KNIME Pricing

Based on our most recent analysis, KNIME pricing and cost details are described here:

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Starting From: Still gathering data
Pricing Model: Still gathering data
Free Trial: Still gathering data

KNIME Benefits and Insights

Why use KNIME?

Key differentiators & advantages of KNIME

Open-Source: Join a network of thousands of users, enabling collaboration and support. The source code is free to download and access.
Free To Use: Save money by getting access to all of the platform’s features for free. Licensed productivity and collaboration extensions are available at a cost.
Increased Business Intelligence: Get digestible, actionable data to make informed business decisions. Aggregating large datasets into predictive and prescriptive models via comprehensive visualizations and summary statistics gives users projections for the best course of action.
Scalable: Obtain access to big data by scaling up the project in-platform. Integrations to distributed and multi-threaded data processing allow projects to grow.
End-To-End Analytics: It is capable of handling some tasks from start to finish without integrations. Additional integrations may be required for increasing scale and completing more sophisticated analytics.

Industry Expertise

The KNIME platform originated in 2004 at the University of Konstanz in Germany. It has more than 15,000 regular users in at least 60 countries, spanning industries such as pharmaceutical, CRM, financial analysis and life sciences.

KNIME Reviews

Average customer reviews & user sentiment summary for KNIME:

236 reviews

89%

of users would recommend this product

Synopsis of User Ratings and Reviews

Based on an aggregate of KNIME reviews taken from the sources above, the following pros & cons have been curated by a SelectHub Market Analyst.

Pros

Functionality: It provides a comprehensive set of nodes and functions to process large quantities of data, as noted by 69% of users who referred to functionality.
User Friendly: It is intuitive and easy to use, as noted by 79% of reviewers who refer to ease of use.
Connectivity: Around 77% of users who talked about connectivity mentioned its ability to seamlessly connect and integrate with multiple sources.
Cost: All users were happy that the solution is available free of charge, with no data limits.

Cons

Performance: Nearly 95% of reviewers who mentioned performance said that the solution runs slowly and uses too much CPU and memory.
Visualization: Approximately 67% of users who specified visualization talked about its lack of proper visualization options.
Support: About 67% of users who reviewed support mentioned how hard it is to get proper documentation or support.
Learning Curve: KNIME has a steep learning curve, according to about 64% of users who mentioned the learning curve.

Researcher's Summary:

KNIME is a robust open-source solution with cross-platform interoperability. It integrates with a range of software, such as JS, R, Python and Spark. With a variety of nodes and functions, it can process large datasets with a decent level of control in each step. Workflows are displayed as connected nodes, making it easy to isolate and fix specific steps. It also contains built-in tools to create and test supervised and unsupervised machine learning models. Users found the UI very intuitive and flexible. On the flip side, they found the tool visually lacking and primitive. The system also has performance and stability issues. Processing big data is very time consuming since the platform isn’t cloud-based. Users reported excessive memory usage as well. It also lacks reporting or monitoring features. Decent technical knowledge is required to fully leverage its capabilities.

Key Features

Sharing and Collaboration: KNIME Hub is an online repository for existing workflows, nodes and extensions that can be easily installed into a user’s workflow. Upload workflows and search for the components needed for projects.
In-database or Distributed Processing: Process data in-database or through a distributed cluster like Apache Spark for increasing scale. It has prebuilt workflows for in-database processing, like SQL Servers.
Model Predictions and Validation: Using machine learning and AI, produce predictive and prescriptive models. Use performance metrics such as AUC and R2 to verify models.
Visual Workflows: Using a drag-and-drop interface, compose a workflow with little to no coding. Prebuilt generic workflows and components can be downloaded from KNIME Hub.
Data Management: Handles all steps of the extract, transform and load processes. It can ingest, blend, prepare, cleanse and store structured and unstructured data. It can combine data types, including PDF, JSON, CSV and unstructured types like documents and images.
Data Visualizations: Compile analyses into reports with heat graphs, bar charts, scatter plots and more. Visualizations can be exported as PDFs, PowerPoints or other formats.
Tool Blending: Tools with unique domains can be combined within a workflow via native nodes. These include Python or R scripting, processing connectors, machine learning and AI.

Limitations

Some of the product limitations include:

It does not offer monthly billing, only annual
It requires five users and eight cores to qualify for an annual subscription
Lacks integration with Jupyter Notebooks
Doesn’t offer phone support
Error messages may cause interruptions.
Lacks customization for default nodes

Suite Support

Because of the open-source nature of KNIME, it relies heavily on a community forum for support. The forum has nearly 10,000 users, including KNIME personnel, to assist users. Traditional support is described below.

Email:Email support is fulfilled by the ticketing system described below.

Phone: Phone support is not provided.

Training: The vendor offers a “Learning” section on its website, offering FAQs, documentation, white papers, webinars and training courses. Courses take place over a period of time and vary from free or for a price. Certification is available.

Tickets: Users can submit a support ticket through the “Contact” page on the vendor’s website.

KNIME