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Dataiku Reviews

Vendor: Dataiku
4.1 out of 5
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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 69% 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.
Buyer's Guide
Dataiku
August 2025
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Dataiku mindshare

As of August 2025, the mindshare of Dataiku in the Data Science Platforms category stands at 12.9%, up from 9.7% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Dataiku12.9%
Databricks15.3%
KNIME Business Hub11.9%
Other59.9%
Data Science Platforms

PeerResearch reports based on Dataiku reviews

TypeTitleDate
CategoryData Science PlatformsAug 28, 2025Download
ProductReviews, tips, and advice from real usersAug 28, 2025Download
ComparisonDataiku vs DatabricksAug 28, 2025Download
ComparisonDataiku vs KNIME Business HubAug 28, 2025Download
ComparisonDataiku vs Amazon SageMakerAug 28, 2025Download
Suggested products
TitleRatingMindshareRecommending
Databricks4.115.3%96%91 interviewsAdd to research
KNIME Business Hub4.111.9%94%60 interviewsAdd to research
 
 
Key learnings from peers

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.

Review data by company size

By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise7
By reviewers
By visitors reading reviews
Company SizeCount
Small Business289
Midsize Enterprise164
Large Enterprise1012
By visitors reading reviews

Top industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
6%
Insurance Company
5%
Healthcare Company
5%
Retailer
4%
Educational Organization
4%
University
3%
Non Profit
3%
Wholesaler/Distributor
3%
Government
3%
Comms Service Provider
3%
Media Company
3%
Construction Company
2%
Pharma/Biotech Company
2%
Transportation Company
2%
Real Estate/Law Firm
2%
Performing Arts
2%
Hospitality Company
1%
Legal Firm
1%
Recreational Facilities/Services Company
1%
Logistics Company
1%
Outsourcing Company
1%
Consumer Goods Company
1%
Renewables & Environment Company
1%
Marketing Services Firm
1%

Compare Dataiku with alternative products

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Learn more about Dataiku

Dataiku was previously known as Dataiku DSS.

Dataiku customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto

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Dataiku Reviews Summary
Author infoRatingReview Summary
Data Science Lead at a mining and metals company with 10,001+ employees4.0We use Dataiku for oil and gas exploration because of its efficient workflow capabilities and visual interface, making tasks easier without needing a data scientist. Although there are integration issues, the ROI seems positive compared to alternatives considered.
Manager at CTTI - Centre de Telecomunicacions i Tecnologies de la Informació4.0I use Dataiku primarily for preparing health investment research cohorts, valuing its traceability and collaboration features. With multiple engineers on my team, integration with machine learning is crucial. However, the licensing cost is high, and I seek more healthcare sector experience.
Cognitive Business Operation at a consultancy with 10,001+ employees5.0I primarily use Dataiku for data science and AI applications. It's a leader in capabilities and integration but is expensive with limited support. Lower pricing would enhance ROI. Alternatives include Converge.io, Domino Data Lab, and ClearML.
Big Data Consultant at a computer software company with 1,001-5,000 employees4.0My company sells licenses for Dataiku and Alteryx, and I've seen its drag-and-drop and automation features significantly enhance clients' machine learning model development. However, more flexibility with code-based features would be beneficial.
Data Scientist at Electricite De France3.5I use Dataiku for data science and machine learning, enjoying its recipe features for easy data preparation without coding. However, integration with GitHub is challenging, and it struggles with complex data types like text and image.
Consultant at Netsoft4.0My current client uses Dataiku for sentiment analysis and large language models, mainly in marketing and analytics. While it offers strong feature selection, more coding is required compared to DataRobot, which is more suited for financial tasks.
Senior Data Engineer at One Point5.0No summary available
Data Scientist II at Alumnus Software Ltd.4.5No summary available