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 8.3, while Dataiku is ranked #6 with an average rating of 8.2. Databricks holds a 18.2% mindshare in Data Science Platforms, compared to Dataiku’s 12.7% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Dataiku users who would recommend it.

Databricks

Read 88 Databricks reviews

14,742 Views
10,545 Comparison Views

96% willing to recommend

Dataiku

Read 12 Dataiku reviews

6,785 Views
5,638 Comparison Views

100% willing to recommend

Databricks

Dataiku

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Executive SummaryUpdated on Apr 20, 2025

Databricks and Dataiku compete in the data analytics and data science platform category. Databricks appears to have the upper hand due to its seamless scalability and fast processing capabilities.

Features: Databricks offers seamless scalability, leveraging fast processing with Spark, and integrates with multiple programming languages. It automates cluster creation effectively. Dataiku provides an intuitive workflow environment ideal for collaborative data science, with strong AI tool integration and visual data preparation tools.

Room for Improvement: Databricks could improve its visualization and expand its integration library. Its pricing structure is often criticized, and better support for intuitive data science tools is suggested. Dataiku seeks more code-based flexibility, stronger machine learning enhancements, and improved integration with tools like GitHub.

Ease of Deployment and Customer Service: Databricks benefits from a cloud-based design, noted for easy accessibility, though customer support feedback varies. Dataiku is praised for comprehensive documentation that supports smooth deployment but has limitations in direct support.

Pricing and ROI: Databricks uses a pay-per-use model perceived as costly, though justified by scalability and features. Dataiku has straightforward pricing but is viewed as expensive for large deployments. Both platforms typically offer reasonable ROI, with Databricks delivering more direct cost savings through efficient data processing.

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

Buyer's Guide

Databricks vs. Dataiku

April 2025

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Helped 849,190 peers since 2012

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 (7th), 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 April 2025, in the Data Science Platforms category, the mindshare of Databricks is 18.2%, down from 19.1% compared to the previous year. The mindshare of Dataiku is 12.7%, up from 8.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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.

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Quotes from Members

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

Pros

"Databricks is a robust solution for big data processing, offering flexibility and powerful features."

"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."

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

"I would rate them ten out of ten."

"Ability to work collaboratively without having to worry about the infrastructure."

"It offers AI functionalities that assist with code management and machine learning processes."

"The initial setup phase of Databricks was good."

"Its lightweight and fast processing are valuable."

More Databricks pros

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

"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."

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

"The solution is quite stable."

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

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

"I believe the return on investment looks positive."

"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."

More Dataiku pros

Cons

"Anyone who doesn't know SQL may find the product difficult to work with."

"The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms."

"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."

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

"The connectivity with various BI tools could be improved, specifically the performance and real time integration."

"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."

"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."

"This solution only supports queries in SQL and Python, which is a bit limiting."

More Databricks cons

"We still encounter some integration issues."

"I think it would help if Data Science Studio added some more features and improved the data model."

"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."

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

"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."

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

"The license is very expensive."

"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

"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."

"Databricks uses a price-per-use model, where you can use as much compute as you need."

"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."

"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."

"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."

"I would rate the tool’s pricing an eight out of ten."

"The solution is based on a licensing model."

"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."

More Databricks 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."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Financial Services Firm

18%

Educational Organization

12%

Manufacturing Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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 ...

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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

Dremio vs Databricks

Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Tableau vs Databricks

Compared 5% of the time

Amazon SageMaker vs Databricks

Compared 5% of the time

More Databricks Competitors

KNIME vs Dataiku

Compared 18% 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

Microsoft Azure Machine Learning Studio vs Dataiku

Compared 5% of the time

More Dataiku Competitors

Product Reports

Buyer's Guide

Databricks

April 2025

Download Databricks product report

Buyer's Guide

Dataiku

April 2025

Download Dataiku product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Dataiku DSS

Overview

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

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

April 2025

Free Report: Databricks vs. Dataiku

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