Cloudera Data Science Workbench vs H2O.ai comparison

Cloudera and H2O.ai are both solutions in the Data Science Platforms category. Cloudera is ranked #21 with an average rating of 6.0, while H2O.ai is ranked #22. Cloudera holds a 1.5% mindshare in Data Science Platforms, compared to H2O.ai’s 1.5% mindshare. Additionally, 66% of Cloudera users are willing to recommend the solution, compared to 100% of H2O.ai users who would recommend it.

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Executive Summary

We performed a comparison between Cloudera Data Science Workbench and H2O.ai 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. H2O.ai Report (Updated: October 2024).

Buyer's Guide

Cloudera Data Science Workbench vs. H2O.ai

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 H2O.ai is 1.5%, up 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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Kashif Yaseen

Trainee Decision Scientist at a tech services company with 1,001-5,000 employees

Plug-and-play convenience enhances productivity but needs better multimodal support

We mostly used the solution in the domain that I'm working. We had most of the use cases around chatbots and conversational BI The solution was plug-and-play, meaning most of the components were handled by the solution itself rather than building them from scratch. This was useful for our banking…

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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 most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."

"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."

"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."

"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."

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

"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."

"It has the ability to easily change any variable in our research."

"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."

More IBM SPSS Statistics pros

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

"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."

"Fast training, memory-efficient DataFrame manipulation, well-documented, easy-to-use algorithms, ability to integrate with enterprise Java apps (through POJO/MOJO) are the main reasons why we switched from Spark to H2O."

"One of the most interesting features of the product is their driverless component. The driverless component allows you to test several different algorithms along with navigating you through choosing the best algorithm."

"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."

"The most valuable feature of H2O.ai is that it is plug-and-play."

"The most valuable features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."

"It is helpful, intuitive, and easy to use. The learning curve is not too steep."

"The ease of use in connecting to our cluster machines."

Cons

"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."

"The technical support should be improved."

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

"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."

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

"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."

"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."

"Improvements are needed in the user interface, particularly in terms of user-friendliness."

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."

"The interpretability module has room for improvement. Also, it needs to improve its ability to integrate with other systems, like SageMaker, and the overall integration capability."

"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."

"H2O.ai can improve in areas like multimodal support and prompt engineering."

"The model management features could be improved."

"I would like to see more features related to deployment."

"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."

"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."

"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."

Pricing and Cost Advice

"While the pricing of the product may be higher, the accompanying service and features justify the investment."

"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."

"The price of IBM SPSS Statistics could improve."

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

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

"More affordable training for new staff members."

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

"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."

More IBM SPSS Statistics pricing and cost advice

"The product is expensive."

"We have seen significant ROI where we were able to use the product in certain key projects and could automate a lot of processes. We were even able to reduce staff."

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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

11%

Manufacturing Company

10%

Insurance 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'...

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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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Comparisons

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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

Google Cloud Datalab vs Cloudera Data Science Workbench

Compared 9% of the time

Microsoft Azure Machine Learning Studio vs Cloudera Data Science Workbench

Compared 9% of the time

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Databricks vs H2O.ai

Compared 21% of the time

Dataiku vs H2O.ai

Compared 19% of the time

Amazon SageMaker vs H2O.ai

Compared 16% of the time

Microsoft Azure Machine Learning Studio vs H2O.ai

Compared 14% of the time

KNIME vs H2O.ai

Compared 11% of the time

More H2O.ai 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

Data Science Platforms

November 2024

Download H2O.ai product report

Also Known As

SPSS Statistics

CDSW

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IBM

Cloudera

H2O.ai

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.

H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O’s supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models. The H2O platform is used by over 14,000 organizations globally and is extremely popular in both the R & Python communities.

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

poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco

Buyer's Guide

Cloudera Data Science Workbench vs. H2O.ai

October 2024

Free Report: Cloudera Data Science Workbench vs. H2O.ai

Find out what your peers are saying about Cloudera Data Science Workbench vs. H2O.ai and other solutions. Updated: October 2024.

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