KNIME Reviews & Product Details

As a Data Engineer, I like KNIME because it makes data workflows simple with its drag-and-drop approach. I use it for data ingestion, cleaning, transformation, joining, and analysis from different sources such as CSVs, databases, and APIs. The visual workflows make it easy to track data flow and identify issues like duplicates or missing data. I also like that I can use SQL or Python when needed, while keeping everything organized in one workflow. Overall, KNIME saves time and makes data engineering tasks easier to manage. Review collected by and hosted on G2.com.

Large workflows can become difficult to manage when there are many nodes. Review collected by and hosted on G2.com.

The best thing about KNIME is that it makes data analysis simple and easy. It allows me to build workflows with less coding. It helps connect and process data from different sources. It provides useful tools for data cleaning and analysis. It also makes it easy to create charts and reports. It also helps me organize complex data tasks in one place. KNIME saves time and helps me work with data more efficiently. Review collected by and hosted on G2.com.

The least helpful thing about KNIME is that it can feel a little complex at first. Some workflows can become difficult to manage when they get very large. It may also take some time to learn all the available tools. Sometimes, finding the right node for a task can be confusing. Overall, it is useful, but beginners may need some time to get comfortable with it. Review collected by and hosted on G2.com.

KNIME is free to use and open source, available both on Mac & PC. It is able to handle large amounts of data from various sources. I'm a former Alteryx user who switched from corporate consulting (which could afford Alteryx) to a Mac OS based non-profit. KNIME allowed me to apply my skillset without costing the organization large fees or subscriptions to do data management, analysis, and visualization.

I was able to use KNIME to take data from Google Drive, local CSVs, and make API calls all using the simple drag & drop interface. The ability to visually see data flows, especially checking drops or duplications when doing joins, was incredibly helpful. Even more so, the visual component allowed me to walk through the data process with non-technical audiences to show how the data was being transformed and show in real time any data errors.

The KNIME AI feature is a nice to have, especially if you are learning. It helps troubleshoot quick syntax related issues or can help build simple workflows. Review collected by and hosted on G2.com.

A benefit yet also a con of KNIME is how prescriptive each of its nodes tend to be; for example in Alteryx you would have a "Select" tool that would allow you to rename a field, drop fields, and change field types all in one tool. In KNIME, each of those actions requires a different node (column renamer, column filter, string to number etc.) which while may be helpful for transparency, requires additional actions and longer workflows.

KNIME has yet to implement in its modern UI an 'autosave' feature which was available in its classic version. The lack of autosave sometimes results in painful rework due rare, but occurring, instances of workflows freezing/ becoming unresponsive. Review collected by and hosted on G2.com.

What I like best is KNIME's no-code, drag-and-drop approach, which makes it accessible to anyone interested in analytics, regardless of coding background. It also covers the entire analytics maturity spectrum — from basic descriptive analytics to advanced and agentic AI, all within a single tool. That means there's only one platform to learn, and it's both easy to pick up and COMPLETELY FREE, which lowers the barrier to entry enormously for individuals and organizations alike. Review collected by and hosted on G2.com.

Building visually polished data apps isn't very intuitive — it takes more effort than it should. Review collected by and hosted on G2.com.

As an experienced Internal Audit Manager, regional data analytics community contributor, and data analytics trainer, I confidently consider KNIME one of the best tools for Auditing, Accounting & Finance, Risk, and Compliance (AAFRC) professionals.

The most helpful feature is its visual workflow approach, which provides a clear end-to-end view of the entire analytical process. This makes analyses transparent, easy to review, and highly auditable.

Key upsides include the ability to efficiently analyze multiple subgroups using looping nodes and identify anomalies using outlier detection techniques. KNIME also requires little to no coding to get started, allowing professionals to focus on insights rather than programming.

In my experience, KNIME has significantly improved the efficiency and effectiveness of my audit projects, enabling broader testing, better risk identification, and higher productivity. Review collected by and hosted on G2.com.

No significant downsides from my experience. KNIME provides strong value through its visual workflows, automation, flexibility, and ability to improve analytical efficiency. Review collected by and hosted on G2.com.

I can't imagine better way to troubleshoot a workflow than what KNIME Business Hub provides. You literally see your workflow on KBH (in web browser) like in the desktop app where you've designed it - with errors and warnings generated during the execution. So easy! Review collected by and hosted on G2.com.

