--- description: Review of KNIME Analytics Platform Software: system overview, features, price and cost information. Get free demos and compare to similar programs on Software Advice Ireland. image: https://gdm-localsites-assets-gfprod.imgix.net/images/software_advice/og_logo-55146305bbe7b450bea05c18e9be9c9a.png title: KNIME Analytics Platform | Reviews, Pricing & Demos - SoftwareAdvice IE --- Breadcrumb: [Home](/) > [Business Intelligence Platform](/directory/4336/bi/software) > [KNIME Analytics Platform](/software/85226/knime-analytics-platform) # KNIME Analytics Platform Canonical: https://www.softwareadvice.ie/software/85226/knime-analytics-platform Page: 1 / 2\ Next: [Next page](https://www.softwareadvice.ie/software/85226/knime-analytics-platform?page=2) > KNIME empowers all data users to build, collaborate, and upskill on data science. KNIME offers complete 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. They can spend time where it matters because 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, all 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 instant 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 an intuitive data app UI \* Easily 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. KNIME 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 > > Verdict: Rated **4.6/5** by 25 users. Top-rated for **Likelihood to recommend**. ----- ## Quick Stats & Ratings | Metric | Rating | Detail | | **Overall** | **4.6/5** | 25 Reviews | | Ease of Use | 4.5/5 | Based on overall reviews | | Customer Support | 3.9/5 | Based on overall reviews | | Value for Money | 4.7/5 | Based on overall reviews | | Features | 4.4/5 | Based on overall reviews | | Recommendation percentage | 90% | (9/10 Likelihood to recommend) | ## About the vendor - **Company**: KNIME.COM - **Location**: Zurich, Switzerland ## Commercial Context - **Starting Price**: €0.00 - **Pricing model**: (Free version available) - **Pricing Details**: KNIME Analytics Platform is free and open source. - **Target Audience**: Self Employed, 2–10, 11–50, 51–200, 201–500, 501–1,000, 1,001–5,000, 5,001–10,000, 10,000+ - **Deployment & Platforms**: Cloud, SaaS, Web-based, Mac (Desktop), Windows (Desktop), Linux (Desktop), Linux (On-Premise) - **Supported Languages**: English - **Available Countries**: Afghanistan, Albania, Algeria, American Samoa, Andorra, Angola, Anguilla, Antigua & Barbuda, Argentina, Armenia, Aruba, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium and 208 more ## Features - AI/Machine Learning - API - Access Controls/Permissions - Ad hoc Query - Ad hoc Reporting - Alerts/Notifications - Auditing - Big Data Analytics - Business Rules Management - Collaboration Tools - Configurable Workflow - Customisable Branding - Customisable Reports - Customisable Templates - Dashboard - Dashboard Creation - Data Blending - Data Classification - Data Clustering - Data Connectors ## Integrations (26 total) - Amazon Aurora - Amazon Comprehend - Amazon DynamoDB - Amazon EMR - Amazon S3 - Apache Hive - Azure Blob Storage - Azure Data Lake Storage - Azure Databricks - Azure Synapse Analytics - ChatGPT - Cloudera Enterprise - Databricks - Google Cloud Storage - Google Sheets ... and 11 more integrations ## Support Options - Email/Help Desk - FAQs/Forum - Knowledge Base - Phone Support ## Category - [Business Intelligence Platform](https://www.softwareadvice.ie/directory/4336/bi/software) ## Related Categories - [Business Intelligence Platform](https://www.softwareadvice.ie/directory/4336/bi/software) - [Machine Learning Software](https://www.softwareadvice.ie/directory/4358/machine-learning/software) - [Predictive Analytics Software](https://www.softwareadvice.ie/directory/481/predictive-analytics/software) - [Manufacturing BI Software](https://www.softwareadvice.ie/directory/3828/manufacturing/software) ## Alternatives 1. [OpenText Analytics Cloud](https://www.softwareadvice.ie/software/415497/opentext-magellan) — 5.0/5 (1 reviews) 2. [Tableau](https://www.softwareadvice.ie/software/1940/tableau) — 4.6/5 (2348 reviews) 3. [Domo](https://www.softwareadvice.ie/software/5822/domo) — 4.3/5 (329 reviews) 4. [JMP](https://www.softwareadvice.ie/software/103067/jmp) — 4.5/5 (53 reviews) 5. [Lumenore](https://www.softwareadvice.ie/software/73339/lumenore) — 4.8/5 (11 reviews) ## Reviews ### "Well created open source for data analysis\!" — 5.0/5 > **Rochelle** | *28 January 2023* | Information Technology & Services | Recommendation rating: 10.0/10 > > **Pros**: One of the pros is of course doesn't require license fee. It is also an open source that can connect to Python and R that is capable of customization. Need to mention also the good community support. > > **Cons**: It took time to understand the functionalities and familiarize the user interface. ----- ### "Data Science 101 Platform for non-IT people" — 4.0/5 > **Ferhat** | *25 January 2020* | Information Technology & Services | Recommendation rating: 7.0/10 > > **Pros**: - Its