KNIME

KNIME Analytics Platform

Composite Score

7.8 /10

CX Score

7.9 /10

33 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

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.

85 Likeliness to Recommend

93 Plan to Renew

79 Satisfaction of Cost Relative to Value

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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.

+86 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

4% Neutral

94% Positive

Pros

Efficient Service
Inspires Innovation
Helps Innovate
Continually Improving Product

Feature Ratings

Average 81

Data Pre-Processing

Openness and Flexibility

Data Exploration and Visualization

Feature Engineering

Model Monitoring and Management

Model Training

Explainability

Data Ingestion

Performance and Scalability

Algorithm Diversity

Ensembling

Vendor Capability Ratings

Average 78

Ease of Implementation

Breadth of Features

Ease of Data Integration

Business Value Created

Ease of Customization

Quality of Features

Availability and Quality of Training

Usability and Intuitiveness

Ease of IT Administration

Product Strategy and Rate of Improvement

Vendor Support

KNIME Analytics Platform Reviews

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

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Good product and easy to delivery

Likeliness to Recommend

8 /10

Pros

Reliable
Caring
Respectful
Acts with Integrity

Role: Student Academic
Industry: Education
Involvement: End User of Application

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Easy to use. Perfect for textual analysis

Likeliness to Recommend

8 /10

Pros

Unique Features
Saves Time
Client's Interest First
Helps Innovate

Kourosh M.

Role: C-Level
Industry: Technology
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Apr 2022

KNIME; visual Innovation

Likeliness to Recommend

9 /10

What differentiates KNIME Analytics Platform from other similar products?

Visual Programming for Data Science

What do you dislike most about this product?

KNIME server complexity

What recommendations would you give to someone considering this product?

Speaking of now, it is the most capable one.

Pros

Enables Productivity
Helps Innovate
Continually Improving Product
Reliable

Cons

Vendor's Interest First

KNIME Analytics Platform

What is KNIME Analytics Platform?

Company Details

Need Assistance?

Awards & Recognition

KNIME Analytics Platform Ratings

85 Likeliness to Recommend

93 Plan to Renew

79 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

+86 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 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.)

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

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.

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

Explainability Ability to explain/ visualize the model.

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.

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

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.

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

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 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.

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.

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.

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

Good product and easy to delivery

Likeliness to Recommend

Pros

Easy to use. Perfect for textual analysis

Likeliness to Recommend

Pros

Kourosh M.

KNIME; visual Innovation

Likeliness to Recommend

Pros

Cons

Most Popular KNIME Analytics Platform Comparisons

Google Cloud Vertex AI

MathWorks MATLAB

AWS Machine Learning

Microsoft Azure Machine Learning

Databricks Data Intelligence Platform

DataRobot AI Platform

Feature Ratings

Data Pre-Processing

Openness and Flexibility

Data Exploration and Visualization

Feature Engineering

Model Monitoring and Management

Model Training

Explainability

Data Ingestion

Performance and Scalability

Algorithm Diversity

Ensembling

Vendor Capability Ratings

Ease of Implementation

Breadth of Features

Ease of Data Integration

Business Value Created

Ease of Customization

Quality of Features

Availability and Quality of Training

Usability and Intuitiveness

Ease of IT Administration

Product Strategy and Rate of Improvement

Vendor Support