KNIME Analytics Platform Reviews

32 Ratings
<a href='' target='_blank' rel='nofollow noopener noreferrer'>trScore algorithm: Learn more.</a>
Score 7.8 out of 100

Do you work for this company? Manage this listing

Overall Rating

Reviewer's Company Size

Last Updated

By Topic




Job Type


Reviews (1-9 of 9)

Ivan Cui | TrustRadius Reviewer
July 01, 2020

KNIME Review from a daily user

Score 7 out of 10
Vetted Review
Verified User
Review Source
My team uses KNIME Analytics Platform to build a variety of Data Science Pipelines. These KNIME workflows are then published through KNIME Server that can help hosting a front end for our end users across many different organizations. The KNIME workflows that we built have many different capabilities, ranging from data extraction, pre-processing, model training and optimization. We also build some self-services analytics platform using KNIME as well as automation tools.
  • Easy to use without much knowledge of coding.
  • Connection to other languages such as JS, R, Python, etc.
  • Workflow is displayed as connected nodes which makes it easy to troubleshoot and visualize.
  • Open-source.
  • Have a decent size community that supports Q&A.
  • Execution on other programming languages is slow.
  • Workflows are very big even building a very simple one due to caching and GUI.
  • Can frequently stop working and quit unexpectedly.
If you have a team of engineers or data scientists who do not like to code, KNIME can be a good platform to build quick and dirty pipelines. However if you are moving away from R&D to deployment, KNIME lacks the scalability compared to Python or R itself. When deploying, you can choose to output json or use their native front end from KNIME Server, but KNIME Server is not free.
KNIME's HQ is in Europe, which makes it hard for US companies to get customer service in time and on time. Their customer service also takes on average 1 to 2 weeks to follow up with your request. KNIME's documentation is also helpful but it does not provide you all the answers you need some of the time.
Read Ivan Cui's full review
Christopher Penn | TrustRadius Reviewer
June 29, 2020

KNIME: Great value, great compatibility

Score 7 out of 10
Vetted Review
Verified User
Review Source
KNIME is used as a bridge piece of software that connects multiple, disparate data sources into a single data pipeline for further analysis downstream. Some level of transformation is done in the processing, mainly for data cleansing, but most of that is left to custom code further on in the pipeline.
  • Connection to multiple data sources.
  • Unified interface for data and cleansing.
  • Cross platform interoperability.
  • Cumbersome UI.
  • Slow to load.
  • Memory/CPU hog.
KNIME is well suited for the data analyst that has multiple disparate data sources and needs to unify them, with a price point that is lower than some other enterprise packages. It's less well suited for smaller data pipelines or pipelines where a ton of custom coding and modification needs to be made.
Good support from the user community, including recipes and templates.
Read Christopher Penn's full review
Viktor Mulac | TrustRadius Reviewer
January 22, 2020

Consultant's best (free) friend

Score 8 out of 10
Vetted Review
Verified User
Review Source
I have used KNIME for advanced data analytics and experiments in the AI (machine learning) area. I have also used this platform for running client data analysis in sourcing and sales areas, including running of prediction models.
This is a framework that allows you to start with simple tasks and gradually increase the analysis complexity.
After going repeatedly through several data sources with tons of data, the painful part has always been preparing and transforming the raw data for analysis. This can be automated and the data acquisition model can be saved and run repeatedly, saving a lot of time. Data cleansing and blending of tables is easy here. It also supports formats as JSON, XML, a quite frequent format nowadays.

