Azure Machine Learning vs. Dataiku

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Machine Learning
Score 7.9 out of 10
N/A
Microsoft's Azure Machine Learning is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud. It replaces the Azure Machine Learning Workbench.
$0
per month
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
Pricing
Azure Machine LearningDataiku
Editions & Modules
Studio Pricing - Free
$0.00
per month
Production Web API - Dev/Test
$0.00
per month
Studio Pricing - Standard
$9.99
per ML studio workspace/per month
Production Web API - Standard S1
$100.13
per month
Production Web API - Standard S2
$1000.06
per month
Production Web API - Standard S3
$9999.98
per month
Discover
Contact sales team
Business
Contact sales team
Enterprise
Contact sales team
Offerings
Pricing Offerings
Azure Machine LearningDataiku
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Azure Machine LearningDataiku
Top Pros
Top Cons
Features
Azure Machine LearningDataiku
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Machine Learning
-
Ratings
Dataiku
9.1
4 Ratings
7% above category average
Connect to Multiple Data Sources00 Ratings10.04 Ratings
Extend Existing Data Sources00 Ratings10.04 Ratings
Automatic Data Format Detection00 Ratings10.04 Ratings
MDM Integration00 Ratings6.52 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Machine Learning
-
Ratings
Dataiku
9.9
4 Ratings
16% above category average
Visualization00 Ratings9.94 Ratings
Interactive Data Analysis00 Ratings10.04 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Machine Learning
-
Ratings
Dataiku
10.0
4 Ratings
19% above category average
Interactive Data Cleaning and Enrichment00 Ratings10.04 Ratings
Data Transformations00 Ratings10.04 Ratings
Data Encryption00 Ratings10.04 Ratings
Built-in Processors00 Ratings10.04 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Machine Learning
-
Ratings
Dataiku
8.7
4 Ratings
2% above category average
Multiple Model Development Languages and Tools00 Ratings5.14 Ratings
Automated Machine Learning00 Ratings10.04 Ratings
Single platform for multiple model development00 Ratings10.04 Ratings
Self-Service Model Delivery00 Ratings10.04 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Azure Machine Learning
-
Ratings
Dataiku
9.0
4 Ratings
5% above category average
Flexible Model Publishing Options00 Ratings9.04 Ratings
Security, Governance, and Cost Controls00 Ratings9.04 Ratings
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Azure Machine LearningDataiku
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Score 9.1 out of 10
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Score 8.3 out of 10
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User Ratings
Azure Machine LearningDataiku
Likelihood to Recommend
8.0
(4 ratings)
10.0
(4 ratings)
Likelihood to Renew
7.0
(1 ratings)
-
(0 ratings)
Usability
7.0
(2 ratings)
10.0
(1 ratings)
Support Rating
7.9
(2 ratings)
9.4
(3 ratings)
Implementation Rating
8.0
(1 ratings)
-
(0 ratings)
User Testimonials
Azure Machine LearningDataiku
Likelihood to Recommend
Microsoft
For [a] data scientist require[d] to build a machine learning model, so he/she didn't worry about infrastructure to maintain it.
All kind of feature[s] such as train, build, deploy and monitor the machine learning model available in a single suite.
If someone has [their] own environment for ML studio, so there [it would] not [be] useful for them.
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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.
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Pros
Microsoft
  • User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
  • Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
  • Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
  • Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
  • Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.
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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.
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Cons
Microsoft
  • It would be great to have text tips that could ease new users to the platform, especially if an error shows up
  • Scenario-based documentation
  • Pre-processing of modules that had been previously run. Sometimes they need to be re-run for no apparent reason
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Dataiku
  • End product deployment.
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Usability
Microsoft
Easy and fastest way to develop, test, deploy and monitor the machine learning model.
- Easy to load the data set
-Drag and drop the process of the Machine learning life cycle.
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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.
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Support Rating
Microsoft
Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.
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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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Implementation Rating
Microsoft
Not sure
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Dataiku
No answers on this topic
Alternatives Considered
Microsoft
It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.
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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.
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Return on Investment
Microsoft
  • Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster;
  • Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat.
  • Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details
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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.
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ScreenShots