Dataiku vs Microsoft Azure Machine Learning Studio comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Dataiku
Ranking in Data Science Platforms
7th
Average Rating
8.2
Number of Reviews
7
Ranking in other categories
No ranking in other categories
Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
2nd
Average Rating
7.6
Number of Reviews
55
Ranking in other categories
AI Development Platforms (1st)
 

Mindshare comparison

As of June 2024, in the Data Science Platforms category, the mindshare of Dataiku is 9.9%, up from 6.7% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 6.2%, down from 10.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
Unique Categories:
No other categories found
AI Development Platforms
16.5%
 

Featured Reviews

RK
May 17, 2024
Gives different aspects of modeling approaches and good for multiple teams' collaboration
I used DataRobot. Dataiku has a different kind of structure to it. It's not financially heavy like DataRobot, which caters more to financial companies, like banks. Dataiku doesn't have that yet. I think they are also working on that area. But yeah, there are some key differences between the two products. DataRobot has an additional feature with financial firms that it creates all these financial metrics when you run a time series analysis. Those things I have not seen in Dataiku. If any financial company is choosing between DataRobot and Dataiku, they will definitely go for DataRobot because it creates all these financial metrics. It creates deltas, time series, time difference fields, and things like that. So, that is an added feature that DataRobot has.
Marta Frąckowiak - PeerSpot reviewer
Apr 20, 2023
A stable solution that provides a comprehensive and helpful documentation to its users
The initial setup for me was initially quite complex, but after completing a course related to Microsoft Azure Machine Learning Studio, it became less complex. However, one needs to have a good understanding of the required parameters and what the model needs to do in order to achieve good performance. So sometimes, it's not that simple. The deployment process took me a couple of hours to complete. I was able to do it quickly because I was using Azure Machine Learning Designer and Python SDK while also learning automation. The setup process for AltaML was easy and could be completed in hours. With Python SDK, the setup process was quite long because of the code that needed to be written, so one needs to know what to write.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Data Science Studio's data science model is very useful."
"The most valuable feature is the set of visual data preparation tools."
"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"The solution is quite stable."
"I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model."
"Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon."
"The most valuable feature of Microsoft Azure Machine Learning Studio is the ease of use for starting projects. It's simple to connect and view the results. Additionally, the solution works well with other Microsoft solutions, such as Power Automate or SQL Server. It is easy to use and to connect for analytics."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"The solution is integrated with our Microsoft Azure tenant, and we don't have to go anywhere else outside the tenant."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"It helps in building customized models, which are easy for clients to use​.​​"
"The solution is very easy to use, so far as our data scientists are concerned."
 

Cons

"The ability to have charts right from the explorer would be an improvement."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"I think it would help if Data Science Studio added some more features and improved the data model."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"Microsoft Azure Machine Learning Studio worked okay for me, so right now, I don't have any room for improvement in mind for it. What I'd like added to Microsoft Azure Machine Learning Studio in its next version is a categorization for use cases or a template that makes the use cases simple to map out, for example, for healthcare, medical, or finance use cases, etc. This would be very helpful for users of Microsoft Azure Machine Learning Studio, especially for beginners."
"Enable creating ensemble models easier, adding more machine learning algorithms."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"I would like to see modules to handle Deep Learning frameworks."
"Microsoft Azure Machine Learning Studio could improve in providing more efficient and cost-effective access to its tools for companies like mine."
"The regulatory requirements of the product need improvement."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
 

Pricing and Cost Advice

"Pricing is pretty steep. Dataiku is also not that cheap."
"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
"We pay only the Azure costs for what we use, which involves some subscription costs. But essentially, you pay for what you use. There are no extra costs in addition to the standard licensing fees."
"When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly."
"On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six."
"There is a lack of certainty with the solution's pricing."
"I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."
"My team didn't deal with the licensing for Microsoft Azure Machine Learning Studio, so I'm unable to comment on pricing, but the money that was spent on the tool was worth it."
"I would rate the pricing an eight out of ten, with ten being very expensive. Not very expensive, not very cheap."
"There isn’t any such expensive costs and only a standard license is required."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
14%
Manufacturing Company
8%
Computer Software Company
7%
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
8%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
Pricing is pretty steep. Dataiku is also not that cheap. It depends on the client and how much they want to spend towards a tool.
What needs improvement with Dataiku Data Science Studio?
The no-code/low-code aspect, where DataRobot doesn't need much coding at all. Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot m...
What is your primary use case for Dataiku Data Science Studio?
My current client has Dataiku. We do sentiment analysis and some small large language models right now. We use Dataiku as a Jupyter Notebook. We use it a lot for marketing and analytics. The market...
Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
What do you like most about Microsoft Azure Machine Learning Studio?
The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem.
 

Also Known As

Dataiku DSS
Azure Machine Learning, MS Azure Machine Learning Studio
 

Learn More

 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Dataiku vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: May 2024.
787,779 professionals have used our research since 2012.