KNIME

KNIME Analytics Platform

Composite Score

7.8 /10

CX Score

8.0 /10

32 Reviews Write a Review

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What is KNIME Analytics Platform?

KNIME offers a complete platform for end-to-end data science, from creating analytical models, to deploying them and sharing insights within the organization, through to data apps and services. The free and open source KNIME Analytics Platform allows users to easily build analyses with an intuitive, low-code/no-code interface. KNIME Business Hub enables users across different disciplines to collaborate and productionize analytical solutions created using KNIME Analytics Platform.

Company Details

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Awards & Recognition

KNIME Analytics Platform won the following awards in the Machine Learning Platforms category

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4 Top Rated Capabilities

2 Top Rated Features

Latest Award, 2024

2 Top Rated Capabilities

5 Top Rated Features

2023

2 Top Rated Capabilities

4 Top Rated Features

2022

KNIME Analytics Platform Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on KNIME Analytics Platform.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

86 Likeliness to Recommend

1
Since last award

93 Plan to Renew

2
Since last award

80 Satisfaction of Cost Relative to Value

1
Since last award

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Emotional Footprint Overview

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+87 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love KNIME Analytics Platform?

2% Negative

0% Neutral

98% Positive

Pros

Inspires Innovation
Efficient Service
Helps Innovate
Acts with Integrity

Feature Ratings

Average 80

Data Exploration and Visualization

Data Pre-Processing

Openness and Flexibility

Feature Engineering

Model Monitoring and Management

Explainability

Model Training

Performance and Scalability

Data Ingestion

Algorithm Diversity

Ensembling

Vendor Capability Ratings

Average 77

Ease of Implementation

Breadth of Features

Business Value Created

Ease of Data Integration

Ease of Customization

Usability and Intuitiveness

Quality of Features

Availability and Quality of Training

Ease of IT Administration

Product Strategy and Rate of Improvement

Vendor Support

KNIME Analytics Platform Reviews

Role: Information Technology
Industry: Technology
Involvement: IT Development, Integration, and Administration

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Great tool for starters

Likeliness to Recommend

6 /10

Pros

Helps Innovate
Continually Improving Product
Includes Product Enhancements
Enables Productivity

Cons

Less Generous
Wastes Time
Less Transparent

Role: Information Technology
Industry: Manufacturing
Involvement: Business Leader or Manager

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Highly capable, open source data science workbench

Likeliness to Recommend

10 /10

Pros

Respectful
Helps Innovate
Unique Features
Effective Service

Cons

Less Generous

Role: Industry Specific Role
Industry: Biotechnology
Involvement: Business Leader or Manager

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Great product for chemical data processing.

Likeliness to Recommend

9 /10

Pros

Continually Improving Product
Performance Enhancing
Enables Productivity
Trustworthy

KNIME Analytics Platform

What is KNIME Analytics Platform?

Company Details

Need Assistance?

Awards & Recognition

KNIME Analytics Platform Ratings

86 Likeliness to Recommend

1 Since last award

93 Plan to Renew

2 Since last award

80 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

+87 Net Emotional Footprint

How much do users love KNIME Analytics Platform?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Data Pre-Processing Ability to wrangle or pre-process data to ready it for model training.

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

Feature Engineering Ability to extract and build features from raw data.

Model Monitoring and Management Ability to monitor model use and performance in production, incl. identifying models for refresh and/or replacement.

Explainability Ability to explain/ visualize the model.

Model Training Ability to train a model with a range of data sets that you provide.

Performance and Scalability Systems performance (time) and scalability end-to-end: from data load and processing to model creation and deployment.

Data Ingestion Ability to access data from various sources on-prem and in the cloud and of various type: structured, unstructured, and semi-structured, real-time, etc.

Algorithm Diversity Provides multiple diverse ready-to-use machine learning algorithms out-of-the-box.

Ensembling 'Ability to combine ML models for best results.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

KNIME Analytics Platform Reviews

Great tool for starters

Likeliness to Recommend

Pros

Cons

Highly capable, open source data science workbench

Likeliness to Recommend

Pros

Cons

Great product for chemical data processing.

Likeliness to Recommend

Pros

Most Popular KNIME Analytics Platform Comparisons

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Feature Ratings

Data Exploration and Visualization

Data Pre-Processing

Openness and Flexibility

Feature Engineering

Model Monitoring and Management

Explainability

Model Training

Performance and Scalability

Data Ingestion

Algorithm Diversity

Ensembling

Vendor Capability Ratings

Ease of Implementation

Breadth of Features

Business Value Created

Ease of Data Integration

Ease of Customization

Usability and Intuitiveness

Quality of Features

Availability and Quality of Training

Ease of IT Administration

Product Strategy and Rate of Improvement

Vendor Support