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 #28. Google holds a 1.5% mindshare in Data Science Platforms, compared to SAP’s 1.2% 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

1,162 Views
802 Comparison Views

80% willing to recommend

SAP Predictive Analytics

Read 3 SAP Predictive Analytics reviews

559 Views
559 Comparison Views

100% willing to recommend

Google Cloud Datalab

SAP Predictive Analytics

Comparison Buyer's Guide

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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

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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)

SAP Predictive Analytics

Ranking in Data Science Platforms

28th

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2026, in the Data Science Platforms category, the mindshare of Google Cloud Datalab is 1.5%, up from 0.9% compared to the previous year. The mindshare of SAP Predictive Analytics is 1.2%, 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	1.5%
SAP Predictive Analytics	1.2%
Other	97.3%

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.

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Gary Cook

Executive at Empowered Analytics

Enables us to forecast and pull trends and has an easy installation

My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

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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."

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

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

"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."

"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

"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."

"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."

"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 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."

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

"The pricing is reasonable"

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Top Industries

By visitors reading reviews

Financial Services Firm

24%

Computer Software Company

10%

University

Comms Service Provider

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.

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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

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Compared 18% of the time

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Compared 16% of the time

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Compared 8% of the time

Dataiku vs Google Cloud Datalab

Compared 8% of the time

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KNIME Business Hub vs SAP Predictive Analytics

Compared 26% of the time

IBM SPSS Statistics vs SAP Predictive Analytics

Compared 21% of the time

Saturn Cloud vs SAP Predictive Analytics

Compared 18% of the time

H2O.ai vs SAP Predictive Analytics

Compared 17% 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

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