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H2O.ai vs KNIME comparison

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Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Ranking in Data Science Platforms
10th
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
H2O.ai
Ranking in Data Science Platforms
22nd
Average Rating
7.6
Number of Reviews
7
Ranking in other categories
Model Monitoring (8th)
KNIME
Ranking in Data Science Platforms
2nd
Average Rating
8.2
Number of Reviews
58
Ranking in other categories
Data Mining (1st)
 

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 H2O.ai is 1.5%, up from 1.5% compared to the previous year. The mindshare of KNIME is 11.0%, up from 8.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

AbakarAhmat - PeerSpot reviewer
Sep 21, 2023
Enhancing survey analysis that provides valued insightfulness
I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…
RK
Dec 11, 2018
It is helpful, intuitive, and easy to use. The learning curve is not too steep.
One example, we are able to automate life insurance. We have to underwrite policies. When somebody applies for a policy, we take their blood, then assign them a risk: substandard, standard, preferred, etc. Depending on this, we price our products. Usually the process is that you take the blood, then it goes to a lab and we get the lab results back, then an underwriter takes a look at the lab results. This is usually done in a two week time frame to get a rating. We were able to build models to automate all of this, and now, it happens in real-time. Somebody can apply online and get issued a policy right away.
Hansong Choi - PeerSpot reviewer
Aug 8, 2022
A low-code platform that reduces data mining time by linking script
I manage our data analytics team for a client in the insurance industry and we use the solution for cancelation probation campaigns, ratio modeling, and automatic claim models.  The solution allows for sharing model designs and model operations with other data analysts. Other solutions such as…

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."
"IBM SPSS Statistics depends on AI."
"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."
"It offers very good visualization."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"The most valuable feature is its robust statistical analysis capabilities."
"The software offers consistency across multiple research projects helping us with predictive analytics capabilities."
"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 is helpful, intuitive, and easy to use. The learning curve is not too steep."
"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"The ease of use in connecting to our cluster machines."
"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."
"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."
"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."
"I was able to apply basic algorithms through just dragging and dropping."
"KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data."
"It offers a node-based data integration and processing system connected through a user-friendly drag-and-drop interface. This makes it an excellent choice for data analytics and engineering tasks."
"It is a stable solution...It is a scalable solution."
"This solution is easy to use and especially good at data preparation and wrapping."
"The product is open-source and therefore free to use."
"From a user-friendliness perspective, it's a great tool."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
 

Cons

"The statistics should be more self-explanatory with detailed automated reports."
"The solution needs more planning tools and capabilities."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."
"There is a learning curve; it's not very steep, but there is one."
"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."
"Better documentation on how to use macros."
"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."
"The model management features could be improved."
"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."
"I would like to see more features related to deployment."
"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."
"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."
"Data visualization needs improvement."
"In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could get an overview of what kind of nodes do I have. Right now, it's like you need to know which node you need, and then you can start typing, but it's actually more difficult to find them."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"I've had some problems integrating KNIME with other solutions."
"To enhance accessibility and user-friendliness, there is a need for improvements in the interface and usability of deep learning and large-scale learning languages."
"KNIME is not scalable."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
 

Pricing and Cost Advice

"The price of IBM SPSS Statistics could improve."
"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."
"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."
"I rate the tool's pricing a five out of ten."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"It's quite expensive, but they do a special deal for universities."
"The price of this solution is a little bit high, which was a problem for my company."
"More affordable training for new staff members."
"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."
"While there are certain limitations in functionality, you can still utilize it efficiently free of charge."
"I use the open-source version."
"This is a free open-source solution."
"I use the tool's free version."
"We're using the free academic license just locally. I went for KNIME because they have a free academic license."
"KNIME Business Hub is expensive for small companies."
"It is expensive to procure the license."
"KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
University
10%
Computer Software Company
9%
Manufacturing Company
8%
Financial Services Firm
19%
Computer Software Company
11%
Manufacturing Company
9%
Insurance Company
6%
Manufacturing Company
12%
Financial Services Firm
12%
Computer Software Company
9%
Educational Organization
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
While the pricing of the product may be higher, the accompanying service and features justify the investment. However...
What needs improvement with IBM SPSS Statistics?
In some cases, the product takes time to load a large dataset. They could improve this particular area.
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What do you like most about KNIME?
Since KNIME is a no-code platform, it is easy to work with.
What is your experience regarding pricing and costs for KNIME?
I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.
What needs improvement with KNIME?
The current UI is primarily in English. Analyzing data in local languages might present challenges or issues.
 

Comparisons

 

Also Known As

SPSS Statistics
No data available
KNIME Analytics Platform
 

Learn More

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Overview

 

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
poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Find out what your peers are saying about H2O.ai vs. KNIME and other solutions. Updated: October 2024.
814,649 professionals have used our research since 2012.