Anaconda vs. KNIME Analytics Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Anaconda
Score 8.6 out of 10
N/A
Anaconda provides access to the foundational open-source Python and R packages used in modern AI, data science, and machine learning. These enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness open-source for competitive advantage and research. Anaconda also provides enterprise-grade security to open-source software through the Premium Repository.
$0
per month
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
Pricing
AnacondaKNIME Analytics Platform
Editions & Modules
Free Tier
$0
per month
Starter Tier
$9
per month
Business Tier
$50
per month per user
Enterprise Tier
60.00+
per month per user
KNIME Community Hub - Individual
$0
KNIME Community Hub - Team
From €250
per month Starts from 3 users
Offerings
Pricing Offerings
AnacondaKNIME Analytics Platform
Free Trial
NoYes
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
AnacondaKNIME Analytics Platform
Considered Both Products
Anaconda
Chose Anaconda
Anaconda gives freedom to do anything with its packages, compared to other non-programming language-based softwares. It is almost possible to do anything with Anaconda. Anaconda brings ease of integrity because it is possible to integrate anything with a Python Py script, …
KNIME Analytics Platform
Chose KNIME Analytics Platform
Comparing the KNIME Analytics Platform to Anaconda and MATLAB, KNIME Analytics Platform's upsides are ease of use thanks to graphical interface and intuitiveness, no requirement of programming/coding and pre-existing nodes. Anybody can use it and create models even though …
Chose KNIME Analytics Platform
Alteryx is a very similar product, almost all the things that are achievable in KNIME Analytics Platform can be done in Alteryx as well, but you have to pay for the Desktop version to conduct the analysis. But with KNIME Analytics Platform it is totally free and can be used …
Chose KNIME Analytics Platform
As a commercial product Alteryx is more polished and can be even easier for a beginner, but KNIME beats Alteryx in functionality and performance. Dataiku takes the integration with Python and Git further than KNIME but isn't at the level of Alteryx and KNIME with its No …
Chose KNIME Analytics Platform
There are two aspects which put KNIME Analytics Platform ahead of other products. Firstly the fact that KNIME Analytics Platform comes at no cost and no restrictions on its use is an instant winner for any organisation wanting to democratise their data. It means that a client …
Chose KNIME Analytics Platform
KNIME Analytics Platform has a nice visualization comparing to Azure Machine Learning Studio. KNIME also has a good amount of built-in preprocessing nodes and ML training nodes that makes it easier to develop workflow instead of writing codes. However this also limits the …
Chose KNIME Analytics Platform
We need to use SAS/STAT package within SAS to use the advanced statistical functions, but KNIME has inbuilt libraries for the same. Also, the integration with Open source (Python, R, Java codes) allows better scalability & more availability of skilled resources to work upon.
Top Pros
Top Cons
Features
AnacondaKNIME Analytics Platform
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Anaconda
9.4
24 Ratings
11% above category average
KNIME Analytics Platform
9.1
19 Ratings
7% above category average
Connect to Multiple Data Sources9.722 Ratings9.619 Ratings
Extend Existing Data Sources8.923 Ratings10.010 Ratings
Automatic Data Format Detection9.621 Ratings9.019 Ratings
MDM Integration9.514 Ratings7.98 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Anaconda
9.2
24 Ratings
9% above category average
KNIME Analytics Platform
8.0
18 Ratings
5% below category average
Visualization9.624 Ratings8.018 Ratings
Interactive Data Analysis8.923 Ratings8.018 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Anaconda
9.4
25 Ratings
13% above category average
KNIME Analytics Platform
8.3
19 Ratings
1% above category average
Interactive Data Cleaning and Enrichment8.823 Ratings9.019 Ratings
Data Transformations9.625 Ratings9.419 Ratings
Data Encryption9.719 Ratings7.47 Ratings
Built-in Processors9.520 Ratings7.48 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Anaconda
9.3
23 Ratings
9% above category average
KNIME Analytics Platform
7.9
18 Ratings
7% below category average
Multiple Model Development Languages and Tools9.622 Ratings9.417 Ratings
Automated Machine Learning8.821 Ratings8.217 Ratings
Single platform for multiple model development8.923 Ratings9.218 Ratings
Self-Service Model Delivery9.618 Ratings5.08 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Anaconda
9.5
20 Ratings
10% above category average
KNIME Analytics Platform
7.3
11 Ratings
16% below category average
Flexible Model Publishing Options9.520 Ratings8.611 Ratings
Security, Governance, and Cost Controls9.519 Ratings5.94 Ratings
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AnacondaKNIME Analytics Platform
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User Ratings
AnacondaKNIME Analytics Platform
Likelihood to Recommend
9.5
(37 ratings)
9.6
(22 ratings)
