Google Cloud Datalab vs SAS Enterprise Miner comparison

Google and SAS are both solutions in the Data Science Platforms category. Google is ranked #19 with an average rating of 7.5, while SAS is ranked #23. Google holds a 1.4% mindshare in Data Science Platforms, compared to SAS’s 1.6% mindshare. Additionally, 80% of Google users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

989 Views
673 Comparison Views

80% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

1,059 Views
805 Comparison Views

93% willing to recommend

Google Cloud Datalab

SAS Enterprise Miner

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

SAS Enterprise Miner and Google Cloud Datalab compete in the data analytics and machine learning space. Google Cloud Datalab has an advantage with its ease of use and scalability.

Features: SAS Enterprise Miner offers robust statistical modeling, decision trees, and regression capabilities, ideal for comprehensive analytics projects. Google Cloud Datalab provides seamless integration with Google’s ecosystem, solidifying its adaptability in data visualization, machine learning, and collaboration for cloud-based projects.

Room for Improvement: SAS Enterprise Miner could enhance integration with cloud services, improve user interface intuitiveness, and simplify deployment processes. Google Cloud Datalab may improve on its AI configurations, its cost structure for large-scale data applications, and documentation specificity for complex implementations.

Ease of Deployment and Customer Service: Google Cloud Datalab uses a straightforward cloud-based deployment model with extensive documentation and community support, allowing for quick setup. SAS Enterprise Miner demands more specialized expertise due to its on-premise deployment, requiring more setup resources.

Pricing and ROI: SAS Enterprise Miner involves higher setup costs due to infrastructure and licensing, promising solid ROI for long-term projects. Google Cloud Datalab’s cloud-based pricing model is more cost-effective, suitable for organizations seeking fast ROI through cloud integration.

To learn more, read our detailed Google Cloud Datalab vs. SAS Enterprise Miner Report (Updated: December 2025).

Buyer's Guide

Google Cloud Datalab vs. SAS Enterprise Miner

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)

SAS Enterprise Miner

Ranking in Data Science Platforms

23rd

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Mining (7th)

Mindshare comparison

As of January 2026, in the Data Science Platforms category, the mindshare of Google Cloud Datalab is 1.4%, up from 1.0% compared to the previous year. The mindshare of SAS Enterprise Miner is 1.6%, up from 0.7% 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	1.4%
SAS Enterprise Miner	1.6%
Other	97.0%

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.

Read full review

reviewer1352853

Executive Head of analytics at a retailer with 5,001-10,000 employees

A stable product that is easy to deploy and can be used for structured and unstructured data mining

We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

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

"The APIs are valuable."

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

"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."

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

"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."

"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."

"Good data management and analytics."

"The solution is able to handle quite large amounts of data beautifully."

"The technical support is very good."

"The most valuable feature is the decision tree creation."

"he solution is scalable."

"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

More SAS Enterprise Miner pros

Cons

"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."

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

"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."

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

"The interface should be more user-friendly."

"The product must provide better integration with cloud-native technologies."

"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."

"The initial setup is challenging if doing it for the first time."

"Virtualization could be much better."

"The ease of use can be improved. When you are new it seems a bit complex."

"The user interface of the solution needs improvement. It needs to be more visual."

"The visualization of the models is not very attractive, so the graphics should be improved."

"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."

More SAS Enterprise Miner 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."

"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."

"The solution must improve its licensing models."

"This solution is for large corporations because not everybody can afford it."

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Top Industries

By visitors reading reviews

Financial Services Firm

26%

Computer Software Company

10%

University

Manufacturing Company

Financial Services Firm

25%

Educational Organization

11%

Manufacturing Company

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	4
Large Enterprise	7

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?

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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

Anaconda Business vs Google Cloud Datalab

Compared 20% of the time

Databricks vs Google Cloud Datalab

Compared 15% of the time

IBM SPSS Statistics vs Google Cloud Datalab

Compared 9% of the time

KNIME Business Hub vs Google Cloud Datalab

Compared 8% of the time

Altair RapidMiner vs Google Cloud Datalab

Compared 5% of the time

More Google Cloud Datalab Competitors

KNIME Business Hub vs SAS Enterprise Miner

Compared 20% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 12% of the time

SAS Visual Analytics vs SAS Enterprise Miner

Compared 8% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 8% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Google Cloud Datalab

January 2026

Download Google Cloud Datalab product report

Buyer's Guide

Data Mining

January 2026

Download SAS Enterprise Miner product report

Also Known As

No data available

Enterprise Miner

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

SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

SAS

Sample Customers

Information Not Available

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare

Buyer's Guide

Google Cloud Datalab vs. SAS Enterprise Miner

December 2025

Free Report: Google Cloud Datalab vs. SAS Enterprise Miner

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