Dataiku vs. KNIME Analytics Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Dataiku
Score 7.9 out of 10
N/A
Dataiku is a French startup and its product, DSS, is a challenger to market incumbents and features some visual tools to assist in building workflows.N/A
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
DataikuKNIME Analytics Platform
Editions & Modules
Discover
Contact sales team
Business
Contact sales team
Enterprise
Contact sales team
KNIME Community Hub - Individual
$0
KNIME Community Hub - Team
From €250
per month Starts from 3 users
Offerings
Pricing Offerings
DataikuKNIME Analytics Platform
Free Trial
YesYes
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
DataikuKNIME Analytics Platform
Considered Both Products
Dataiku
KNIME Analytics Platform
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 …
Top Pros
Top Cons
Features
DataikuKNIME Analytics Platform
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Dataiku
9.1
4 Ratings
7% above category average
KNIME Analytics Platform
9.1
19 Ratings
7% above category average
Connect to Multiple Data Sources10.04 Ratings9.619 Ratings
Extend Existing Data Sources10.04 Ratings10.010 Ratings
Automatic Data Format Detection10.04 Ratings9.019 Ratings
MDM Integration6.52 Ratings7.98 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Dataiku
9.9
4 Ratings
16% above category average
KNIME Analytics Platform
8.0
18 Ratings
5% below category average
Visualization9.94 Ratings8.018 Ratings
Interactive Data Analysis10.04 Ratings8.018 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Dataiku
10.0
4 Ratings
19% above category average
KNIME Analytics Platform
8.3
19 Ratings
1% above category average
Interactive Data Cleaning and Enrichment10.04 Ratings9.019 Ratings
Data Transformations10.04 Ratings9.419 Ratings
Data Encryption10.04 Ratings7.47 Ratings
Built-in Processors10.04 Ratings7.48 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Dataiku
8.7
4 Ratings
2% above category average
KNIME Analytics Platform
7.9
18 Ratings
7% below category average
Multiple Model Development Languages and Tools5.14 Ratings9.417 Ratings
Automated Machine Learning10.04 Ratings8.217 Ratings
Single platform for multiple model development10.04 Ratings9.218 Ratings
Self-Service Model Delivery10.04 Ratings5.08 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Dataiku
9.0
4 Ratings
5% above category average
KNIME Analytics Platform
7.3
11 Ratings
16% below category average
Flexible Model Publishing Options9.04 Ratings8.611 Ratings
Security, Governance, and Cost Controls9.04 Ratings5.94 Ratings
Best Alternatives
DataikuKNIME Analytics Platform
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IBM SPSS Modeler
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Score 7.8 out of 10
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Score 7.8 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.3 out of 10
Mathematica
Mathematica
Score 8.3 out of 10
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Score 7.8 out of 10
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All AlternativesView all alternativesView all alternatives
User Ratings
DataikuKNIME Analytics Platform
Likelihood to Recommend
10.0
(4 ratings)
9.6
(22 ratings)
Likelihood to Renew
-
(0 ratings)
9.4
(4 ratings)
Usability
10.0
(1 ratings)
9.0
(3 ratings)
Support Rating
9.4
(3 ratings)
9.0
(6 ratings)
Implementation Rating
-
(0 ratings)
7.0
(2 ratings)
Ease of integration
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
DataikuKNIME Analytics Platform
Likelihood to Recommend
Dataiku
Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.
Read full review
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
Dataiku
  • The intuitiveness of this tool is very good.
  • Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visuals
  • The way you can control things, the set of APIs gives a lot of flexibility to a developer.
Read full review
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.
Read full review
Cons
Dataiku
  • End product deployment.
Read full review
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.
Read full review
Likelihood to Renew
Dataiku
No answers on this topic
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
Dataiku
As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.
Read full review
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
Dataiku
The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.
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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
Dataiku
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
Dataiku
Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
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
Dataiku
  • Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.
  • Platform also ease tracking of data processing workflow, unlike Excel.
  • Build-in data visualizations covers many use cases with minimal customization; time saver.
Read full review
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.
Read full review
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.