About KNIME Analytics Platform

KNIME Analytics Platform is an on-premise data analytics platform, which helps small to large businesses create and manage data science applications or services. The drag-and-drop interface allows users to create workflow prototypes, monitor performance and streamline in-data processing or distributed computing using Apache Spark framework. 

Key features of KNIME Analytics Platform include predictions, data cleaning, filtering, data model validation and reporting. Users can build machine learning models to automate data processes such as classification, dimensionality reduction, regression and cluster analysis, leveraging the use of artificial intelligence across operations.

Businesses can use KNIME Analytics Platform to integrate data from any s...


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Supported Operating System(s):

Windows 7, Windows Vista, Windows XP, Mac OS, Linux, Windows 2000, Windows 8, Windows 10

15 Reviews of KNIME Analytics Platform

Average User Ratings

Overall

4.53 / 5 stars

Ease-of-use

4.5

Value for money

4.5

Customer support

4.0

Functionality

4.5

Ratings Snapshot

5 stars

(8)

8

4 stars

(7)

7

3 stars

(0)

0

2 stars

(0)

0

1 stars

(0)

0

Likelihood to Recommend

Not likely

Very likely

Showing 1 - 5 of 15 results

August 2019

Yashoda from University of Jaffna

Verified Reviewer

Company Size: 1 employee

Industry: Program Development

Time Used: Less than 12 months

Review Source: Capterra


Ease-of-use

5.0

Value for money

5.0

Customer support

5.0

Functionality

5.0

August 2019

A Suitable software for Engineering Undergraduates

This is a good software which helps to solve statistical ptoblems,mathematical problems and also algorithm problems.so in Engineering there have lots of problems belongs to aforesaid kind of problems.so this can be useful for pre- Engineers.

Pros

This software gives most accurate answers and it has more sensitivity & most of values have precision.

Cons

sometimes error messages displaying while works are in progress

January 2020

Ferhat from Garanti BBVA

Company Size: 5,001-10,000 employees

Industry: Information Technology and Services

Time Used: More than 2 years

Review Source: Capterra


Ease-of-use

5.0

Value for money

3.0

Customer support

3.0

Functionality

3.0

January 2020

Data Science 101 Platform for non-IT people

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.

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

Reasons for Choosing KNIME Analytics Platform

Not only other options were very expensive and KNIME was free but also KNIME came with much more functionality, compared to other end-user packages.

May 2020

Anonymous

Verified Reviewer

Company Size: 5,001-10,000 employees

Time Used: Less than 12 months

Review Source: Capterra


Ease-of-use

3.0

Value for money

5.0

Customer support

2.0

Functionality

4.0

May 2020

Solid Platform for Small Datasets and Broad Data Connectivity

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.

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.

Reasons for Choosing KNIME Analytics Platform

In the end, we moved away from KNIME and chose Alteryx.

February 2021

Javvad from Zain Telecom

Company Size: 501-1,000 employees

Industry: Telecommunications

Time Used: Less than 12 months

Review Source: Capterra


Ease-of-use

4.0

Value for money

4.0

Customer support

2.0

Functionality

4.0

February 2021

KNIME for data analytics

Overall KNIME is a solid ETL tool which can automate most of the daily workflows.

Pros

The interface is user friendly, the modules are categorized and available for drag and drop on the workflow. Due to this, any complex workflow can be created. Like getting data from a DB, cleansing it, filtering it, blending it with another data source and reporting it is just a breeze in KNIME. Any changes required can be done on a specific module without the need to start from scratch.

Cons

In the field of geospatial data analysis, KNIME lags as there are no specialized modules for it, otherwise it gets the work done.

Reasons for Switching to KNIME Analytics Platform

Price

September 2020

Anonymous

Verified Reviewer

Company Size: 51-200 employees

Review Source: Capterra


Ease-of-use

4.0

Value for money

5.0

Functionality

4.0

September 2020

Great for all types of data scientists

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.

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.

Reasons for Choosing KNIME Analytics Platform

The pricing model for KNIME was better for us, because the free version includes a lot more than the others, and right now, helping clients get started for free and easily is the most important part to us.