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Dataiku vs SAS Visual Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Categories and Ranking

Dataiku
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
12
Ranking in other categories
Data Science Platforms (6th)
SAS Visual Analytics
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
40
Ranking in other categories
Data Visualization (9th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Dataiku is designed for Data Science Platforms and holds a mindshare of 11.7%, up 10.9% compared to last year.
SAS Visual Analytics, on the other hand, focuses on Data Visualization, holds 3.4% mindshare, down 5.2% since last year.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Dataiku11.7%
Databricks13.9%
KNIME Business Hub11.9%
Other62.5%
Data Science Platforms
Data Visualization Market Share Distribution
ProductMarket Share (%)
SAS Visual Analytics3.4%
Tableau Enterprise19.2%
Apache Superset9.2%
Other68.2%
Data Visualization
 

Q&A Highlights

HE
Jun 07, 2023
 

Featured Reviews

RichardXu - PeerSpot reviewer
The platform organizes workflows visually and efficiently
One of the valuable features of Dataiku is the workflow capability. It allows us to organize a workflow efficiently. The platform has a visual interface, making it much easier for educated professionals to organize their work. This feature is useful because it simplifies tasks and eliminates the need for a data scientist. If you are knowledgeable about AI, you can directly write using primitive tools like Pantera flow, PyTorch, and Scikit-learn. However, Dataiku makes this process much easier.
Renato Vazamin - PeerSpot reviewer
Single environment for multiple phases saves us time, and has good visualizations
We had that solution installed previously in another solution, Selvaya, but I don't think we used it at the time. We are now using SAS Detect Investigation as a complementary solution, in which we have part of the process, use a gene, SAS collects information and identifies some business situations, and the business guys use Visual Analytics to explore the results of the process. We previously used the FICO platform, but we switched because FICO's pricing was not scalable. Bringing more data or workloads to the platform required a significant investment in order to scale. We needed to change because we have a lot of data to process every day. FICO was also a little more complicated than SAS Visual Analytics.

Quotes from Members

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

Pros

"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"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."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"The solution is quite stable."
"I believe the return on investment looks positive."
"The technical support services are good."
"We've found the product to be stable and reliable."
"I would rate the overall solution a ten out of ten."
"The tool's most valuable features are its ease of use and advanced data visualization capabilities."
"Data handling is one of the best features of SAS Visual Analytics."
"The speed to display charts and react to users' choices is great."
"The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced technologies such as machine learning and artificial intelligence. This helps with quality assurance processes."
"The flexibility of the configuration is valuable to me."
 

Cons

"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."
"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."
"We still encounter some integration issues."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
"The license is very expensive."
"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."
"There is a need for coding when it comes to digital reporting which can be intimidating."
"The integration aspects of the solution could be improved."
"Better connectivity with other data origins, better visualization, and the ability to create KPIs directly would all help."
"There are a few little things that are predefined and can be done out of the box immediately. There is no business intelligence application that is predefined, which is something some customers or prospects would love to have. Small and mid-sized companies would struggle with it because they prefer something standard that has been predefined by somebody else."
"The charts and tables could use better sorting, primarily using other variables than the ones on the figure. If they could implement views like in the older version (previous to Viya), it would be very nice."
"A bit more flexibility in the temperatization will be helpful."
"The installation process can be a bit complex."
"Colours used on report objects"
 

Pricing and Cost Advice

"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."
"Pricing is pretty steep. Dataiku is also not that cheap."
"It was licensed for corporate use, and its licensing was on a yearly basis."
"Licensing is simple."
"It's approximately $114,000 US dollars per year."
"The cost of the solution can be expensive. There is an additional cost for users."
"$10,000 per annum for an enterprise license."
"SAS Visual Analytics is expensive, as is the rest of the platform."
"Visual Analytics is expensive for a small company like mine. You also need to deploy it on a server or cloud, so you pay for the license as well as the cost of the cloud or the server that you will deploy on."
"I work with the tool's free version...The tool's corporate version is very expensive and requires a monthly hire."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
6%
Financial Services Firm
19%
Government
10%
Computer Software Company
9%
University
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise7
By reviewers
Company SizeCount
Small Business13
Midsize Enterprise8
Large Enterprise19
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies. However, it is a pricey solution and I primarily recommend it to bigger companies.
What needs improvement with Dataiku Data Science Studio?
There is room for improvement in terms of allowing for more code-based features. I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend ...
What is your primary use case for Dataiku Data Science Studio?
My company sells licenses for both Dataiku and Alteryx, and we have clients who use them. I engage with several companies in telecommunications, retail, and energy to assess how our clients are uti...
What do you like most about SAS Visual Analytics?
The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced technologies such as machine learning and artificial intelligence. This helps w...
What is your experience regarding pricing and costs for SAS Visual Analytics?
It's about an average of five. It's easy to scale, but it comes with cost.
What needs improvement with SAS Visual Analytics?
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI. It may be that our current subscription does not include AI-enabled features, but I wo...
 

Comparisons

 

Also Known As

Dataiku DSS
SAS BI
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms. Updated: September 2025.
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