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 15.3% mindshare in Data Science Platforms, compared to Dataiku’s 12.9% 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

23,965 Views
10,784 Comparison Views

96% willing to recommend

Dataiku

Read 12 Dataiku reviews

6,233 Views
6,046 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: July 2025).

Buyer's Guide

Databricks vs. Dataiku

July 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 (8th), 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 August 2025, in the Data Science Platforms category, the mindshare of Databricks is 15.3%, down from 19.8% compared to the previous year. The mindshare of Dataiku is 12.9%, up from 9.7% 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

"It's great technology."

"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."

"Databricks offers various courses that I can use, whether it's PySpark, Scala, or R."

"The most valuable feature is the ability to use SQL directly with Databricks."

"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."

"I work in the data science field and I found Databricks to be very useful."

"The tool helps with data processing and analytics with large-scale data or big data since it is associated with managing data at a large scale."

"Databricks' most valuable feature is the data transformation through PySpark."

More Databricks pros

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

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

"The solution is quite stable."

"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."

"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."

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

"Our clients can easily drag and drop components and use them on the spot."

More Dataiku pros

Cons

"Costs can quickly add up if you don't plan for it."

"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."

"The initial setup is difficult."

"The initial setup of Databricks could be complex."

"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."

"It's not easy to use, and they need a better UI."

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

"As a data engineer, I see cluster failure in our Databricks user databases as a major issue."

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."

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

"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."

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

"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)."

"The license is very expensive."

"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."

More Dataiku cons

Pricing and Cost Advice

"Databricks' cost could be improved."

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

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

"The pricing depends on the usage itself."

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

"Databricks are not costly when compared with other solutions' prices."

"The solution requires a subscription."

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

10%

Manufacturing Company

Healthcare Company

Financial Services Firm

18%

Manufacturing Company

10%

Computer Software Company

Energy/Utilities 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...

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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 6% of the time

Tableau Enterprise vs Databricks

Compared 5% of the time

Apache Flink vs Databricks

Compared 3% of the time

More Databricks Competitors

KNIME Business Hub vs Dataiku

Compared 19% 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

August 2025

Download Databricks product report

Buyer's Guide

Dataiku

August 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

July 2025

Free Report: Databricks vs. Dataiku

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