Above all the platform and community is wide with hundreds of add-on modules. Frequently, someone has already solved a similar task as you. Before trying to model anything from scratch, it is a good idea to skim through modules and hopefully you can find a good one to use. And finally, it supports simple as well as complex analytics, including AI algorithms.
  • Great UX interface, easy connection of data sources, good handling of the analytical model, easy to modify.
  • It provides good level of control of what happens with your data in each step.
  • Great tool from data preprocessing, from analysis to visualization.
  • Great community and a lot of modules to reuse.
  • Supports machine learning - it is easy to configure and run.
  • It is Open Source!
  • If you are familiar with Python, you can use this easy programming language to add additional functions to your analytical model.
  • Automation - e.g. RapidMiner Studio provides a Turbo Prep function, where one can get to working on models more quickly (RapidMiner is not open source though)
  • KNIME does not replace a regular reporting tool - it is not meant to. However, if I have already spent some time developing a data acquisition and analytical model, it would be nice to be able to deploy, for example, a monitoring or reporting module that would process data autonomously and react accordingly.
If you are searching for a tool with a low total cost of ownership (TCO), that is easy to understand, and that comprises many prepared modules, KNIME is great. The tool is very intuitive with a lot of examples to learn. You can find a bit better tools, like RapidMiner Studio, but this is a paid, commercial solution. Yes, you can get a free RapidMiner license to process up to 50,000 lines of data, but this is not sufficient for serious work. Most of my use cases today require a bigger license, so KNIME is an attractive alternative price-wise.
Read Viktor Mulac's full review
Anonymous | TrustRadius Reviewer
January 22, 2020

Easy to use Intuitive Data Analytics platform for non - CS people

Score 8 out of 10
Vetted Review
Verified User
Review Source
KNIME Analytics Platform is actively used as the Predictive Analytical tool in the whole organization across departments in all domains, from production to sales to marketing to IT. We already had reporting tools, ETL tools, visualization tools but a friendly, relatively easy to use with no programming knowledge was required to disseminate Predictive Analytics across the organization. KNIME Analytics Platform was chosen for this because anyone can use it with a little bit of training, and it does not require Computer Science knowledge/background. It is used to create a predictive model for various business domains and kinds of models, such as classification, regression, and clustering.
  • Graphical UI
  • Ease of Use
  • Speed: It works slow, especially the opening.
  • Degree of freedom and customization in default nodes.
KNIME Analytics Platform is best suited for an introduction to Data Science/Data Analytics. Since this area requires a somewhat computer science background because of data reading, retrieving, handling, preprocessing, model development, deployment is all carried out in some programming languages, and it is hard for a non-CS major to do these without knowing Python/R. This is where the KNIME Analytics Platform becomes handy. It contains graphical, drag-drop nodes that do these for you with no coding. Nodes are connected with one's output being another's input, as a workflow. Therefore end-to-end pipeline can be built with no coding. It also enables newcomers to the profession to follow up on what's going on in the pipeline, makes it easier to troubleshoot/debug, because it is very visual and intuitive. However, when high customization, sophisticated models, and speed is needed. KNIME Analytics Platform is less flexible and slow. So it is best for non-CS people, the business units.
Since it is relatively new, there has not developed a vast previously asked/frequently asked questions library that comes up when you google an issue you come across with. This will happen only in time, and as the community grows. Because of the same reason, the community is not big. Consequently, it is possible not to receive good, fast responses to asked questions in community hubs and forums.
Read this authenticated review
Anonymous | TrustRadius Reviewer
October 04, 2019

Knime, your one-stop-ETL-software-shop

Score 8 out of 10
Vetted Review
Verified User
Review Source
KNIME is used across the entire business. We primarily use it as an ETL tool and to act as the input for other BI software such as Tableau and QlikView. KNIME is also used for initial machine learning functions.
  • KNIME works better than most tools for ETL functions.
  • Easy to track the different steps
  • Easy to isolate and fix specific workflow steps.
  • It does not have proper visualization.
  • Some other BI tools (QlikView) have much easier functions for data interaction.
  • Some other BI tools (Tableau) can be set up much faster.
  • It is not an easy tool to use for non-tech savvy staff.
KNIME is quite useful for initial data exploration and to share and discuss your process (workflow) with someone that does not how KNIME works. KNIME's visualisation tools can not be compared to most BI tools, because of the limited amount of available charts.
I've only interacted with KNIME support once before and the problem was resolved in a reasonable time.
Read this authenticated review
Rohit Narang | TrustRadius Reviewer
March 25, 2019

KNIME blended With R skills Is a great GUI Based Analytics & Mining Tool, Specially for Advanced Statistical Usage

