
datarobot
Statista
Montecarlito
RapidMiner
IBM ILOG CPLEX Optimization Studio
Jupyter
Displayr
KNIME, the open platform for your data.

Celonis
Soroco Scout Platform
Software AG webMethods
Signavio Process Intelligence
QPR ProcessAnalyzer
Kofax Insight
PAFnow
Process mining and execution management software in the cloud that is simple and affordable.

Which is more popular?
Based on our record, KNIME should be more popular than UiPath Process Mining. It has been mentioned 2 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | knime.com | uipath.com |
| Pricing | ||
| Company | Startup from Switzerland · 50 - 99 employees | — |
| Listed in |
What each product offers, as listed by its team.


Possible disadvantages
Possible disadvantages
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
KNIME is particularly well-suited for data scientists, business analysts, and researchers who need to process, analyze, and visualize data efficiently without delving into extensive coding. It's an excellent option for organizations seeking a collaborative platform for team-based analytics projects and for those looking to incorporate advanced machine learning capabilities into their operations. Due to its adaptable nature and extensive support for various data sources and technologies, it's also ideal for enterprises and academic institutions with diverse data requirements.
No analysis of UiPath Process Mining yet.
Walkthroughs and reviews on video.
How often each product is chosen within a category, 0–100% relative to the other.


Share your experience with using KNIME and UiPath Process Mining. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


Knime Analytics Platform is an open-source Business Intelligence software that has been developed as an integration platform for creating analytical reports. It is a software that might be difficult for a novice to...
KNIME KNIME is an open-source tool that allows you to build or manipulate software to fit your company goals. KNIME is a free data analysis tool. KNIME is a valuable tool that is freely accessible and can be modified...
Some platforms are also available in free open source or community editions -- examples include Dataiku and H2O. Knime combines an open source analytics platform with a commercial Knime Server software package that...
We have no reviews of UiPath Process Mining yet. Be the first one to post
Recommendations tracked on public social media and blogs since March 2021.


I'd recommend to look into the free and open source KNIME tool (knime.com). It may not look easy to use right away, but if you stick with it for a little while and attend its learning guides, KNIME will grow on you. You can even have it... Source: about 3 years ago
That would cause a problem because ultimately this query will be scheduled to run multiple times a day on a KNIME server. Source: over 3 years ago
For your use case it sounds like you should be using UI Path instead. Source: over 3 years ago
When comparing KNIME and UiPath Process Mining, you can also consider the following products.

Become an AI-Driven Enterprise with Automated Machine Learning
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Celonis offers process mining tool for analyzing & visualizing business processes.
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The Statistics Portal for Market Data, Market Research and Market Studies
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Scout Platform is an artificial intelligence bases process mining and execution management software, helps large enterprises, Visualize their entire process in one place with interactive task maps that allow teams to work collaboratively.
Compare Soroco Scout Platform to KNIME or UiPath Process Mining:
MonteCarlito is a free Excel-add-in to do Monte-Carlo-simulations.
Compare Montecarlito to KNIME or UiPath Process Mining:

Software AG’s webMethods enables you to quickly integrate systems, partners, data, devices and SaaS applications
Compare Software AG webMethods to KNIME or UiPath Process Mining: