KNIME Business Hub vs SAP Predictive Analytics [EOL] comparison

Knime and SAP are both solutions in the Data Science Platforms category. Additionally, 94% of Knime users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.

KNIME Business Hub

Read 63 KNIME Business Hub reviews

9,188 Views
6,891 Comparison Views

94% willing to recommend

SAP Predictive Analytics [EOL]

Read 3 SAP Predictive Analytics [EOL] reviews

100% willing to recommend

KNIME Business Hub

SAP Predictive Analytics [EOL]

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Executive SummaryUpdated on Jun 3, 2026

KNIME Business Hub and SAP Predictive Analytics [EOL] compete in the data analytics sector. KNIME Business Hub appears to have an advantage due to its support and cost-effectiveness, but SAP Predictive Analytics [EOL] offers more sophisticated features, which is a significant value add.

Features: KNIME Business Hub offers collaborative capabilities and easy integration with multiple data sources. It includes an extensive library of machine learning algorithms. Alternatively, SAP Predictive Analytics [EOL]'s strength lies in predictive modeling with advanced automation.

Ease of Deployment and Customer Service: KNIME Business Hub uses a straightforward cloud deployment model, combined with strong, responsive customer support. SAP Predictive Analytics [EOL] involves a complex on-premise setup but offers extensive customization options.

Pricing and ROI: KNIME Business Hub maintains a competitive pricing structure with a promising ROI due to low initial costs. On the other hand, SAP Predictive Analytics [EOL] requires more substantial upfront investment, yet provides a longer-term return on investment due to its advanced predictive analytics.

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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

KNIME Business Hub

Average Rating

8.2

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Mining (1st), Data Science Platforms (3rd)

SAP Predictive Analytics [EOL]

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Featured Reviews

NataliaRaffo

Co Founder & Chief Data Officer Cdo at NTT DATA

Workflow automation has accelerated advanced analytics and machine learning delivery

Sometimes it is a little bit difficult to use some nodes when we have many large-scale data, for example, CSV files with a large amount of data. It is sometimes difficult to try to import the data in KNIME Business Hub nodes because I think that some features that are in the CSV in text, for example, large text, is difficult for KNIME Business Hub to import these fields. I don't know why, but it is very difficult. We need to try to use different nodes for importing the data, such as File Reader and CSV Reader. However, I think that it is always the features that have much text, it is difficult for KNIME Business Hub to understand and import this information. I don't know why, or maybe I don't know if we don't know what the better option is to configure the node to import all the CSV or the data set. However, we have always had this problem. In some nodes, sometimes it is the same because sometimes, for example, I have a CSV and in my CSV, I have a feature that is, for example, a date. When I import this data set in the File Reader node, I have problems with this field because it is a date, but the problem is that it imports it as text, for example. We try to use their nodes that convert text to date, but sometimes it is difficult, and it is not immediate to transform the text into a date. So we needed to convert the text into a date in the CSV, and then import it again in the KNIME Business Hub node and try to have a good read of this field. I know that KNIME Business Hub has some nodes to convert text to date and others, but sometimes it is difficult to use these nodes. I don't know why. Maybe it needs a specific format for the date and we need to transform our feature in this option. So sometimes it is a large process to convert these features. However, sometimes we need to investigate and search for other nodes, and try with other nodes to import these cases.

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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.

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

"It is a stable solution...It is a scalable solution."

"If you want to do composable artificial intelligence and get return on investment fast, go with KNIME Business Hub."

"I believe the main benefits I receive from KNIME Business Hub are automation, because when I work through the workflow one time, I can reuse it later on, saving considerable time for many tasks."

"I am very happy with the product and it would be hard to find something better in the market."

"The nicest part of KNIME is that the designer tool is free."

"The product is open-source and therefore free to use."

"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."

"I was able to apply basic algorithms through just dragging and dropping."

More KNIME Business Hub pros

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

"We always purchase SAP support because it is very good."

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

"SAP Predictive Analytics is better suited for business users because it hides the complexity of the model, whereas Microsoft Azure Machine Learning provides a lot more flexibility for technical professionals to tweak the model."

"I have found that the solution is very stable."

Cons

"Regarding integration capabilities, I do not think it is that easy to integrate KNIME Business Hub with another product because the connector does not have many options."

"It's difficult to provide input on the improvement area because it's more of self-learning. However, there are times when I am not able to do certain things. I don't know if it's because the solution doesn't allow me or if it's because of the lack of knowledge."

"We do not have much documentation in Portuguese."

"I feel the query performance is slower than my old code."

"When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area."

"KNIME's licensing and data management aren't as straightforward relative to Alteryx. Alteryx's tools are more sophisticated, so you need fewer to use it compared to KNIME. I think tab implementation could be easier, too."

"It could be easier to use."

"The current UI is primarily in English. Analyzing data in local languages might present challenges or issues."

More KNIME Business Hub cons

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

"The license fee appears to be prohibitively expensive and overly secretive, leading our clients to opt for cloud-based solutions that only charge for data storage and processing time."

Pricing and Cost Advice

"For beginners, the free desktop version is very attractive, but the full server version can be more expensive. I have only used the free version and it offers a fair pricing system. I have been promoting it to others without any compensation or request from the company, simply because I am enthusiastic about it. I am not aware of the pricing for the server version, but it seems to be widely used."

