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KNIME Analytics Platform

KNIME Analytics Platform

Overview

What is KNIME Analytics Platform?

KNIME enables users to analyze, upskill, and scale data science without any coding. The platform that lets users blend, transform, model and visualize data, deploy and monitor analytical models, and share insights organization-wide with data apps and services.

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Pricing

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KNIME Community Hub Personal Plan

$0

Cloud

KNIME Analytics Platform

$0

On Premise

KNIME Community Hub Team Plan

€99

Cloud
per month 3 users

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visithttps://www.knime.com/knime…

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services
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Product Demos

Break into Deep Learning for Image Data without Code

YouTube

Automating Financial Calculations with KNIME

YouTube

Leveraging ChatGPT in KNIME workflows

YouTube

Best Practices to Build KNIME Workflows

YouTube

Automating Out of Spreadsheet Hell with KNIME

YouTube
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Features

Platform Connectivity

Ability to connect to a wide variety of data sources

9.1
Avg 8.3

Data Exploration

Ability to explore data and develop insights

8
Avg 8.3

Data Preparation

Ability to prepare data for analysis

8.3
Avg 8.2

Platform Data Modeling

Building predictive data models

8
Avg 8.4

Model Deployment

Tools for deploying models into production

7.3
Avg 8.5
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Product Details

What is KNIME Analytics Platform?

KNIME empowers data users to build, collaborate, and upskill on data science. KNIME offers support across the data science life cycle, from creating analytical models to deploying them and sharing insights across the enterprise.

Users of KNIME tend to wear one of four hats:

Data experts can accelerate time to insight, collaborate with other disciplines, and empower upskilling across business functions. KNIME lets them:
* Connect to any data, access any analytic technique, and the choice to code in any language
* Get to insights faster using a low-code/no-code interface
* Eliminate repetitive, manual work by creating reusable, automated workflows
* Save and share Python scripts, analytical models, or data processes for reuse
* Provide blueprints that non-experts can learn and upskill from independently
* Speed up learning by accessing workflow samples by KNIME community members and experts
* Validate models with performance metrics and carry out cross validation to guarantee model stability
* Automatically document each step of the analysis visually * Maintain models and fix mistakes more easily with version control, debugging, tracking, and auditing

Business & domain experts can access and blend data, perform advanced analyses, and deliver timely insights in a visual, interactive environment that eliminates the need to code. They can prep data faster and do deeper analyses because KNIME lets them:
* Connect to all data sources and access any file format in one visual environment.
* Transform data self-sufficiently in the same visual environment without IT dependency
* Use visual workflows from others as blueprints to get started faster
* Automate repetitive data tasks like data prep and reporting with reusable workflows
* Minimize the time to spot and fix errors with each step of the analysis clearly visible, and track changes with version control
* Access thousands of self-explanatory nodes to perform the actions needed on data
* Create workflows of any complexity by joining nodes together via drag and drop

End users can get insights with custom-built, interactive data apps without needing to know how to code or build analytical models. They can make faster, data-driven decisions with advanced analytics at their disposal because KNIME lets them:
* Interact with analyses of any complexity level with a data app UI
* Access data apps via the browser with a secure connection or shareable link
* Identify patterns with job-relevant data apps and provide feedback to improve the model
* Lower the barrier between them and data science teams, enhancing analytics output accuracy
* Choose to get insights from simple dashboards or complex, interactive visualizations
* Explore data and perform ad hoc analyses using interaction points within data apps
* Avoid vendor lock-in and adapt to changing business needs with an extensible platform

MLOps and IT teams use KNIME to securely deploy, manage, and scale with a single installation while ensuring enterprise-grade security and governance. The platform enables them to:
* Safely deploy and monitor models from one single place
* Ensure adherence to best practices
* Meet enterprise needs while ensuring data security and governance
* Securely productionization data science at scale

KNIME Analytics Platform Features

Platform Connectivity Features

  • Supported: Connect to Multiple Data Sources
  • Supported: Extend Existing Data Sources
  • Supported: Automatic Data Format Detection

Data Exploration Features

  • Supported: Visualization
  • Supported: Interactive Data Analysis

Data Preparation Features

  • Supported: Interactive Data Cleaning and Enrichment
  • Supported: Data Transformations

Platform Data Modeling Features

  • Supported: Multiple Model Development Languages and Tools
  • Supported: Automated Machine Learning
  • Supported: Single platform for multiple model development
  • Supported: Self-Service Model Delivery

Model Deployment Features

  • Supported: Flexible Model Publishing Options
  • Supported: Security, Governance, and Cost Controls

