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Azure Databricks vs Dataiku 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

Azure Databricks
Ranking in Data Science Platforms
20th
Average Rating
8.0
Reviews Sentiment
3.7
Number of Reviews
3
Ranking in other categories
No ranking in other categories
Dataiku
Ranking in Data Science Platforms
4th
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
21
Ranking in other categories
No ranking in other categories
 

Featured Reviews

VishnuReddy2 - PeerSpot reviewer
Consulting Enterprise Architect at R2V2.ai
Unified data platform has supported real-time analytics and advanced machine learning workflows
The real-time processing with Azure Databricks is supported through integration from external systems, for which we have to go with tools such as Matillion's HVR or Kafka. I have experience using HVR, high-volume replication. You get real-time data replicated into Azure Databricks using these tools. When looking for performance metrics in Azure Databricks, it depends on the processing. It can process millions of records quickly, and it is driven by the Spark framework, which is pretty strong in terms of framework perspective. The columnar database is another strong feature which helps enhance its performance. Prior to the introduction of Unity Catalog, there was no metadata capability in Azure Databricks. It was very simplistic, but now with the Unity Catalog introduction and Delta Sharing capabilities, Azure Databricks is at the top-notch at this point in time. In comparison, SAP BW is a little bit more mature because apart from RBAC, it gives data-level authorization, which is a little bit not that great in Azure Databricks at this point in time.
SK
Senior Data Scientist at Deloitte
Visual workflows have streamlined healthcare analytics and have reduced reporting time significantly
In terms of improvement, I cannot comment on the LLMs or the agentic view as I have not used them yet. However, I feel that better documentation is necessary. Dataiku should establish a stronger community since this is proprietary software, where users can share knowledge. Although they have some community interaction, it is often challenging to find assistance when stuck. For example, when I was new to Dataiku and trying to use an external optimization tool such as CPLEX, I struggled with resource directory linking to a project's notebook. Detailed documentation and community discussions could have significantly alleviated these issues for users such as myself.

Quotes from Members

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

Pros

"Azure Databricks gives the capability to handle a lot of big data use cases and machine learning use cases, but machine learning use cases need quite a lot of compute power, and that is where the cost spikes up."
"The best features in Azure Databricks for me are that it's easy to use, flexible, and has fast processing, and you can use multiple data types."
"Regarding the learning curve, it is a good technology; it is the first time I am working on a cloud platform, and before that, I have not worked on any data engineering tool that is on cloud, so it is good learning."
"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."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"The most valuable feature is the set of visual data preparation tools."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"The solution is quite stable."
"The best features Dataiku offers include the ability for users to use the node without having to code and the functionality related to low-code/no-code."
"I rate the overall product as eight out of ten."
 

Cons

"At this point, I cannot comment on the cost being ideal; it is on the higher side, but in the cloud-based environment, compared to on-premise, it could be far lesser in cost."
"I have given the product a rating of six out of ten just because I do not use all of the functionalities, and I see some direction for improvement as well; also, every product has something to improve, and I have not used many features in this product."
"One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."
"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."
"In terms of enhancing collaboration within my team, I would not say Dataiku is the best one because it's so expensive."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"Maybe on the interface in general, the information can easily get lost."
"I think it would help if Data Science Studio added some more features and improved the data model."
"I find that it is a little slow during use. When I use Dataiku to run my script to transfer data, it takes more time than I would expect for the operation to complete."
"I would like to have better exclusion of data capability."
 

Pricing and Cost Advice

Information not available
"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."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
18%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise2
Large Enterprise13
 

Questions from the Community

What is your experience regarding pricing and costs for Azure Databricks?
Regarding the licensing cost of Azure Databricks, it has evolved quite a lot. The compute is the biggest cost, as with any other big data solutions. The storage cost is almost minimal or negligible...
What needs improvement with Azure Databricks?
Overall, my experience has been positive with Azure Databricks; they have many features, but there is no use case for me to use those features, such as Delta Live Tables and Genie. In my opinion, I...
What is your primary use case for Azure Databricks?
The primary use cases for me are the reportings I have to do, so I need to ingest data from the file and create reports. I do not utilize it for real-time data processing. I have not integrated Azu...
What is your experience regarding pricing and costs for Dataiku Data Science Studio?
I am not the person involved in the process regarding pricing, setup cost, and licensing.
What needs improvement with Dataiku Data Science Studio?
To improve Dataiku, it could enhance its visualization features, as it is not possible in Dataiku to create direct visualizations or to integrate a web app directly or in a simpler way as it is pos...
What is your primary use case for Dataiku Data Science Studio?
My main use case for Dataiku is for data science and AI projects. I use Dataiku for a demand forecasting use case where the objective is to predict the demand for each product for the next four mon...
 

Also Known As

No data available
Dataiku DSS
 

Overview

 

Sample Customers

Information Not Available
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Find out what your peers are saying about Azure Databricks vs. Dataiku and other solutions. Updated: March 2026.
885,311 professionals have used our research since 2012.