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

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 12, 2025

Databricks and Dataiku are prominent products competing in the realm of data analytics and artificial intelligence. Databricks might have an edge due to its high-speed analytics and integration, while Dataiku is favored for user-friendly interfaces and extensive data integration capabilities.

Features: Databricks offers efficient large-scale analytics, automated cluster creation, and collaborative notebooks. It supports popular programming languages like SQL and Python, making it a versatile choice for developers. Dataiku presents visual data preparation tools, flexibility in using various coding languages, and seamless data handling directly into BigQuery, which is beneficial for non-technical users.

Room for Improvement: Databricks could benefit from enhanced visualization tools, improved integration features, and a more transparent pricing structure. The user experience could be more intuitive for non-programmers. Dataiku faces collaboration challenges, complex data type handling issues, and partial reliance on coding, which can be barriers for users seeking low-code or no-code solutions.

Ease of Deployment and Customer Service: Databricks provides a versatile deployment environment across public, private, and hybrid clouds, with generally positive customer support, though some users experience delays. Dataiku is mostly on-premises, with limited cloud deployment options, and its thorough documentation reduces the need for frequent technical support, showcasing its ease of use and setup efficiency.

Pricing and ROI: Databricks is perceived as expensive but competitive, offering strong ROI due to high performance and scalability despite a complex licensing model. Dataiku also tends to be costly upfront but is praised for its cost-effectiveness in complex analytics and machine learning tasks. Databricks' pay-as-you-go model may lead to cost savings on extensive workloads, while Dataiku offers potential savings through efficient data handling and preparation.

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

Buyer's Guide

Databricks vs. Dataiku

March 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 (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

"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."

"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."

"The main features of the solution are efficiency."

"The notebooks and the ability to share them with collaborators are valuable, as multiple developers can use a single cluster."

"I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature."

"There are good features for turning off clusters."

"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."

"The solution is easy to use and has a quick start-up time due to being on the cloud."

More Databricks pros

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

"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."

"The solution is quite stable."

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

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

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

"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 believe the return on investment looks positive."

More Dataiku pros

Cons

"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."

"Databricks' technical support takes a while to respond and could be improved."

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

"CI/CD needs additional leverage and support."

"The integration features could be more interesting, more involved."

"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."

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

"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."

More Databricks cons

"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 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."

"We still encounter some integration issues."

"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."

"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."

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

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

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

More Dataiku cons

Pricing and Cost Advice

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

"The pricing depends on the usage itself."

"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."

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

"We only pay for the Azure compute behind the solution."

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

"The solution is affordable."

"Databricks' cost could be improved."

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

17%

Educational Organization

14%

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?

The pricing for Dataiku is very high, which is its biggest downside. The model they follow is not consumption-based, making it expensive.

See all answers

What needs improvement with Dataiku Data Science Studio?

Dataiku's pricing is very high, and commercial transparency is a challenge. Support is also an area needing improvement. More features like LLM security, holographic encryption, and enhanced GPU in...

See all answers

What is your primary use case for Dataiku Data Science Studio?

My primary use case for Dataiku ( /products/dataiku-reviews ) is for data science, Gen ( /products/gen-reviews ) AI, and data science applications. Our AGN team also uses it for various purposes.

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

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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 8% of the time

Microsoft Azure Machine Learning Studio vs Dataiku

Compared 5% of the time

More Dataiku Competitors

Product Reports

Buyer's Guide

Databricks

March 2025

Download Databricks product report

Buyer's Guide

Dataiku

March 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

March 2025

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