

Compared 11% of the time

Altair RapidMiner vs Dataiku

Compared 6% of the time

Anaconda Business vs Dataiku

Compared 2% of the time

More Dataiku Competitors

Databricks vs Google Cloud Datalab

Compared 13% of the time

Anaconda Business vs Google Cloud Datalab

Compared 13% of the time

Altair RapidMiner vs Google Cloud Datalab

Compared 8% of the time

Qlik Sense vs Google Cloud Datalab

Compared 7% of the time

Tableau Enterprise vs Google Cloud Datalab

Compared 7% of the time

More Google Cloud Datalab Competitors

Product Reports

Buyer's Guide

Dataiku

March 2026

Download Dataiku product report

Buyer's Guide

Google Cloud Datalab

March 2026

Download Google Cloud Datalab product report

Also Known As

Dataiku DSS

No data available

Overview

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

Dataiku

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

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto

Information Not Available

Buyer's Guide

Dataiku vs. Google Cloud Datalab

March 2026

Free Report: Dataiku vs. Google Cloud Datalab

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

DOWNLOAD NOW

884,797 professionals have used our research since 2012.

See our Dataiku vs. Google Cloud Datalab report.

See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.