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 #7 with an average rating of 7.5. Databricks holds a 19.1% mindshare in Data Science Platforms, compared to Dataiku’s 12.1% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Dataiku users who would recommend it.

Databricks

Read 85 Databricks reviews

17,588 Views
11,896 Comparison Views

96% willing to recommend

Dataiku

Read 9 Dataiku reviews

7,151 Views
5,935 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: December 2024).

Buyer's Guide

Databricks vs. Dataiku

December 2024

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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

Streaming Analytics (1st)

Dataiku

Ranking in Data Science Platforms

7th

Average Rating

8.0

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2025, in the Data Science Platforms category, the mindshare of Databricks is 19.1%, up from 18.5% compared to the previous year. The mindshare of Dataiku is 12.1%, up from 7.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Parag Bhosale

Senior Data Engineer at a logistics company with 51-200 employees

Integrating engineering and learning, but cost challenges arise with cluster management

We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller. We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly. We need to stay in sync with the DVR versions, and migrations can pose challenges. For example, issues arose when we moved a cluster from a previous version to the latest one. We could use their job clusters, however, that increases costs, which is challenging for us as a startup. Maintaining this infrastructure can be a headache.

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Sabrine Bendimerad

Data Scientist at Electricite De France

Saves a lot of time because I can quickly handle all the data preparation tasks and concentrate on building my machine learning algorithms

One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to use GitHub with Dataiku, in practice, it was difficult to manage our code effectively and push it from Dataiku to GitHub. Another limitation was its ability to handle different types of data. While Dataiku is powerful for working with structured data, like regular or geospatial data, it struggled with more complex data types such as text and image. In addition to the challenges with GitHub integration, the limited support for diverse data types was another feature lacking at that time.

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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

"The simplicity of development is the most valuable feature."

"It helps integrate data science and machine learning capabilities."

"The initial setup is pretty easy."

"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."

"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."

"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."

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

"The load distribution capabilities are good, and you can perform data processing tasks very quickly."

More Databricks pros

"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 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."

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

"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."

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

"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."

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

More Dataiku pros

Cons

"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."

"It would be great if Databricks could integrate all the cloud platforms."

"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."

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

"The initial setup is difficult."

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

"Performance could be improved."

"The integration and query capabilities can be improved."

More Databricks cons

"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."

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

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

"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 ability to have charts right from the explorer would be an improvement."

"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 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 affordable."

"It is an expensive tool. The licensing model is a pay-as-you-go one."

"The product pricing is moderate."

"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."

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

"I would rate Databricks' pricing seven out of ten."

"The price is okay. It's competitive."

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

17%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Financial Services Firm

18%

Educational Organization

16%

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 ...

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...

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What is your experience regarding pricing and costs for Dataiku Data Science Studio?

It is very expensive.

See all answers

What needs improvement with Dataiku Data Science Studio?

See all answers

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

We use the solution for data science and machine learning.

See all answers

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Microsoft Power BI vs Databricks

Compared 7% of the time

Tableau vs Databricks

Compared 5% of the time

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KNIME vs Dataiku

Compared 16% of the time

Alteryx vs Dataiku

Compared 11% of the time

RapidMiner vs Dataiku

Compared 11% of the time

Amazon SageMaker vs Dataiku

Compared 7% of the time

Microsoft Azure Machine Learning Studio vs Dataiku

Compared 6% of the time

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Product Reports

Buyer's Guide

Databricks

January 2025

Download Databricks product report

Buyer's Guide

Dataiku

January 2025

Download Dataiku product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Dataiku DSS

Learn More

Databricks

Dataiku

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.

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.

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

December 2024

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