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 65 KNIME Business Hub reviews

9,934 Views
7,649 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 (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

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

"It's a very powerful and simple tool to use."

"It is a free open-source tool that performs very similarly to other expensive tools."

"We have achieved more data-driven decisions since using KNIME Business Hub, for example, we collected and created workflows to analyze the energy consumption of our headquarters building, which helped significantly improve our energy efficiency."

"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."

"One of the greatest advantages of KNIME is that it can be used by those without any coding experience. those with no coding background can use it."

"The technical support is excellent, fast, accurate, and friendly."

"This is a very handy tool and I use it quite interactively."

"Automation is most valuable. It allows me to automatically download information from different sources, and once I create a workflow, I can apply it anytime I want. So, there is efficiency at the same time."

More KNIME Business Hub pros

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

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

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

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

"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."

Cons

"We are worried about the performance when it comes to using a lot of data that has many rows and columns."

"KNIME's documentation is not strong."

"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."

"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."

"I'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something."

"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 solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."

"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."

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

"The price for Knime is okay."

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

"KNIME is a cost-effective solution because it’s free of cost."

"We're using the free academic license just locally. I went for KNIME because they have a free academic license."

"The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."

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

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

"KNIME Business Hub is expensive for small companies."

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

10%

University

Manufacturing Company

Outsourcing Company

17%

Construction Company

15%

Transportation Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	21
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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Comparisons

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Compared 8% of the time

Altair RapidMiner vs KNIME Business Hub

Compared 7% of the time

Alteryx One vs KNIME Business Hub

Compared 7% of the time

Dataiku vs KNIME Business Hub

Compared 7% of the time

SAS Enterprise Miner vs KNIME Business Hub

Compared 6% of the time

More KNIME Business Hub Competitors

IBM SPSS Statistics vs SAP Predictive Analytics [EOL]

Compared 6% of the time

Saturn Cloud vs SAP Predictive Analytics [EOL]

Compared 5% of the time

Dataiku vs SAP Predictive Analytics [EOL]

Compared 5% of the time

Alteryx One vs SAP Predictive Analytics [EOL]

Compared 5% of the time

IBM SPSS Modeler vs SAP Predictive Analytics [EOL]

Compared 4% of the time

More SAP Predictive Analytics [EOL] Competitors

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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