Altair RapidMiner vs Google Cloud Datalab comparison

Altair and Google are both solutions in the Data Science Platforms category. Altair is ranked #7 with an average rating of 8.1, while Google is ranked #18 with an average rating of 7.8. Altair holds a 7.6% mindshare in Data Science Platforms, compared to Google’s 1.0% mindshare. Additionally, 96% of Altair users are willing to recommend the solution, compared to 80% of Google users who would recommend it.

Altair RapidMiner

Read 24 Altair RapidMiner reviews

5,047 Views
4,340 Comparison Views

96% willing to recommend

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

740 Views
577 Comparison Views

80% willing to recommend

Altair RapidMiner

Google Cloud Datalab

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Jun 8, 2025

Altair RapidMiner and Google Cloud Datalab are competing in the data processing and analytics domain. Altair RapidMiner has an edge in ease of use and customer support, whereas Google Cloud Datalab offers a broader feature set, which makes it appealing despite its higher cost.

Features: Altair RapidMiner offers a drag-and-drop interface, pre-built templates, and a user-friendly design that simplifies complex data analyses. In contrast, Google Cloud Datalab provides extensive integration with Google Cloud services, supports advanced analytics capabilities, and offers APIs for seamless data operations.

Room for Improvement: Altair RapidMiner could improve its integration capabilities with third-party services and expand its cloud storage options. Additionally, its complex data set handling and automation features could be enhanced. Google Cloud Datalab could benefit from simplifying its deployment process, improving initial setup times, and offering a more intuitive user interface for non-technical users.

Ease of Deployment and Customer Service: Altair RapidMiner offers straightforward deployment and comprehensive customer support, ensuring quick operational readiness. Google Cloud Datalab's deployment requires technical proficiency due to its integration with the Google Cloud ecosystem, appealing to more technically adept users, but it provides robust cloud-based scalability and support.

Pricing and ROI: Altair RapidMiner offers competitive setup costs aimed at delivering quicker ROI through easy-to-learn interfaces and efficient training processes. Its pricing is attractive to small and medium enterprises, focusing on rapid adoption and reduced training costs. Google Cloud Datalab, though more costly initially, promises long-term ROI with scalable solutions, justified for larger businesses willing to invest in comprehensive cloud environments.

To learn more, read our detailed Altair RapidMiner vs. Google Cloud Datalab Report (Updated: July 2025).

Buyer's Guide

Altair RapidMiner vs. Google Cloud Datalab

July 2025

Download the complete report

Helped 865,384 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

Altair RapidMiner

Ranking in Data Science Platforms

7th

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Predictive Analytics (2nd)

Google Cloud Datalab

Ranking in Data Science Platforms

18th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Visualization (19th)

Mindshare comparison

As of August 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.6%, up from 7.2% compared to the previous year. The mindshare of Google Cloud Datalab is 1.0%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Rathnam Makam

Senior Technical Manager at a computer software company with 1,001-5,000 employees

A no-code tool that helps to build machine learning models

One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users. I haven't explored the tool's latest version, so I'm unaware of the current features. However, I think it would be beneficial if they could enhance capabilities related to deep neural networks, provide better support for generating UI, and allow for importing and utilizing large language models.

Read full review

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

Quotes from Members

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

Pros

"RapidMiner is very easy to use."

"The most valuable features are the Binary classification and Auto Model."

"The solution is stable."

"The best part of RapidMiner is efficiency."

"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."

"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."

"RapidMiner for Windows is an excellent graphical tool for data science."

"I've been using a lot of components from the Strategic Extension and Python Extension."

More Altair RapidMiner pros

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

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

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

"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 APIs are valuable."

Cons

"The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade."

"Currently, I am unsure of all the AI features available in Altair RapidMiner, particularly advanced AI capabilities like neural networks and deep learning."

"I would appreciate improvements in automation and customization options to further streamline processes."

"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."

"I would like to see all users have access to all of the deep learning models, and that they can be used easily."

