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

9,373 Views
7,123 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]

Comparison Buyer's Guide

Download the report

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.

To learn more, read our detailed Data Science Platforms Report (Updated: August 2026).

Buyer's Guide

Data Science Platforms

August 2026

Download the complete report

Helped 908,800 peers since 2012

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 (2nd), 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

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.

Read full review

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

"Overall KNIME serves its purpose and does a good job."

"With KNIME, I am able to get that process down to under one minute, with data broken down into individual tabs."

"Easy to use, stable, and powerful."

"This solution is easy to use and it can be used to create any kind of model."

"I've never had any problems with stability."

"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."

"The solution is very easy to use"

"I've tried to utilize KNIME to the fullest extent possible to replace Excel."

More KNIME Business Hub pros

"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."

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

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

"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."

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."

"For graphics, the interface is a little confusing. So, this is a point that could be improved."

"From the point of view of the interface, they can do a little bit better."

"For now, the license is quite expensive for us and it would be helpful if that was reduced."

"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."

"It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved."

"It could input more data acquisitions from other sources and it is difficult to combine with Python."

"I think the data visualization part is the area most in need of improvement."

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

"KNIME offers a free version"

"KNIME Business Hub is expensive for small companies."

"KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."

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

"With KNIME, you can use the desktop version free of charge as much as you like. I've yet to hit its limits. If I did, I'd have to go to the server version, and for that you have to pay. Fortunately, I don't have to at the moment."

"I use the open-source version."

"This is a free open-source solution."

"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"

See which vendors are best for you

Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.

See recommendations

908,800 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

12%

University

Manufacturing Company

Educational Organization

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	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

Ask a question

Earn 20 points

Comparisons

Databricks vs KNIME Business Hub

Compared 9% of the time

Dataiku vs KNIME Business Hub

Compared 9% 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 5% 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 6% 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

Dataiku 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

August 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

Buyer's Guide

Data Science Platforms

August 2026

Download Free Report

Find out what your peers are saying about Databricks, Dataiku, Amazon Web Services (AWS) and others in Data Science Platforms. Updated: August 2026.

DOWNLOAD NOW

908,800 professionals have used our research since 2012.

See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.