ease of use makes it possible for non-IT, non-developer, non-CS background people to make data manipulation, preprocessing, mining, visualization and modelling. - It has a graphical interface with nodes and connections so that you don't need to know Python/R to make predictive models or association rules/recommendation systems. - There's a vast library of functions - Even more functions are created by the community so non-existing customized functions are created by the community, via existing functions. - The visual flow of data makes it easy to understand and interpret it. - It teaches the CRISP-DM methodology in an intuitive way thanks to its graphical user interface - It can connect to SQL and similar servers so that the data can be read directly. - It is possible to write own Python/R script for custom needs. > > **Cons**: - Custom needs are hard to carry out. - Functions have limited abilities and parameters - Data visualization is weak and relatively primitive - Model development is easy but deployment is hard - It is very slow unfortunately and I think this is KNIME's most important drawback > > It was the tool I learned the Data Science in the first place. So it is really good and intuitive with its graphical interface. For example you understand train-test split very well because you literally see the split as you work on it. As I progressed and needed more functions and more custom solutions, I started using Python scripts and solved it like that. So it gave me all these abilities. ----- ### "Solid Platform for Small Datasets and Broad Data Connectivity" — 4.0/5 > **Verified Reviewer** | *1 May 2020* | Health, Wellness & Fitness | Recommendation rating: 6.0/10 > > **Pros**: There is a wide range of tools to process and prep data in the platform natively and additional tools that can be download within the platform. The ability to customize the settings for most of the tools allows the user to adjust the output. Even more technical settings, like hyperparameter tuning, can be done in the tool UI. There are numerous input and output options and types. > > **Cons**: Pulling in very basic files, like Excel spreadsheets can be a bit challenging where other platforms handle files with ease. Also, database connections are not seamless. The Java memory errors also limit the size of data that can be processed without making manual adjustments to settings. Lastly, not being a cloud-based platform, processing big data is very time-consuming. > > The two main reasons we used KNIME were to process and prep data, then to conduct machine learning by training models and processing predictions. KNIME is great with data prep and blend as long as the data set is small to medium in size (\< 4GB). There were areas where we struggled and that was when models were more complex (\> 50 variables) and being able to deploy and schedule jobs. We had to download JDBC drivers for our database connections, which was not something we had to do with other platforms. ----- ### "Great for all types of data scientists" — 5.0/5 > **Verified Reviewer** | *26 September 2020* | Higher Education | Recommendation rating: 9.0/10 > > **Pros**: Some drag and drop tools for machine learning are really limited, but KNIME is not. There are a ton of capabilities of the tool that are built in, and there are even more that are available online, like AutoML. It gives citizen data scientists the ability to create good models without knowing a programming language, and it increases the bandwidth of actual data scientists by allowing them to easily create more models and experiments. > > **Cons**: Of course, it is more limited than a programming language, and if you're familiar with building models programmatically, there is a learning curve that will slow you down and limit you at first. > > I have had a very positive experience with KNIME and like it a lot more than other drag and drop machine learning tools I have tried out. ----- ### "Using KNIME for reporting" — 5.0/5 > **Sasha** | *12 January 2024* | Information Technology & Services | Recommendation rating: 8.0/10 > > **Pros**: KNIME allowed me to pull data from large google sheets and manipulate them in a clear and easy way. The visual representation of each node makes it really easy to use and understand even for people without a background in data analytics. The KNIME website also provides a lot of resources on using the platform > > **Cons**: Very large google sheets containing a lot of data cannot always be extracted due to the size. > > Good and would recommend to non technical professionals as well ----- Page: 1 / 2\ Next: [Next page](https://www.softwareadvice.ie/software/85226/knime-analytics-platform?page=2) ## Links - [View on SoftwareAdvice](https://www.softwareadvice.ie/software/85226/knime-analytics-platform) ## This page is available in the following languages | Locale | URL | | de | | | en | | | en-AU | | | en-GB | | | en-IE | | | en-NZ | | | fr | | ----- ## Structured Data