KNIME Business Hub vs SAP Predictive Analytics [EOL] comparison

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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 66 KNIME Business Hub reviews

9,750 Views
7,410 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

6.7

Number of Reviews

Ranking in other categories

Data Mining (1st), Data Science Platforms (5th)

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

Filippo Elmino

Data Analyst at Politecnico di Milano

Automation has transformed payroll reporting and empowers nontechnical teams to run data workflows

KNIME Business Hub could be improved by increasing integration between KNIME and other tools, such as where companies store data and data visualization tools, making it easier to integrate with these tools and faster to create dashboard updates and quick data extraction through KNIME. An ETL process must communicate with both data sources and the data visualization layer. The integration needs to be more robust, and the nodes that act as connectors to these sources and tools need to be more robust, as the flow often broke when the problem was just a connection issue. This should be improved and perhaps expanded. Another problem was that KNIME could not integrate with all tools. Expanding the possibilities of creating reports and connecting to data visualization tools, especially on the data visualization side, would be useful. The output of an ETL process or ETL flow is visualization through a dashboard or report, so more downstream integration in the process would be needed. Regarding improvements needed in KNIME Business Hub, there may be a hierarchy of users and certain applications created. On the security side of accessing company data, I do not know whether this is already sufficiently considered by KNIME or not. I hope so, because certain data are sensitive and need to be handled with care. The fact that KNIME is enabled to access such data means you also need to ensure that authorizations and data processing policies are respected. Because some company data are sensitive, the fact that KNIME reads them also requires guaranteeing that a policy is respected on the other side. I hope this has already been considered by KNIME Business Hub; I am not aware, but if it has not, this could be an aspect to consider: privacy and the protection of company data when they are read by a system that is not company-owned but still must read them with all proper requirements and safeguards.

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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

"We leverage KNIME flexibility in order to query data from our database and manipulate them for any ad-hoc business case, before presenting results to stakeholders."

"We have found KNIME valuable when it comes to its visualization."

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

"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."

"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."

"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."

"I would rate the stability of KNIME a ten out of ten."

"If you like data analysis, KNIME is the best option; it's free and easy to set up."

More KNIME Business Hub pros

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

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

Cons

"Visual analytics is the main point for improvement for KNIME Business Hub. Computer vision is the most important because now there is a new age of large language models and visual language models."

"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."

"KNIME could improve when it comes to large data markets."

"It could be easier to use."

"The diversity of native algorithms could be improved."

"In the previous versions, I had some issues when reading large Excel files due to memory usage."

"In my environment, I need to access a lot of servers with different characteristics and access methods. Some of my servers have to be accessed using proxy which is not supported by KNIME, so I still need to create the middleware to supply the source of my KNIME configurations."

"The documentation needs a proper rework. "

More KNIME Business Hub cons

"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."

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

Pricing and Cost Advice

"It is free of cost. It is GNU licensed."

"KNIME Business Hub is expensive for small companies."

"KNIME is free and open source."

"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."

"The price for Knime is okay."

"They have different versions, but I am using the open-source one."

"The price of KNIME is quite reasonable and the designer tool can be used free of charge."

"At this time, I am using the free version of Knime."

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

11%

Manufacturing Company

University

Outsourcing Company

18%

Construction Company

16%

Transportation Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	22
Midsize Enterprise	16
Large Enterprise	35

No data available

Questions from the Community

What needs improvement with KNIME?

See all answers

What is your primary use case for KNIME?

I used KNIME Business Hub in my previous role for approximately six months, from April to September 2025. The primary use case for KNIME Business Hub was creating an ETL flow for the HR team that g...

See all answers

What advice do you have for others considering KNIME?

Regarding concrete examples of metrics or results obtained with KNIME Business Hub, we definitely saved a lot in terms of time and productivity. The work was also much more fluid and activities wer...

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Product Reports

Buyer's Guide

KNIME Business Hub

October 2026

Download KNIME Business Hub product report

Buyer's Guide

Data Science Platforms

October 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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