Databricks vs Dataiku comparison

Databricks and Dataiku are both solutions in the Data Science Platforms category. Databricks is ranked #1 with an average rating of 8.4, while Dataiku is ranked #6 with an average rating of 8.2. Databricks holds a 13.9% mindshare in Data Science Platforms, compared to Dataiku’s 11.7% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Dataiku users who would recommend it.

Databricks

Read 91 Databricks reviews

20,775 Views
8,933 Comparison Views

96% willing to recommend

Dataiku

Read 12 Dataiku reviews

5,844 Views
5,669 Comparison Views

100% willing to recommend

Databricks

Dataiku

Comparison Buyer's Guide

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Executive SummaryUpdated on Jul 27, 2025

Databricks and Dataiku compete in the field of large-scale analytics and data science. Databricks seems to have the upper hand in performance and speed, while Dataiku appeals to users looking for ease of use and visual interface.

Features: Databricks offers a unified platform with scalable Spark clusters, a robust machine learning library, and seamless cloud integration. Dataiku provides a drag-and-drop interface, visual workflows, and promotes effective collaboration without needing extensive coding.

Room for Improvement: Databricks users seek enhanced visualization capabilities, more libraries for predictive analytics, and better BI integration. Pricing, interface simplicity, and documentation depth are also concerns. Dataiku users want improvements in handling complex data types, enhanced GitHub integration, and broader machine learning training capabilities. The pricing model, especially for large deployments, is noted as expensive.

Ease of Deployment and Customer Service: Databricks supports cloud-based deployment, allowing quick scaling and deployment, with generally favorable reviews for technical support. Dataiku offers both on-premises and cloud deployment options, praised for comprehensive documentation and intuitive platform nature, although more detailed support and integration assistance is needed.

Pricing and ROI: Databricks utilizes a pay-per-use model, found flexible but sometimes expensive, especially for large-scale deployments. Integration costs can add to the expense, yet performance justifies the cost for many users. Dataiku’s non-consumption-based model is perceived as higher and less cost-effective for smaller cases, with the high price point being a significant drawback despite appreciation for affordability compared to some competitors.

To learn more, read our detailed Databricks vs. Dataiku Report (Updated: September 2025).

Buyer's Guide

Databricks vs. Dataiku

September 2025

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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

Databricks

Ranking in Data Science Platforms

1st

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (9th), Streaming Analytics (1st)

Dataiku

Ranking in Data Science Platforms

6th

Average Rating

8.2

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Data Science Platforms category, the mindshare of Databricks is 13.9%, down from 19.2% compared to the previous year. The mindshare of Dataiku is 11.7%, up from 10.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Databricks	13.9%
Dataiku	11.7%
Other	74.4%

Data Science Platforms

Featured Reviews

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

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RichardXu

Data Science Lead at a mining and metals company with 10,001+ employees

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.

Read full review

Quotes from Members

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

Pros

"I would rate them ten out of ten."

"The solution is an impressive tool for data migration and integration."

"It's very simple to use Databricks Apache Spark."

"Databricks is a scalable solution. It is the largest advantage of the solution."

"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."

"Databricks serves as a single platform that can handle numerous end-to-end machine learning tasks."

"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."

"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."

More Databricks pros

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

"Cloud-based process run helps in not keeping the systems on while processes are running."

"I rate the overall product as eight out of ten."

"The most valuable feature is the set of visual data preparation tools."

"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."

"Data Science Studio's data science model is very useful."

"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."

"One of the valuable features of Dataiku is the workflow capability."

More Dataiku pros

Cons

"A lot of people are required to manage this solution."

"The integration of data could be a bit better."

"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."

"I would like more integration with SQL for using data in different workspaces."

"The pricing of Databricks could be cheaper."

"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."

"In the next release, I would like to see more optimization features."

"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."

More Databricks cons

"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."

"There is room for improvement in terms of allowing for more code-based features."

"We still encounter some integration issues."

"The license is very expensive."

"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."

"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."

"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."

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."

More Dataiku cons

Pricing and Cost Advice

"The price of Databricks is reasonable compared to other solutions."

"The cost for Databricks depends on the use case. I work on it as a consultant, so I'm using the client's Databricks, so it depends on how big the client is."

"We're charged on what the data throughput is and also what the compute time is."

"The solution is a good value for batch processing and huge workloads."

"The solution is affordable."

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."

"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."

More Databricks 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."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

Manufacturing Company

Healthcare Company

Financial Services Firm

17%

Manufacturing Company

10%

Computer Software Company

Energy/Utilities Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	25
Midsize Enterprise	12
Large Enterprise	56

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	1
Large Enterprise	7

Questions from the Community

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 ...

See all answers

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

See all answers

Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...

See all answers

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.

See all answers

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 ...

See all answers

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...

See all answers

Comparisons

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 5% of the time

Tableau Enterprise vs Databricks

Compared 4% of the time

Apache Flink vs Databricks

Compared 3% of the time

More Databricks Competitors

KNIME Business Hub vs Dataiku

Compared 20% of the time

Alteryx vs Dataiku

Compared 12% of the time

Altair RapidMiner vs Dataiku

Compared 10% of the time

Amazon SageMaker vs Dataiku

Compared 9% of the time

Domino Data Science Platform vs Dataiku

Compared 5% of the time

More Dataiku Competitors

Product Reports

Buyer's Guide

Databricks

October 2025

Download Databricks product report

Buyer's Guide

Dataiku

October 2025

Download Dataiku product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Dataiku DSS

Overview

Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.

Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.

What features make Databricks unique?

Notebook: Enables collaborative work among team members.
Delta Lake: Optimizes data management operations.
Unity Catalog: Provides governance over data assets.
Cloud Integration: Seamlessly connects with major cloud platforms.

What benefits can users expect from Databricks?

Versatility: Supports diverse applications in data science and engineering.
Performance: Delivers efficient handling of large-scale analytics tasks.
Collaboration: Enhances teamwork in data projects.
Unified Environment: Centralizes machine learning and analytics activities.

In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.

Databricks

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

Dataiku

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto

Buyer's Guide

Databricks vs. Dataiku

September 2025

Free Report: Databricks vs. Dataiku

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