"There is a Community Edition and paid versions available."

"It is expensive to procure the license."

"KNIME Business Hub is expensive for small companies."

"The price for Knime is okay."

"KNIME is free and open source."

"KNIME is an open-source tool, so it's free to use."

"There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server."

More KNIME Business Hub pricing and cost advice

"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

12%

Manufacturing Company

University

Educational Organization

Outsourcing Company

17%

Construction Company

17%

Comms Service Provider

Hospitality Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	21
Midsize Enterprise	16
Large Enterprise	32

No data available

Questions from the Community

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.

See all answers

What needs improvement with KNIME?

I would describe KNIME Decision Hub as somewhat helpful in making data-driven decisions more efficient. It could have been a scalable decisioning as a service at the back end, but it's not working ...

See all answers

What is your primary use case for KNIME?

I mainly use KNIME Business Hub currently for data ETLs and then it meets with predictive analytics. Sometimes I utilize it for forecasting, but mostly it's predictive analytics. I have utilized bo...

See all answers

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Comparisons

Dataiku vs KNIME Business Hub

Compared 9% of the time

Databricks vs KNIME Business Hub

Compared 8% of the time

Alteryx vs KNIME Business Hub

Compared 8% of the time

Altair RapidMiner vs KNIME Business Hub

Compared 7% of the time

Microsoft Azure Machine Learning Studio vs KNIME Business Hub

Compared 6% of the time

More KNIME Business Hub Competitors

Saturn Cloud vs SAP Predictive Analytics [EOL]

Compared 6% of the time

IBM SPSS Statistics vs SAP Predictive Analytics [EOL]

Compared 5% of the time

Starburst Galaxy vs SAP Predictive Analytics [EOL]

Compared 5% of the time

Starburst Enterprise vs SAP Predictive Analytics [EOL]

Compared 5% of the time

Altair RapidMiner vs SAP Predictive Analytics [EOL]

Compared 5% of the time

More SAP Predictive Analytics [EOL] Competitors

Product Reports

Buyer's Guide

KNIME Business Hub

July 2026

Download KNIME Business Hub product report

Buyer's Guide

Data Science Platforms

June 2026

Download SAP Predictive Analytics [EOL] product report

Also Known As

KNIME Analytics Platform

SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA

Overview

KNIME Business Hub offers a no-code interface for data preparation and integration, making analytics and machine learning accessible. Its extensive node library allows seamless workflow execution across various data tasks.

KNIME Business Hub stands out for its user-friendly, no-code platform, promoting efficient data preparation and integration, even with Python and R. Its node library covers extensive data processes from ETL to machine learning. Community support aids users, enhancing productivity with minimal coding. However, its visualization, documentation, and interface require refinement. Larger data tasks face performance hurdles, demanding enhanced cloud connectivity and library expansions for deep learning efficiencies.

What are the most important features of KNIME Business Hub?

No-Code Interface: Simplifies data preparation without coding expertise.
Node Library: Supports diverse data tasks, including ETL and machine learning.
Python and R Integration: Seamlessly connects with popular programming languages.
Automation Capabilities: Enhances workflow productivity.
Visual Workflow Tools: Offers efficient data handling with visual aids.

What benefits and ROI can users expect from KNIME Business Hub?

Increased Productivity: Streamlined data tasks reduce development time.
Community Support: Access to extensive resources and user assistance.
Cost-Effective: Robust performance even on standard hardware.
Accessible Learning Curve: Simplicity allows easy access for educational and professional use.
Enhanced Prototyping: Ideal for decision model testing.

KNIME Business Hub finds application in data transformation, cleansing, and multi-source integration for analytics and reporting. Companies utilize it for predictive modeling, clustering, classification, machine learning, and automating workflows. Its coding-free approach suits educational and professional settings, assisting industries in data wrangling, ETLs, and prototyping decision models.

Knime

SAP Predictive Analytics [EOL] offered a powerful platform for creating predictive models that supported business decision-making by utilizing historical data to anticipate future trends.

SAP Predictive Analytics [EOL] was designed to integrate with existing SAP environments, allowing businesses to leverage their existing data infrastructure. It provided users with intuitive tools to automate data preparation and model management, simplifying complex analytical processes. Data scientists could efficiently build and deploy predictive models to address specific business questions. SAP emphasized ease of deployment and scalability, ensuring the platform met the needs of data-driven enterprises.

What are the key features?

Automated Model Creation: Streamlines the process of generating predictive models, reducing time and effort.
Data Preparation: Simplifies data cleaning and preparation, ensuring high-quality input for analysis.
Seamless Integration: Easily integrates with SAP environments, enhancing data accessibility.

What benefits should users consider in reviews?

Informed Decision-Making: Provides insights that help businesses make data-informed decisions.
Efficiency in Analysis: Reduces the time needed to develop and deploy predictive models.
Scalability: Supports expanding data needs as businesses grow.

In industries like manufacturing and retail, SAP Predictive Analytics [EOL] helped optimize supply chains and inventory management by forecasting demand trends. Financial sector users implemented it to enhance risk analysis and fraud detection models, providing valuable insights for mitigating potential risks.

SAP

Sample Customers

Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG

mBank

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