Dataiku Reviews

Name: Dataiku
Brand: Dataiku
Rating: 4.1 (12 reviews)

4.1 out of 5

12 reviews
100% willing to recommend

795 followers

What is Dataiku?

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.

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Dataiku is the #6 ranked solution in top Data Science Platforms. PeerSpot users give Dataiku an average rating of 8.2 out of 10. Dataiku is most commonly compared to Databricks: Dataiku vs Databricks. Dataiku is popular among the large enterprise segment, accounting for 66% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 18% of all views.

Helped 856,873 peers since 2012

Featured Dataiku reviews

RichardXu

Data Science Lead at a mining and metals company with 10,001+ employees

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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Sabrine Bendimerad

Data Scientist at Electricite De France

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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Hamdi Charksi

Senior Data Engineer at One Point

The use case is data science, and we've deployed Data Science Studio in multiple regions for four environments: dev, preset, pre-production, and production The solution responds to the requirements of the business team. Data Science Studio's data science model is very useful. I think it would…

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Dataiku mindshare

As of June 2025, the mindshare of Dataiku in the Data Science Platforms category stands at 13.0%, up from 8.7% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Data Science Platforms

PeerResearch reports based on Dataiku reviews

Type	Title	Date
Category	Data Science Platforms	Jun 15, 2025	Download
Product	Reviews, tips, and advice from real users	Jun 15, 2025	Download
Comparison	Dataiku vs Databricks	Jun 15, 2025	Download
Comparison	Dataiku vs Amazon SageMaker	Jun 15, 2025	Download
Comparison	Dataiku vs KNIME	Jun 15, 2025	Download

Title	Rating	Mindshare	Recommending
Databricks	4.1	16.5%	96%	91 interviews Add to research
KNIME	4.1	12.0%	94%	60 interviews Add to research

Valuable Features

Dataiku's features include a process scheduler, cloud-based processes, comprehensive functionalities, easy prediction deployment, and visual data preparation tools. Users appreciate its integration with languages like Python and R as well as BigQuery access. The interface is user-friendly, offering both code and visual options. Feature selection, model creation, workflow organization, collaboration, traceability, and automation are notable. It supports Spark for distributed computing and excels in data science, MLOps, and integration with public cloud platforms.

"Our clients can easily drag and drop components and use them on the spot."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"I believe the return on investment looks positive."

Room for Improvement

Dataiku faces challenges in server stability, query engine reliability, and user interface complexity. Improvements are needed in data exclusion, message broadcasting, and deep learning integration. Users call for better handling of complex data types and enhanced support for non-IT users. Pricing is considered high, and GitHub integration is problematic. Developers seek more flexibility in code-based components and support for parallel machine learning. Enhancements in error messaging, GPU integration, and commercial transparency are also desired.

"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."
"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."

ROI

Users highlighted that the platform's ability to streamline data science processes and enhance collaboration among team members leads to more efficient project completion. Dataiku's versatility and user-friendly interface enable users to manage large datasets effectively and apply complex algorithms, which in turn results in significant time savings and increased productivity. Additionally, the software's scalability allows for ongoing growth and adaptation in diverse environments.

Pricing

Enterprise users perceive Dataiku's pricing as high, with annual licensing fees around €20 ($22) for the basic version and €40 ($44) for the comprehensive version per key. While some find it more affordable compared to competitors like Alteryx, others consider it expensive, especially since it’s not consumption-based. Users note it's suited for larger companies, with no extra costs beyond licensing. Pricing experiences vary, but it often depends on budget allocation for data tools.

"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."

Popular Use Cases

Dataiku's primary uses include ETL development, predicting time-series data, data preparation, and data modeling. It is employed for data migration between Redshift warehouses, sentiment analysis, and various marketing and analytics tasks. Data science, machine learning, and AI applications in sectors like oil, gas exploration, health research, telecommunications, retail, and energy are also supported. Dataiku serves multiple environments, functioning as a Jupyter Notebook and aiding in AI platform operations.

Service and Support

Dataiku's service and support receive mixed feedback. Customers appreciate the quick response time, often citing interactions with technical leaders for complex issues. Some find their expertise and promptness satisfactory, rating them highly. Others mention adequate support through chat but express dissatisfaction with assistance and billing issues. While partnering with local experts enhances industry-specific help, there is inconsistency in determining superior support. Despite some challenges, many acknowledge responsive and knowledgeable service.

Deployment

Many users found Dataiku's initial setup straightforward and simple. Some mentioned deployment taking only a few days, while others said it required several months. One user highlighted the ease of single-person deployment if experienced. Tutorials and guidelines were beneficial, though post-deployment adjustments were needed to stabilize the platform. Customization added time to the process, but managing was possible within a week for most. Several users relied on their IT teams for setup tasks.

Scalability

Dataiku exhibits scalability with ease of integration into current architectures and cloud platforms, supporting numerous users. While some find it slow with large datasets, others have not encountered limits. Many users benefit from its scalable capabilities, with companies ranging from small teams to those with hundreds of employees effectively utilizing it. Generally, it scores high on scalability, though some think improvements could be made.

Stability

Some users face stability issues with Dataiku, citing bugs in SQL operations, server downtime, and privacy issues. Others find it stable, using tools like resource control and macros for optimization. Dependence on open-source libraries can affect consistency. While a few experience occasional freezing, many rate it positively for their tasks. Some users, focusing on specific features, find it meets expectations but acknowledge its stability could be influenced by third-party updates.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

Download our Dataiku Buyer's Guide for additional reliable information.