Sold by: DataikuÂ
Overview
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Dataiku 3-Minute Demo
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Product video
Dataiku is The Universal AI Platform™, empowering teams to deliver AI and analytics projects faster - all within a secure, collaborative, and governed environment.
- Data Scientists use familiar tools to focus on high-impact work, with automation and streamlined collaboration.
- Business Analysts get faster insights with intuitive data prep and accessible machine learning.
- Data Teams scale projects with built-in governance and transparency.
Built for AWS
- Connect securely to all data sources, including Amazon S3, Amazon Redshift, and Amazon RDS.
- Scale data and ML processing with Dataiku elastic compute powered by Amazon EKS for Python, R, Spark, and more.
- Accelerate AI development with pre-built workflows integrating AWS AI services, such as Amazon SageMaker and Amazon Comprehend.
- Distributed creation of advanced analytics through its visual platform, fostering greater collaboration between technical and non-technical teams.
- Leverage the Dataiku LLM Mesh to connect to Amazon Bedrock for Chat, RAG, and Agentic workflows.
AI at Scale, Supported Every Step
With expert services and a robust learning platform, Dataiku helps organizations of any size adopt AI at scale - quickly and confidently.
Highlights
- Take full advantage of your investment in the AWS platform with Dataiku's unique push down to Amazon's storage and compute.
- Empower more users to clean and enrich data, build advanced data pipelines and machine learning models in a visual interface.
- Accelerate deployment on AWS, leveraging Sagemaker and Bedrock, with a fully managed service (SaaS) hosted and managed by Dataiku.
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Deployed on AWS
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Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Dataiku | Contact us for pricing | $1.00 |
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
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AI generated from product descriptions
Data Source Connectivity
Secure connection to multiple AWS data sources including Amazon S3, Amazon Redshift, and Amazon RDS
Elastic Compute Processing
Scalable data and machine learning processing powered by Amazon EKS supporting Python, R, Spark, and multiple programming environments
AI Service Integration
Pre-built workflows integrating with AWS AI services like Amazon SageMaker and Amazon Comprehend
Large Language Model Connectivity
LLM Mesh capability for connecting to Amazon Bedrock to support Chat, Retrieval-Augmented Generation (RAG), and Agentic workflows
Collaborative Analytics Platform
Visual platform enabling distributed creation of advanced analytics with collaboration between technical and non-technical teams
Data Platform Architecture
Unified platform integrating data engineering, analytics, business intelligence, data science, and machine learning on a single architecture
Open Source Foundation
Built on open source data projects with support for open standards and data formats
Lakehouse Infrastructure
Provides a common data management approach using a lakehouse architecture running on Amazon S3
Data Intelligence Engine
Advanced engine capable of interpreting organizational data context and enabling broad data access across teams
Collaborative Workflow
Native collaboration capabilities enabling cross-functional data and AI workflow integration
Data Workflow Automation
Drag-and-drop interface with 300+ analytic building blocks for creating and automating data workflows
Machine Learning Capabilities
Automated machine learning (AutoML) and feature engineering for data science use cases across skill levels
Data Preparation Tools
Comprehensive data access, preparation, blending, enrichment, and statistical analytics platform
Geospatial Analytics
Integrated geospatial analytics capabilities for spatial data processing and analysis
Cloud-Native Analytics
Browser-based, cloud-native experience for building and automating data pipelines with reduced technical complexity
Standard contract
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Customer reviews
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186 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Information Technology and Services
Dataiku for Data Science/AI projects
Reviewed on Aug 26, 2025
Review provided by G2
What do you like best about the product?
SImple to use & scale. Flexibity & integrated well into the any infra.
What do you dislike about the product?
The main drawbacks of Dataiku is cost, scalability limitations, integration complexity, performance issues, and the need for user training.
What problems is the product solving and how is that benefiting you?
Dataiku addressed critical issues in data quality, operational efficiency, analytics collaboration, AI scalability, compliance, and business-user empowerment, serving as a unified platform for enterprise data innovation and value generationtion.
Aniket D.
A Powerful Platform for End-to-End Data Science & Collaboration
Reviewed on Aug 23, 2025
Review provided by G2
What do you like best about the product?
Dataiku is excellent for managing the entire data pipeline from data preparation to machine learning and deployment. The best part is it easy to implement. The best part is how it allows both technical and non-technical users to collaborate on the same platform. Visual workflows make it easy to build projects without heavy coding, while advanced users can still dive deep with Python, R, or SQL. The integration with cloud platforms and version control is also very smooth.
What do you dislike about the product?
The platform can feel heavy for smaller projects, and the initial learning curve is a bit steep for beginners. Also, the licensing costs can be high for small companies or startups.
What problems is the product solving and how is that benefiting you?
For me, Dataiku mainly solves the problem of collaboration between technical and non-technical teams. Earlier, a lot of time used to get wasted when data scientists, analysts, and business teams worked separately and had to constantly exchange files and reports. With Dataiku, we can all work on the same platform data cleaning, model building, and visualization happen in one place. It also saves me from doing repetitive manual tasks since a lot of workflows can be automated. Overall, it has made our data projects faster, more transparent, and easier to manage.
Federico B.
Great website and great platform!!
Reviewed on Aug 22, 2025
Review provided by G2
What do you like best about the product?
It brings together data people analysts, engineers, scientists on one platform
What do you dislike about the product?
honestly, is that it can feel a bit heavy and slow, especially on large projects with a lot of visual recipes or datasets.
What problems is the product solving and how is that benefiting you?
Collaboration gaps, i think it brings data scientists, analysts, engineers, and business users into one shared workspace
Stacey Leveille-Casseus S.
Functionality
Reviewed on Aug 20, 2025
Review provided by G2
What do you like best about the product?
Strong version control, shared projects, and role-based access enhance teamwork across data and business teams
What do you dislike about the product?
Some powerful capabilities are only available in higher-tier or enterprise versions, which may not be cost-effective for smaller teams
What problems is the product solving and how is that benefiting you?
Covers the full data lifecycle: ingestion, preparation, modeling, deployment, and monitoring
Sanket B.
Emerging player in Data Science
Reviewed on Aug 20, 2025
Review provided by G2
What do you like best about the product?
One of the best feature in Dataiku is No code feature which can help resources who are not comfortable in coding. It supports Python/R libraries and workflow playbook.
What do you dislike about the product?
Still expensive solution for implementation.
What problems is the product solving and how is that benefiting you?
Generally Dataiku helped us to build Data Science projects and predictive analysis to build some KPI's.