Score 9 out of 10
Vetted Review
Verified User
Review Source
We use KNIME due to its high-value predictive analytics and its ability to find patterns as a data mining tool. Its risk analytics are used in our department for the development of new models and model validation using time series for low default portfolios. Primarily for creating univariate and multivariate analysis and finding statistical significance of variables, and further correlations with a blend of statistical procedures in the banking industry.
  • For non-programming based functional users, it's a blessing as it doesn't require coding, programming skills to perform data mining. The full desktop version of KNIME is free and open source, with no limit to data.
  • Connect to Open source: It also offers excellent integration with a wide range of other open source software such as Python, R, Spark, and even ImageJ for image analysis.
  • Great Integration of functionalities: We never move data between applications/platforms to complete the project. Raw data is easily ingested in the tool, processed, can be performed statistics, summarised and exported to various formats.
  • Visualization can be improved further though it has been better with new versions, with a lot of scope available. However, connectivity to Tableau somehow overcomes this. Also, skilled resources are difficult to find for KNIME, due to other solutions having better penetration.
  • Knowledge of R/Python is required to fully use the statistical analysis (rather than just data mining). Also, memory usage is a problematic issue sometimes.
  • Not enough domain usage experience can be shared between KNIME users as well.
It is well suited for organizations having day to day advanced statistical procedures requirements. We use ANOVA, multivariate regression using time series modeling and several calibrations in our models for periodic change due to agile macro-sensitive economic forecasts.
Read Rohit Narang's full review
Sergio Pulido Tamayo | TrustRadius Reviewer
August 07, 2018

KNIME Analytics Platform: the proof that open source can be the best

Score 10 out of 10
Vetted Review
Verified User
Review Source
We use KNIME across the whole organization. It is used to solve a wide range of business problems, from ETL and data integration, to advanced analytics and customer segmentation.
  • Connect to different data sources (uses JDBC)
  • Process large quantities of data
  • Integrate different machine learning frameworks and techniques
  • Use and integrate with cloud and big data environments
  • Does not have integration with Jupyter Notebooks
  • The tools for script writing and development are not easy to use or don't have many features
  • Memory usage is problematic some of the time
Perfect for training of non-expert users. It is well suited for any kind of analytics endeavor. It is appropriate for many information automation tasks.
Read Sergio Pulido Tamayo's full review
Anonymous | TrustRadius Reviewer
December 10, 2018

Knime for interactive training purposes

Score 8 out of 10
Vetted Review
Verified User
Review Source
KNIME has been used as a training tool for students to use. This program acts as a basic way for students with limited bioinformatic and computational skills to solve big data problems. The program has been used for simulated drug discovery training purposes.
  • Easy to use
  • Open source; extra programs can be added easily
  • User interface can be crowded at times
KNIME Analytics Platform is well suited as a training program for students from a variety of computation backgrounds. It integrates well many of the common chemical and biological programs and data files into one program that can then be used to process and sort large inventories.
Read this authenticated review
Anonymous | TrustRadius Reviewer
August 24, 2018

KNIME Analytics: Developer Review

Score 10 out of 10
Vetted Review
Verified User
Review Source
We use KNIME Analytics for our client (one of the Big Four). The use of this platform is for NLP related tasks. Specifically for Information Retrieval. It is used by a division within the organisation.
  • Text processing is easily performed by the various extensions within this platform
  • Integrates multiple languages like Python, R , Java etc. all in one place
  • Also provides many options for text parsing like CoreNLP, OpenNLP
  • Documentation is poor
  • The developers are mostly not native English speakers therefore their verbiage is sometimes ambiguous in the given examples
It is good for data ingestion given various formats. Thereafter more time can be dedicated to data analysis and other downstream tasks.
Read this authenticated review

Feature Scorecard Summary

Connect to Multiple Data Sources (6)
Extend Existing Data Sources (6)
Automatic Data Format Detection (6)
MDM Integration (6)
Visualization (6)
Interactive Data Analysis (6)
Interactive Data Cleaning and Enrichment (6)
Data Transformations (6)
Data Encryption (5)
Built-in Processors (6)
Multiple Model Development Languages and Tools (5)
Automated Machine Learning (5)
Single platform for multiple model development (5)
Self-Service Model Delivery (5)
Flexible Model Publishing Options (4)
Security, Governance, and Cost Controls (3)

About KNIME Analytics Platform

Swiss company KNIME offers their KNIME Analytics Platform for big data and predictive analytics.

KNIME Analytics Platform Technical Details

Operating Systems: Unspecified
Mobile Application:No