"The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."

"RapidMiner can improve deep learning by enhancing the features."

"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."

More Altair RapidMiner 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."

"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."

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

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

Pricing and Cost Advice

"Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year."

"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."

"I used an educational license for this solution, which is available free of charge."

"For the university, the cost of the solution is free for the students and teachers."

"I'm not fully aware of RapidMiner's price because we had licenses provided, but from my analysis, it's moderately priced, not too high or too low. It's worth the investment."

"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."

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

865,384 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

University

11%

Computer Software Company

11%

Educational Organization

10%

Manufacturing Company

Financial Services Firm

30%

University

Government

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about RapidMiner?

RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the dat...

See all answers

What is your experience regarding pricing and costs for RapidMiner?

I started with a trial version. We are likely to purchase a license, which may offer additional features.

See all answers

What needs improvement with RapidMiner?

Currently, I am unsure of all the AI features available in Altair RapidMiner, particularly advanced AI capabilities like neural networks and deep learning. It would be beneficial if the platform co...

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?

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

Comparisons

KNIME Business Hub vs Altair RapidMiner

Compared 51% of the time

Dataiku vs Altair RapidMiner

Compared 15% of the time

Tableau Enterprise vs Altair RapidMiner

Compared 8% of the time

Alteryx vs Altair RapidMiner

Compared 7% of the time

IBM SPSS Modeler vs Altair RapidMiner

Compared 3% of the time

More Altair RapidMiner Competitors

Anaconda Business vs Google Cloud Datalab

Compared 32% of the time

IBM SPSS Statistics vs Google Cloud Datalab

Compared 24% of the time

Databricks vs Google Cloud Datalab

Compared 19% of the time

KNIME Business Hub vs Google Cloud Datalab

Compared 13% of the time

Oracle Analytics Cloud vs Google Cloud Datalab

Compared 12% of the time

More Google Cloud Datalab Competitors

Product Reports

Buyer's Guide

Altair RapidMiner

August 2025

Download Altair RapidMiner product report

Buyer's Guide

Google Cloud Datalab

August 2025

Download Google Cloud Datalab product report

Overview

Altair RapidMiner is a leading platform for data science and machine learning, offering a user-friendly interface with powerful tools for predictive analytics. It supports integration with APIs, Python, and cloud services for streamlined workflow creation.

RapidMiner provides an efficient data science environment featuring drag-and-drop functionality, automation tools, and a wide array of algorithms, making it adaptable for novices and experts alike. Users benefit from easy data preparation and analysis alongside robust support from a vibrant community. Challenges include better onboarding and deep learning model accessibility, alongside calls for enhanced image processing and large language model integration.

What features make Altair RapidMiner stand out?

Data science tools: Facilitates machine learning and predictive analytics.
Code-optional GUI: Enables non-programmers to create workflows seamlessly.
Integration: Supports APIs, Python, and cloud services.
Drag-and-drop functionality: Simplifies workflow creation for users.
Algorithm variety: Offers diverse methods for data analysis.

What benefits and ROI should users consider when evaluating?

Efficiency: Saves time in data preparation and workflow automation.
Accessibility: Intuitive design aids beginners and experts.
Community: Access to extensions and collaborative resources.
Documentation: Comprehensive tutorials enhance learning.

Altair RapidMiner is extensively used in business and academia, facilitating tasks like predictive analytics, segmentation, and deployment. In education, it supports data science teaching and research, while in industries such as telecom, banking, and healthcare, it's used for data mining, decision trees, and market analysis.

Altair

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

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

Information Not Available

Buyer's Guide

Altair RapidMiner vs. Google Cloud Datalab

July 2025

Free Report: Altair RapidMiner vs. Google Cloud Datalab

Find out what your peers are saying about Altair RapidMiner vs. Google Cloud Datalab and other solutions. Updated: July 2025.

DOWNLOAD NOW

865,384 professionals have used our research since 2012.

See our Altair RapidMiner 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.