Variable Loop End has a kink that costed me some headache - order of flow variables is important apparently. But that's a minor thing only. Review collected by and hosted on G2.com.

KNIME stands out as a truly versatile open-source platform that empowers users to perform complex data analysis and develop AI solutions without writing code. Its visual workflow interface significantly lowers the barrier for non-programmers while still providing advanced extensibility for experts. KNIME integrates well with Python, R, and popular machine learning libraries, enabling seamless end-to-end development from data preparation to model deployment. The platform’s community, extensible ecosystem, and commitment to openness make it an invaluable tool for data professionals across industries Review collected by and hosted on G2.com.

While KNIME provides powerful functionality, the initial learning curve can be challenging for users unfamiliar with data science concepts or visual programming. Some integrations, especially with external APIs or cloud services, may require additional configuration or third-party extensions. Nonetheless, the documentation and community support largely mitigate these limitations. Review collected by and hosted on G2.com.

The workflow operation with the ability to create meta-nodes and comment within the workflow. Everything is in one place, allowing complexity to be hidden while remaining accessible. True no-code/low-code with no limits. Perfectly integrates with Big Data tools or industrial models (Kafka, RabbitMQ). Very quick to learn and implement. The integrated AI is a good support, and the available nodes allow for developing powerful models step by step. Completely free with no limitations other than deployment. Quite efficient to replace R or Python scripts, Excel macros. The ability to just copy-paste branches or start a new one from anywhere allows for working along the lines of creativity. Review collected by and hosted on G2.com.

Not enough graphical nodes (typically plotly graphs) natively yet. It wouldn't be complicated to add and would bring a lot for data mining. Fortunately, you can create a Python component once and then reuse it as a classic node (so without coding) and share it with colleagues. Review collected by and hosted on G2.com.

KNIME stands out for its intuitive visual interface that makes building data workflows straightforward, even for users with limited coding experience. The drag and drop UI is clean, well organised, and easy to navigate, which reduces the learning curve while still supporting advanced users through Python, R, SQL, and other integrations.

The platform performs reliably when handling large datasets and complex workflows, and its automation capabilities save significant time on repetitive tasks. I also appreciate the growing AI and machine learning features, which make it easier to build predictive models and integrate intelligent data processing into workflows.

From a value perspective, KNIME offers an excellent return on investment, especially considering the capabilities available in its free version and the scalability of its enterprise offerings. The documentation, tutorials, and community resources make onboarding smooth, while the support ecosystem helps users quickly resolve issues and learn best practices. Overall, KNIME is a flexible, powerful, and cost effective platform for data analytics, automation, and AI driven workflows. Review collected by and hosted on G2.com.

While KNIME is a powerful platform, the interface can feel overwhelming for new users because of the large number of available nodes and configuration options. Some complex workflows may also become difficult to manage visually as they grow in size.

Performance can slow down when processing very large datasets or highly complex workflows, especially on systems with limited resources. Although the platform integrates well with many tools, configuring certain enterprise or third party integrations can require additional technical knowledge.

I would also like to see more AI assisted workflow creation, smarter recommendations during workflow development, and a more modern interface in some areas. Improving these aspects would make the platform even more accessible and efficient for both beginners and experienced users. Review collected by and hosted on G2.com.

I use KNIME Software to build visual, low-code data workflows, which makes data cleaning, analysis, and machine learning tasks much easier. It's great for RPA-style automation because I can chain repetitive tasks and avoid manual work. I like that I can create reusable workflows with KNIME that keep everything consistent and help reduce manual mistakes. The visual workflow builder is fantastic because it's easy to see exactly what's happening at each step, and I don't have to rewrite an entire script if I need to update something—I just modify the workflow. It really simplifies understanding and troubleshooting my process, allowing me to quickly identify what needs to be changed without sifting through long scripts. Review collected by and hosted on G2.com.

The interface can feel overwhelming at first because there are so many nodes and configuration options. It takes some time to understand the best way to structure workflows, especially if you are new to the platform. The onboarding experience could be improved with more guided tutorials, sample end-to-end workflows, and more interactive walkthroughs. This would make it much easier to get comfortable with the platform without having to rely on external tutorials heavily. The main challenge was understanding how different nodes work and how to design efficient workflows. Review collected by and hosted on G2.com.