KNIME Analytics Platform Screenshots

Screenshot of the KNIME Modern UI. This is the the new user interface for the KNIME Analytics Platform that is available with improved look and feel as the default interface, from KNIME Analytics Platform version 5.1.0 release.Screenshot of the KNIME Analytics Platform user interface - the KNIME Workbench - displays the current, open workflow(s). Here is the general user interface layout — application tabs, side panel, workflow editor and node monitor.Screenshot of the KNIME user interface elements — workflow toolbar, node action bar, rename components and metanodes.Screenshot of the entry page, which is displayed by clicking the Home tab. From here users can; check out example workflows to get started, access a local workspace, or even start a new workflow by clicking the yellow plus button.Screenshot of the status of a KNIME node, which shows whether it's configured, not configured, executed, or has an error.Screenshot of the KNIME node action bar, which can be used to configure, execute, cancel, reset, and - when available - open the view.Screenshot of the common node port types. Nodes can have multiple input ports and multiple output ports. A collection of interconnected nodes, using the input ports on the left and output ports on the right, constitutes a workflowScreenshot of the three ways nodes can be added to the workflow canvas; drag & drop, double click on the node in the node repository, or drop a connection into an empty area to display the quick nodes adding panel.Screenshot of how to set a workflow coach preferences.Screenshot of replacing a node into the workflow editor via drag & drop.Screenshot of the annotation field of a node, which is helpful for explainability and documenting of a workflow.Screenshot of the annotation function, which is helpful for explainability and documenting of a workflow.Screenshot of the space explorer, which is where users can manage workflows, folders, components, and files in a space, either local or remote on a KNIME Hub instance.Screenshot of the node repository, which is where currently installed nodes are available. Here, users can search for and then add a node from the repository into the workflow editor by drag & drop.Screenshot of the node monitor. This is located on the bottom part of the workbench and is especially useful to inspect intermediate output tables in the workflow.Screenshot of the KNIME Business Hub teams view. Resources can be owned by a team (e.g. spaces & the contained workflows, files, or components) so that team members can access these resources.Screenshot of the KNIME Collections view. Upskill users by providing selected workflows, nodes, and links about a specific, common topic.Screenshot of the KNIME Business Hub versioning. Track changes to workflows easily and in a transparent way.Screenshot of the KNIME Business Hub deployment options. After a workflow is uploaded to KNIME Hub different type of deployments can be created. For example: a Data App, schedule, API service, or trigger.Screenshot of the KNIME Business Hub Data Apps Portal. This page is available to every registered user. Consumers, for example, can access to this page to see all the data apps that have been shared with them, execute them at any time, interact with the workflow via a user interface, without the need to build a workflow or even know what happens under the hood.

KNIME Analytics Platform Videos

a short animated video, on how Katie uses KNIME to make sense of data within her organization.
the recap of the Fall Summit 2022, where the community discusses what they love most about KNIME.

KNIME Analytics Platform Technical Details

Deployment TypesOn-premise, Software as a Service (SaaS), Cloud, or Web-Based
Operating SystemsWindows, Linux, Mac
Mobile ApplicationNo
Supported CountriesGlobal
Supported LanguagesEnglish

Frequently Asked Questions

KNIME enables users to analyze, upskill, and scale data science without any coding. The platform that lets users blend, transform, model and visualize data, deploy and monitor analytical models, and share insights organization-wide with data apps and services.

KNIME Analytics Platform starts at $0.

Alteryx, Dataiku, and Qlik Sense are common alternatives for KNIME Analytics Platform.

Reviewers rate Extend Existing Data Sources highest, with a score of 10.

The most common users of KNIME Analytics Platform are from Enterprises (1,001+ employees).
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Comparisons

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Reviews and Ratings

(66)

Reviews

(1-5 of 18)
Companies can't remove reviews or game the system. Here's why

An incredibly comprehensive and powerful data analytics platform that is somehow free

Rating: 10 out of 10
October 17, 2023
RB
Vetted Review
Verified User
KNIME Analytics Platform
6 years of experience
There are two aspects which put KNIME Analytics Platform ahead of other products. Firstly the fact that KNIME Analytics Platform comes at no cost and no restrictions on its use is an instant winner for any organisation wanting to democratise their data. It means that a client is free to install it on as many machines as they wish without worrying about costs, the number of seats required or payment models or procurement negotiation. It also means that we are not building costs into our clients business.

Secondly, KNIME Analytics Platform has a very comprehensive set of tools for importing/exporting data, data manipulation and data science. Some products offer analytics packages on top of their base offering at additional cost and they are still not as comprehensive as what you get with KNIME Analytics Platform for free. For some types of analysis you may require to download additional packages with KNIME Analytics Platform, but its invariably at no cost, those packages are kept out of the main download to keep the size down. Due to the easy integration with R and Python, I view KNIME Analytics Platform as also having the capabilities of those languages too. This has helped me in the past with seamlessly importing a rare filetype and using very specific models not directly available in KNIME Analytics Platform.

KNIME Analytics Platform Makes Life Easier and More Fun

Rating: 10 out of 10
September 19, 2023
MC
Vetted Review
Verified User
KNIME Analytics Platform
3 years of experience
  • SQLite is an easy to use SQL interface, but it is still SQL and not GUI like KNIME
  • Microsoft Excel as the advantage of being universally known, but when VBA code is needed for complex tasks it can become unstable and slow
  • Microsoft Access is an entry level DB that is easy to use and has a nice GUI. However, it gets really slow for large tables which we frequently work with. It craps out at about 500,000 records and 50 fields.

Value for money!

Rating: 10 out of 10
November 05, 2023
Vetted Review
Verified User
KNIME Analytics Platform
2 years of experience
Alteryx is a very similar product, almost all the things that are achievable in KNIME Analytics Platform can be done in Alteryx as well, but you have to pay for the Desktop version to conduct the analysis. But with KNIME Analytics Platform it is totally free and can be used anyone who wants to perform analysis on their own. Dataiku is also a very powerful product, but we felt there are two main disadvantages with Dataiku. Everything has to be done only on the server. There is no desktop version for Dataiku. This could be advantageous to some, but it isn't for us. The product is very expensive.

Empowering People

Rating: 9 out of 10
October 20, 2023
Vetted Review
Verified User
KNIME Analytics Platform
10 years of experience
As a commercial product Alteryx is more polished and can be even easier for a beginner, but KNIME beats Alteryx in functionality and performance. Dataiku takes the integration with Python and Git further than KNIME but isn't at the level of Alteryx and KNIME with its No Code/Low Code interface. In comparison to both Alteryx and Dataiku, KNIME is more versatile and significantly cheaper to deploy.
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