DataRobot vs. KNIME Analytics Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
DataRobot
Score 8.2 out of 10
N/A
The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users AI to drive business outcomes, that is available on the user's cloud platform-of-choice, on-premise, or as a fully-managed service. The solutions include tools providing data preparation enabling users to explore and…N/A
KNIME Analytics Platform
Score 7.8 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
Pricing
DataRobotKNIME Analytics Platform
Editions & Modules
No answers on this topic
KNIME Community Hub Personal Plan
$0
KNIME Analytics Platform
$0
KNIME Community Hub Team Plan
€99
per month 3 users
KNIME Business Hub
From €35,000
per year
Offerings
Pricing Offerings
DataRobotKNIME Analytics Platform
Free Trial
YesNo
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
DataRobotKNIME Analytics Platform
Features
DataRobotKNIME Analytics Platform
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
DataRobot
-
Ratings
KNIME Analytics Platform
9.2
Ratings
10% above category average
Connect to Multiple Data Sources00 Ratings9.60 Ratings
Extend Existing Data Sources00 Ratings10.00 Ratings
Automatic Data Format Detection00 Ratings9.10 Ratings
MDM Integration00 Ratings7.90 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
DataRobot
-
Ratings
KNIME Analytics Platform
8.1
Ratings
3% below category average
Visualization00 Ratings8.00 Ratings
Interactive Data Analysis00 Ratings8.10 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
DataRobot
-
Ratings
KNIME Analytics Platform
8.3
Ratings
2% above category average
Interactive Data Cleaning and Enrichment00 Ratings9.00 Ratings
Data Transformations00 Ratings9.50 Ratings
Data Encryption00 Ratings7.40 Ratings
Built-in Processors00 Ratings7.40 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
DataRobot
-
Ratings
KNIME Analytics Platform
8.0
Ratings
5% below category average
Multiple Model Development Languages and Tools00 Ratings9.50 Ratings
Automated Machine Learning00 Ratings8.20 Ratings
Single platform for multiple model development00 Ratings9.30 Ratings
Self-Service Model Delivery00 Ratings5.00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
DataRobot
-
Ratings
KNIME Analytics Platform
7.3
Ratings
16% below category average
Flexible Model Publishing Options00 Ratings8.60 Ratings
Security, Governance, and Cost Controls00 Ratings5.90 Ratings
Best Alternatives
DataRobotKNIME Analytics Platform
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Score 7.7 out of 10
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
Medium-sized Companies
InterSystems IRIS
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Score 7.7 out of 10
Posit
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Score 10.0 out of 10
Enterprises
InterSystems IRIS
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Score 7.7 out of 10
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Score 10.0 out of 10
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User Ratings
DataRobotKNIME Analytics Platform
Likelihood to Recommend
8.6
(0 ratings)
9.6
(0 ratings)
Likelihood to Renew
6.3
(0 ratings)
9.5
(0 ratings)
Usability
-
(0 ratings)
9.0
(0 ratings)
Support Rating
8.2
(0 ratings)
9.3
(0 ratings)
Implementation Rating
-
(0 ratings)
7.0
(0 ratings)
Ease of integration
-
(0 ratings)
10.0
(0 ratings)
User Testimonials
DataRobotKNIME Analytics Platform
Likelihood to Recommend
DataRobot can be used for risk assessment, such as predicting the likelihood of loan default. It can handle both classification and regression tasks effectively. It relies on historical data for model training. If you have limited historical data or the data quality is poor, it may not be the best choice as it requires a sufficient amount of high-quality data for accurate model building.
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KNIME Analytics Platform has vastly improved our effectiveness when working with large data sets. The self documenting GUI allows analysts to focus on what they are trying to accomplish, not complex code syntax. If we were to use traditional tools, like SQL, work would take much longer and it would be more difficult to collaborate both internally and with clients. Since KNIME Analytics Platform is database oriented, some spreadsheet functions are not supported, which is as it should be. For small data sets we often use Excel vlookup and pivot tables in place of KNIME Analytics Platform. If VBA code is requried, we go to KNIME Analytics Platform as we find VBA to be unstable in Excel.
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Pros
  • The breadth of models available to use is helpful and allows much more analytical power than programming them all yourself.
  • The built-in variable diagnostics are helpful when testing large variable sets to see which perform the best.
  • Many of the adjustments on the models are easy to use/it's easy to re-run and kick off new models as you want to try new things.
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  • Visual programming as oppose to scripting encourages data analysts to reap deeper insights from their data
  • Large community contribution in extending the KNIME Analytics Platform into other areas of analytics, e.g. Text Analytics, Predictive Analytics, ML, etc.
  • Open source with periodic updates ensures it is equipped to deal with the most sophisticated data analytics use case
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Cons
  • Further improvements to their text analysis tool, to be more like the Qualtrics text analysis tool, would be a great addition. Qualtrics has templates built into their text analysis tool for customer service, quality control, etc, and will automatically slot your text responses into categories associated with certain sub areas of those larger categories.
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  • 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.
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Likelihood to Renew
DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.
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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
No answers on this topic
The training KNIME Analytics Platform provide helps you get to grips with a product that is already very intuitive. There is a KNIME Analytics Platform way of thinking about addressing problems, but once you understand a couple of patterns which you see again and again in your workflow it all makes sense.
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Support Rating
As I am writing this report I am participating with Datarobot Engineers in an complex environment and we have their whole support. We are in Mexico and is not common to have this commitment from companies without expensive contract services. Installing is on premise and the client does not want us to take control and they, the client, is also limited because of internal IT regulations ,,, soo we are just doing magic and everybody is committed.
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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
No answers on this topic
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
I've done machine learning through python before, however having to code and test each model individually was very time consuming and required a lot of expertise. The data Robot approach, is an excellent way of getting to a well placed starting point. You can then pick up the model from there and fine tune further if you need.
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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 is free to install it on as many machines as they wish without worrying about costs, the number of seats required or payment models or procurement negotiation. It also means that we are not building costs into our clients business. Secondly, KNIME Analytics Platform has a very comprehensive set of tools for importing/exporting data, data manipulation and data science. Some products offer analytics packages on top of their base offering at additional cost and they are still not as comprehensive as what you get with KNIME Analytics Platform for free. For some types of analysis you may require to download additional packages with KNIME Analytics Platform, but its invariably at no cost, those packages are kept out of the main download to keep the size down. Due to the easy integration with R and Python, I view KNIME Analytics Platform as also having the capabilities of those languages too. This has helped me in the past with seamlessly importing a rare filetype and using very specific models not directly available in KNIME Analytics Platform.
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Return on Investment
  • We have been able to cut costs by not buying leads that we will not be able to sell on
  • We have been able to deploy loan eligibility reporting which brought in new business
  • We have been able to improve the performance of our credit providers and our partners which has helped to retain business
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  • 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

DataRobot Screenshots

Screenshot of Decision FlowsScreenshot of No Code App BuilderScreenshot of AI AppsScreenshot of Automated Time SeriesScreenshot of MLOpsScreenshot of Model Insights

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.