Likelihood to Renew
7.0
(1 ratings)
9.4
(4 ratings)
Usability
9.0
(2 ratings)
9.0
(3 ratings)
Support Rating
8.9
(9 ratings)
9.0
(6 ratings)
Implementation Rating
-
(0 ratings)
7.0
(2 ratings)
Ease of integration
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
AnacondaKNIME Analytics Platform
Likelihood to Recommend
Anaconda
As a Data Analyst, it is my job to analyze large datasets using complex mathematical models. Anaconda provides a one-stop destination with tools like PyCharm, Jupyter, Spyder, and RStudio. One case where it is well suited is for someone who has just started his/her career in this field. The ability to install Anaconda requires zero to little skills and its UI is a lot easier for a beginner to try. On the other hand, for a professional, its ability to handle large data sets could be improved. From my experience, it has happened a lot that the system would crash with big files.
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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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Pros
Anaconda
  • It provides easy access to software like Jupyter, Spyder, R and QT Console etc.
  • Easy installation of Anaconda even without much technical knowledge.
  • Easy to navigate through files in Jupyter and also to install new libraries.
  • R Studio in Anaconda is easy to use for complex machine learning algorithms.
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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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Cons
Anaconda
  • Although I have generally had positive experiences with Anaconda, I have had trouble installing specific python libraries. I tried to remedy the solution by updating other packages, but in the end, things got really messed up, and I ended up having to uninstall and reinstall a total of about 4 times over the past 2 years.
  • If you have the free version of Anaconda, there is not much support. Googling questions and error messages are helpful, but there were times when I wished I would have been able to ask technical support to help me troubleshoot issues.
  • There were a few times when I tried to install tensorflow and tensorboard via Anaconda on a PC, but I could not get them to install properly. Anaconda allows you to create 'environments' , which allow you to install specific versions of python and associated libraries. You can keep your environments separate so they do not conflict with one another. Anyway, I ended up having to create several 'conda envrionments' just so I could use tensforflow/tensorboard and a few other utilities to avoid errors. This was somewhat annoying, because every time I wanted to run a specific model, I'd have to open up the specific conda environment with the appropriate python libraries.
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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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Likelihood to Renew
Anaconda
It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.
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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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Usability
Anaconda
The interface is an easy to use command-line interface, or a GUI for launching and/or discovering different parts of the system.
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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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Support Rating
Anaconda
Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.
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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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Implementation Rating
Anaconda
No answers on this topic
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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Alternatives Considered
Anaconda
ANACONDA VS Alteryx Analytics: Even though I find Alteryx to be an excellent tool for managing extremely massive data, Anaconda is much better and easy for analytics. Anaconda VS. MicroStrategy Analytics: Compared with Anaconda, MicroStrategy Analytics is very difficult to use and counter-intuitive Anaconda VS. Power BI For Office 365: One of the main advantages of BI for Office 364 is its capacity to data connectivity. However, it's very hard to edit data connections, once BI for Office is deployed in other platforms
Read full review
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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Return on Investment
Anaconda
  • Positive: Lower maintenance cost compared to other tools on the market
  • Positive: Ease in hiring professionals already accustomed to the tool in the job market
  • Positive: Projects are portable, allowing you to share projects with others and execute projects on different platforms, reducing deployment costs
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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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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.