Cloudera Data Science Workbench vs Google Cloud Datalab comparison

Cloudera and Google are both solutions in the Data Science Platforms category. Cloudera is ranked #21 with an average rating of 6.0, while Google is ranked #15 with an average rating of 7.8. Cloudera holds a 1.5% mindshare in Data Science Platforms, compared to Google’s 1.0% mindshare. Additionally, 66% of Cloudera users are willing to recommend the solution, compared to 80% of Google users who would recommend it.

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Executive Summary

We performed a comparison between Cloudera Data Science Workbench and Google Cloud Datalab based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Cloudera Data Science Workbench vs. Google Cloud Datalab Report (Updated: October 2024).

Buyer's Guide

Cloudera Data Science Workbench vs. Google Cloud Datalab

October 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Cloudera Data Science Workbench is 1.5%, down from 1.8% compared to the previous year. The mindshare of Google Cloud Datalab is 1.0%, down from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

AbakarAhmat

Software Engineer at a university with 10,001+ employees

Enhancing survey analysis that provides valued insightfulness

I used traditional tools where I would prepare data, click through menus, and use SQL Server for data visualization. We switched to IBM SPSS because it offers strong certification and aligns well with the standards we prioritize in our surveys. In terms of popularity, it stands out as the top choice in the market, especially in the research and university domains. Many different organizations and institutions use SPSS for statistical analytics. While there are other tools like MCLab and similar options available, SPSS is the most renowned and widely used among them.

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Ismail Peer

Program Management Lead Advisor at Unionbank Philippines

Useful for data science modeling but improvement is needed in MLOps and pricing

If you don't configure CDSW well, then it might be not useful for you. Deploying the tool can vary in complexity, but most of the time, it's relatively simple and straightforward. Triggering a job from data to production is easy, as the platform automates the deployment process. However, ensuring optimal resource allocation is essential for smooth operations.

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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.

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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 SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."

"The most valuable feature is its robust statistical analysis capabilities."

"It offers very good visualization."

"The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."

"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."

"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."

"The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."

"The most valuable features are the small learning curve and its ability to hold a lot of data."

More IBM SPSS Statistics pros

"I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."

"The Cloudera Data Science Workbench is customizable and easy to use."

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

"The APIs are valuable."

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

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

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

"Google Cloud Datalab is very customizable."

Cons

"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."

"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."

"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."

"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."

"The reports could be better."

"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."

"Better documentation on how to use macros."

"I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better."

More IBM SPSS Statistics cons

"The tool's MLOps is not good. It's pricing also needs to improve."

"Running this solution requires a minimum of 12GB to 16GB of RAM."

"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."

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

"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."

"The interface should be more user-friendly."

Pricing and Cost Advice

"We think that IBM SPSS is expensive for this function."

"The price of this solution is a little bit high, which was a problem for my company."

"I rate the tool's pricing a five out of ten."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."

"More affordable training for new staff members."

"It's quite expensive, but they do a special deal for universities."

"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."

More IBM SPSS Statistics pricing and cost advice

"The product is expensive."

"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."

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816,406 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

University

Computer Software Company

Manufacturing Company

Financial Services Firm

35%

Manufacturing Company

11%

Healthcare Company

Government

Financial Services Firm

20%

Computer Software Company

14%

University

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about IBM SPSS Statistics?

The software offers consistency across multiple research projects helping us with predictive analytics capabilities.

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What is your experience regarding pricing and costs for IBM SPSS Statistics?

The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...

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What needs improvement with IBM SPSS Statistics?

IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the result...

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What do you like most about Cloudera Data Science Workbench?

I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don'...

See all answers

What needs improvement with Cloudera Data Science Workbench?

The tool's MLOps is not good. It's pricing also needs to improve.

See all answers

What is your primary use case for Cloudera Data Science Workbench?

We have different use cases. Our banking use case uses machine learning to identify customer life events and recommen...

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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?

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...

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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 serv...

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Comparisons

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 14% of the time

Alteryx vs IBM SPSS Statistics

Compared 14% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

Amazon SageMaker vs IBM SPSS Statistics

Compared 5% of the time

More IBM SPSS Statistics Competitors

Amazon SageMaker vs Cloudera Data Science Workbench

Compared 29% of the time

Databricks vs Cloudera Data Science Workbench

Compared 29% of the time

Dataiku vs Cloudera Data Science Workbench

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs Cloudera Data Science Workbench

Compared 9% of the time

KNIME vs Cloudera Data Science Workbench

Compared 6% of the time

More Cloudera Data Science Workbench Competitors

Databricks vs Google Cloud Datalab

Compared 25% of the time

IBM SPSS Modeler vs Google Cloud Datalab

Compared 10% of the time

KNIME vs Google Cloud Datalab

Compared 9% of the time

Microsoft Azure Machine Learning Studio vs Google Cloud Datalab

Compared 8% of the time

More Google Cloud Datalab Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

November 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Data Science Platforms

November 2024

Download Cloudera Data Science Workbench product report

Buyer's Guide

Google Cloud Datalab

November 2024

Download Google Cloud Datalab product report

Also Known As

SPSS Statistics

CDSW

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IBM

Cloudera

Google

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. Access any data anywhere – from cloud object storage to data warehouses, CDSW provides connectivity not only to CDH but the systems your data science teams rely on for analysis.

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.

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA

IQVIA, Rush University Medical Center, Western Union

Information Not Available

Buyer's Guide

Cloudera Data Science Workbench vs. Google Cloud Datalab

October 2024

Free Report: Cloudera Data Science Workbench vs. Google Cloud Datalab

Find out what your peers are saying about Cloudera Data Science Workbench vs. Google Cloud Datalab and other solutions. Updated: October 2024.

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