KNIME Analytics Platform vs. Wolfram Mathematica

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
KNIME Analytics Platform
Score 8.3 out of 10
N/A
KNIME enables users to analyze, upskill, and scale data science without any coding. The platform that lets users blend, transform, model and visualize data, deploy and monitor analytical models, and share insights organization-wide with data apps and services.
$0
per month
Mathematica
Score 8.2 out of 10
N/A
Wolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.
$1,520
per year
Pricing
KNIME Analytics PlatformWolfram Mathematica
Editions & Modules
KNIME Community Hub - Individual
$0
KNIME Community Hub - Team
From €250
per month Starts from 3 users
Standard Cloud
$1,520
per year
Standard Desktop
$3,040
one-time fee
Standard Desktop & Cloud
$3,344
one-time fee
Mathematica Enterprise Edition
$8,150.00
one-time fee
Offerings
Pricing Offerings
KNIME Analytics PlatformMathematica
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsDiscounts available for students and educational institutions. The Network Edition reduce per-user license costs through shared deployment across any number of machines on a local-area network.
More Pricing Information
Community Pulse
KNIME Analytics PlatformWolfram Mathematica
Top Pros
Top Cons
Features
KNIME Analytics PlatformWolfram Mathematica
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
KNIME Analytics Platform
9.1
19 Ratings
7% above category average
Wolfram Mathematica
-
Ratings
Connect to Multiple Data Sources9.619 Ratings00 Ratings
Extend Existing Data Sources10.010 Ratings00 Ratings
Automatic Data Format Detection9.019 Ratings00 Ratings
MDM Integration7.98 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
KNIME Analytics Platform
8.0
18 Ratings
5% below category average
Wolfram Mathematica
-
Ratings
Visualization8.018 Ratings00 Ratings
Interactive Data Analysis8.018 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
KNIME Analytics Platform
8.3
19 Ratings
1% above category average
Wolfram Mathematica
-
Ratings
Interactive Data Cleaning and Enrichment9.019 Ratings00 Ratings
Data Transformations9.419 Ratings00 Ratings
Data Encryption7.47 Ratings00 Ratings
Built-in Processors7.48 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
KNIME Analytics Platform
7.9
18 Ratings
7% below category average
Wolfram Mathematica
-
Ratings
Multiple Model Development Languages and Tools9.417 Ratings00 Ratings
Automated Machine Learning8.217 Ratings00 Ratings
Single platform for multiple model development9.218 Ratings00 Ratings
Self-Service Model Delivery5.08 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
KNIME Analytics Platform
7.3
11 Ratings
16% below category average
Wolfram Mathematica
-
Ratings
Flexible Model Publishing Options8.611 Ratings00 Ratings
Security, Governance, and Cost Controls5.94 Ratings00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Wolfram Mathematica
9.9
6 Ratings
16% above category average
Pixel Perfect reports00 Ratings9.84 Ratings
Customizable dashboards00 Ratings9.94 Ratings
Report Formatting Templates00 Ratings9.96 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Wolfram Mathematica
9.9
9 Ratings
21% above category average
Drill-down analysis00 Ratings9.98 Ratings
Formatting capabilities00 Ratings9.98 Ratings
Integration with R or other statistical packages00 Ratings9.97 Ratings
Report sharing and collaboration00 Ratings9.99 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Wolfram Mathematica
9.3
8 Ratings
11% above category average
Publish to Web00 Ratings9.97 Ratings
Publish to PDF00 Ratings9.08 Ratings
Report Versioning00 Ratings9.97 Ratings
Report Delivery Scheduling00 Ratings8.95 Ratings
Delivery to Remote Servers00 Ratings8.95 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Wolfram Mathematica
9.9
9 Ratings
19% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.99 Ratings
Location Analytics / Geographic Visualization00 Ratings9.98 Ratings
Predictive Analytics00 Ratings9.98 Ratings
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User Ratings
KNIME Analytics PlatformWolfram Mathematica
Likelihood to Recommend
9.6
(22 ratings)
9.9
(9 ratings)
Likelihood to Renew
9.4
(4 ratings)
-
(0 ratings)
Usability
9.0
(3 ratings)
-
(0 ratings)
Support Rating
9.0
(6 ratings)
9.5
(2 ratings)
Implementation Rating
7.0
(2 ratings)
-
(0 ratings)
Ease of integration
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
KNIME Analytics PlatformWolfram Mathematica
Likelihood to Recommend
KNIME
KNIME Analytics Platform is excellent for people who are finding Excel frustrating, this can be due to errors creeping in due to manual changes or simply that there are too many calculations which causes the system to slow down and crash. This is especially true for regular reporting where a KNIME Analytics Platform workflow can pull in the most recent data, process it and provide the necessary output in one click. I find KNIME Analytics Platform especially useful when talking with audiences who are intimidated by code. KNIME Analytics Platform allows us to discuss exactly how data is processed and an analysis takes place at an abstracted level where non-technical users are happy to think and communicate which is often essential when they are subject matter experts whom you need for guidance. For experienced programmers KNIME Analytics Platform is a double-edged sword. Often programmers wish to write their own code because they are more efficient working that way and are constrained by having to think and implement work in nodes. However, those constraints forcing development in a "KNIME way" are useful when working in teams and for maintenance compared to some programmers' idiosyncratic styles.
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Wolfram
We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.
Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.
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Pros
KNIME
  • Summarize instrument level financial data with relevant statistics
  • Map transactions from core extracts to groups of like transactions using rule engines
  • Machine learning using random forests and other techniques to analyze data and identify correlations for use in predictive models
  • Fill out sampling data from averages.
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Wolfram
  • It allows straightforward integration of analytic analysis of algebraic expressions and their numerical implemented.
  • Supports varying programmatic paradigms, so one can choose what best fits the problem or task: pure functions, procedural programming, list processing, and even (with a bit of setup) object-oriented programming.
  • The extensive and rich tools for graphical rendering make it very easy to not just get 2D and 3D renderings of final output, but also to do quick-and-dirty 2D and 3D rendering of intermediate results and/or debugging results.
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Cons
KNIME
  • 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.
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Wolfram
  • Should include more libraries and functions.
  • Should include more functions that can be used in Machine Learning.
  • Should include more functions that can be used in Data Science.
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Likelihood to Renew
KNIME
We are happy with Knime product and their support. Knime AP is versatile product and even can execute Python scripts if needed. It also supports R execution as well; however, it is not being used at our end
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Wolfram
No answers on this topic
Usability
KNIME
KNIME Analytics Platform offers a great tradeoff between intuitiveness and simplicity of the user interface and almost limitless flexibility. There are tools that are even easier to adopt by someone new to analytics, but none that would provide the scalability of KNIME when the user skills and application complexity grows
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Wolfram
No answers on this topic
Support Rating
KNIME
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.
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Wolfram
Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.
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Implementation Rating
KNIME
KNIME Analytics Platform is easy to install on any Windows, Mac or Linux machine. The KNIME Server product that is currently being replaced by the KNIME Business Hub comes as multiple layers of software and it took us some time to set up the system right for stability. This was made harder by KNIME staff's deeper expertise in setting up the Server in Linux rather than Windows environment. The KNIME Business Hub promises to have a simpler architecture, although currently there is no visibility of a Windows version of the product.
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Wolfram
No answers on this topic
Alternatives Considered
KNIME
Having used both the Alteryx and [KNIME Analytics] I can definitely feel the ease of using the software of Alteryx. The [KNIME Analytics] on the other hand isn't that great but is 90% of what Alteryx can do along with how much ease it can do. Having said that, the 90% functionality and UI at no cost would be enough for me to quit using Alteryx and move towards [KNIME Analytics].
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Wolfram
We have evaluated and are using in some cases the Python language in concert with the Jupyter notebook interface. For UI, we using libraries like React to create visually stunning visualizations of such models. Mathematica compares favorably to this alternative in terms of speed of development. Mathematica compares unfavorably to this alternative in terms of license costs.
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Return on Investment
KNIME
  • It is suited for data mining or machine learning work but If we're looking for advanced stat methods such as mixed effects linear/logistics models, that needs to be run through an R node.
  • Thinking of our peers with an advanced visualization techniques requirement, it is a lagging product.
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Wolfram
  • Easy to solve huge mathematical equations, so it saved time there
  • Doing analysis and plotting graphs is also another plus point
  • Learning is very slow, and it took lot of time to learn its scripting language
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ScreenShots

KNIME Analytics Platform Screenshots

Screenshot of the KNIME Modern UI. This is the the new user interface for the KNIME Analytics Platform that is available with improved look and feel as the default interface, from KNIME Analytics Platform version 5.1.0 release.Screenshot of the KNIME Analytics Platform user interface - the KNIME Workbench - displays the current, open workflow(s). Here is the general user interface layout — application tabs, side panel, workflow editor and node monitor.Screenshot of the KNIME user interface elements — workflow toolbar, node action bar, rename components and metanodes.Screenshot of the entry page, which is displayed by clicking the Home tab. From here users can; check out example workflows to get started, access a local workspace, or even start a new workflow by clicking the yellow plus button.Screenshot of the status of a KNIME node, which shows whether it's configured, not configured, executed, or has an error.Screenshot of the KNIME node action bar, which can be used to configure, execute, cancel, reset, and - when available - open the view.