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 7.8. Databricks holds a 18.5% mindshare in Data Science Platforms, compared to Dataiku’s 12.5% 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

15,712 Views
11,084 Comparison Views

96% willing to recommend

Dataiku

Read 11 Dataiku reviews

6,993 Views
5,785 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

7th

Average Rating

8.2

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2025, in the Data Science Platforms category, the mindshare of Databricks is 18.5%, up from 18.7% compared to the previous year. The mindshare of Dataiku is 12.5%, up from 8.0% 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

"Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."

"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."

"The setup was straightforward."

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

"Databricks has a scalable Spark cluster creation process. The creators of Databricks are also the creators of Spark, and they are the industry leaders in terms of performance."

"The initial setup phase of Databricks was good."

"We have the ability to scale, collaborate and do machine learning."

"The fast data loading process and data storage capabilities are great."

More Databricks pros

"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."

"The solution is quite stable."

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

"Dataiku is highly regarded as it is a leader in the Gartner ranking."

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

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

"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."

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

More Dataiku pros

Cons

"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."

"There has been a significant evolution in databases. One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files."

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

"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."

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

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

"The solution has some scalability and integration limitations when consolidating legacy systems."

"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."

More Databricks cons

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

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

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

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

"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."

"The license is very expensive."

"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."

"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

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

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

"The solution requires a subscription."

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

"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."

"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."

"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."

"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."

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

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...

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

There are no extra expenses beyond the existing licensing cost.

See all answers

What needs improvement with Dataiku Data Science Studio?

I need more experience in the sector, which is health. The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience.

See all answers

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

I use that IQ since I am preparing cohorts for health investment research.

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 8% of the time

Amazon SageMaker vs Databricks

Compared 6% of the time

Tableau vs Databricks

Compared 5% of the time

More Databricks Competitors

KNIME vs Dataiku

Compared 17% of the time

Alteryx vs Dataiku

Compared 12% of the time

Altair RapidMiner vs Dataiku

Compared 11% 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

Free Report: Databricks vs. Dataiku

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