Google Cloud Datalab vs SAP Predictive Analytics comparison

Google and SAP are both solutions in the Data Science Platforms category. Google is ranked #19 with an average rating of 7.5, while SAP is ranked #27. Google holds a 1.4% mindshare in Data Science Platforms, compared to SAP’s 0.9% mindshare. Additionally, 80% of Google users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

989 Views
673 Comparison Views

80% willing to recommend

SAP Predictive Analytics

Read 3 SAP Predictive Analytics reviews

426 Views
422 Comparison Views

100% willing to recommend

Google Cloud Datalab

SAP Predictive Analytics

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 5, 2024

SAP Predictive Analytics and Google Cloud Datalab compete in predictive analytics and data exploration. SAP Predictive Analytics is preferred for its data integration features, while Google Cloud Datalab is noted for its flexibility and integration with Google Cloud services. SAP appeals to enterprises seeking integrated solutions, whereas Google Cloud Datalab attracts those prioritizing flexibility and cloud-native operations.

Features: SAP Predictive Analytics offers automated predictive modeling, strong data management, and comprehensive data integration capabilities, fitting large enterprises needing seamless IT integration. Google Cloud Datalab provides easy deployment, open-source flexibility, and integration with Google Cloud's machine learning tools, appealing to projects needing cloud-native solutions and customizability.

Ease of Deployment and Customer Service: SAP Predictive Analytics ensures a smooth deployment within the SAP ecosystem with direct support channels for rapid resolution. Google Cloud Datalab supports cloud-based deployments and encourages collaboration through Jupyter notebooks. Its community-reliant support model offers a different experience than SAP's dedicated customer service.

Pricing and ROI: SAP Predictive Analytics has higher setup costs but delivers significant ROI through its deep integration capabilities that streamline complex workflows. Google Cloud Datalab offers scalable pricing, substantial ROI through its features for data exploration, and is ideal for organizations focused on cloud infrastructure.

To learn more, read our detailed Google Cloud Datalab vs. SAP Predictive Analytics Report (Updated: December 2025).

Buyer's Guide

Google Cloud Datalab vs. SAP Predictive Analytics

December 2025

Download the complete report

Helped 880,844 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

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)

SAP Predictive Analytics

Ranking in Data Science Platforms

27th

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

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 SAP Predictive Analytics is 0.9%, up from 0.4% 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%
SAP Predictive Analytics	0.9%
Other	97.7%

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

Abdul-Rasool

Senior Practice Manager - Head of SAP at a tech consulting company with 201-500 employees

Easy to implement, good data forecasting and reporting

This solution works for acquired data but not live, real-time data. If we connect it to a live backend system then we cannot perform predictive analytics on top of that. We have to first upload data to the cloud, manage the staging environment, and then perform the analysis. In the next release of this solution, I would like to see more automation in generating the models. The system can suggest the dimensions and measures that should be used, and pre-populate some of the information based on that. Power users would not have as much need for this, but this type of automation would be very helpful for business end-users.

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

"The APIs are valuable."

"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."

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

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

"The most valuable features are the analytics and reporting."

"I think the features of the actual ability to forecast and pull trends and correlations has been really good."

Cons

"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."

"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."

"This solution works for acquired data but not live, real-time data."

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."

"A free trial version is available for testing out this solution."

"The pricing is reasonable"

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

880,844 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

26%

Computer Software Company

10%

University

Manufacturing Company

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.

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

Ask a question

Earn 20 points

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

Qlik Sense vs Google Cloud Datalab

Compared 7% of the time

More Google Cloud Datalab Competitors

KNIME Business Hub vs SAP Predictive Analytics

Compared 41% of the time

IBM SPSS Statistics vs SAP Predictive Analytics

Compared 32% of the time

H2O.ai vs SAP Predictive Analytics

Compared 27% of the time

More SAP Predictive Analytics Competitors

Product Reports

Buyer's Guide

Google Cloud Datalab

January 2026

Download Google Cloud Datalab product report

Buyer's Guide

Data Science Platforms

January 2026

Download SAP Predictive Analytics product report

Also Known As

No data available

SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA

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

SAP® Predictive Analytics software brings predictive insight to business users, analysts, data scientists, and developers in your company. Unlock the potential of Big Data from virtually any source with the power of predictive automation. By automating the building and management of sophisticated predictive models to deliver insight in real time, this software makes it easier to make better, more profitable decisions across the enterprise.

SAP

Sample Customers

Information Not Available

mBank

Buyer's Guide

Google Cloud Datalab vs. SAP Predictive Analytics

December 2025

Free Report: Google Cloud Datalab vs. SAP Predictive Analytics

Find out what your peers are saying about Google Cloud Datalab vs. SAP Predictive Analytics and other solutions. Updated: December 2025.

DOWNLOAD NOW

880,844 professionals have used our research since 2012.

See our Google Cloud Datalab vs. SAP Predictive Analytics 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.